METHOD AND APPARATUS FOR OPTIMIZING RAILROAD TRAIN OPERATION FOR A TRAIN INCLUDING MULTIPLE DISTRIBUTED-POWER LOCOMOTIVES

Abstract

One embodiment of the invention comprises a system for operating a railway vehicle (8) comprising a lead powered unit (14/15) and a non-lead powered unit (16/17/18) during a trip along a track The system comprises a first element (65) for determining a location of the vehicle or a time from the beginning of a current trip, aa processor (62) operable to receive information from the first element (65) and an algorithm embodied within the processor (62) having access to the information to create a trip plan that optimizes performance of one or both of the lead unit (14/15) and the non-lead unit (16/17/18) in accordance with one or more operational criteria for one or more of the vehicle (8), the lead unit (14/15) and the non-lead unit (16/17/18).

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part application claiming the benefit of U.S. patent application entitled Trip Optimization System and Method for a Train, filed on Mar. 20, 2006 and assigned application Ser. No. 11/385,354, which is hereby incorporated by reference.

FIELD OF THE INVENTION

This embodiments of the invention relate to optimizing train operations, and more particularly to optimizing train operations for a train including multiple distributed power locomotive consists by monitoring and controlling train operations to improve efficiency while satisfying schedule constraints.

BACKGROUND OF THE INVENTION

A locomotive is a complex system with numerous subsystems, each subsystem interdependent on other subsystems. An operator aboard a locomotive applies tractive and braking effort to control the speed of the locomotive and its load of railcars to assure safe and timely arrival at the desired destination. Speed control must also be exercised to maintain in-train forces within acceptable limits, thereby avoiding excessive coupler forces and the possibility of a train break. To perform this fimction and comply with prescribed operating speeds that may vary with the train's location on the track, the operator generally must have extensive experience operating the locomotive over the specified terrain with various railcar consists.

However, even with sufficient knowledge and experience to assure safe operation, the operator generally cannot operate the locomotive to minimize fuel consumption (or other operating characteristics, e.g., emissions) during a trip. Multiple operating factors affect fuel consumption, including, for example, emission limits, locomotive fuel/emissions characteristics, size and loading of railcars, weather, traffic conditions and locomotive operating parameters. An operator can more effectively and efficiently operate a train (through the application of tractive and braking efforts) if provided control information that optimizes performance during a trip while meeting a required schedule (arrival time) and using a minimal amount of fuel (or optimizing another operating parameter), despite the many variables that affect performance. Thus it is desired for the operator to operate the train under the guidance (or control) of an apparatus or process that advises the application

A distributed power train 8, as illustrated in FIGS. 1 and 2, comprises locomotives 14-18 distributed in spaced-apart relation within the train consist. In addition to the head end locomotive consist 12A, including locomotives 14 and 15, the train 8 comprises one or more additional locomotive consists (referred to as remote consists and the locomotives thereof referred to as remote units or remote locomotives) 12B and 12C. The remote unit consist 12B comprises the remote locomotives 16 and 17; the remote unit consist 12C comprises the remote locomotive 18. A distributed power train can improve train operation and handling by applying tractive and braking efforts at locations other than the train's head end.

The locomotives of the remote consists 12B and 12C are controlled by commands issued by the head end lead unit 14 and carried over a communications system 10. Such commands, for example, may instruct the remote units to apply braking or tractive effort. The communications system 10, referred to as a distributed power communications system, also carries remote unit replies to lead unit commands, remote unit alarm condition messages and remote unit operational parametric data. The remote unit transmissions are transmitted to the head end lead unit 14 for the attention of the engineer. Typically, the distributed power communications system permits the train to be subdivided into a lead consist and as many as four remote consists, with each remote consist independently controllable from the head end.

The types, contents and format of the various messages carried over the communications system 10 are described in detail in the commonly owned U.S. Pat. Nos. 5,039,038 and 4,582,580, both entitled Railroad Communication System, which are incorporated by reference herein.

For a remote consist including two or more locomotives, one of the consist locomotives is designated the remote consist lead unit, such as the locomotive 16 for the remote consist 12B. The remote consist lead unit 16 receives commands and messages from the lead unit 14, executes the commands and messages as required and issues corresponding commands and messages to the linked locomotive 17 over an interconnecting cable 19 (referred to as a train line or an MU (multiple unit) line). The lead unit 14 also controls operation of the linked locomotive 15 by issuing commands via the MU line 19 connecting the two locomotives.

The communications system 10 provides communications between the head end lead unit 14 and land-based sites, such as a dispatching center, a locomotive monitoring and diagnostic center, a rail yard, a loading/unloading facility and wayside equipment. For example, the remote consists 12B and 12C can be controlled from either the head end lead unit 14 (FIG. 1) or a control tower 40 (FIG. 2).

It should be understood that the only difference between the systems of FIGS. 1 and 2 is that the issuance of commands and messages from the lead unit 14 of FIG. 1 is replaced by the control tower 40 of FIG. 2. Typically, the control tower 40 communicates with the lead unit 14, which in turn is linked to the locomotive 15 by the MU line 17 and to the remote consists 12B and 12C by the communications system 10.

The distributed power train 8 of FIGS. 1 and 2, further comprises a plurality of railcars 20 interposed between the lead consist 12A and the remote consists 12B/12C. The arrangement of the consists 12A-12C and railcars 20 illustrated in FIGS. 1 and 2 is merely exemplary as the present invention can be applied to other locomotive/railcar arrangements.

The railcars 20 comprise an air brake system (not shown in FIGS. 1 and 2) that applies the railcar air brakes in response to a pressure drop in a brake pipe 22 and releases the air brakes upon a pressure rise in the brake pipe 22. The brake pipe 22 runs the length of the train for conveying the air pressure changes specified by the individual air brake controls 24 in the lead unit 14 and the remote units 16-18.

In certain applications an off-board repeater 26 is disposed within radio communications distance of the train 8 for relaying communications signals between the lead unit 14 and the remote consists 12B and 12C over the communications system 10.

Each of the locomotives 14-18, the off board repeater 26 and the control tower 40 comprises a transceiver 28 operative with an antenna 29 for receiving and transmitting communications signals over the communications system 10. The transceiver 28 in the lead unit 14 is associated with a lead controller 30 for generating and issuing the commands and messages from the lead unit 14 to the remote consists 12B and 12C and receiving reply messages therefrom. Commands are generated in the lead controller 30 in response to operator control of the traction and braking controls within the lead unit 14. Each locomotive 15-18 and the off-board repeater 26 comprises a remote controller 32 for processing and responding to received signals and for issuing reply messages, alarms and commands.

BRIEF DESCRIPTION OF THE INVENTION

According to one embodiment, the present invention comprises a system for operating a railway vehicle comprising a lead powered unit and a non-lead powered unit during a trip along a track. The system comprises a first element for determining a location of the vehicle or a time from the beginning of a current trip, a processor operable to receive information from the first element and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of one or both of the lead unit and the non-lead unit in accordance with one or more operational criteria for one or more of the vehicle, the lead unit and the non-lead unit.

According to another embodiment the present invention comprises a method for operating a railway vehicle comprising a lead unit and a non-lead unit during a trip along a track. The method comprises determining vehicle operating parameters and operating constraints and executing an algorithm according to the operating parameters and operating constraints to create a trip plan for the vehicle that separately optimizes performance of the lead unit and the non-lead unit, wherein execution of the trip plan permits independent control of the lead unit and the non-lead unit.

According to yet another embodiment, the invention comprises a computer software code for operating a railway vehicle comprising a computer processor, a lead unit and a non-lead unit during a trip along a track. The computer software code comprises a software module for determining vehicle operating parameters and operating constraints and a software module for executing an algorithm according to the operating parameters and operating constraints to create a trip plan for the vehicle that independently optimizes performance of the lead unit and the non-lead unit, wherein execution of the trip plan permits independent control of the lead unit and the non-lead unit.

BRIEF DESCRIPTION OF THE DRAWINGS

A more particular description of the embodiments of the invention will be rendered by reference to specific embodiments thereof that are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope, the aspects of the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:

FIGS. 1 and 2 depict distributed power railroad trains to which the teachings of the present invention can be applied.

FIG. 3 depicts an exemplary illustration of a flow chart of the present invention;

FIG. 4 depicts a simplified model of the train that may be employed;

FIG. 5 depicts an exemplary embodiment of elements of the present invention;

FIG. 6 depicts an exemplary embodiment of a fuel-use/travel time curve;

FIG. 7 depicts an exemplary embodiment of segmentation decomposition for trip planning;

FIG. 8 depicts an exemplary embodiment of a segmentation example;

FIG. 9 depicts an exemplary flow chart of the present invention;

FIG. 10 depicts an exemplary illustration of a dynamic display for use by the operator;

FIG. 11 depicts another exemplary illustration of a dynamic display for use by the operator;

FIG. 12 depicts another exemplary illustration of a dynamic display for use by the operator.

DETAILED DESCRIPTION OF THE INVENTION

Reference will now be made in detail to the embodiments consistent with the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numerals used throughout the drawings refer to the same or like parts.

Aspects of the present invention solve certain problems in the art by providing a system, method, and computer implemented method for determining and implementing a driving strategy of a train including a locomotive consist and a plurality of railcars, by monitoring and controlling (either directly or through suggested operator actions) a train's operations to improve certain objective operating parameters while satisfying schedule and speed constraints. The embodiments of the present invention are also applicable to a train including a plurality of locomotive consists, referred to as a distributed power train.

Persons skilled in the art will recognize that an apparatus, such as a data processing system, including a CPU, memory, I/O, program storage, a connecting bus, and other appropriate components, could be programmed or otherwise designed to facilitate the practice of the methods of the invention embodiments. Such a system would include appropriate program means for executing the methods of the invention.

In another embodiment, an article of manufacture, such as a pre-recorded disk or other similar computer program product, for use with a data processing system, includes a storage medium and a program recorded thereon for directing the data processing system to facilitate the practice of the methods of the invention. Such apparatus and articles of manufacture also fall within the spirit and scope of the embodiments of the invention.

Broadly speaking, the embodiments of the invention teachs a method, apparatus, and program for determining and implementing a driving strategy of a train to improve certain objective operating parameters while satisfying schedule and speed constraints. To facilitate an understanding of the present inventions, it is described hereinafter with reference to specific implementations thereof. The embodiments are described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. For example, the software programs that underlie the invention embodiments can be coded in different languages, for use with different processing platforms. In the description that follows, examples of the embodiments of the invention are described in the context of a web portal that employs a web browser. It will be appreciated, however, that the principles that underlie these embodiments can be implemented with other types of computer software technologies as well.

Moreover, those skilled in the art will appreciate that the inventions may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. The inventions may also be practiced in a distributed computing environment where tasks are performed by remote processing devices that are linked through a communications network. In the distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices. These local and remote computing environments may be contained entirely within the locomotive, or within adjacent locomotives in consist or off-board in wayside or central offices where wireless communications are provided between the computing environments.

The term locomotive consist means one or more locomotives in succession, connected together so as to provide motoring and/or braking capability with no railcars between the locomotives, such as the locomotive consists 12A, 12B and 12C of FIG. 1. A train may comprise one or more locomotive consists such as the locomotive consist 12A, 12B and 12C. Specifically, there may be a lead consist (such as the consist 12A) and one or more remote consists, such as a first remote consist (such as the remote consist 12B) midway along the line of railcars and another remote consist (such as the remote consist 12C) at an end-of-train position. Each locomotive consist may have a first or lead locomotive (such as the lead unit locomotive 14 of the consist 12A and the lead unit locomotive 16 of the remote consist 12B) and one or more trailing locomotives (such as the locomotive 15 of the consist 12A and the locomotive 17 of the remote consist

Though a consist is usually considered as connected successive locomotives, those skilled in the art will readily recognize that a group of locomotives may also be recognized as a consist even with at least one railcar separating the locomotives, such as when the consist is configured for distributed power operation, as described above, wherein throttle and braking commands are relayed from the lead locomotive to the remote locomotives by the communications system 10. Towards this end, the term locomotive consist should be not be considered a limiting factor when discussing multiple locomotives within the same train.

Referring now to the drawings, embodiments of the present invention will be described. These embodiments can be implemented in numerous ways, including as a system (including a computer processing system), a method (including a computerized method), an apparatus, a computer readable medium, a computer program product, a graphical user interface, including a web portal, or a data structure tangibly fixed in a computer readable memory. Several embodiments of the invention are discussed below.

FIG. 3 depicts an exemplary illustration of a flow chart of one embodiment of the present invention. As illustrated, instructions are input specific to planning a trip either on board or from a remote location, such as a dispatch center 110. Such input information includes, but is not limited to, train position, consist composition (such as locomotive models), locomotive tractive power performance of locomotive traction transmission, consumption of engine fuel as a function of output power, cooling characteristics, intended trip route (effective track grade and curvature as function of milepost or an “effective grade” component to reflect curvature, following standard railroad practices), car makeup and loading (including effective drag coefficients), desired trip parameters including, but not limited to, start time and location, end location, travel time, crew (user and/or operator) identification, crew shift expiration time and trip route.

This data may be provided to the locomotive 142 (see FIG. 3) according to various techniques and processes, such as, but not limited to, manual operator entry into the locomotive 142 via an onboard display, linking to a data storage device such as a hard card, hard drive and/or USB drive or transmitting the information via a wireless communications channel from a central or wayside location 141, such as a track signaling device and/or a wayside device, to the locomotive 142. Locomotive 142 and train 131 load characteristics (e.g., drag ) may also change over the route (e.g., with altitude, ambient temperature and condition of the rails and rail-cars), causing a plan update to reflect such changes according to any of the methods discussed above. The updated data that affects the trip optimization process can be supplied by any of the methods and techniques described above and/or by real-time autonomous collection of locomotive/train conditions. Such updates include, for example, changes in locomotive or train characteristics detected by monitoring equipment on or off board the locomotive(s) 142.

A track signal system indicates certain track conditions and provides instructions to the operator of a train approaching the signal. The signaling system, which is described in greater detail below, indicates, for example, an allowable train speed over a segment of track and provides stop and run instructions to the train operator. Details of the signal system, including the location of the signals and the rules associated with different signals are stored in the onboard database 163 (see FIG. 9).

Based on the specification data input into the various embodiments of the present invention, an optimal trip plan that minimizes fuel use and/or generated emissions subject to speed limit constraints and a desired start and end time is computed to produce a trip profile 112. The profile contains the optimal speed and power (notch) settings for the train to follow, expressed as a fanction of distance and/or time from the beginning of the trip, train operating limits, including but not limited to, the maximum notch power and brake settings, speed limits as a function of location and the expected fuel used and emissions generated. In an exemplary embodiment, the value for the notch setting is selected to obtain throttle change decisions about once every 10 to 30 seconds.

Those skilled in the art will readily recognize that the throttle change decisions may occur at a longer or shorter intervals, if needed and/or desired to follow an optimal speed profile. In a broader sense, it should be evident to ones skilled in the art that the profiles provide power settings for the train, either at the train level, consist level and/or individual locomotive level. As used herein, power comprises braking power, motoring power and airbrake power. In another preferred embodiment, instead of operating at the traditional discrete notch power settings, the present invention embodiments determine a desired power setting, from a continuous range of power settings, to optimize the speed profile. Thus, for example, if an optimal profile specifies a notch setting of 6.8, instead of a notch setting of 7, the locomotive 142 operates at 6.8. Allowing such intermediate power settings may provide additional efficiency benefits as described below.

The procedure for computing the optimal profile can include any number of methods for computing a power sequence that drives the train 131 to minimize fuel and/or emissions subject to locomotive operating and schedule constraints, as summarized below. In some situations the optimal profile may be sufficiently similar to a previously determined profile due to the similarity of train configurations, route and environmental conditions. In these cases it may be sufficient to retrieve the previously-determined driving trajectory from the database 163 and operate the train accordingly.

When a previous plan is not available, methods to compute a new plan include, but are not limited to, direct calculation of the optimal profile using differential equation models that approximate train physics of motion. According to this process, a quantitative objective function is determined, commonly the function comprises a weighted sum (integral) of model variables that correspond to a fuel consumption rate and emissions generated plus a term to penalize excessive throttle variations.

An optimal control formulation is established to minimize the quantitative objective function subject to constraints including but not limited to, speed limits and minimum and maximum power (throttle) settings. Depending on planning objectives at any time, the problem may be setup to minimize fuel subject to constraints on emissions and speed limits or to minimize emissions subject to constraints on fuel use and arrival time. It is also possible to setup, for example, a goal to minimize the total travel time without constraints on total emissions or fuel use where such relaxation of constraints is permitted or required for the mission.

Throughout the document exemplary equations and objective functions are presented for minimizing locomotive fuel consumption. These equations and functions are for illustration only as other equations and objective functions can be employed to optimize fuel consumption or to optimize other locomotive/train operating parameters.

Mathematically, the problem to be solved may be stated more precisely. The basic physics are expressed by:

$\frac{x}{t}=v;x\left(0\right)=0.0;x\left(T_f\right)=D$ $\frac{v}{t}=T_e\left(u,v\right)-G_a\left(x\right)-R\left(v\right);v\left(0\right)=0.0;v\left(T_f\right)=0.0$

where x is the position of the train, v is train velocity, t is time (in miles, miles per hour and minutes or hours as appropriate) and u is the notch (throttle) command input. Further, D denotes the distance to be traveled, T_f the desired arrival time at distance D along the track, T_e is the tractive effort produced by the locomotive consist, G_a is the gravitational drag (which depends on train length, train makeup and travel terrain) and R is the net speed dependent drag of the locomotive consist and train combination. The initial and final speeds can also be specified, but without loss of generality are taken to be zero here (train stopped at beginning and end of the trip). The model is readily modified to include other dynamics factors such the lag between a change in throttle u and a resulting tractive or braking effort.

All these performance measures can be expressed as a linear combination of any of the following:

$\underset{u\left(t\right)}{\min }{\int }_0^{T_f}F\left(u\left(t\right)\right)t-\mathrm{Minimize}\mathrm{total}\mathrm{fuel}\mathrm{consumption}$ $\underset{u\left(t\right)}{\min }T_f-\mathrm{Minimize}\mathrm{Travel}\mathrm{Time}$ $\underset{u_i}{\min }\sum _{i=2}^{n_d}{\left(u_i-u_{i-1}\right)}^2-\mathrm{Minimize}\mathrm{notch}\mathrm{jockeying}\left(\mathrm{piecewise}\mathrm{constant}\mathrm{input}\right)$ $\underset{u\left(t\right)}{\min }{\int }_0^{T_f}{\left(\frac{u}{t}\right)}^2t-\mathrm{Minimize}\mathrm{notch}\mathrm{jockeying}\left(\mathrm{continuous}\mathrm{input}\right)$

Replace the fuel term F(·) in (1) with a term corresponding to emissions production. A commonly used and representative objective function is thus

$\begin{array}{cc}\underset{u\left(t\right)}{\min }{\alpha }_1{\int }_0^{T_f}F\left(u\left(t\right)\right)t+{\alpha }_3T_f+{\alpha }_2{\int }_0^{T_f}{\left(\frac{u}{t}\right)}^2t& \left(\mathrm{OP}\right)\end{array}$

The coefficients of the linear combination depend on the importance (weight) given to each of the terms. Note that in equation (OP), u(t) is the optimizing variable that is the continuous notch position. If discrete notch is required, e.g. for older locomotives, the solution to equation (OP) is discretized, which may result in lower fuel savings. Finding a minimum time solution (α₁ set to zero and α₂ set to zero or a relatively small value) is used to find a lower bound for the achievable travel time (T_f=T_fmin). In this case, both u(t) and T_f are optimizing variables. The preferred embodiment solves the equation (OP) for various values of T_f with T_f>T_fmin with α₃ set to zero. In this latter case, T_f is treated as a constraint.

For those familiar with solutions to such optimal problems, it may be necessary to adjoin constraints, e.g. the speed limits along the path:

0≦v≦SL(x)

or when using minimum time as the objective, the adjoin constraint may be that an end point constraint must hold, e.g. total fuel consumed must be less than what is in the tank, e.g. via:

$0<{\int }_0^{T_f}F\left(u\left(t\right)\right)t\le W_F$

where W_F is the fuel remaining in the tank at T_f. Those skilled in the art will readily recognize that equation (OP) can presented in other forms and that the version above is an exemplary equation for use in the embodiments of the present invention.

Reference to emissions in the context of the embodiments of the present invention is generally directed to cumulative emissions produced in the form of oxides of nitrogen (NOx), unburned hydrocarbons and particulates. By design, every locomotive must be compliant with EPA emission standards, and thus in an embodiment of the present invention that optimizes emissions this may refer to mission-total emissions, for which there is no current EPA specification. Operation of the locomotive according to the optimized trip plan is at all times compliant with EPA emission standards.

If a key objective during a trip is to reduce emissions, the optimal control formulation, equation (OP), is amended to consider this trip objective. A key flexibility in the optimization process is that any or all of the trip objectives can vary by geographic region or mission. For example, for a high priority train, minimum time may be the only objective on one route because of the train's priority. In another example emission output could vary from state to state along the planned train route.

To solve the resulting optimization problem, in an exemplary embodiment the present invention transcribes a dynamic optimal control problem in the time domain to an equivalent static mathematical programming problem with N decision variables, where the number ‘N’ depends on the frequency at which throttle and braking adjustments are made and the duration of the trip. For typical problems, this N can be in the thousands. In an exemplary embodiment a train is traveling a 172-mile stretch of track in the southwest United States. Utilizing certain aspects of the present invention, an exemplary 7.6% fuel consumption may be realized when comparing a trip determined and followed using the present features of the inventions versus a trip where the throttle/speed is determined by the operator according to standard practices. The improved savings is realized because the optimization provided by the present invention produces a driving strategy with both less drag loss and little or no braking loss compared to the operator controlled trip.

To make the optimization described above computationally tractable, a simplified model of the train may be employed, such as illustrated in FIG. 4 and set forth in the equations discussed above. A key refinement to the optimal profile is produced by deriving a more detailed model with the optimal power sequence generated, to test if any thermal, electrical and mechanical constraints are violated, leading to a modified profile with speed versus distance that is closest to a run that can be achieved without damaging the locomotive or train equipment, i.e. satisfying additional implied constraints such thermal and electrical limits on the locomotive and in-train forces.

Referring back to FIG. 3, once the trip is started 112, power commands are generated 114 to put the start the plan. Depending on the operational set-up of the various embodiments of the present invention, one command causes the locomotive to follow the optimized power command 116 so as to achieve optimal speed. According to its various embodiments, the present invention obtains actual speed and power information from the locomotive consist of the train 118. Due to the common approximations in the models used for the optimization, a closed-loop calculation of corrections to the optimized power is obtained to track the desired optimal speed. Such corrections of train operating limits can be made automatically or by the operator, who always has ultimate control of the train.

In some cases, the model used in the optimization may differ significantly from the actual train. This can occur for many reasons, including but not limited to, extra cargo pickups or setouts, locomotives that fail in-route, errors in the initial database 163 and data entry errors by the operator. For these reasons a monitoring system uses real-time train data to estimate locomotive and/or train parameters in real time 120. The estimated parameters are then compared to the assumed parameters when the trip was initially created 122. Based on any differences in the assumed and estimated values, the trip may be re-planned 124. Typically the trip is re-planned if significant savings can be realized from a new plan.

Other reasons a trip may be re-planned include directives from a remote location, such as dispatch, and/or an operator request of a change in objectives to be consistent with global movement planning objectives. Such global movement planning objectives may include, but are not limited to, other train schedules, time required to dissipate exhaust from a tunnel, maintenance operations, etc. Another reason may be due to an onboard failure of a component. Strategies for re-planning may be grouped into incremental and major adjustments depending on the severity of the disruption, as discussed in more detail below. In general, a “new” plan must be derived from a solution to the optimization problem equation (OP) described above, but frequently faster approximate solutions can be found, as described herein.

In operation, the locomotive 142 will continuously monitor system efficiency and continuously update the trip plan based on the actual measured efficiency whenever such an update may improve trip performance. Re-planning computations may be carried out entirely within the locomotive(s) or fully or partially performed at a remote location, such as dispatch or wayside processing facilities where wireless technology can communicate the new plan to the locomotive 142. The various embodiments of the present invention may also generate efficiency trends for developing locomotive fleet data regarding efficiency transfer functions. The fleet-wide data may be used when determining the initial trip plan, and may be used for network-wide optimization tradeoff when considering locations of a plurality of trains. For example, the travel-time fuel-use tradeoff curve as illustrated in FIG. 6 reflects a capability of a train on a particular route at a current time, updated from ensemble averages collected for many similar trains on the same route. Thus, a central dispatch facility collecting curves like FIG. 6 from many locomotives could use that information to better coordinate overall train movements to achieve a system-wide advantage in fuel use or throughput.

Many events during daily operations may motivate the generation of a new or modified plan, including a new or modified trip plan that retains the same trip objectives, for example, when a train is not on schedule for a planned meet or pass with another train and therefore must make up the lost time. Using the actual speed, power and location of the locomotive, a planned arrival time is compared with a currently estimated (predicted) arrival time 25. Based on a difference in the times, as well as the difference in parameters (detected or changed by dispatch or the operator) the plan is adjusted 126. This adjustment may be made automatically responsive to a railroad company's policy for handling departures from plan or manually as the on-board operator and dispatcher jointly decide the best approach for returning the plan. Whenever a plan is updated but where the original objectives, such as but not limited to arrival time remain the same, additional changes may be factored in concurrently, e.g. new future speed limit changes, which could affect the feasibility of recovering the original plan. In such instances if the original trip plan cannot be maintained, or in other words the train is unable to meet the original trip plan objectives, as discussed herein other trip plan(s) may be presented to the operator, remote facility and/or dispatch.

A re-plan may also be made when it is desired to change the original objectives. Such re-planning can be done at either fixed preplanned times, manually at the discretion of the operator or dispatcher or autonomously when predefined limits, such a train operating limits, are exceeded. For example, if the current plan execution is running late by more than a specified threshold, such as thirty minutes, the embodiments of the invention can re-plan the trip to accommodate the delay at the expense of increased fuel consumption as described above or to alert the operator and dispatcher as to the extent to which lost time can be regained, if at all, (i.e. what is the minimum time remaining or the maximum fuel that can be saved within a time constraint). Other triggers for re-plan can also be envisioned based on fuel consumed or the health of the power consist, including but not limited time of arrival, loss of horsepower due to equipment failure and/or equipment temporary malfunction (such as operating too hot or too cold), and/or detection of gross setup errors, such in the assumed train load. That is, if the change reflects impairment in the locomotive performance for the current trip, these may be factored into the models and/or equations used in the optimization process.

Changes in plan objectives can also arise from a need to coordinate events where the plan for one train compromises the ability of another train to meet objectives and arbitration at a different level, e.g. the dispatch office, is required. For example, the coordination of meets and passes may be further optimized through train-to-train communications. Thus, as an example, if an operator knows he is behind schedule in reaching a location for a meet and/or pass, communications from the other train can advise the operator of the late train (and/or dispatch). The operator can enter information pertaining to the expected late arrival for recalculating the train's trip plan. According to various embodiments, the present invention can also be used at a high level or network-level, to allow a dispatch to determine which train should slow down or speed up should it appear that a scheduled meet and/or pass time constraint may not be met. As discussed herein, this is accomplished by trains transmitting data to dispatch to prioritize how each train should change its planning objective. A choice can be made either based on schedule or fuel saving benefits, depending on the situation.

For any of the manually or automatically initiated re-plans, the invention may present more than one trip plan to the operator. In an exemplary embodiment the present invention presents different profiles to the operator, allowing the operator to select the arrival time and also understand the corresponding fuel and/or emission impact. Such information can also be provided to the dispatch for similar considerations, either as a simple list of alternatives or as a plurality of tradeoff curves such as illustrated in FIG. 6.

In one embodiment the present invention includes the ability to learn and adapt to key changes in the train and power consist that can be incorporated either in the current plan and/or for future plans. For example, one of the triggers discussed above is loss of horsepower. When building up horsepower over time, either after a loss of horsepower or when beginning a trip, transition logic is utilized to determine when a desired horsepower is achieved. This information can be saved in the locomotive database 161 for use in optimizing either future trips or the current trip should loss of horsepower occur again later.

FIG. 5 depicts an exemplary embodiment of elements of the present invention. A locator element 130 determines a location of the train 131. The locator element 130 comprises a GPS sensor or a system of sensors that determine a location of the train 131. Examples of such other systems may include, but are not limited to, wayside devices, such as radio frequency automatic equipment identification (RF AEI) tags, dispatch, and/or video-based determinations. Another system may use tachometer(s) aboard a locomotive and distance calculations from a reference point. As discussed previously, a wireless communication system 147 may also be provided to allow communications between trains and/or with a remote location, such as dispatch. Information about travel locations may also be transferred from other trains over the communications system.

A track characterization element 133 provides information about a track, principally grade, elevation and curvature information. The track characterization element 133 may include an on-board track integrity database 136. Sensors 138 measure a tractive effort 140 applied by the locomotive consist 142, throttle setting of the locomotive consist 142, locomotive consist 142 configuration information, speed of the locomotive consist 142, individual locomotive configuration information, individual locomotive capability, etc. In an exemplary embodiment the locomotive consist 142 configuration information may be loaded without the use of a sensor 138, but is input by other approaches as discussed above. Furthermore, the health of the locomotives in the consist may also be considered. For example, if one locomotive in the consist is unable to operate above power notch level 5 this information is used when optimizing the trip plan.

Information from the locator element may also be used to determine an appropriate arrival time of the train 131. For example, if there is a train 31 moving along a track 134 toward a destination and no train is following behind it, and the train has no fixed arrival deadline to satisfy, the locator element, including but not limited to radio frequency automatic equipment identification (RF AEI) tags, dispatch, and/or video-based determinations, may be used to determine the exact location of the train 131. Furthermore, inputs from these signaling systems may be used to adjust the train speed. Using the on-board track database, discussed below, and the locator element, such as GPS, embodiments of the invention can adjust the operator interface to reflect the signaling system state at the given locomotive location. In a situation where signal states indicate restrictive speeds ahead, the planner may elect to slow the train to conserve fuel consumption.

Information from the locator element 130 may also be used to change planning objectives as a function of distance to a destination. For example, owing to inevitable uncertainties about congestion along the route, “faster” time objectives on the early part of a route may be employed as hedge against delays that statistically occur later. If on a particular trip such delays do not occur, the objectives on a latter part of the journey can be modified to exploit the built-in slack time that was banked earlier and thereby recover some fuel efficiency. A similar strategy can be invoked with respect to emission-restrictive objectives, e.g. emissions constraints that apply when approaching an urban area.

As an example of the hedging strategy, if a trip is planned from New York to Chicago, the system may provide an option to operate the train slower at either the beginning of the trip, at the middle of the trip or at the end of the trip. The embodiments of the present invention optimize the trip plan to allow for slower operation at the end of the trip since unknown constraints, such as but not limited to weather conditions, track maintenance, etc., may develop and become known during the trip. As another consideration, if traditionally congested areas are known, the plan is developed with an option to increase the driving flexibility around such regions. Therefore, in one embodiment the present invention may also consider weighting/penalizing as a function of time/distance into the future and/or based on known/past experiences. Those skilled in the art will readily recognize that such planning and re-planning to take into consideration weather conditions, track conditions, other trains on the track, etc., may be considered at any time during the trip wherein the trip plan is adjusted accordingly.

FIG. 5 further discloses other elements that may be part of an embodiment of the present invention. A processor 144 operates to receive information from the locator element 130, track characterizing element 133 and sensors 138. An algorithm 146 operates within the processor 144. The algorithm 146 computes an optimized trip plan based on parameters involving the locomotive 142, train 131, track 134, and objectives of the mission as described herein. In an exemplary embodiment the trip plan is established based on models for train behavior as the train 131 moves along the track 134 as a solution of non-linear differential equations derived from applicable physics with simplifying assumptions that are provided in the algorithm. The algorithm 146 has access to the information from the locator element 130, track characterizing element 133 and/or sensors 138 to create a trip plan minimizing fuel consumption of a locomotive consist 142, minimizing emissions of a locomotive consist 142, establishing a desired trip time, and/or ensuring proper crew operating time aboard the locomotive consist 42. In an exemplary embodiment, a driver or controller element, 151 is also provided. As discussed herein the controller element 151 may control the train as it follows the trip plan. In an exemplary embodiment discussed further herein, the controller element 151 makes train operating decisions autonomously. In another exemplary embodiment the operator may be involved with directing the train to follow or deviate from the trip plan in his discretion.

In one embodiment of the present invention the trip plan is modifiable in real time as the plan is being executed. This includes creating the initial plan for a long distance trip, owing to the complexity of the plan optimization algorithm. When a total length of a trip profile exceeds a given distance, an algorithm 46 may be used to segment the mission by dividing the mission into waypoints. Though only a single algorithm 146 is discussed, those skilled in the art will readily recognize that more than one algorithm may be used and that such multiple algorithms are linked to create the trip plan.

The trip waypoints may include natural locations where the train 131 stops, such as, but not limited to, single mainline sidings for a meet with opposing traffic or for a pass with a train behind the current train, a yard siding, an industrial spur where cars are picked up and set out and locations of planned maintenance work. At such waypoints the train 131 may be required to be at the location at a scheduled time, stopped or moving with speed in a specified range. The time duration from arrival to departure at waypoints is called dwell time.

In an exemplary embodiment, the present invention is able to break down a longer trip into smaller segments according to a systematic process. Each segment can be somewhat arbitrary in length, but is typically picked at a natural location such as a stop or significant speed restriction, or at key waypoints or mileposts that define junctions with other routes. Given a partition or segment selected in this way, a driving profile is created for each segment of track as a function of travel time taken as an independent variable, such as shown in FIG. 6. The fuel used/travel-time tradeoff associated with each segment can be computed prior to the train 131 reaching that segment of track. A total trip plan can therefore be created from the driving profiles created for each segment. In one embodiment the invention optimally distributes travel time among all segments of the trip so that the total trip time required is satisfied and total fuel consumed over all the segments is minimized. An exemplary three segment trip is disclosed in FIG. 8 and discussed below. Those skilled in the art will recognize however, though segments are discussed, the trip plan may comprise a single segment representing the complete trip.

FIG. 6 depicts an exemplary embodiment of a fuel-use/travel time curve. As mentioned previously, such a curve 150 is created when calculating an optimal trip profile for various travel times for each segment. That is, for a given travel time 151, fuel used 152 is the result of a detailed driving profile computed as described above. Once travel times for each segment are allocated, a power/speed plan is determined for each segment from the previously computed solutions. If there are any waypoint speed constraints between the segments, such as, but not limited to, a change in a speed limit, they are matched during creation of the optimal trip profile. If speed restrictions change only within a single segment, the fuel use/travel-time curve 150 has to be re-computed for only the segment changed. This process reduces the time required for re-calculating more parts, or segments, of the trip. If the locomotive consist or train changes significantly along the route, e.g. loss of a locomotive or pickup or set-out of railcars, then driving profiles for all subsequent segments must be recomputed creating new instances of the curve 150. These new curves 150 are then used along with new schedule objectives to plan the remaining trip.

Once a trip plan is created as discussed above, a trajectory of speed and power versus distance allows the train to reach a destination with minimum fuel and/or emissions at the required trip time. There are several techniques for executing the trip plan. As provided below in more detail, in one exemplary embodiment of a coaching mode, the present invention displays control information to the operator. The operator follows the information to achieve the required power and speed as determined according to the optimal trip plan. Thus in this mode the operator is provided with operating suggestions for use in driving the train. In another exemplary embodiment, control actions to accelerate the train or maintain a constant speed are performed by the present invention. However, when the train 131 must be slowed, the operator is responsible for applying brakes by controlling a braking system 152. In another exemplary embodiment, the present invention commands power and braking actions as required to follow the desired speed-distance path.

Feedback control strategies are used to correct the power control sequence in the profile to account for such events as, but not limited to, train load variations caused by fluctuating head winds and/or tail winds. Another such error may be caused by an error in train parameters, such as, but not limited to, train mass and/or drag, as compared with assumptions in the optimized trip plan. A third type of error may occur due to incorrect information in the track database 136. Another possible error may involve un-modeled performance differences due to the locomotive engine, traction motor thermal deration and/or other factors. Feedback control strategies compare the actual speed as a fumction of position with the speed in the desired optimal profile. Based on this difference, a correction to the optimal power profile is added to drive the actual velocity toward the optimal profile. To assure stable regulation, a compensation algorithm may be provided that filters the feedback speeds into power corrections to assure closed-loop performance stability. Compensation may include standard dynamic compensation as used by those skilled in the art of control system design to meet performance objectives.

The embodiments of the invention allow the simplest and therefore fastest means to accommodate changes in trip objectives, which is the rule rather than the exception in railroad operations. In an exemplary embodiment, to determine the fuel-optimal trip from point A to point B where there are stops along the way, and for updating the trip for the remainder of the trip once the trip has begun, a sub-optimal decomposition method can be used for finding an optimal trip profile. Using modeling methods, the computation method can find the trip plan with specified travel time and initial and final speeds to satisfy all the speed limits and locomotive capability constraints when there are stops. Though the following discussion is directed to optimizing fuel use, it can also be applied to optimize other factors, such as, but not limited to, emissions, schedule, crew comfort and load impact. The method may be used at the outset in developing a trip plan, and more importantly to adapting to changes in objectives after initiating a trip.

As discussed herein, aspects of the invention may employ a setup as illustrated in the exemplary flow chart depicted in FIG. 7 and as an exemplary three segment example depicted in detail in FIGS. 8. As illustrated, the trip may be broken into two or more segments, T1, T2, and T3, though as discussed herein, it is possible to consider the trip as a single segment. As discussed herein, the segment boundaries may not result in equal-length segments. Instead the segments use natural or mission specific boundaries. Optimal trip plans are pre-computed for each segment. If fuel use versus trip time is the trip object to be met, fuel versus trip time curves are generated for each segment. As discussed herein, the curves may be based on other factors wherein the factors are objectives to be met with a trip plan. When trip time is the parameter being determined, trip time for each segment is computed while satisfying the overall trip time constraints.

FIG. 8 illustrates speed limits for an exemplary three segment 200 mile trip 197. Further illustrated are grade changes over the 200 mile trip 198. A combined chart 199 illustrating curves of fuel used for each segment of the trip over the travel time is also shown.

Using the optimal control setup described previously, the present computation method can find the trip plan with specified travel time and initial and final speeds, to satisfy all the speed limits and locomotive capability constraints when there are stops. Though the following detailed discussion is directed to optimizing fuel use, it can also be applied to optimize other factors as discussed herein, such as, but not limited to, emissions. The method can accommodate desired dwell times at stops and considers constraints on earliest arrival and departure at a location as may be required, for example, in single-track operations where the time to enter or pass a siding is critical.

Embodiments of the present invention find a fuel-optimal trip from distance D₀ to D_M, traveled in time T, with M−1 intermediate stops at D₁, . . . ,D_M−1, and with the arrival and departure times at these stops constrained by

t_min(i)≦t_αrr(D_i)≦t_max(i)−Δt_i

t_αrr(D_i)+Δt_i≦t_dep(D_i)≦t_max(i) i=1, . . . M−1

where t_αrr(D_i), t_dep(D_i), and Δt_i are the arrival, departure, and minimum stop time at the i^th stop, respectively. Assuming that fuel-optimality implies minimizing stop time, therefore t_dep(D_i)=t_αrr(D_i)+Δt_i which eliminates the second inequality above. Suppose for each i=1, . . . ,M, the fuel-optimal trip from D_i−1 to D_i for travel time t, T_min(i)≦t≦T_max(i), is known. Let F_i(t) be the fuel-use corresponding to this trip. If the travel time from D_j−1 to D_j is denoted T_j, then the arrival time at D_i is given by

$t_{\mathrm{arr}}\left(D_i\right)=\sum _{j=1}^i\left(T_j+\Delta t_{j-1}\right)$

where Δt₀ is defined to be zero. The fuel-optimal trip from D₀ to D_M for travel time T is then obtained by finding T_i, i=1, . . . ,M, which minimizes

$\sum _{i=1}^MF_i\left(T_i\right)T_{\min }\left(i\right)\le T_i\le T_{\max }\left(i\right)$

subject to

$t_{\min }\left(i\right)\le \sum _{j=1}^i\left(T_j+\Delta t_{j-1}\right)\le t_{\max }\left(i\right)-\Delta t_ii=1,\dots ,M-1$ $\sum _{j=1}^M\left(T_j+\Delta t_{j-1}\right)=T$

Once a trip is underway, the issue is re-determining the fuel-optimal solution for the remainder of the trip (originally from D₀ to D_M in time T) as the trip is traveled, but where disturbances preclude following the fuel-optimal solution. Let the current distance and speed be x and v, respectively, where D_i−1<x≦D_i. Also, let the current time since the beginning of the trip be t_act. Then the fuel-optimal solution for the remainder of the trip from x to D_M, which retains the original arrival time at D_M, is obtained by finding

{tilde over (T)}_i, T_j, j=i+1, . . . M, which minimizes

${\tilde{F}}_i\left({\tilde{T}}_i,x,v\right)+\sum _{j=i+1}^MF_j\left(T_j\right)$

subject to

$t_{\min }\left(i\right)\le t_{\mathrm{act}}+{\tilde{T}}_i\le t_{\max }\left(i\right)-\Delta t_i$ $t_{\min }\left(k\right)\le t_{\mathrm{act}}+{\tilde{T}}_i+\sum _{j=i+1}^k\left(T_j+\Delta t_{j-1}\right)\le t_{\max }\left(k\right)-\Delta t_k$ $k=i+1,\dots ,M-1$ $t_{\mathrm{act}}+{\tilde{T}}_i+\sum _{j=i+1}^M\left(T_j+\Delta t_{j-1}\right)=T$

Here, {tilde over (F)}_i(t, x, v) is the fuel-used of the optimal trip from x to D_i, traveled in time t, with initial speed at x of v.

As discussed above, an exemplary process to enable more efficient re-planning constructs the optimal solution for a stop-to-stop trip from partitioned segments. For the trip from D_i−1 to D_i, with travel time T_i, choose a set of intermediate points D_ij, j=1, . . . , N_i−1. Let D_i0=D_i−1 and D_iNi=D_i. Then express the fuel-use for the optimal trip from D_i−1 to D_i as

$F_i\left(t\right)=\sum _{j=1}^{N_i}f_{\mathrm{ij}}\left(t_{\mathrm{ij}}-t_{i,j-1},v_{i,j-1},v_{\mathrm{ij}}\right)$

where f_ij(t, v_i,j−1, v_ij) is the fuel-use for the optimal trip from D_ij−1 to D_ij, traveled in time t, with initial and final speeds of v_ij−1 and v_ij. Furthermore, t_ij is the time in the optimal trip corresponding to distance D_ij. By definition, t_iNi−t_i0=T_i. Since the train is stopped at D_i0 and D_iN, v_i0=v_iNi=0.

The above expression enables the function F_i(t) to be alternatively determined by first determining the functions f_ij(·),1≦j≦N_i, then finding τ_ij,1≦j≦N_iand v_ij,1≦j<N_i, that minimize

$F_i\left(t\right)=\sum _{j=1}^{N_i}f_{\mathrm{ij}}\left({\tau }_{\mathrm{ij}},v_{i,j-1},v_{\mathrm{ij}}\right)$

subject to

$\sum _{j=1}^{N_i}{\tau }_{\mathrm{ij}}=T_i$ $v_{\min }\left(i,j\right)\le v_{\mathrm{ij}}\le v_{\max }\left(i,j\right)j=1,\dots ,N_i-1$ $v_{i0}=v_{{\mathrm{iN}}_i}=0$

By choosing D_ij (e.g., at speed restrictions or meeting points), v_max(i,j)−v_min(i,j) can be minimized, thus minimizing the domain over which f_ij( ) needs to be known.

Based on the partitioning described above, a simpler suboptimal re-planning approach than that described above restricts re-planning to times when the train is at distance points D_ij,1≦i≦M,1≦j≦N_i. At point D_ij, the new optimal trip from D_ij to D_M can be determined by finding τ_ik, j<k≦N_i, v_ik, j<k<N_i and

τ_ik, i<m≦M, 1≦n≦N_m, v_min, i<m≦M, 1≦n<N_m, which minimize

$\sum _{k=j+1}^{N_i}f_{\mathrm{ik}}\left({\tau }_{\mathrm{ik}},v_{i,k-1},v_{\mathrm{ik}}\right)+\sum _{m=i+1}^M\sum _{n=1}^{N_m}f_{\mathrm{mn}}\left({\tau }_{\mathrm{mn}},v_{m,n-1},v_{\mathrm{mn}}\right)$

subject to

$t_{\min }\left(i\right)\le t_{\mathrm{act}}+\sum _{k=j+1}^{N_i}{\tau }_{\mathrm{ik}}\le t_{\max }\left(i\right)-\Delta t_i$ $t_{\min }\left(n\right)\le t_{\mathrm{act}}+\sum _{k=j+1}^{N_i}{\tau }_{\mathrm{ik}}+\sum _{m=i+1}^n\left(T_m+\Delta t_{m-1}\right)\le t_{\max }\left(n\right)-\Delta t_n$ $n=i+1,\dots ,M-1$ $t_{\mathrm{act}}+\sum _{k=j+1}^{N_i}{\tau }_{\mathrm{ik}}+\sum _{m=i+1}^M\left(T_m+\Delta t_{m-1}\right)=T$

where

$T_m=\sum _{n=1}^{N_m}{\tau }_{\mathrm{mn}}$

A further simplification is obtained by waiting on the re-computation of T_m, i<m≦M, until distance point D_i is reached. In this way at points D_ij between D_i−1, and D_i, the minimization above needs to be performed only over τ_ik, j<k≦N_i, v_ik, j<k<N_i. T_i is increased as needed to accommodate any longer actual travel time from D_i−1 to D_ij than planned. This increase is later compensated, if possible, by the re-computation of T_mi<m≦M, at distance point D_i.

With respect to the closed-loop configuration disclosed above, the total input energy required to move a train 131 from point A to point B consists of the sum of four components, specifically difference in kinetic energy between the points A and B; difference in potential energy between the points A and B; energy loss due to friction and other drag losses; and energy dissipated by the application of the brakes. Assuming the start and end speeds are equal (e.g., stationary) the first component is zero. Furthermore, the second component is independent of driving strategy. Thus, it suffices to minimize the sum of the last two components.

Following a constant speed profile minimizes drag loss. Following a constant speed profile also minimizes total energy input when braking is not needed to maintain constant speed. However, if braking is required to maintain constant speed, applying braking just to maintain constant speed will most likely increase total required energy because of the need to replenish the energy dissipated by the brakes. A possibility exists that some braking may actually reduce total energy usage if the additional brake loss is more than offset by the resultant decrease in drag loss caused by braking, by reducing speed variation.

After completing a re-plan from the collection of events described above, the new optimal notch /speed plan can be followed using the closed loop control described herein. However, in some situations there may not be enough time to carry out the segment-decomposed planning described above, and particularly when there are critical speed restrictions that must be respected, an alternative may be preferred. Aspects of the present invention accomplish this with an algorithm referred to as “smart cruise control”. The smart cruise control algorithm is an efficient process for generating, on the fly, an energy-efficient (hence fuel-efficient) sub-optimal prescription for driving the train 131 over a known terrain. This algorithm assumes knowledge of the position of the train 131 along the track 134 at all times, as well as knowledge of the grade and curvature of the track versus position. The method relies on a point-mass model for the motion of the train 131, whose parameters may be adaptively estimated from online measurements of train motion as described earlier.

The smart cruise control algorithm has three principal components, specifically a modified speed limit profile that serves as an energy-efficient guide around speed limit reductions; an ideal throttle or dynamic brake setting profile that attempts to balance minimizing speed variations and braking; and a mechanism for combining the latter two components to produce a notch command, employing a speed feedback loop to compensate for mismatches of modeled parameters when compared to reality parameters. Smart cruise control can accommodate strategies in the embodiments of the invention without active braking (i.e. the driver is signaled and assumed to provide the requisite braking) or a variant that does provide active braking.

With respect to the cruise control algorithm that does not control dynamic braking, the three exemplary components are a modified speed limit profile that serves as an energy-efficient guide around speed limit reductions, a notification signal to notify the operator when braking should be activated, an ideal throttle profile that attempts to balance minimizing speed variations and notifying the operator to apply brakes and a mechanism employing a feedback loop to compensate for mismatches of model parameters to reality parameters.

One embodiment of the present invention includes an approach to identify key parameter values of the train 131. For example, with respect to estimating train mass, a Kalman filter and a recursive least-squares approach may be utilized to detect errors that may develop over time.

FIG. 9 depicts an exemplary flow chart of the present invention. As discussed previously, a remote facility, such as a dispatch center 160 can provide information for use by the steps of the flow chart. As illustrated, such information is provided to an executive control element 162. Also supplied to the executive control element 162 is a locomotive modeling information database 163, a track information database 136 such as, but not limited to, track grade information and speed limit information, estimated train parameters such as, but not limited to, train weight and drag coefficients, and fuel rate tables from a fuel rate estimator 164. The executive control element 162 supplies information to the planner 112, which is disclosed in more detail in FIG. 3. Once a trip plan has been calculated, the plan is supplied to a driving advisor, driver or controller element 151. The trip plan is also supplied to the executive control element 162 so that it can compare the trip when other new data is provided.

As discussed above, the driving advisor 151 can automatically set a notch power, either a pre-established notch setting or an optimum continuous notch power value. In addition to supplying a speed command to the locomotive 131, a display 168 is provided so that the operator can view what the planner has recommended. The operator also has access to a control panel 169. Through the control panel 169 the operator can decide whether to apply the notch power recommended. Towards this end, the operator may limit a targeted or recommended power. That is, at any time the operator always has final authority over the power setting for operation of the locomotive consist, including whether to apply brakes if the trip plan recommends slowing the train 131. For example, if operating in dark territory, or where information from wayside equipment cannot electronically transmit information to a train and instead the operator views visual signals from the wayside equipment, the operator inputs commands based on information contained in the track database and visual signals from the wayside equipment. Based on how the train 131 is functioning, information regarding fuel measurement is supplied to the fuel rate estimator 164. Since direct measurement of fuel flows is not typically available in a locomotive consist, all information on fuel consumed to a point in the trip and projections into the future if the optimal plans are followed use calibrated physics models, such as those used in developing the optimal plans. For example, such predictions may include, but are not limited to, the use of measured gross horse-power and known fuel characteristics to derive the cumulative fuel used.

The train 131 also has a locator device 130 such as a GPS sensor, as discussed above. Information is supplied to the train parameters estimator 165. Such information may include, but is not limited to, GPS sensor data, tractive/braking effort data, braking status data, speed and any changes in speed data. With information regarding grade and speed limit information, train weight and drag coefficients information is supplied to the executive control element 162.

The embodiments of the present invention may also allow the use of continuously variable power throughout the optimization planning and closed loop control implementation. In a conventional locomotive, power is typically quantized to eight discrete levels. Modem locomotives can realize continuous variation in horsepower that may be incorporated into the previously described optimization methods. With continuous power, the locomotive 142 can further optimize operating conditions, e.g., by minimizing auxiliary loads and power transmission losses, and fine tuning engine horsepower regions of optimum efficiency or to points of increased emissions margins. Example include, but are not limited to, minimizing cooling system losses, adjusting alternator voltages, adjusting engine speeds, and reducing number of powered axles. Further, the locomotive 142 may use the on-board track database 36 and the forecasted performance requirements to minimize auxiliary loads and power transmission losses to provide optimum efficiency for the target fuel consumption/emissions. Examples include, but are not limited to, reducing a number of powered axles on flat terrain and pre-cooling the locomotive engine prior to entering a tunnel.

In one embodiment, the present invention may also use the on-board track database 136 and the forecasted performance to adjust the locomotive performance, such as to ensure that the train has sufficient speed as it approaches a hill and/or tunnel. For example, this could be expressed as a speed constraint at a particular location that becomes part of the optimal plan generation created solving the equation (OP). Additionally, one embodiment may incorporate train-handling rules, such as, but not limited to, tractive effort ramp rates and maximum braking effort ramp rates. These may incorporated directly into the formulation for optimum trip profile or alternatively incorporated into the closed loop regulator used to control power application to achieve the target speed.

In a preferred embodiment the present invention is installed only on a lead locomotive of the train consist. Even though in one embodiment the present invention is not dependent on data or interactions with other locomotives in the train, it may be integrated with a consist manager, as disclosed in U.S. Pat. No. 6,691,957 and patent application Ser. No. 10/429,596 (both owned by the Assignee and both incorporated by reference), functionality and/or a consist optimizer functionality to improve efficiency. Interaction with multiple trains is not precluded as illustrated by the example of dispatch arbitrating two “independently optimized” trains described herein.

In a train utilizing a consist manager, the lead locomotive in a locomotive consist may operate at a different notch power setting than other locomotives in that consist. The other locomotives in the consist operate at the same notch power setting. In one embodiment, the present invention may be utilized in conjunction with the consist manager to command different notch power settings for the locomotives in the consist. Thus based on this embodiment, since the consist manager divides a locomotive consist into two groups, lead locomotive and trailing units, the lead locomotive can be commanded to operate at a certain notch power and the trailing locomotives can be commanded to operate at a different notch power, each trailing locomotive not necessarily operating at the same notch power.

Likewise, when a consist optimizer is used with a locomotive consist, in one embodiment the present invention can be used in conjunction with the consist optimizer to determine notch power for each locomotive in the locomotive consist. For example, suppose that a trip plan recommends a notch power setting of four for the locomotive consist. Based on the location of the train, the consist optimizer can use this information to determine the notch power setting for each locomotive in the consist. In this implementation, the efficiency of setting notch power settings over intra-train communication channels is improved. Furthermore, implementation of this configuration may be performed utilizing the distributed power communications system.

An embodiment of the present invention may be used with a distributed power train such as illustrated in FIGS. 1 and 2 and described above. Absent the teachings of the present inventions, a distributed power train can be operated in a normal or an independent mode. In the normal mode, the operator in the lead unit 14 of the lead consist 12A commands each of the locomotive consists 12A, 12B and 12C to operate at the same notch power or to apply the same braking effort as applied by the lead locomotive 14. If the lead locomotive 14 of the lead consist 12A commands motoring at notch N8, all other locomotives 15-18 are commanded to motoring at notch N8 by a signal transmitted over the communications system 10 from the lead locomotive 14.

In the independent mode, the distributed power train is segregated into two independent locomotive consist groups, i.e., a front group and a back group by the operator when the communications system is set-up. For example, the locomotive consist 12A is configured as the front group and the locomotive consists 12B and 12C are configured as the back group. Each of the front and back groups can be commanded to different operation. For example, as the train crests a mountaintop, the front group locomotives 14 and 15 in the lead consist 12A (on the downward slope of the mountain) are commanded to progressively lower notch settings (including perhaps a braking setting) as the front group descends the grade. The back group locomotives 16, 17 and 18 in the remote consists 12B and 12C (on the upward slope of the mountain) remain in a motoring mode until the end of the train crests the mountain. The division of the train into front and back groups and differential control of the two groups can minimize tensile forces on the mechanical couplers that connect the railcars and the locomotives. According to the prior art, operating the distributed power train in independent mode requires the operator to manually command the front group locomotives and the back group locomotives via a display in the lead locomotive.

Using the physics based planning model, train set-up information (including the performance capabilities and location of each locomotive in the train, which can be determined by the operator during set-up or automatically by one embodiment of the trip optimizer), on-board track database information, operating rules, location determination systems, real-time closed loop power/brake controls, sensor feedback, etc. (as described elsewhere herein), one embodiment of the trip optimizer system of the present invention determines optimum operation for each locomotive 14-18 to achieve optimal train operation. Responsive to the optimized trip plan, the trip optimizer controls the distributed power train by independently controlling each locomotive, whether in the same or a different locomotive consist. Thus the trip optimizer, as applied to a distributed power train, provides more granular train control and optimizes train performance to the individual locomotive level. Unlike the prior art distributed power trains in which the locomotives are segregated and controlled according to a front group and a back group, independent trip optimizer control of the individual locomotives according to the aspects of the present invention segregates the train into multiple consists (where by electing to group certain locomotives together or control each locomotive independently, the number independently controlled locomotives can include any number up to the total number of locomotives in the train). Thus the performance of the train and its individual locomotives can be controlled to improve fuel consumption, for example.

The trip optimizer and/or the lead unit operator can command each individual locomotive or one or more locomotive consists to operate at different notch and/or braking settings to optimize the performance of each individual locomotive. If desired, of course, all locomotives can be operated at the same notch power or brake setting. The notch power or braking settings are communicated over the distributed communications system 10 to the remote locomotives 15-18 for execution at each remote locomotive. Thus application of the trip optimizer concepts to a distributed power train allows the train to be segregated into smaller controlled sections (creating multiple, individually-controlled but coupled trains) to improve train operation and control, including a reduction in in-train forces, simplification of in-train force management, improved control over stopping distances and more optimal performance for each locomotive. Further, longer and/or heavier trains can be better and more safely controlled when the locomotives are subject to independent and individual control.

Since operating parameters of the train are affected by the location of the locomotives in the train and the number of railcars between the locomotives, independent control of the locomotives reduces the affects of these factors on train performance and control. The trip optimizer also controls train acceleration and deceleration by raising or lowering the notch position of one or more of the remote locomotives by suitable commands sent over the communications system 10, promoting economy, flexibility in train makeup, train force reduction, increased train sizes, etc.

Independent locomotive control also offers additional degrees of freedom for use by the trip optimizing algorithm. Additional objectives or constraints relating to in-train forces can therefore be incorporated into the performance function for optimization.

A dynamic brake modem link can also be used to provide the optimized trip control information to each locomotive of the train. This link is a serial high frequency communications signal imposed on a DC voltage carried by a trainline that connects the locomotives of the train. The modem carries signals to the operator in the lead locomotive that indicate the application of dynamic brakes at one or more remote locomotives.

According to this embodiment of the trip optimizer, various train operating parameters can be optimized, including fuel consumption, emissions generated, sand control, application of tractive and braking efforts and air brake applications. The train length, in-train force limits and stopping distances, which are constrained by the position and control of the locomotives in the consist and the number of cars in the train between locomotives, can also be optimized. The embodiment thus allows the railroad to run longer and/or heavier trains and provides better performance as measured by costs, such as the cost of fuel and sand. Increased train length increases railroad network throughput, without sacrificing train handling characteristics.

Furthermore, as discussed with respect to other embodiments, the present inventions as applied to distributed power trains may be used for continuous corrections and re-planning based on previous or expected railroad crossings, grade changes, approaching sidings, approaching depot yards and approaching fuel stations where each locomotive in the consist may require a different control operation. For example, if the train is coming over a hill, the lead locomotive may enter a braking mode whereas the remote locomotives, having not reached the peak of the hill may have to remain in a motoring state.

FIGS. 10, 11 and 12 depict exemplary illustrations of dynamic displays for use by the operator. FIG. 8 illustrates a provided trip profile 172. Within the profile a location 173 of the locomotive is indicated. Such information as train length 205 and the number of cars 206 in the train is provided. Elements are also provided regarding track grade 207, curve and wayside elements 208, including bridge location 209 and train speed 210. The display 168 allows the operator to view such information and also see where the train is along the route. Information pertaining to distance and/or estimated time of arrival to such locations as crossings 212, signals 214, speed changes 216, landmarks 218 and destinations 220 is provided. An arrival time management tool 225 is also provided to allow the user to determine the fuel savings realized during the trip. The operator has the ability to vary arrival times 227 and witness how this affects the fuel savings. As discussed herein, those skilled in the art will recognize that fuel saving is an exemplary example of only one objective that can be reviewed with a management tool. Thus, depending on the parameter being viewed, other parameters, discussed herein can be viewed and evaluated with a management tool visible to the operator. The operator is also provided with information regarding the time duration that the crew has been operating the train. In exemplary embodiments time and distance information may either be illustrated as the time and/or distance until a particular event and/or location or it may provide a total elapsed time.

As illustrated in FIG. 11 an exemplary display provides information about consist data 230, an events and situation graphic 232, an arrival time management tool 234 and action keys 236. Similar information as discussed above is provided in this display as well. This display 168 also provides action keys 238 to allow the operator to re-plan as well as to disengage 240 the control features of the present inventions.

FIG. 12 depicts another exemplary embodiment of the display. Typical information for a modern locomotive including air-brake status 172, analog speedometer with digital inset 174, and information about tractive effort in pounds force (or traction amps for DC locomotives) is visible. An indicator 14 shows the current optimal speed in the plan being executed as well as an accelerometer graphic to supplement the readout in mph/minute. Important new data for optimal plan execution is in the center of the screen, including a rolling strip graphic 176 with optimal speed and notch setting versus distance compared to the current history of these variables. In this exemplary embodiment, location of the train is derived using the locator element. As illustrated, the location is provided by identifying how far the train is away from its final destination, an absolute position, an initial destination, an intermediate point and/or an operator input.

The strip chart provides a look-ahead to changes in speed required to follow the optimal plan, which is useful in manual control and monitors plan versus actual during automatic control. As discussed herein, such as when in the coaching mode, the operator can either follow the notch or speed suggested by the embodiments of the invention. The vertical bar gives a graphic of desired and actual notch, which are also displayed digitally below the strip chart. When continuous notch power is utilized, as discussed above, the display will simply round to closest discrete equivalent, the display may be an analog display so that an analog equivalent or a percentage or actual horse power/tractive effort is displayed.

Critical information on trip status is displayed on the screen, and shows the current grade the train is encountering 188, either by the lead locomotive, a location elsewhere along the train or an average over the train length. A cumulative distance traveled in the plan 190, cumulative fuel used 192, the location of or the distance to the next stop as planned 194 and current and projected arrival time 196 at the next stop are also disclosed. The display 168 also shows the maximum possible time to destination with the computed plans available. If a later arrival is required, a re-plan is executed. Delta plan data shows status for fuel and schedule ahead or behind the current optimal plan. Negative numbers mean less fuel or early compared to plan, positive numbers mean more fuel or late compared to plan. Typically these parameters trade-off in opposite directions (slowing down to save fuel makes the train late and conversely).

At all times these displays l68 gives the operator a snapshot of the trip status with respect to the currently instituted driving plan. This display is for illustrative purpose only as there are many other ways of displaying/conveying this information to the operator and/or dispatch. Towards this end, any other items of information disclosed above can be added to the display to provide a display that is different than those disclosed.

Other features that may be included in different embodiments of the present invention include, but are not limited to, generating of data logs and reports. This information may be stored on the train and downloaded to an off-board system. The downloads may occur via manual and/or wireless transmission. This information may also be viewable by the operator via the locomotive display. The data may include such information as, but not limited to, operator inputs, time system is operational, fuel saved, fuel imbalance across locomotives in the train, train journey off course and system diagnostic issues, such as a GPS sensor malfunction.

Since trip plans may also take into consideration allowable crew operation time, an embodiment of the present invention may take such information into consideration as a trip is planned. For example, if the maximum time a crew may operate is eight hours, then the trip can be fashioned to include stopping location for a new crew to replace the present crew. Such specified stopping locations may include, but are not limited to rail yards, meet/pass locations, etc. If, as the trip progresses, the trip time may be exceeded, the present invention may be overridden by the operator to meet other criteria as determined by the operator. Ultimately, regardless of the operating conditions of the train, such as but not limited to high load, low speed, train stretch conditions, etc., the operator remains in control to command a safe speed and/or operating condition of the train.

Using the aspects of the present invention, the train may operate in a plurality of different operational concepts. In one operational concept the present invention provides commands for commanding propulsion and dynamic braking. The operator handles all other train functions. In another operational concept, the present invention provides commands for commanding propulsion only. The operator handles dynamic braking and all other train functions. In yet another operational concept, the present invention provides commands for commanding propulsion, dynamic braking and application of the airbrake. The operator handles all other train fuictions.

The present inventions may also notify the operator of upcoming items of interest or actions to be taken, such as forecasting logic of the present invention, the continuous corrections and re-planning to the optimized trip plan, the track database. The operator can also be notified of upcoming crossings, signals, grade changes, brake actions, sidings, rail yards, fuel stations, etc. These notifications may occur audibly and/or through the operator interface.

Specifically using the physics based planning model, train set-up information, on-board track database, on-board operating rules, location determination system, real-time closed loop power/brake control, and sensor feedback, the system presents and/or notify the operator of required actions. The notification can be visual and/or audible. Examples include notification of crossings that require the operator to activate the locomotive horn and/or bell and “silent” crossings that do not require the operator to activate the locomotive horn or bell.

In another exemplary embodiment, using the physics based planning model discussed above, train set-up information, on-board track database, on-board operating rules, location determination system, real-time closed power/brake control, and sensor feedback, the present invention may present the operator information (e.g. a gauge on display) that allows the operator to see when the train will arrive at various locations, as illustrated in FIG. 11. The system allows the operator to adjust the trip plan (target arrival time). This information (actual estimated arrival time or information needed to derive off-board) can also be communicated to the dispatch center to allow the dispatcher or dispatch system to adjust the target arrival times. This allows the system to quickly adjust and optimize for the appropriate target function (for example trading off speed and fuel usage).

This written description of the various embodiments of the invention uses examples to disclose these embodiments, including the best mode, and also to enable any person skilled in the art to make and use the embodiments of the invention. The patentable scope of these embodiments are defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims. For example, although described in the context of a railroad network over which trains comprising locomotives and railcars operate, the teachings of the invention are also applicable to other railway and rail-based systems and vehicles including, but not limited to, interurban trains, people movers, shuttles and trams.

Claims

1. A system for operating a railway vehicle comprising a lead powered unit and a non-lead powered unit during a trip along a track, the system comprising:

a first element for determining a location of the vehicle or a time from the beginning of a current trip;

a processor operable to receive information from the first element; and

an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of one or both of the lead unit and the non-lead unit in accordance with one or more operational criteria for one or more of the vehicle, the lead unit and the non-lead unit.

2. The system of claim 1 wherein the vehicle comprises a train, and wherein the lead unit comprises a lead locomotive and the non-lead unit comprises a remote locomotive.

3. The system of claim 2 further comprising one or more railcars between the lead locomotive and the remote locomotive.

4. The system of claim 1 wherein the trip plan comprises tractive effort applications and braking effort applications for the lead and the non-lead units.

5. The system of claim 1 wherein the first element determines information for segments of the track.

6. The system of claim 1 wherein the one or more operational criteria comprises minimizing a cost element associated with operation of the vehicle, the operation of the lead unit or the operation of the non-lead unit.

7. The system of claim 1 farther comprising a control element in each of the lead and the non-lead units wherein the processor determines a control parameter for the lead and the non-lead units, the control parameter supplied to the control element in each of the lead and the non-lead units for controlling the lead and the non-lead units according to the trip plan.

8. The system of claim 7 further comprising a communications link between the lead unit and the non-lead units wherein the control parameter is supplied to the non-lead unit over the communications link.

9. The system of claim 7 further comprising a communications link between the lead and the non-lead units wherein the processor is disposed on the lead unit and the control parameter is supplied from the lead unit to the non-lead unit over the communications link.

10. The system of claim 7 wherein the lead unit and the non-lead unit are independently controlled according to different control parameters.

11. The system of claim 10 wherein the different control parameters are intended to independently optimize performance of the lead unit and each of the non-lead unit according to a cost element.

12. The system of claim 7 wherein the control element autonomously directs the vehicle to follow the trip plan.

13. The system of claim 7 wherein the control parameter comprises a notch setting.

14. The system of claim 1 wherein an operator directs the train in accordance with the trip plan.

15. The system of claim 1 wherein the algorithm updates the trip plan responsive to the information received from the first element during the trip.

16. The system of claim 1 wherein the non-lead unit comprises a-first non-lead unit and a second non-lead unit, each of the lead unit, wherein each of the first non-lead unit and the second non-lead unit is operationally classified into a first group or a second group, and wherein the algorithm determines a first control parameter for the first group and a second different control parameter for the second group.

17. The system of claim 1 wherein the trip plan generates a speed trajectory for the lead unit and the non-lead unit.

18. The system of claim 1 wherein the algorithm comprises independent constraints related to independent control of the lead unit and the non-lead unit.

19. The system of claim 1 wherein the trip plan that optimizes performance comprises optimizing at least one of fuel consumption, emissions generated, sand control and in-train forces limits of the lead unit and the non-lead unit.

20. The system of claim 1 wherein the algorithm updates the trip plan as the train progresses on a trip.

21. The system of claim 1 further comprising a sensor for measuring an operating condition of the lead unit or the non-lead unit wherein the processor is operable to receive information from the sensor.

22. The system of claim 1 wherein the first element comprises a track characterization element that determines information about at least one of a change in speed restriction on the track, a change in track grade, a change in track curvature and a change in a traffic pattern on a track segment.

23. The system of claim 1 further comprising a control element in each of the lead unit and the non-lead unit wherein the processor determines a power parameter for the lead unit and the non-lead unit, the power parameter supplied to the control element in each of the lead unit and the non-lead unit for controlling the lead unit and the non-lead unit, and wherein the power parameter is selected from a continuous range of power parameters or from a plurality of discrete power parameters.

24. The system of claim 1 further comprising an input device in communication with the processor for transferring information to the processor, the input device further comprising a non-lead unit location, a roadside device or a user.

25. The system of claim 1 further comprising a database in communication with the processor comprising operating information for the lead unit and the non-lead unit.

26. The system of claim 1 wherein the vehicle further comprises a plurality of non-lead units each independently controllable from the lead unit.

27. The system of claim 26 wherein independent control of each one of the plurality of non-lead units permits performance optimization of each one of the plurality of non-lead units.

28. A method for operating a railway vehicle comprising a lead unit and a non-lead unit during a trip along a track, the method comprising:

determining vehicle operating parameters and operating constraints; and

executing an algorithm according to the operating parameters and operating constraints to create a trip plan for the vehicle that separately optimizes performance of the lead unit and the non-lead unit, wherein execution of the trip plan permits independent control of the lead unit and the non-lead unit.

29. The method of claim 28 wherein the vehicle comprises a train, and wherein the lead unit comprises a lead locomotive and the non-lead unit comprises a remote locomotive and further comprising one or more railcars between the lead locomotive and the remote locomotive.

30. The method of claim 28 wherein the step of determining further comprises determining a location of the vehicle or a time from the beginning of a current vehicle trip.

31. The method of claim 28 wherein the step of determining further comprises determining track characterization information.

32. The method of claim 28 further comprising determining a speed trajectory for the trip plan and determining from the speed trajectory tractive effort applications and braking effort applications at the lead unit and at the non-lead unit and communicating the tractive effort applications and braking effort applications to the lead unit and the non-lead unit.

33. The method of claim 33 wherein the vehicle further comprises a communications link between the lead unit and the non-lead unit, and wherein the step of executing is performed at the lead unit and the tractive effort applications and braking effort applications are communicated from the lead unit to the non-lead unit over the communications link.

34. The method of claim 28 wherein the trip plan comprises different parameters for controlling operation of the lead unit and the non-lead unit to independently optimize performance of the lead unit and the non-lead unit.

35. The method of claim 34 wherein the optimized performance comprises optimizing at least one of fuel consumption, emissions generated, sand control and in-vehicle force limits.

36. The method of claim 28 wherein the step of determining vehicle operating parameters and operating constraints further comprises determining different operating parameters and operating constraints for the lead unit and the non-lead unit.

37. The method of claim 28 wherein the vehicle further comprises a plurality of non-lead units each independently controllable from the lead unit to optimize performance of each one of the plurality of non-lead units.

38. A computer software code for operating a railway vehicle comprising a computer processor, a lead unit and a non-lead unit during a trip along a track, the computer software code comprising:

a software module for determining vehicle operating parameters and operating constraints; and

a software module for executing an algorithm according to the operating parameters and operating constraints to create a trip plan for the vehicle that independently optimizes performance of the lead unit and the non-lead unit, wherein execution of the trip plan permits independent control of the lead unit and the non-lead unit.

39. The computer software code of claim 38 fuirther comprising a software module for determining a speed trajectory for the trip plan and for determining from the speed trajectory tractive effort applications and braking effort applications at the lead unit and the non-lead unit.

40. The computer software code of claim 39 wherein the vehicle further comprises a communications link between the lead unit and the non-lead unit, and wherein the software module for executing the algorithm is executed on the lead unit, further comprising a software module for communicating the tractive effort applications and the braking effort applications from the lead unit to the non-lead unit over the communications link.

41. The computer software code of claim 38 wherein the trip plan comprises different parameters for controlling operation of the lead unit and the non-lead unit to independently optimize performance of the lead unit and the non-lead unit.

42. The computer software code of claim 41 wherein the optimized performance comprises optimizing at least one of fuel consumption, emissions generated, sand control and in-vehicle forces limits.

43. The computer software code of claim 38 wherein the software module for determining vehicle operating parameters and operating constraints further comprises determining different operating parameters and operating constraints for the lead unit and the non-lead unit.

44. The computer software code of claim 38 wherein the vehicle further comprises a plurality of non-lead units each independently controllable from the lead unit, and wherein the software module for executing the algorithm permits independent control of each one of the plurality of non-lead units to optimize performance of each one of the plurality of non-lead units.