Abstract: A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to generate vehicle-level commands based on received vehicle operation commands. The received vehicle operation commands can comprise input commands corresponding to at least one of an autonomous vehicle (AV) mode of operation or a manual mode of operation. The processor is also programmed to generate target actuator commands based on the vehicle-level commands and transmit the target actuator commands to at least one actuator.

Abstract: A system for estimating a lateral velocity and a longitudinal velocity of a vehicle includes a plurality of sensors for monitoring data indicative of a travel state of the vehicle and one or more controllers in electronic communication with the plurality of sensors. The one or more controllers executes instructions to receive the data indicative of the travel state of the vehicle from the plurality of sensors. The one or more controllers estimate at least one initial estimated state of the vehicle based on the data indicative of the travel state of the vehicle. The one or more controllers fuse together the data indicative of the travel state of the vehicle with the at least one initial estimated state of the vehicle to determine the lateral velocity and a longitudinal velocity of the vehicle based on a single state estimation scheme.

Abstract: A system for adaptive tire force prediction in a motor vehicle includes a control module that executes program code portions that receive real-time static and dynamic data from motor vehicle sensors, that model forces at each tire of the motor vehicle at one or more incremental time steps, that estimate actual forces at each tire of the motor vehicle at each of the one or more incremental time steps, that adaptively predict tire forces at each tire of the motor vehicle at each of the one or more incremental time steps, that generate one or more control commands for actuators of the motor vehicle, that capture discrepancies between real-time force estimations and nominal force calculations at each tire of the motor vehicle, and that apply compensation parameters to reduce tracking errors in the one or more control commands to the one or more actuators of the motor vehicle.

Abstract: A motor vehicle includes first and second drive axles coupled to respective sets of road wheels, torque actuators inclusive of rotary electric machines configured to transmit respective output torques to the drive axles, and a main controller in communication with the torque actuators. The controller receives vehicle inputs indicative of a total longitudinal and lateral motion request. In response, the controller calculates a total longitudinal torque request and/or a total longitudinal speed request, a yaw rate request, and a lateral velocity request, then determines, using a cost optimization function, a torque vector for allocating the total longitudinal torque request and/or speed request, the yaw rate request, and the lateral velocity request to the drive axles within predetermined constraints. The controller also transmits a closed-loop control signal to each torque actuator or local controllers thereof to apply the torque vector via the drive axles.

Abstract: A propulsion system, control system, and method use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values. The set of possible command values that has the lowest cost is determined and defined as a selected set of command values. In some circumstances, the MPC-determined command value may be replaced by another transmission ratio command based on override inputs. Minimum and maximum transmission ratios are determined based on the override inputs, and a constrained (or arbitrated) transmission ratio is determined therefrom. The constrained or arbitrated transmission ratio is used to determine whether to apply an MPC-determined transmission ratio or a transmission ratio based on the arbitrated transmission ratio to determine an ultimate commanded transmission ratio. Pressure(s) are commanded to a transmission pulley assembly, which is configured to implement the ultimate commanded transmission ratio.

Abstract: A method includes calculating a first estimated state of charge (SOC) of a battery at a first time, receiving a voltage value representing a measured voltage across the battery at a second time, calculating a filter gain at the second time, and calculating a second estimated SOC of the battery at the second time based on the first estimated SOC, the voltage value, and the filter gain. Another method includes storing, in a memory, a library of equivalent circuit models representing a battery, determining an operational mode of a battery based on a load associated with the battery, selecting one of the equivalent circuit models based on the determined operational mode, and calculating a state of charge of charge (SOC) of the battery using the selected equivalent circuit model.

Abstract: A method for controlling a propulsion system of a motor vehicle includes: optimizing both torque control and fuel economy during transient operating conditions; performing a steady state control enable function to identify when steady state operating conditions are present including: determining a commanded axle torque; obtaining a measured actual axle torque; and identifying when the commanded axle torque is substantially equal to the measured actual axle torque and outputting a signal; and further includes: directing the signal output from the control enable function to each of an integral action calculator and a Ym filter; performing an integral action calculation to identify an axle torque integral action; and setting a steady state flag when steady state operating conditions are present which fixes system variables directed to optimizing torque control, temporarily ceasing further optimization of torque control when the steady state flag is set.

Abstract: A propulsion system, control system, and method use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values. The set of possible command values that has the lowest cost is determined and defined as a selected set of command values. In some circumstances, the MPC-determined command value may be replaced by another transmission ratio command based on override inputs. Minimum and maximum transmission ratios are determined based on the override inputs, and a constrained (or arbitrated) transmission ratio is determined therefrom. The constrained or arbitrated transmission ratio is used to determine whether to apply an MPC-determined transmission ratio or a transmission ratio based on the arbitrated transmission ratio to determine an ultimate commanded transmission ratio. Pressure(s) are commanded to a transmission pulley assembly, which is configured to implement the ultimate commanded transmission ratio.

Abstract: A propulsion system, control system, and method are provided for optimizing fuel economy, which use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values of based on a first predetermined weighting value, a second predetermined weighting value, a plurality of predicted values, and a plurality of requested values. The set of possible command values having the lowest cost is determined and defined as a set of selected command values. Fuel is minimized by minimizing engine power for a requested axle power. Accordingly, a fuel consumption rate requested value is determined based on an air-per-cylinder (APC) requested value.

Abstract: A propulsion system, control system, and method are provided for optimizing fuel economy, which use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values based on weighting values, a plurality of predicted values, and a plurality of requested values. The set of possible command values having the lowest cost is determined. A linearized axle torque requested value and a linearized axle torque measured value are each created by subtracting an estimated disturbance. The estimated disturbance is determined based on a model of a relationship between measured engine output torque and measured transmission ratio. The linearized axle torque measured value is used to compute the predicted values, which are used to determine the cost. The linearized axle torque requested value is also used to determine the cost.

Abstract: A propulsion system, control system, and method are provided for optimizing fuel economy, which use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values based on weighting values, a plurality of predicted values, and a plurality of requested values. The set of possible command values having the lowest cost is determined. A linearized axle torque requested value and a linearized axle torque measured value are each created by subtracting an estimated disturbance. The estimated disturbance is determined based on a model of a relationship between measured engine output torque and measured transmission ratio. The linearized axle torque measured value is used to compute the predicted values, which are used to determine the cost. The linearized axle torque requested value is also used to determine the cost.

Abstract: A propulsion system, control system, and method are provided for optimizing fuel economy, which use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values of based on a first predetermined weighting value, a second predetermined weighting value, a plurality of predicted values, and a plurality of requested values. The set of possible command values having the lowest cost is determined and defined as a set of selected command values. Fuel is minimized by minimizing engine power for a requested axle power. Accordingly, a fuel consumption rate requested value is determined based on an air-per-cylinder (APC) requested value.

Abstract: A propulsion system, control system, and method are provided that use model predictive control to generate an initial selected engine output torque value. A minimum torque limit is determined by selecting a minimum acceptable engine output torque. A maximum torque limit is determined by selecting a maximum acceptable engine output torque. A desired engine output torque value is set as: a) the minimum torque limit, if the initial selected engine output torque value is less than the minimum torque limit; b) the maximum torque limit, if the initial selected engine output torque value is greater than the maximum torque limit; or c) the initial selected engine output torque value, if the initial selected engine output torque value is neither greater than the maximum torque limit nor less than the minimum torque limit.

Abstract: A propulsion system, control system, and method are provided for optimizing fuel economy, which use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values of based on a first predetermined weighting value, a second predetermined weighting value, a plurality of predicted values, and a plurality of requested values. The set of possible command values having the lowest cost is determined and defined as a set of selected command values. Arbitration is performed including at least one of the following: A) determining at least one requested value based on arbitrating between a driver requested value and an intervention requested value; and B) determining a desired command value by arbitrating between a selected command value of the set of selected command values and a command intervention value.

Abstract: A propulsion system, control system, and method are provided for optimizing fuel economy, which use model predictive control systems to generate a plurality of sets of possible command values and determine a cost for each set of possible command values of based on a first predetermined weighting value, a second predetermined weighting value, a plurality of predicted values, and a plurality of requested values. The set of possible command values having the lowest cost is determined and defined as a set of selected command values. Arbitration is performed including at least one of the following: A) determining at least one requested value based on arbitrating between a driver requested value and an intervention requested value; and B) determining a desired command value by arbitrating between a selected command value of the set of selected command values and a command intervention value.

Abstract: A propulsion system, control system, and method are provided that use model predictive control to generate an initial selected engine output torque value. A minimum torque limit is determined by selecting a minimum acceptable engine output torque. A maximum torque limit is determined by selecting a maximum acceptable engine output torque. A desired engine output torque value is set as: a) the minimum torque limit, if the initial selected engine output torque value is less than the minimum torque limit; b) the maximum torque limit, if the initial selected engine output torque value is greater than the maximum torque limit; or c) the initial selected engine output torque value, if the initial selected engine output torque value is neither greater than the maximum torque limit nor less than the minimum torque limit.

Abstract: A method includes calculating a first estimated state of charge (SOC) of a battery at a first time, receiving a voltage value representing a measured voltage across the battery at a second time, calculating a filter gain at the second time, and calculating a second estimated SOC of the battery at the second time based on the first estimated SOC, the voltage value, and the filter gain. Another method includes storing, in a memory, a library of equivalent circuit models representing a battery, determining an operational mode of a battery based on a load associated with the battery, selecting one of the equivalent circuit models based on the determined operational mode, and calculating a state of charge of charge (SOC) of the battery using the selected equivalent circuit model.

Abstract: A method includes calculating a first estimated state of charge (SOC) of a battery at a first time, receiving a voltage value representing a measured voltage across the battery at a second time, calculating a filter gain at the second time, and calculating a second estimated SOC of the battery at the second time based on the first estimated SOC, the voltage value, and the filter gain. Another method includes storing, in a memory, a library of equivalent circuit models representing a battery, determining an operational mode of a battery based on a load associated with the battery, selecting one of the equivalent circuit models based on the determined operational mode, and calculating a state of charge of charge (SOC) of the battery using the selected equivalent circuit model.