Abstract: A method and system for estimating the state-of-health of a battery The invention relates to a method for estimating the state-of-health, SoHest, of a battery in a vehicle, the method comprising: determining (100) a first battery property and a battery temperature of a battery in a vehicle; calculating (102) a state-of-health, SoHcalc, of a battery cell based on the determined first battery property using a predetermined model; providing (104) a function f estimating a battery cell degradation rate; updating (106) a state-of health estimated in a previous time step according to SoHest?SoHest+ƒ·dt+K·(SoHcalc?SoHest), where K is a gain factor which is dependent on operating conditions of the vehicle, and wherein K is modified (108) for each time step using a reinforcement learning agent.

Abstract: A method of monitoring a spot quality of an electron beam includes directing the electron beam to a first measurement point in a powder layer a plurality of times, adjusting a focus offset of the electron beam each of the plurality of times the electron beam is directed to the first measurement point, measuring x-ray emissions from the first measurement point each of the plurality of times the electron beam is directed to the first measurement point, and determining a drift in a focus or an intensity of the electron beam based on the measured x-ray emissions.

Abstract: The invention relates to a method (100) for estimating an operating parameter of a battery cell of a battery unit in an electrical propulsion system of a vehicle, the operating parameter being indicative of one of capacity and impedance of the battery cell, the method comprising: selecting (110) at least one battery cell in the battery unit for determining the operating parameter of the battery cell; providing (120) a set of state-of-charge (SOC) estimators, each SOC estimator having a selected operating parameter value for a given time period; and using (130) the set of SOC estimators to determine a value of the operating parameter of the battery cell by performing voltage error minimization.

Abstract: A method for controlling a vehicle travelling along a route is provided.

Abstract: A method of visualizing output data of a traffic planning method for controlling a plurality of vehicles (v1, v2, . . . ), wherein each vehicle occupies one node in a shared set of planning nodes (wp1, wp2, . . . ) and is movable to other nodes along predefined edges between pairs of the nodes, wherein the output data indicates respective planned node occupancies of the vehicles for a sequence of time steps, the method comprising: obtaining a graphical representation of the planning nodes; and in the graphical representation, indicating each vehicle's planned movements between the nodes by linear graphical elements, wherein an appearance parameter of the linear graphical elements has a time variation with respect to the time step, which time variation is common to all vehicles. The appearance parameter may be a line width, line style, color or texture.

Abstract: The present disclosure generally relates to a computer implemented method for operating an autonomous vehicle, specifically in relation to efficient planning of interactions with service providers. The present disclosure also relates to a corresponding control system and computer program product.

Abstract: A traffic planning method for controlling a plurality of vehicles, wherein each vehicle occupies one node in a shared set of planning nodes and is movable to other nodes along predefined edges between pairs of the nodes in accordance with a finite set of motion commands. In the method, initial node occupancies of the vehicles are obtained, and a sequence of motion commands are determined by optimizing a state-action value function which depends on node occupancies s and the motion commands a to be given. The state-action value function includes a command-dependent term, which is updated in each iteration based on a reward function, and a command-independent term, which penalizes node occupancies with too small inter-vehicle gaps and is exempted from said updating.

Abstract: A computer-implemented method of managing a machine-learning, ML, algorithm which is dependent on one or more hyperparameters is described. The method comprises: providing a plurality of instances of the ML algorithm using different values of the hyperparameters; obtaining a plurality of input states; mapping each predefined input to a plurality of outputs using the instances of the ML algorithm; evaluating a predefined quality metric for the outputs; and on the basis of statistics of the quality metric for the outputs, selecting at least one instance of the ML algorithm for continued use. In some embodiments, a technical system is controlled using one primary instance of the ML algorithm. If the selected instance of the ML algorithm is not the primary instance, the primary instance may optionally be replaced by the selected instance.

Abstract: A traffic planning method for controlling a plurality of vehicles is disclosed, wherein each vehicle occupies one node in a shared set of planning nodes and is movable to other nodes along predefined edges between pairs of the nodes in accordance with a finite set of motion commands. The method comprises: obtaining initial node occupancies of the vehicles; from said finite set of motion commands, determining a mean number of feasible motion commands in a neighborhood of the initial node occupancies; determining a search depth d which makes optimal use of a predefined computational budget; and determining a suitable sequence of motion commands by means of an optimization process which considers the search depth d.

Abstract: The invention relates to a method for controlling vehicles (V1-V3) in a mission along a route, comprising—selecting at least two progress control value sets (u, tw), each value set comprising a respective value (u1, u2, u3, tw) of a progress control parameter for at least one of the vehicles, wherein each progress control parameter value influences the rate of progress of the respective vehicle, —determining, for each of the selected progress control value sets, a respective distribution (SoBfut) of the vehicles, if the at least one of the vehicles is controlled based on the respective selected progress control value set (u, tw), so that each progress control value set is correlated to a respective distribution (SoBfut) of the vehicles, —identifying, from the selected progress control value sets, based at least partly on the determinations of the distributions (SOBfut), a progress control value set (u, tw) for controlling the at least one of the vehicles, and—controlling the at least one of the vehicles (V1-V

Abstract: There is provided a method for controlling a plurality of vehicles sharing a set of common resources Each vehicle's motion is controllable by a finite set of predefined commands. The method includes forming subsets of the common resources on the basis of predefined motion constraints of individual ones of the vehicles; partitioning the vehicles into disjoint clusters on the basis of the subsets; executing a tree-based planning algorithm. Each execution including an evaluation of sequences of the predefined commands to be fed to the vehicles in a single cluster and a selection of a preferred sequence of the commands; and feeding the preferred sequence of commands to the vehicles in each cluster.

Abstract: Provided herein is a method for controlling the charging of at least one electrically driven vehicle of a vehicle fleet including a plurality of vehicles, the method includes the step of receiving from a first vehicle entering a charging area and a second vehicle entering the charging area after the first vehicle state of charge information and information to a spatial distance between the first vehicle and the second vehicle, and/or to a time difference of an estimated arrival time at the charging area between the first and the second vehicle. The method further includes the step of making a charging decision on the basis of said information received from said first and second vehicle, wherein said decision is selected from charging the first vehicle, or not charging the first vehicle.

Abstract: The invention relates to a method for controlling a vehicle (1), the method comprising—establishing (S1) a plurality of example situations, wherein each example situation is characterized by a plurality of example situation features, including at least a velocity of the vehicle (VS), a velocity change of the vehicle (VCS), and a road inclination (?S), —determining (S2), for each of plurality of the example situations, a example situation cost (CS) dependent on a cost for operating the vehicle in the respective example situation, —subsequently obtaining (S3) topology data, indicative of a topology of a route (RT) to be travelled by the vehicle, —determining (S4-S8, S41), based at least partly on the route topology, and at least a plurality of the example situation costs (CS), a velocity profile (VP) for the vehicle along the route (RT).

Abstract: The invention relates to a method for controlling charging of at least one electrically driven vehicle of a vehicle fleet including a plurality of vehicles at a charging area, the method includes the step of defining a reference minimum charging energy level for a battery of the vehicle. Further the method includes the step of determining a charging energy level of the battery of the vehicle and comparing the charging energy level with the reference minimum charging energy level. Lastly the method includes assigning a charging command to the vehicle to charge the vehicle if the determined charging energy level of the battery is below said reference minimum charging energy level, and wherein the charging command depends from a charging parameter or a combination of multiple charging parameters if the determined charging energy level of the battery of the vehicle is above said reference minimum charging energy level.

Abstract: The invention provides a method for controlling a plurality of vehicles which are repeating a cycle of driving along a route, which has at least one single vehicle area (SLTA1, . . .

Abstract: The invention relates to a method for determining an operational parameter indicative of the power capability of an energy storage system (ESS) of a vehicle, wherein the method comprises the steps of determining a state temperature of the ESS; determining an acceptable temperature increase of the ESS for a given time period based on the determined state temperature of the ESS and a maximum temperature threshold of ESS, the maximum temperature threshold being indicative of any one of a safety temperature level of the ESS and an operational life time temperature level of the ESS; and determining a maximum operational power level of the ESS for the given time period based on the determined acceptable temperature increase of the ESS.

Abstract: An apparatus for forming at least one three-dimensional article through successive fusion of parts of a powder bed, which parts corresponds to successive cross sections of the three-dimensional article, the apparatus comprising: a powder distributor configured for evenly distributing a layer of powder on top of a work table provided inside a build chamber; and at least one high energy beam source emanating at least one high energy beam configured for fusing the powder layer in selected locations corresponding to the cross section of the three-dimensional article, wherein the apparatus further comprising at least one target area arranged spaced apart from the layer of powder for emanating light when irradiated by the at least one high energy beam.

Abstract: The invention relates to a method for controlling vehicles (V1-V3) in a mission along a route, comprising—selecting at least two progress control value sets (u, tw), each value set comprising a respective value (u1, u2, u3, tw) of a progress control parameter for at least one of the vehicles, wherein each progress control parameter value influences the rate of progress of the respective vehicle, —determining, for each of the selected progress control value sets, a respective distribution (SoBfut) of the vehicles, if the at least one of the vehicles is controlled based on the respective selected progress control value set (u, tw), so that each progress control value set is correlated to a respective distribution (SoBfut) of the vehicles, —identifying, from the selected progress control value sets, based at least partly on the determinations of the distributions (SOBfut), a progress control value set (u, tw) for controlling the at least one of the vehicles, and—controlling the at least one of the vehicles (V1-V

Abstract: The present disclosure generally relates to a computer implemented method for operating a vehicle (104, 106, 108), specifically in relation to efficient transporting of a predefined cargo. The present disclosure also relates to a corresponding arrangement and computer program product.

Abstract: The invention relates to a method for balancing an electrical energy storage module (1) comprising a plurality of units (3) for an electric vehicle (5). The energy storage module (1) is operative according to a first balancing target type. A present operating condition of the energy storage module is determined (S402), and a future operating condition of the energy storage module is determined (S404). Further, there is selected (S406) a second balancing target type among a plurality of predetermined balancing targets (204) based on the present operating condition and the future operating condition, each of the balancing targets being indicative of an energy storage unit characteristic to be balanced in order to achieve the balancing target type. There is further provided to switch (S408) from balancing the energy storage module according to the first balancing target type to balancing the energy storage module according to the second balancing target type.