Abstract: Methods and systems of optimizing battery charging are disclosed. Battery state sensors are used to determine anode overpotential of a battery multiple times during multiple charge cycles. In a first phase, a reinforcement learning model (e.g., actor-critic model) is trained with rewards given throughout each charge cycle of the battery to optimize training. The reinforcement learning model can determine state-of-health characteristics of the battery over the charge cycles, and in a second phase, the reinforcement learning model is augmented accordingly. During this augmentation, the reinforcement learning model is trained with rewards given on a charge cycle-by-cycle basis, wherein rewards are given after looking at the charging optimization after the conclusion of each charge cycle.

Abstract: An electric vehicle (EV) chassis is disclosed that may be a modular platform flexible as a basis for numerous other EV platforms. It is contemplated that the entire electric drivetrain (i.e., powertrain, wheels, steering) may be supplied to an automotive original equipment manufacturer (OEM). The OEM may use the EV chassis for integration within a representative passenger compartment. The chassis may also be reconfigurable with the modularity at various levels that include the energy storage system, the entire chassis system, or any level in-between. The chassis may further be designed to allow connection of multiple modules to enable a larger scale energy storage that may be provided to homes, buildings, or the electric power grid.

Abstract: A computer-implemented method for operating a motor vehicle, in particular an electrically drivable motor vehicle, depending on a predicted state of health of an electrical energy store, in particular a vehicle battery. The method includes: providing vehicle parameters which influence the state of health of the electrical energy store; predicting the vehicle parameters at a prediction point in time; ascertaining the predicted state of health depending on the predicted vehicle parameters with the aid of a data-based state of health model which is trained to output a state of health of the electrical energy store depending on the vehicle parameters; and signaling the predicted state of health.

Abstract: An electrochemical battery system includes at least one electrochemical cell, a thermal control system operably connected to the at least one electrochemical cell, a memory in which a physics-based model of the at least one electrochemical cell is stored and in which program instructions are stored, and a controller operably connected to the at least one electrochemical cell, the thermal control system and the memory. The controller is configured to execute the program instructions to identify a first requested operation, obtain a first generated target temperature which is based on the physics-based model and the identified first requested operation, and control the thermal control system based upon the obtained first target temperature while controlling the at least one electrochemical cell based upon the identified first requested operation.

Abstract: Battery management systems and methods for use with lithium-ion batteries that employ silicon-based negative electrodes. The battery management systems and methods consider the lithiation/delithiation properties of silicon-based anode materials by considering voltage relaxation behavior. The battery management systems and methods may also be applied to other materials that similarly display an apparent hysteresis in the lithiation/delithiation processes and/or form multiple phases with different electrochemical properties.

Abstract: A computer-implemented method for predicting a modeled state of health of an electrical energy store having at least one electrochemical unit, in particular a battery cell, or by according to rule-based and/or data-based mapping even in an entire system. The method including providing a data-based state of health model trained to assign a modeled state of health to the electrical energy store based on characteristics of operating variables of the electrical energy store; generating a characteristic of at least one load variable based on a provided usage pattern using a usage model; generating the characteristics of operating variables based on the at least one load variable using a predefined dynamic model; and determining a predicted modeled state of health based on the generated characteristics of operating variables.

Abstract: A battery includes an electrode that exhibits a crystal structure change when lithiated beyond a threshold potential and a battery management system. The battery management system includes a controller configured to, while the battery is online, determine the threshold potential, determine battery operating parameters based on the determined threshold potential, and operate the battery based on the determined battery operating parameters.

Abstract: A method, system, and non-transitory computer readable medium for determining a pseudo-optimal charging algorithm for a specific battery are disclosed. An electrochemical battery model is characterized based on the physical characteristics of a specific battery. An optimal charging profile is determined for the specific battery using the highly accurate electrochemical battery model. A pseudo-optimal charging profile is determined which closely approximates the optimal charging profile. However, the pseudo-optimal charging profile is comprised of simple building blocks which are easily and efficiently implemented in embedded applications having limited computational power/memory. An optimization process is used to determine optimal control parameters for the simple building blocks, trigger conditions and thresholds, and adaptation parameters for adapting the pseudo-optimal charging profile as the battery ages.

Abstract: An electric vehicle (EV) chassis is disclosed that may be a modular platform flexible as a basis for numerous other EV platforms. It is contemplated that the entire electric drivetrain (i.e., powertrain, wheels, steering) may be supplied to an automotive original equipment manufacturer (OEM). The OEM may use the EV chassis for integration within a representative passenger compartment. The chassis may also be reconfigurable with the modularity at various levels that include the energy storage system, the entire chassis system, or any level in-between. The chassis may further be designed to allow connection of multiple modules to enable a larger scale energy storage that may be provided to homes, buildings, or the electric power grid.

Abstract: A Li-ion battery management system comprises a Li-ion cell, one or more sensors configured to sense one or more operating conditions of the Li-ion cell, a controller having non-transitory memory for storing machine instructions that are to be executed by the controller and operatively connected to the Li-ion cell, the machine instructions when executed by the controller implement the following functions: receive the one or more operating conditions and a trained machine learning (ML) model, and output an indicator value along a state of charge (SOC) trajectory in response to the one or more operating conditions and the trained ML model to control a fast charge state of the Li-ion cell from a current source.

Abstract: A computer-implemented method for operating a motor vehicle, in particular an electrically drivable motor vehicle, depending on a predicted state of health of an electrical energy store, in particular a vehicle battery. The method includes: providing vehicle parameters which influence the state of health of the electrical energy store; predicting the vehicle parameters at a prediction point in time; ascertaining the predicted state of health depending on the predicted vehicle parameters with the aid of a data-based state of health model which is trained to output a state of health of the electrical energy store depending on the vehicle parameters; and signaling the predicted state of health.

Abstract: A method for generating battery characteristics for a battery having a target composition includes identifying open-circuit potential (OCP) characteristics for two similar battery compositions having different proportions of elements. The OCP characteristics are converted to dQ/dV characteristics and linearly combined to derived a target dQ/dV characteristic. The target dQ/dV characteristic is integrated to derived a target OCP characteristic. A battery constructed of the target composition is operated according to the target OCP characteristic.

Abstract: A battery management system includes a memory, a current sensor that measures a current flow through a battery to a load, a voltage sensor that measures a voltage level between a first terminal and a second terminal of the battery that are each connected to the load, and the memory, a temperature sensor that measures a temperature level of the battery; and a controller configured to be operatively connected to the current sensor, temperature sensor, and voltage sensor. The controller is configured to receive a measurement of a first current level and a first voltage level and utilize a corrected capacity and corrected open circuit voltage estimate to output an estimated open circuit voltage of the battery as compared to an estimated capacity.

Abstract: Battery management systems and methods for use with lithium-ion batteries that employ silicon-based negative electrodes. The battery management systems and methods consider the lithiation/delithiation properties of silicon-based anode materials by considering voltage relaxation behavior. The battery management systems and methods may also be applied to other materials that similarly display an apparent hysteresis in the lithiation/delithiation processes and/or form multiple phases with different electrochemical properties.

Abstract: A method for generating battery characteristics for a battery having a target composition includes identifying open-circuit potential (OCP) characteristics for two similar battery compositions having different proportions of elements. The OCP characteristics are converted to dQ/dV characteristics and linearly combined to derived a target dQ/dV characteristic. The target dQ/dV characteristic is integrated to derived a target OCP characteristic. A battery constructed of the target composition is operated according to the target OCP characteristic.

Abstract: A method and system for managing a battery system. The method including receiving at least one measured characteristic of the battery over a pre-defined time horizon from the at least one sensor, receiving at least one estimated characteristic of the battery from a electrochemical-based battery model based on differential algebraic equations, determining a cost function of a Moving Horizon Estimation based on the at least one measured characteristic and the at least one estimated characteristic, updating the electrochemical-based battery model based on the cost function, estimating at least one state of the at least one battery cell by applying the electrochemical-based battery model, and regulating at least one of charging or discharging of the battery based on the estimation of the at least one state of the at least one battery cell.

Abstract: In one embodiment, an electrochemical battery system includes at least one electrochemical cell, a thermal control system operably connected to the at least one electrochemical cell, a memory in which a physics-based model of the at least one electrochemical cell is stored and in which program instructions are stored, and a controller operably connected to the at least one electrochemical cell, the thermal control system and the memory. The controller is configured to execute the program instructions to identify a first requested operation, obtain a first generated target temperature which is based on the physics-based model and the identified first requested operation, and control the thermal control system based upon the obtained first target temperature while controlling the at least one electrochemical cell based upon the identified first requested operation.

Abstract: A Li-ion battery management system comprises a Li-ion cell, one or more sensors configured to sense one or more operating conditions of the Li-ion cell, a controller having non-transitory memory for storing machine instructions that are to be executed by the controller and operatively connected to the Li-ion cell, the machine instructions when executed by the controller implement the following functions: receive the one or more operating conditions and a trained machine learning (ML) model, and output an indicator value along a state of charge (SOC) trajectory in response to the one or more operating conditions and the trained ML model to control a fast charge state of the Li-ion cell from a current source.

Abstract: A battery system in one embodiment includes a cell with an anode including graphite and a minor active material that displays an apparent thermodynamic hysteresis. A controller is operably connected to a memory which is configured to execute program instructions in the memory to perform a charge of the cell to a first potential, and a discharge of the cell from the first potential to generate a first discharge versus capacity curve. After a second charge of the cell to a second potential and a second discharge of the cell from the second potential to generate a second discharge versus capacity curve, the controller identifies a shift between the first discharge versus capacity curve and the second discharge versus capacity curve and updates a model of the cell based upon the identified shift. The controller then modifies at least one operating parameter of the cell based upon the updated model.

Abstract: Methods and systems are described of managing a battery system. The battery system including at least one battery cell and one or more sensors configured to measure a temperature of the at least one battery cell. The method includes receiving a measurement of the temperature of the at least one battery cell, estimating an open circuit potential of the at least one battery cell, estimating a capacity fade of the at least one battery cell based on the open circuit potential of the at least one battery cell and a ratio of a change in the open circuit potential relative to a change in the temperature of the at least one battery cell, and regulating at least one of charging or discharging of the at least one battery cell based on the estimation of the capacity fade.