Abstract: Methods and systems are provided for determining a state of charge of a battery. A magnetic force between the battery and a magnet is detected. The state of charge of the battery is determined based on the detected magnetic force.

Abstract: A system and method for estimating the state-of-charge (SOC) of a battery cell in a vehicle using a magnetic sensor that measures changes in magnetism of the battery cell. The method provides an offset correction to a current output signal from the magnetic sensor that calibrates the current output signal to a known magnetic field strength, provides a temperature correction to the current output signal that corrects the current output signal based on a temperature of the magnetic sensor, and provides a current correction to the current output signal that removes portions of the magnetic field caused by other battery cells, where the corrected current output signal is converted to the battery cell SOC.

Abstract: System and methods for determining battery system power capability in a vehicle are presented. Peak power capability estimation systems and methods disclosed herein may compensate regressed parameters in a battery system circuit model for an effect of current magnitude. Utilizing the disclosed methods for accurately estimating peak power capability of a battery system may provide for, among other things, improved battery system performance modeling and/or improved battery system control and management decisions.

Abstract: A battery state estimator which combines an electrochemical solid-state concentration model with an empirical equivalent-circuit model. The battery state estimator uses a reduced-order physics-based electrochemical solid-state concentration model to calculate open circuit voltage of a battery cell, and uses the calculated open circuit voltage in an equivalent-circuit model to evaluate a diffusion voltage drop and other battery cell parameters. The battery state estimator is implemented in an online estimator framework using an extended Kalman filter, with a measured terminal voltage and measured current as inputs. A state of charge of the battery cell can be determined from the calculated open circuit voltage, and the state of charge along with the other parameters from the equivalent-circuit model are used to evaluate battery pack performance and to control battery pack charging and discharging.

Abstract: A system and method for estimating parameters of a rechargeable energy storage system during a plug-in charge mode include reading a first measured voltage and a measured current from the rechargeable energy storage system while charging the rechargeable energy storage system during a plug-in charge mode, interrupting the charge to stop current flow to the rechargeable energy storage system for a predetermined period of time, reading a second measured voltage during the charge interrupt, calculating a resistance based on the first measured voltage, the second measured voltage and the measured current, calculating an open circuit voltage of the rechargeable energy storage system based on the resistance, the second measured voltage, the measured current and determining the state-of-charge for the rechargeable energy storage system using the open circuit voltage.

Abstract: A method and system for heating a vehicle battery, such as the type used for vehicle propulsion in a hybrid electric vehicle (HEV). Depending on the battery chemistry involved, such batteries may not perform well in extremely cold environments. For instance, a lithium-ion battery can exhibit a high internal resistance when the battery is extremely cold, which in turn can negatively affect the available power or other capabilities of the battery. According to an exemplary embodiment, the method and system take advantage of the high internal resistance in a cold vehicle battery by purposely cycling electrical current in and/or out of the battery so that heat is created. This heat warms up the vehicle battery and thereby improves its overall performance and capabilities.

Abstract: System and methods for determining battery system energy capability in a vehicle are presented. A voltage offset of a battery system may be determined based on comparison of an open circuit voltage of the battery system and a measured voltage. An estimated remaining pack energy may be determined based, at least in part, on the voltage offset. Similarly, an estimated total pack energy may be determined based, at least in part, on the voltage offset. An energy capability of the battery system may be determined based on the estimated remaining pack energy and the estimated total pack energy.

Abstract: A number of illustrative variations may include a method, which may include using at least a segment of impedance-based battery power capability estimation data, and using real-time linear regression, which may be used as a method of estimating future behavior of a system based on current and previous data points, to provide a robust state of power predictor.

Abstract: A method and system for manipulating, adjusting or otherwise controlling a state-of-charge (SOC) operating range for a high voltage vehicle battery, such as the type used for hybrid or electric vehicle propulsion. By providing a dynamic SOC operating range that changes in response to changing battery conditions, the battery performance may be improved so that the battery life is extended. Depending on the particular embodiment, the dynamic SOC operating range may have different combinations of hard and/or soft boundaries or limits.

Abstract: Systems and methods for improvements in battery state of charge accuracy, charge termination consistency, capacity estimation, and energy delivery consistency. More specifically, embodiments herein detail systems and methods using an algorithm to calculate the change in state of charge for a given voltage change (dSOC/dV) at a given temperature in a region around the present voltage measurement or estimation and to set a signal indicating when the measurement should not be used due to potential error.

Abstract: Systems and methods are disclosed for estimating a state of a battery system such as a current-limited state of power and/or a voltage-limited state of power using a battery system model incorporating a nonlinear resistance element. Parameters of elements included in a battery cell model associated with a nonlinear resistance of a battery cell may be directly parameterized and used in connection with state estimation methods. By accounting for the nonlinear effect, embodiments of the disclosed systems and methods may increase available battery power utilized in connection with battery system control and/or management decisions over a larger window of operating conditions.

Abstract: System and methods for determining battery system power capability in a vehicle are presented. Peak power capability estimation systems and methods disclosed herein may compensate regressed parameters in a battery system circuit model for an effect of current magnitude. Utilizing the disclosed methods for accurately estimating peak power capability of a battery system may provide for, among other things, improved battery system performance modeling and/or improved battery system control and management decisions.

Abstract: A battery model and equivalent circuit that includes an ohmic resistance, a first RC-pair that models a battery cell charge transfer reaction and double layer processes and a second RC-pair that models battery cell diffusion. Each of the ohmic resistance, the charge transfer reaction resistance and the diffusion resistance in the model are variable resistances, where each resistance changes in response to a change in voltage potential across the resistance.

Abstract: A number of variations include a method, which may include using at least a segment of voltage-based Battery State Estimation data, and using real-time linear regression, which may be a method of estimating future behavior of a system based on current and previous data points, to provide a robust and fast-adapting impedance response approximator. Linear regression may be performed by forming an RC circuit which is “equivalent” to electrochemical impedance spectroscopy data and processing the runtime values of that RC circuit using any number of known real-time linear regression algorithms including, but not limited, to a weighted recursive least squares (WRLS), Kalman filter or other means.

Abstract: A method and system for use with a vehicle battery pack having a number of individual battery cells, where the method estimates, extrapolates or otherwise determines individual cell resistances. According to an exemplary embodiment, the method and system use a voltage and temperature reading for each of the individual battery cells, as well as a voltage and current reading for the overall battery pack to determine one or more cell resistance values, such as a minimum and maximum cell resistance for the battery pack. This approach relies upon temperature deviations in the battery pack to make assumptions or estimates regarding individual battery cell resistances. By having individual cell resistance values—instead of using an overall pack resistance value and building in a buffer to account for cell variations—better and more accurate cell-level data can be obtained that, in turn, can improve charging, discharging, cell balancing and/or other battery-related processes.

Abstract: A method for modeling changes in the state of charge vs. open circuit voltage (SOC-OCV) curve for a lithium-ion battery cell as it ages. During battery pack charging, voltage and current data are gathered for a battery cell. A set of state equations are used to determine the stoichiometry and state of charge of the cathode half-cell based on the charging current profile over time. The voltage and current data, along with the stoichiometry and state of charge of the cathode half-cell, are then used to estimate maximum and minimum solid concentration values at the anode, using an error function parameter regression/optimization. With stoichiometric conditions at both the cathode and anode calculated, the cell's capacity and a new SOC-OCV curve can be determined.

Abstract: A battery state estimator which combines an electrochemical solid-state concentration model with an empirical equivalent-circuit model. The battery state estimator uses a reduced-order physics-based electrochemical solid-state concentration model to calculate open circuit voltage of a battery cell, and uses the calculated open circuit voltage in an equivalent-circuit model to evaluate a diffusion voltage drop and other battery cell parameters. The battery state estimator is implemented in an online estimator framework using an extended Kalman filter, with a measured terminal voltage and measured current as inputs. A state of charge of the battery cell can be determined from the calculated open circuit voltage, and the state of charge along with the other parameters from the equivalent-circuit model are used to evaluate battery pack performance and to control battery pack charging and discharging.

Abstract: Adaptive estimation techniques to create a battery state estimator to estimate power capabilities of the battery pack in a vehicle. The estimator adaptively updates circuit model parameters used to calculate the voltage states of the ECM of a battery pack. The adaptive estimation techniques may also be used to calculate a solid-state diffusion voltage effects within the battery pack. The adaptive estimator is used to increase robustness of the calculation to sensor noise, modeling error, and battery pack degradation.

Abstract: Methods and systems are provided for determining a state of charge of a battery. The battery is subjected to a predetermined magnetic field such that the battery and the predetermined magnetic field jointly create a resultant magnetic field. The resultant magnetic field is sensed. The state of charge of the battery is determined based on the resultant magnetic field.

Abstract: Methods are disclosed for modeling changes in capacity and the state of charge vs. open circuit voltage (SOC-OCV) curve for a battery cell as it ages. During battery pack charging, voltage and current data are gathered for a battery cell. In one method, using multiple data points taken during the plug-in charge event, data optimization is used to determine values for two parameters which define a scaling and a shifting of the SOC-OCV curve from its original shape at the cell's beginning of life to its shape in the cell's current condition. In a second method, only initial and final voltages and current throughput data are needed to determine the values of the two parameters. With the scaling and shifting parameters calculated, the cell's updated capacity and updated SOC-OCV curve can be determined. The methods can also be applied to data taken during a discharge event.