Abstract:
A battery system includes a battery that couples to an electrical system. The battery system also includes a battery control module that electrically couples to the battery. The battery control module monitors at least one monitored parameter of the battery, and the battery control module recursively calculates a first capacity estimation of the battery using two linear regression models based on at least an equivalent circuit model, the at least one monitored parameter, and a Kalman filter.
Abstract:
Embodiments describe a battery system that includes a first battery module coupled to a regenerative braking system and a control module that controls operation of the battery system by: determining a predicted driving pattern over a prediction horizon using a driving pattern recognition model based in part on a battery current and a previous driving pattern; determining a predicted battery resistance of the first battery module over the prediction horizon using a recursive battery model based in part on the predicted driving pattern, the battery current, a present bus voltage, and a previous bus voltage; determining a target trajectory of a battery temperature of the first battery module over a control horizon using an objective function; and controlling magnitude and duration of electrical power supplied from the regenerative such that a predicted trajectory of the battery temperature is guided toward the target trajectory of the battery temperature during the control horizon.
Abstract:
A method of predicting battery test results includes using a battery test computer to predict a battery test result for a battery undergoing testing. The battery test computer comprises a tangible, non-transitory computer-readable medium storing a battery test management system implemented as one or more sets of instructions. The battery test management system includes a predictive module configured to predict the battery test result using less than all data required for the battery test to be complete, a validation module configured to validate the prediction, and a training module configured to re-train the predictive module based on results generated by the validation module. The battery test computer also includes processing circuitry configured to execute the one or more sets of instructions, and outputting, via a user interface, the prediction of the result and a confidence level associated with the prediction.
Abstract:
A battery system includes a battery that couples to an electrical system. The battery system also includes a battery control module that electrically couples to the battery. The battery control module performs a parallel current integration process on an initial state of charge using an actual capacity and a candidate capacity of the battery. Additionally, the battery control module performs a directional comparison between an estimated state of charge of the battery and results of the parallel current integration process. Further, the battery control module determines validity of the estimated state of charge based at least in part on the directional comparison between the estimated state of charge of the battery and the results of the parallel current integration process
Abstract:
A battery system includes a lithium ion battery that couples to an electrical system. The battery system also includes a battery management system that electrically couples to the lithium ion battery and controls one or more recharge parameters of the lithium ion battery. Additionally, the battery management system monitors one or more parameters of the lithium ion battery. Further, the battery management system controls the recharge parameters of the lithium ion battery based on at least one lithium plating model and the monitored parameters. Furthermore, the at least one lithium plating model indicates a relationship between the one or more parameters of the lithium ion battery and a likelihood of lithium plating occurring in the lithium ion battery.
Abstract:
A method of predicting battery test results includes using a battery test computer to predict a battery test result for a battery undergoing testing. The battery test computer comprises a tangible, non-transitory computer-readable medium storing a battery test management system implemented as one or more sets of instructions. The battery test management system includes a predictive module configured to predict the battery test result using less than all data required for the battery test to be complete, a validation module configured to validate the prediction, and a training module configured to re-train the predictive module based on results generated by the validation module. The battery test computer also includes processing circuitry configured to execute the one or more sets of instructions, and outputting, via a user interface, the prediction of the result and a confidence level associated with the prediction.
Abstract:
A battery system includes a battery that couples to an electrical system. The battery system also includes a battery control module that electrically couples to the battery. The battery control module performs a parallel current integration process on an initial state of charge using an actual capacity and a candidate capacity of the battery. Additionally, the battery control module performs a directional comparison between an estimated state of charge of the battery and results of the parallel current integration process. Further, the battery control module determines validity of the estimated state of charge based at least in part on the directional comparison between the estimated state of charge of the battery and the results of the parallel current integration process.
Abstract:
A battery system includes a battery that couples to an electrical system. The battery system also includes a battery control module that electrically couples to the battery. The battery control module monitors at least one monitored parameter of the battery, and the battery control module recursively calculates a first capacity estimation of the battery using two linear regression models based on at least an equivalent circuit model, the at least one monitored parameter, and a Kalman filter.
Abstract:
Embodiments describe a battery system that includes a first battery module coupled to a regenerative braking system and a control module that controls operation of the battery system by: determining a predicted driving pattern over a prediction horizon using a driving pattern recognition model based in part on a battery current and a previous driving pattern; determining a predicted battery resistance of the first battery module over the prediction horizon using a recursive battery model based in part on the predicted driving pattern, the battery current, a present bus voltage, and a previous bus voltage; determining a target trajectory of a battery temperature of the first battery module over a control horizon using an objective function; and controlling magnitude and duration of electrical power supplied from the regenerative such that a predicted trajectory of the battery temperature is guided toward the target trajectory of the battery temperature during the control horizon.