Battery state identification algorithm for embedded controller
The estimation of the state of charge(SOC)of the battery is one of the core issues in the research of the battery management system.It is of great engineering practical significance to improve the accuracy and rapidity of the SOC estimation.In order to solve the estimation error problem of the existing full SOC domain fitting Kalman filtering(KF)algorithm at the charge/discharge terminal,an extended KF(EKF)subsection fitting optimization algorithm based on the first-order RC model is proposed,which improves the accuracy of SOC estimation.Finally,the corresponding modeling and simulation are completed in MATLAB/Simulink environment,and a lithium ion battery charging and discharging experimental platform is designed and built for testing based on the proposed SOC estimation algorithm.The simulation and experimental results verify the accuracy of the proposed estimation algorithm.
batteryequivalent circuitstate of charge estimationKalman filtering
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