Battery SOC Estimation Based on Temperature-dependent RC Model and SMFEKF Algorithm
To meet the requirements of SOC estimation accuracy and robustness,a temperature-dependent second-order RC equivalent circuit model is established,taking a lithium-ion battery cell as the study object and considering the effects of temperature change on open-circuit voltage,polarization resistance,polarization capacitance,and capacity.Simulation results show that the model has higher accuracy than the second-order RC model.Based on this model,the extended Kalman filter algorithm with multiple suboptimal fading factor is used to estimate SOC.The results show that the root mean square error of SOC estimation of the SMFEKF algorithm based on the variable temperature model and the constant temperature model is reduced by 42.7%and 48.2%,respectively,compared with the EKF algorithm under variable temperature conditions,which can ensure strong robustness of estimation results.The maximum relative error and root mean square error of SOC estimation results based on the variable temperature model are smaller than those of the constant temperature model under the DST condition in the variable temperature environment,which proves that the model has strong temperature adaptability and can have higher estimation accuracy under the variable temperature condition.
lithium batterystate of chargesuboptimal fading factortemperature-dependent equivalent circuit modelSMFEKF algorithm
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