Parameter Identification of Lithium-ion Batteries Based on Frequency Decoupling and Double Kalman Filtering
The complex dynamic process inside lithium-ion batteries occurs on the time scale of milliseconds to hundreds of seconds.Neglecting the dynamic process of batteries and lacking decoupling mechanisms in identification algorithms may cause cross interference among parameters,resulting in identification results lacking physical significance.A parameter identification algorithm based on frequency decoupling and dual Kalman filtering was proposed for the purpose.The battery model was divided into the fast dynamic part and the slow dynamic part,the fast dynamic response frequency was decoupled by use of a high pass filter,and the slow dynamic parameters at different time scales were identified through dual Kalman filtering algorithm.The results show that the algorithm has strong voltage dynamic tracking ability,with the lowest root mean square error of 0.83 mV.The parameter identification results have reasonable electrochemical kinetic significance,and the high consistency of the results under different operating conditions proves the feasibility and effectiveness of this algorithm.
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维普
