Abstract：When the recursive least square (RLS) method is applied to the multi-time scale system of lithium battery, problems such as low accuracy of model parameter identification and poor adaptability of working conditions will occur. For this reason, the dual polarization (DP) model is taken as the research object. Firstly, according to the different time-varying characteristics of the model parameters, the identification process of ohmic resistance is separated to reduce the number of parameters to be identified by RLS, and the mutual influence of the parameters is reduced, which improves the accuracy of RLS identification and reduces the amount of calculation. Secondly, considering the low accuracy of the model parameter online identification and the high accuracy of offline identification for constant current condition, an adaptive output equivalent circuit model for the full working condition is proposed to further improve the accuracy of the model. Simulations based on the actual operating conditions show that, the full-condition adaptive equivalent circuit model has higher accuracy than the R-DP online model with known ohmic resistance and the DP offline model, the better balance is achieved between model accuracy and running speed.
郭向伟, 邢程, 司阳, 朱军, 谢东垒. RLS锂电池全工况自适应等效电路模型[J]. 电工技术学报, 2022, 37(16): 4029-4037.
Guo Xiangwei, Xing Cheng, Si Yang, Zhu Jun, Xie Donglei. RLS Adaptive Equivalent Circuit Model of Lithium Battery under Full Working Condition. Transactions of China Electrotechnical Society, 2022, 37(16): 4029-4037.
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2022, Vol. 37 
