State of internal temperature(SOIT)can be used to assess the risk of thermal runaway and improve the accuracy of state of charge(SOC)and state of health(SOH)estimation of lithium(Li)battery.On the basis of analysis of the equivalent circuit model and thermal model of Li battery,a dual polarization thermo-electric coupling model is proposed to reflect the internal temperature rise and noise influence during SOC estimation of Li battery.The experiments of constant current discharge and hybrid pulse power characteristics(HPPC)and the recursive least square method with forgetting factor are applied to obtain identification parameters of equivalent circuit model and thermal model of Li battery,respectively.In order to deal with thermal noise,adaptive unscented Kalman filtering(AUKF)is proposed by combining UKF with adaptive covariance matching,which completes the online correction of process noise covariance and measurement noise covariance during SOIT estimation.The experimental results verify that when the internal current and voltage fluctuations of Li battery are intensified due to external factors,AUKF is significantly prior to UKF in restraining the SOIT estimation error increasing.
关键词
锂电池/内温状态估算/热电耦合/双重极化/自适应无迹卡尔曼滤波
Key words
lithium(Li)battery/state of internal temperature(SOIT)estimation/thermo-electric coupling/dual polarization/adaptive unscented Kalman filtering(AUKF)
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