基于安时积分和无迹卡尔曼滤波的锂离子电池SOC估算方法研究

基于Thevenin等效模型建立二阶RC等效电路模型，通过混合脉冲动力功率特性测试实验获取电池脉冲放电数据，进行电池等效电路参数辨识。为弥补锂离子电池荷电状态在90%~100%区间时电池模型参数辨识拟合误差而引起其估算误差的缺陷，综合采用安时积分与无迹卡尔曼滤波估算电池荷电状态。使用硬件在环仿真测试平台及环境模拟测试平台进行电池管理系统设计，在不同工况下对电池进行荷电状态估算，结果表明荷电状态估算误差范围为-1.5%~1.0%，该方法估算精度较高，效果理想。

SOC Estimation of Lithium-ion Battery Based on Ampere Hour Integral and Unscented Kalman Filter

Based on Thevenin equivalent model, the second-order RC equivalent circuit model was established. The pulse discharge data of battery were obtained by the tests of hybrid pulse power characteristics, and the parameters of battery equivalent circuit were identified. In order to make up the fitting errors of battery model parameter identification when the SOC of lithium-ion batteries was in the range of 90% to 100%, ampere hour integral and UKF were used comprehensively to estimate battery's SOC. Battery management system was designed by using HIL test platform and environmental simulation test platform. The results of SOC estimation of batteries under different operating conditions show that the estimation errors of SOC are from -1.5% to 1.0%. This method has relatively high accuracy and good effectiveness.