某款纯电动车OCV修正致SOC跳变问题的优化

Optimization of SOC Jump Caused by OCV Correction of a Certain Pure Electric Vehicle

SOC估算有如开路电压法、安时积分法、神经网络法、卡尔曼滤波法等多种方法[1]。江淮某轻型纯电物流车磷酸铁锂电池SOC估算采用较为成熟、稳定的安时积分策略、充电末端Vmax校准及放电末端OCV修正策略[2]。市场车辆在环境14℃~16℃时,放电末端常出现修正导致SOC5~8%幅度的跳变,文章通过对比分析,细化不同温度SOC-OCV矩阵,较好的解决上述问题。

SOC estimation methods include open circuit voltage method,ampere hour integration method,neural network method,Kalman filter method,etc.The SOC estimation of lithium iron phosphate battery of a light pure electric logistics vehicle in Jianghuai adopts a more mature and stable ampere hour integration strategy,Vmax calibration at the charging end and OCV correction strategy at the discharge end.In the environment of 14℃-16℃,the end of discharge often appears correction,which leads to the jump of soc5-8%.In this paper,the soc-ocv matrix at different temperatures is refined through comparative analysis,so as to better solve the above problems.