动力锂离子电池荷电态估计的建模与仿真

State of charge estimation for a Li-ion driving battery

针对混合动力车用8Ah锂离子电池荷电状态(SOC)的估算,研究了基于该种电池稳态特性的Map建模与仿真.选取对SOC有重要影响的电压、电流、温度等参数,对电池倍率充放电特性和开路电压与SOC关系进行了系统研究.再通过插值、拟合等方法补充实验缺省数据,获得Map模型的参数,从而建立电池稳态特性Map模型.将建立的模型在模拟工况实验中进行仿真和修正,采用温度系数修正法进行补偿.采取了一些数据压缩方法,以加快查询速度.模拟工况的结果表明,该模型对电池稳态SOC估算的误差在±4%以内.

For state of charge （SOC） estimation of a hybrid electric vehicle＇s （HEV） 8Ah Li-ion Battery, a Map model of the battery＇s stable state characteristics was built and then emulated. Significant parameters for the battery SOC estimation, including voltage, current, temperature, and so on, were chosen. Many tests, including high charge rate, discharge, and open circuit voltage （OCV）-SOC were systematically carried out. By using interpola- tion and fitting, any missing data was added in and then the battery＇s estimated stable-state SOC Map model was built. In view of temperature influences on the SOC, a temperature coefficient was advanced to modify the SOC. In order to effectively apply the algorithm, measures were taken to compress the data and accelerate the query rate. Emulations and modifications of the Li-ion battery were done, and the results indicate that estimations of SOC using this Map model yield S0C estimation errors within ±4%.