电动汽车锂离子电池SOC检测技术的研究  

Research on electric vehicles lithium-ion battery SOC detection technology

作　　者：马树才[1] 范青[1] 张晓[1] 谢芳[2] 

机构地区：[1]河北北方学院信息科学与工程学院,河北张家口075000 [2]张家口职业技术学院,河北张家口075000

出　　处：《电源技术》2014年第10期1812-1814,共3页Chinese Journal of Power Sources

基　　金：国家科技部"农村医疗卫生服务平台与应用示范"项目(2012BAH05F04)

摘　　要：安全、高效的电池是电动汽车的动力源。锂离子电池的荷电状态(SOC)是电动汽车能量管理的重要依据,对电动汽车的安全运行有着直接的影响。以磷酸铁锂电池为研究对象,充分考虑电池温度、充放电次数、电池老化等因素的影响,利用BP神经网络构建出锂离子电池SOC预测模型,并经仿真证明了这种方法的精确度和可靠性。Safe and efficient battery were the power source of electric vehicles. SOC of lithium-ion battery was an important basis for electric vehicle energy management, and the safe operation of electric car was directly impacted. The LiFePO4 battery was taken as the research object. Under the full consideration of influence to the battery temperature, charge and discharge times, battery aging and other factors, a predictive model of lithium-ion SOC based on BP neural network was built. The accuracy and reliability were proved by simulation.

关 键 词：电动汽车 锂离子电池 神经网络 荷电状态 

分 类 号：TM912[电气工程—电力电子与电力传动]