Comparison of Four Intelligent Algorithms for Battery SOC Estimation in Electric Vehicle

摘要：

It is of great importance to accurately estimate the battery State-Of-Charge (SOC) during electric vehicle driving process. Although much research work has been carried on in recent years, it still cannot be totally solved. Four intelligent algorithms with good nonlinear approximation ability are adopted to estimate the battery SOC, which are BP neural network (BPNN), Elman neural network (Elman), ε-SVR and v-SVR. The simulation results show that, all the four algorithms can get good approximation to the actual value, and the average estimation error is less than 2％, while the estimation performance using v-SVR algorithm is best.

关键词： Electric vehicles State-Of-Charge Elman neural network ε-SVR v-SVR

作者: Qingsheng Shi Xiujuan Li Xiaoping Zhang

作者单位: College of Electrical Engineering, Henan University of technology, Zhengzhou 450007

会议类型: 国际会议

会议名称: 2010 International Conference on Information Technology and Industrial Engineering(2010年信息技术与工业工程国际学术会议 ITIE 2010)

会议地点: 武汉

会议语种:英文

页码: 691-694

在线出版日期: 2010-06-06（万方平台首次上网日期，不代表论文的发表时间）