Self-adaptive Filtering Based State of Charge Estimation Method for Electric Vehicle Batteries

WANG Junping¹  CAO Binggang¹  CHEN Quanshi²

(1. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049; 2. State Key Laboratory of Automobile Safety & Energy Conservation, Tsinghua University, Beijing 100084)

Abstract: The state of charge (SOC) estimation of battery pack based on Kalman filtering method is suitable for estimating the SOC for hybrid electric vehicles where the current fluctuates drastically. However, the uncertainty due to battery model and statistical information of the system and measurement noise will result in filtering divergence. The self-adaptive filtering method can deal with this problem. The federal urban driving schedule is studied and the battery pack is charged and discharged, then a battery’s state space model with single state is built. Then the SOC is taken as a state of the system, the SOC is estimated based on the self-adaptive filtering method. The bench test results show that this method is with high accuracy and reliability of estimation, less computation amount, and is quite suitable for practical application.

Key words: Ni/MH battery pack  State of charge  Self-adaptive filtering

CLC No: TM912.1

国家高技术研究发展计划(863计划, 2003AA501100)和汽车安全与节能国家重点实验室开放基金(KF2007-04)资助项目. Received 20070624, received in revised form 20080202

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