关键词: 荷电状态, 镍氢电池组, 自适应滤波, 表面质量, 超声波振动, 磁力研磨, 研磨效率, 锥孔

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, Self-adaptive filtering, State of charge, Finishing efficiency, Magnetic abrasive finishing, Surface quality, Ultrasonic vibration, Taper hole