吉林大学学报(工学版) ›› 0, Vol. ›› Issue (): 1165-1170.doi: 10.7964/jdxbgxb201305003

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Insulation detection algorithm for high-power battery system based on internal resistance model

HE Yao, LIU Xing-tao, ZHANG Chen-bin, CHEN Zong-hai   

  1. Department of Automation, University of Science and Technology of China, Hefei 230027, China
  • Received:2013-08-29 Revised:2013-08-29
  • Contact: 陈宗海(1963- ),男,教授,博士生导师.研究方向:复杂系统的建模仿真与控制,机器人与智能系统,量子系统控制与量子态操纵.E-mail:chenzh@ustc.edu.cn E-mail:chenzh@ustc.edu.cn

Abstract: To improve the accuracy of insulation detection between the high-power battery system and the chassis of electric vehicles under complicated working conditions, this paper builds a new insulation detection model. This model takes the battery internal resistances into consideration for insulation detection. Based on the proposed model, a Reliability Algorithm (RA) is developed. This algorithm realizes the reliability measurement of the detection dataset according to the change interval of the total voltage, and then selects a binary dataset that has the maximum reliability to calculate the system insulation resistance of the battery system. In order to restrain the random measurement noise, the moving average filter is applied to process the results. The experiments carried out the test platform of electric vehicles and the numerical simulation show that the internal resistance model and the reliability algorithm for insulation detection have good estimation accuracy and high robustness.

CLC Number: 

  • U463.63
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[2] CHEN Yan-hong, WU Wei-jing, LIU Hong-wei, SHEN Shuai, LI Ce-yuan, GENG Huan-liang. Thermal characteristics of battery for pure electric vehicles [J]. 吉林大学学报(工学版), 2014, 44(4): 925-932.
[3] HE Yao, LIU Xing-tao, ZHANG Chen-bin, CHEN Zong-hai. Insulation detection algorithm for high-power battery system based on internal resistance model [J]. 吉林大学学报(工学版), 2013, 43(05): 1165-1170.
[4] He Hong-wen, Yu Xiao-jiang . Performance evaluation of electric vehicle power battery
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