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《Journal of Henan Agricultural University》 2015-03
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Estimation of electric vehicle lead-acid battery SOC based on Kalman filtering algorithm

CHEN Dongzhao;JIA Lijun;Henan Mechanical and Electrical Vocational College;  
On the basis of Kalman filtering method calculating ways of electric vehicle power battery charged state are estimated and adjusted in time according to the actual working condition variables,and combined with the characteristics of the pure electric vehicle driving cycle,the battery recycling,charge and discharge voltage and current,and effective variables such as environment temperature based on Kalman filtering algorithm are optimized. The test results show that the optimized Kalman algorithm can be of pure electric vehicles in the process of driving of the real-time estimation. Its estimation error is less than 8%,meeting the current requirements for lead-acid battery SOC estimation.
【Fund】: 河南省科技厅科技发展计划项目(142102210042)
【CateGory Index】: U469.72
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