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HE Yao,HUANG Dongming,LIU Xintian.SOC Estimation of Battery Pack Based on Dual Kalman Filtering Algorithm at Different Temperatures[J].JOURNAL OF POWER SUPPLY,2018,16(5):112-118
SOC Estimation of Battery Pack Based on Dual Kalman Filtering Algorithm at Different Temperatures
Received:June 23, 2016  Revised:March 21, 2018
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DOI:10.13234/j.issn.2095-2805.2018.5.112
Keywords:lithium-ionpowerbattery pack  temperature  state-of-charge  dual Kalman filtering algorithm
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HE Yao Clean Energy Automotive Research Institute, Hefei University of Technology, Hefei , China
HUANG Dongming Clean Energy Automotive Research Institute, Hefei University of Technology, Hefei , China 1024679311@qq.com
LIU Xintian Clean Energy Automotive Research Institute, Hefei University of Technology, Hefei , China
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Abstract:
      The state of charge(SOC) of a lithium-ion power battery pack is an important parameter for the entire batzt-ery management system, which can directly reflect the remaining mileage that electric vehicles can run. As a result, it is essential to accurately estimate the SOC of the battery pack. Due to the nonuniformity of each cell in the battery pack, as well as the complex driving environment in which electric vehicles run, statistical methods are used in this paper to fit the model parameters into temperature-related factors on the basis of the Vmin model, which describes the minimum load voltage of a single cell in the battery pack. Through simulating the actual driving environment of electrical vehicles, an experiment is carried out at different temperatures, thus an improved Vmin model can be obtained. With the combination of dual Kalman filtering algorithm, the SOC estimation of the entire battery pack is realized. Simulation and experimental results show that the proposed method has advantage in improving the SOC estimation accuracy of the battery pack.
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