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Research on the Use Behaviors of Data-Driven Vehicle Power Battery
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Fan Zhang1, 2, Zixuan Xing2, Minghu Wu1, Shaoyuan Wei3, Yang Gao3
Automobile Technology | 2023, (3) : 49 - 55
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Automobile Technology | 2023, (3): 49-55
Research on the Use Behaviors of Data-Driven Vehicle Power Battery
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Fan Zhang1, 2, Zixuan Xing2, Minghu Wu1, Shaoyuan Wei3, Yang Gao3
Affiliations
  • 1 Hubei University of Technology, Wuhan 430068
  • 2 Hubei Engineering Research Center of New Energy and Power Grid Equipment Safety Monitoring, Wuhan 430068
  • 3 Sunwoda Electronics Co., Ltd., Shenzhen 518108
Published: 2023-03-24 doi: 10.19620/j.cnki.1000-3703.20220223
Outline
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Based on the actual operating data of electric vehicles, this paper proposed an analysis method of in-service power battery usage behaviors, so as to quantitatively evaluate the charging behaviors and driving behaviors of vehicles, and provide effective support for battery fault diagnosis. Firstly, characteristic parameters of power battery use behaviors based on membership function were extracted, and then the accumulative risk score of using behaviors was defined and calculated. Finally, the battery use behavior differences between vehicles and vehicles in different time dimensions were quantitatively analyzed by using the idea of horizontal and vertical comparison. Experimental results show that there is a strong positive correlation between the battery using behavior score quantified in this paper and battery pack consistency, which can fully evaluate the using behavior of power battery, and provide data support for battery fault diagnosis.

Power battery  /  Charging behaviors  /  Driving behaviors  /  Membership function
Fan Zhang, Zixuan Xing, Minghu Wu, Shaoyuan Wei, Yang Gao. Research on the Use Behaviors of Data-Driven Vehicle Power Battery[J]. Automobile Technology, 2023 , (3) : 49 -55 . DOI: 10.19620/j.cnki.1000-3703.20220223
Year 2023 volume Issue 3
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Article Info
doi: 10.19620/j.cnki.1000-3703.20220223
  • Online Date:2025-12-07
  • Published:2023-03-24
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  • Revised:2022-05-26
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Affiliations
    1 Hubei University of Technology, Wuhan 430068
    2 Hubei Engineering Research Center of New Energy and Power Grid Equipment Safety Monitoring, Wuhan 430068
    3 Sunwoda Electronics Co., Ltd., Shenzhen 518108
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
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占总种数比例
Percentage of
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Genus
种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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