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A critical review on inconsistency mechanism, evaluation methods and improvement measures for lithium-ion battery energy storage systems

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  • Tian, Jiaqiang
  • Fan, Yuan
  • Pan, Tianhong
  • Zhang, Xu
  • Yin, Jianning
  • Zhang, Qingping

Abstract

With the rapid development of electric vehicles and smart grids, the demand for battery energy storage systems is growing rapidly. The large-scale battery system leads to prominent inconsistency issues. This work systematically reviewed the causes, hazards, evaluation methods and improvement measures of lithium-ion battery inconsistency. From material to manufacture and usage, the process and conditions of each link affect battery consistency. The hazards of battery pack inconsistency include increasing system failure rate, reducing service performance and accelerating life decay. Inconsistency evaluation methods are summarized as statistics-based, machine learning-based and information fusion-based methods. Moreover, the improvement measures of battery inconsistency are reviewed from the aspects of the production process, sorting technology, topology optimization, equalization control and thermal management. In addition, the future works on challenges and prospects of battery inconsistency research are revealed, in hope of inspiring the efficient operation and maintenance of large-scale battery energy storage systems.

Suggested Citation

  • Tian, Jiaqiang & Fan, Yuan & Pan, Tianhong & Zhang, Xu & Yin, Jianning & Zhang, Qingping, 2024. "A critical review on inconsistency mechanism, evaluation methods and improvement measures for lithium-ion battery energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    • Handle: RePEc:eee:rensus:v:189:y:2024:i:pb:s1364032123008365
    DOI: 10.1016/j.rser.2023.113978
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    1. Feng, Fei & Hu, Xiaosong & Hu, Lin & Hu, Fengling & Li, Yang & Zhang, Lei, 2019. "Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 102-113.
    2. Wei, Jingwen & Dong, Guangzhong & Chen, Zonghai & Kang, Yu, 2017. "System state estimation and optimal energy control framework for multicell lithium-ion battery system," Applied Energy, Elsevier, vol. 187(C), pages 37-49.
    3. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    4. Hu, Xiaosong & Feng, Fei & Liu, Kailong & Zhang, Lei & Xie, Jiale & Liu, Bo, 2019. "State estimation for advanced battery management: Key challenges and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    5. Li, Penghua & Liu, Jianfei & Deng, Zhongwei & Yang, Yalian & Lin, Xianke & Couture, Jonathan & Hu, Xiaosong, 2022. "Increasing energy utilization of battery energy storage via active multivariable fusion-driven balancing," Energy, Elsevier, vol. 243(C).
    6. Sheng, Lei & Zhang, Hengyun & Su, Lin & Zhang, Zhendong & Zhang, Hua & Li, Kang & Fang, Yidong & Ye, Wen, 2021. "Effect analysis on thermal profile management of a cylindrical lithium-ion battery utilizing a cellular liquid cooling jacket," Energy, Elsevier, vol. 220(C).
    7. Bizhong Xia & Yadi Yang & Jie Zhou & Guanghao Chen & Yifan Liu & Huawen Wang & Mingwang Wang & Yongzhi Lai, 2019. "Using Self Organizing Maps to Achieve Lithium-Ion Battery Cells Multi-Parameter Sorting Based on Principle Components Analysis," Energies, MDPI, vol. 12(15), pages 1-17, August.
    8. Zhang, Qi & Tang, Yanyan & Bunn, Derek & Li, Hailong & Li, Yaoming, 2021. "Comparative evaluation and policy analysis for recycling retired EV batteries with different collection modes," Applied Energy, Elsevier, vol. 303(C).
    9. Wei, Zhongbao & Hu, Jian & Li, Yang & He, Hongwen & Li, Weihan & Sauer, Dirk Uwe, 2022. "Hierarchical soft measurement of load current and state of charge for future smart lithium-ion batteries," Applied Energy, Elsevier, vol. 307(C).
    10. Tian, Jiaqiang & Liu, Xinghua & Li, Siqi & Wei, Zhongbao & Zhang, Xu & Xiao, Gaoxi & Wang, Peng, 2023. "Lithium-ion battery health estimation with real-world data for electric vehicles," Energy, Elsevier, vol. 270(C).
    11. Zheng, Xuejing & Yang, Xueqing & Miao, Hongfei & Liu, Huzhen & Yu, Yanzhe & Wang, Yaran & Zhang, Huan & You, Shijun, 2022. "A factor analysis and self-organizing map based evaluation approach for the renewable energy heating potentials at county level: A case study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    12. Xu, Meng & Reichman, Benjamin & Wang, Xia, 2019. "Modeling the effect of electrode thickness on the performance of lithium-ion batteries with experimental validation," Energy, Elsevier, vol. 186(C).
    13. Tian, Jiaqiang & Wang, Yujie & Liu, Chang & Chen, Zonghai, 2020. "Consistency evaluation and cluster analysis for lithium-ion battery pack in electric vehicles," Energy, Elsevier, vol. 194(C).
    14. Fan, Xinyuan & Zhang, Weige & Sun, Bingxiang & Zhang, Junwei & He, Xitian, 2022. "Battery pack consistency modeling based on generative adversarial networks," Energy, Elsevier, vol. 239(PE).
    15. Wassiliadis, Nikolaos & Ank, Manuel & Wildfeuer, Leo & Kick, Michael K. & Lienkamp, Markus, 2021. "Experimental investigation of the influence of electrical contact resistance on lithium-ion battery testing for fast-charge applications," Applied Energy, Elsevier, vol. 295(C).
    16. Zhang, Xu & Wang, Yujie & Wu, Ji & Chen, Zonghai, 2018. "A novel method for lithium-ion battery state of energy and state of power estimation based on multi-time-scale filter," Applied Energy, Elsevier, vol. 216(C), pages 442-451.
    17. Zhang, Caiping & Jiang, Yan & Jiang, Jiuchun & Cheng, Gong & Diao, Weiping & Zhang, Weige, 2017. "Study on battery pack consistency evolutions and equilibrium diagnosis for serial- connected lithium-ion batteries," Applied Energy, Elsevier, vol. 207(C), pages 510-519.
    18. Ding, Zhixiong & Wu, Wei & Chen, Youming & Leung, Michael, 2020. "Dynamic characteristics and performance improvement of a high-efficiency double-effectthermal battery for cooling and heating," Applied Energy, Elsevier, vol. 264(C).
    19. Murali, G. & Sravya, G.S.N. & Jaya, J. & Naga Vamsi, V., 2021. "A review on hybrid thermal management of battery packs and it's cooling performance by enhanced PCM," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    20. Arno Kwade & Wolfgang Haselrieder & Ruben Leithoff & Armin Modlinger & Franz Dietrich & Klaus Droeder, 2018. "Current status and challenges for automotive battery production technologies," Nature Energy, Nature, vol. 3(4), pages 290-300, April.
    21. Wu, Muyao & Zhong, Yiming & Wu, Ji & Wang, Yuqing & Wang, Li, 2023. "State of health estimation of the lithium-ion power battery based on the principal component analysis-particle swarm optimization-back propagation neural network," Energy, Elsevier, vol. 283(C).
    22. Wang, Yujie & Chen, Zonghai, 2020. "A framework for state-of-charge and remaining discharge time prediction using unscented particle filter," Applied Energy, Elsevier, vol. 260(C).
    23. Xiaoyu Li & Kai Song & Guo Wei & Rengui Lu & Chunbo Zhu, 2015. "A Novel Grouping Method for Lithium Iron Phosphate Batteries Based on a Fractional Joint Kalman Filter and a New Modified K-Means Clustering Algorithm," Energies, MDPI, vol. 8(8), pages 1-26, July.
    24. Lai, Xin & Huang, Yunfeng & Deng, Cong & Gu, Huanghui & Han, Xuebing & Zheng, Yuejiu & Ouyang, Minggao, 2021. "Sorting, regrouping, and echelon utilization of the large-scale retired lithium batteries: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    25. Tian, Jiaqiang & Xu, Ruilong & Wang, Yujie & Chen, Zonghai, 2021. "Capacity attenuation mechanism modeling and health assessment of lithium-ion batteries," Energy, Elsevier, vol. 221(C).
    26. Das, Utpal Kumar & Shrivastava, Prashant & Tey, Kok Soon & Bin Idris, Mohd Yamani Idna & Mekhilef, Saad & Jamei, Elmira & Seyedmahmoudian, Mehdi & Stojcevski, Alex, 2020. "Advancement of lithium-ion battery cells voltage equalization techniques: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    27. Zhiwei He & Mingyu Gao & Guojin Ma & Yuanyuan Liu & Lijun Tang, 2016. "Battery Grouping with Time Series Clustering Based on Affinity Propagation," Energies, MDPI, vol. 9(7), pages 1-11, July.
    28. Jiang, Jiuchun & Ruan, Haijun & Sun, Bingxiang & Wang, Leyi & Gao, Wenzhong & Zhang, Weige, 2018. "A low-temperature internal heating strategy without lifetime reduction for large-size automotive lithium-ion battery pack," Applied Energy, Elsevier, vol. 230(C), pages 257-266.
    29. Chang, Chun & Wu, Yutong & Jiang, Jiuchun & Jiang, Yan & Tian, Aina & Li, Taiyu & Gao, Yang, 2022. "Prognostics of the state of health for lithium-ion battery packs in energy storage applications," Energy, Elsevier, vol. 239(PB).
    30. Li, Changlong & Cui, Naxin & Chang, Long & Cui, Zhongrui & Yuan, Haitao & Zhang, Chenghui, 2022. "Effect of parallel connection topology on air-cooled lithium-ion battery module: Inconsistency analysis and comprehensive evaluation," Applied Energy, Elsevier, vol. 313(C).
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