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Simple Diagnosis of Lifetime Characteristics of Used Automotive Storage Battery Cells

Author

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  • Norihiro Shimoi

    (Department of Electrical and Electronic Engineering, Tohoku Institute of Technology, 35-1 Yagiyama, Kasumicho, Taihaku-ku, Sendai 982-8577, Japan)

  • Kazuyuki Tohji

    (Department of Electrical and Electronic Engineering, Tohoku Institute of Technology, 35-1 Yagiyama, Kasumicho, Taihaku-ku, Sendai 982-8577, Japan)

Abstract

In constructing a nanogrid for the effective use of renewable energy, such as solar power, the use of storage batteries is considered as a stabilizer for capturing renewable energy and outputting it in an energy-saving manner. Storage batteries that are included in a battery management system that includes their reuse in a vehicle are expected to be discharged into the market in large quantities over their long lifetime. Storage battery modules obtained from an unspecified number of electric vehicles (EVs), hybrid vehicles (HVs) and plug-in hybrid vehicles (PHVs) will vary in their charge/discharge capacity from module to module and it is crucial to determine the stability in terms of the state of charge and the state of health of the modules before their reuse. However, in an automotive storage battery module, multiple battery cells are connected in series or in parallel, and there is no established method of managing the variation in the output of each battery cell. Therefore, in this study, we propose an accurate charge–discharge state estimation technique for each cell using impedance characteristic evaluation based on an electrochemical method as a simple and quick method of grasping the charge–discharge performance of storage batteries equipped in a vehicle.

Suggested Citation

  • Norihiro Shimoi & Kazuyuki Tohji, 2022. "Simple Diagnosis of Lifetime Characteristics of Used Automotive Storage Battery Cells," Energies, MDPI, vol. 15(23), pages 1-9, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8814-:d:980841
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    References listed on IDEAS

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    1. Yang, Fangfang & Xing, Yinjiao & Wang, Dong & Tsui, Kwok-Leung, 2016. "A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile," Applied Energy, Elsevier, vol. 164(C), pages 387-399.
    2. Zuchang Gao & Cheng Siong Chin & Wai Lok Woo & Junbo Jia, 2017. "Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO 4 Battery in Actual Embedded Application," Energies, MDPI, vol. 10(1), pages 1-22, January.
    3. He, Yao & Liu, XingTao & Zhang, ChenBin & Chen, ZongHai, 2013. "A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries," Applied Energy, Elsevier, vol. 101(C), pages 808-814.
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    1. Nikolay Vikhorev & Andrey Kurkin & Dmitriy Aleshin & Danil Ulyanov & Maksim Konstantinov & Andrey Shalukho, 2023. "Battery Dynamic Balancing Method Based on Calculation of Cell Voltage Reference Value," Energies, MDPI, vol. 16(9), pages 1-17, April.

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