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Control-oriented thermal-electrochemical modeling and validation of large size prismatic lithium battery for commercial applications

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  • Li, Dongdong
  • Yang, Lin
  • Li, Chun

Abstract

Adopting the uniform temperature for thermal-electrochemical model is not suitable to simulate the large size battery which has big temperature difference between internal and surface. Furthermore, heavy computational burden of coupling model hinders the control-oriented onboard applications. Therefore, considering the compensation with spatial temperature, a control-oriented thermal-electrochemical model is proposed and validated for commercial large size battery. For both parts of coupled model, the multilayer thermal model and polynomial approximation method are applied to describe the thermal behavior and electrochemical process. And the two-way effects are coupled by the temperature dependent parameters which have vital influence in electrochemical reactions. Furthermore, the effectiveness of control-oriented thermal model and electrochemical model is validated under two typical cycles and constant current loading at wide temperature range (−25 °C–45 °C). Meanwhile, the variation of temperature dependent parameters and accuracy of coupled model are validated under two typical cycles at wide ambient temperature range. The results show that, for commercial large size battery, comparing with famous pseudo-two-dimensional model widely used in offline simulation, the accuracy is improved on average at different temperatures, and computational time falls 98.5% under dynamic loading conditions which satisfies the requirement of online calculation.

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  • Li, Dongdong & Yang, Lin & Li, Chun, 2021. "Control-oriented thermal-electrochemical modeling and validation of large size prismatic lithium battery for commercial applications," Energy, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:energy:v:214:y:2021:i:c:s0360544220321642
    DOI: 10.1016/j.energy.2020.119057
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    References listed on IDEAS

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    Cited by:

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    2. Lu, Xin & Chen, Ning & Li, Hui & Guo, Shiyu & Chen, Zengtao, 2023. "Simulation of the temperature distribution of lithium-ion battery module considering the time-delay effect of the porous electrodes," Energy, Elsevier, vol. 284(C).
    3. Hao Fan & Lan Wang & Wei Chen & Bin Liu & Pengxin Wang, 2023. "A J-Type Air-Cooled Battery Thermal Management System Design and Optimization Based on the Electro-Thermal Coupled Model," Energies, MDPI, vol. 16(16), pages 1-19, August.
    4. Zhang, Qisong & Yang, Lin & Guo, Wenchao & Qiang, Jiaxi & Peng, Cheng & Li, Qinyi & Deng, Zhongwei, 2022. "A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system," Energy, Elsevier, vol. 241(C).
    5. Gao, Yizhao & Zhu, Chong & Zhang, Xi & Guo, Bangjun, 2021. "Implementation and evaluation of a practical electrochemical- thermal model of lithium-ion batteries for EV battery management system," Energy, Elsevier, vol. 221(C).
    6. S. Tamilselvi & S. Gunasundari & N. Karuppiah & Abdul Razak RK & S. Madhusudan & Vikas Madhav Nagarajan & T. Sathish & Mohammed Zubair M. Shamim & C. Ahamed Saleel & Asif Afzal, 2021. "A Review on Battery Modelling Techniques," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    7. Eapen, Deepa Elizabeth & Suresh, Resmi & Patil, Sairaj & Rengaswamy, Raghunathan, 2021. "A systems engineering perspective on electrochemical energy technologies and a framework for application driven choice of technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    8. Gao, Yizhao & Liu, Chenghao & Chen, Shun & Zhang, Xi & Fan, Guodong & Zhu, Chong, 2022. "Development and parameterization of a control-oriented electrochemical model of lithium-ion batteries for battery-management-systems applications," Applied Energy, Elsevier, vol. 309(C).

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