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<p>During charging and discharging, lithium-ion batteries generate a substantial amount of heat, which may lead to thermal runaway and compromise both battery safety and longevity. The battery thermal management system (BTMS) is to monitor and regulate battery temperature in real-time, ensuring that batteries maintain optimal operating temperatures under various conditions to enable efficient and safe operation. As a complex, multidisciplinary coupled system, traditional design methods for BTMS encounter limitations in precision and response speed, making it challenging to fully meet the increasingly stringent thermal management requirements of lithium-ion batteries. To address this, by combining the advantages of twin data (TD) and multidisciplinary design optimization (MDO), a TD-driven MDO method is proposed for the BTMS in this study. A TD-driven MDO framework is firstly proposed and the corresponding configuration and operation processes are detailedly provided. Then, the multidisciplinary analysis of the BTMS is performed using the multidisciplinary hierarchical analysis method and subsequently the TD for the BTMS is built by employing the Radial Basis Function (RBF). With objectives to maximize battery life, minimize battery size, and minimize operating temperature, the TD-driven MDO model is developed for the BTMS and solved using the proposed TD-driven MDO framework. Computational Fluid Dynamics (CFD) simulations are used to verify the accuracy of the proposed approach, and comparisons with traditional MDO methods confirm its superiority. Results demonstrate that the proposed TD-driven MDO method can effectively extend battery lifespan by 25.25% and lower the maximum operating temperature by 7.21%, demonstrating comprehensive superiorities compared to the conventional method.</p>

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Twin data-driven multidisciplinary design optimization of air-based battery thermal management system in electric vehicles

  • 期刊论文

  • 发表日期：

    2025年10月15日

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  • Xiaobang Wang,
  • Tongrong Zhang,
  • Zijun Gao,
  • Bing Liang,
  • Jie Zhao,
  • Zhijie Liu

摘要

During charging and discharging, lithium-ion batteries generate a substantial amount of heat, which may lead to thermal runaway and compromise both battery safety and longevity. The battery thermal management system (BTMS) is to monitor and regulate battery temperature in real-time, ensuring that batteries maintain optimal operating temperatures under various conditions to enable efficient and safe operation. As a complex, multidisciplinary coupled system, traditional design methods for BTMS encounter limitations in precision and response speed, making it challenging to fully meet the increasingly stringent thermal management requirements of lithium-ion batteries. To address this, by combining the advantages of twin data (TD) and multidisciplinary design optimization (MDO), a TD-driven MDO method is proposed for the BTMS in this study. A TD-driven MDO framework is firstly proposed and the corresponding configuration and operation processes are detailedly provided. Then, the multidisciplinary analysis of the BTMS is performed using the multidisciplinary hierarchical analysis method and subsequently the TD for the BTMS is built by employing the Radial Basis Function (RBF). With objectives to maximize battery life, minimize battery size, and minimize operating temperature, the TD-driven MDO model is developed for the BTMS and solved using the proposed TD-driven MDO framework. Computational Fluid Dynamics (CFD) simulations are used to verify the accuracy of the proposed approach, and comparisons with traditional MDO methods confirm its superiority. Results demonstrate that the proposed TD-driven MDO method can effectively extend battery lifespan by 25.25% and lower the maximum operating temperature by 7.21%, demonstrating comprehensive superiorities compared to the conventional method.