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Multi-Objective Optimization of Activation Time and Discharge Time of Thermal Battery Using a Genetic Algorithm Approach

Author

Listed:
  • Qing Li

    (School of Electromechanical Engineering, Xidian University, Xi’an 710071, China
    The 18th Research Institute of China Electronics Technology Group Corporation, Tianjin 300384, China)

  • Yu-Qiang Shao

    (School of Electromechanical Engineering, Xidian University, Xi’an 710071, China)

  • Huan-Ling Liu

    (School of Electromechanical Engineering, Xidian University, Xi’an 710071, China)

  • Xiao-Dong Shao

    (School of Electromechanical Engineering, Xidian University, Xi’an 710071, China)

Abstract

Activation time and discharge time are important criteria for the performance of thermal batteries. In this work a heat transfer analysis is carried out on the working process of thermal batteries. The effects of the thicknesses of heat pellets which are divided into three groups and that of the thickness of insulation layers on activation time and discharge time of thermal batteries are numerically studied using Fluent 15.0 when the sum of the thickness of heating plates and insulation layers remain unchanged. According to the numerical results, the optimal geometric parameters are obtained by using multi-objective genetic algorithm. The results show that the activation time is mainly determined by the thickness of the bottom heat pellet, while the discharge time is determined by the thickness of the heat pellets and that of the insulation layers. The discharge time of the optimized thermal battery is increased by 4.08%, and the activation time is increased by 1.23%.

Suggested Citation

  • Qing Li & Yu-Qiang Shao & Huan-Ling Liu & Xiao-Dong Shao, 2020. "Multi-Objective Optimization of Activation Time and Discharge Time of Thermal Battery Using a Genetic Algorithm Approach," Energies, MDPI, vol. 13(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6477-:d:458541
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    References listed on IDEAS

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