Design and optimization of a hybrid battery thermal management system for electric vehicle based on surrogate model

The hybrid thermal management scheme for lithium-ion battery combining the advantages of various thermal management strategies has been widely adopted. However, due to the complex influence parameters involved in the hybrid thermal management system, its optimal design has become a difficult problem. In this study, a hybrid thermal management system based on phase change material (PCM), liquid cooling, and heat pipe is first designed, and then a precise and reliable numerical heat transfer model is established. In order to optimize the system and improve the optimization efficiency, the Adaptive-Kriging-High dimensional model representation (HDMR) method is used to construct a surrogate model of the thermal management system, and the influencing factors sensitivity analysis and optimization design of the hybrid thermal management system are also conducted. The results show that the thermal conductivity of PCM, the thickness of PCM, the length of heat pipe and the velocity of inlet water have a significant influence on the maximum temperature and temperature difference of the battery system. According to the optimization design of these four factors based on the multi-objective particle swarm optimization (MOPSO), it is found that the optimized thermal management system has the best ability to dissipate heat and maintain temperature uniformity as compared to the original design. In addition, this optimization system has the ability to prevent thermal runaway propagation under the condition of thermal abuse conditions. With these prominent performances, the proposed method is expected to provide insights into the engineering design and optimization of the battery thermal management system for electric vehicle. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

A hybrid thermal management system combining PCM, liquid cooling, and heat pipe is designed, with a numerical heat transfer model established. The Adaptive-Kriging-HDMR method is used to construct a surrogate model and optimize design for the system. Significant influencing factors such as the thermal conductivity of PCM and the velocity of inlet water are identified for improving heat dissipation and temperature uniformity.