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• W4385652246 startingPage "121289" @default.
• W4385652246 abstract "The battery thermal management system is of critical significance to the safety and efficient operation of lithium-ion batteries (LIBs). In the battery thermal management system, the structure parameters limit the performance of liquid cooling systems. In this article, a two-step surrogate model is constructed to optimize the structure of the liquid cooling system, which balances the performance and cost of the cooling system. Firstly, the construction procedure of the two-step surrogate model consists of three parts: the generation of the approximate and detailed simulations, the construction and correction of the primary model, and the accuracy verification of the secondary model. The two-step surrogate model balances the accuracy and the spent resources, by using a large number of approximate simulations and little detailed simulations. Compared with the conventional single-step surrogate model, the time required to construct the two-step surrogate model is reduced by 1024 min, although the mean absolute error is increased just marginally from 0.3334 °C to 0.3696 °C. Secondly, the cold plate structure optimization under different working conditions is completed by combining the second-generation non-dominated genetic algorithm. The variation of the flow channel diameter with the working conditions is analyzed. Taking the structure parameters when the maximum temperature is the minimum value as an example, the diameter of the flow channel decreases drastically with the increase of the battery heat generation rate at the beginning, and finally remains at 3 mm. Moreover, the diameter of flow channel tends to increase linearly with the increase of coolant flow rate." @default.
• W4385652246 created "2023-08-09" @default.
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• W4385652246 date "2023-11-01" @default.
• W4385652246 modified "2023-10-15" @default.
• W4385652246 title "Structure optimization of the battery thermal management system based on surrogate modeling of approximate and detailed simulations" @default.
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• W4385652246 doi "https://doi.org/10.1016/j.applthermaleng.2023.121289" @default.
• W4385652246 hasPublicationYear "2023" @default.
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