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Iterative Dynamic Programming Strategy for Electric Vehicle Battery Thermal Management Optimization
Advanced Theory and Simulations ( IF 2.9 ) Pub Date : 2022-04-14 , DOI: 10.1002/adts.202100602 Yan Ma 1 , Jiayi Li 2
Advanced Theory and Simulations ( IF 2.9 ) Pub Date : 2022-04-14 , DOI: 10.1002/adts.202100602 Yan Ma 1 , Jiayi Li 2
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Lithium-ion batteries are extensively used in electric vehicles because of their superior performance in the general environment of global energy shortage. However, lithium-ion batteries generate large amounts of heat as the battery packs are charged and discharged. If this accumulated heat is not dissipated timely, then the power supply system will fail, resulting in safety accidents. Therefore, a high-efficiency and energy-saving optimization strategy is required for both ensuring operating temperature of the battery and saving energy. Herein, a lumped thermal model is established on the basis of the heat generation characteristics of batteries and Newton's law of cooling, and its exactitude is proven by comparison with a liquid cooling system established using AMESim. In addition, to reduce computation time and enhance the real-time capability, an iterative dynamic programming (IDP) method is proposed to determine the optimal values iteratively in a multidimensional search space, in view of the high nonlinearity and time-variability of a battery thermal management system as well as the complexity of dynamic programming (DP). Thus, the results from co-simulations performed in Matlab and AMESim verify that the proposed strategy has high cooling efficiency and can save considerable energy for cooling system compared with PID and DP.
中文翻译：
电动汽车电池热管理优化的迭代动态规划策略
锂离子电池因其在全球能源短缺的大环境下的优越性能而被广泛应用于电动汽车。然而，锂离子电池在电池组充电和放电时会产生大量热量。如果这些积聚的热量没有及时散去，那么供电系统就会出现故障，从而导致安全事故。因此，既要保证电池的工作温度，又要节能，需要一种高效节能的优化策略。本文根据电池的发热特性和牛顿冷却定律建立了集总热模型，并通过与AMESim建立的液冷系统进行对比验证了其准确性。此外，针对电池热管理系统的高非线性和时变性，提出了一种迭代动态规划（IDP）方法，用于在多维搜索空间中迭代确定最优值，以减少计算时间并提高实时性。以及动态规划（DP）的复杂性。因此，在 Matlab 和 AMESim 中进行的联合仿真结果验证了所提出的策略具有较高的冷却效率，与 PID 和 DP 相比，可以为冷却系统节省大量能源。
更新日期：2022-04-14
中文翻译：
电动汽车电池热管理优化的迭代动态规划策略
锂离子电池因其在全球能源短缺的大环境下的优越性能而被广泛应用于电动汽车。然而，锂离子电池在电池组充电和放电时会产生大量热量。如果这些积聚的热量没有及时散去，那么供电系统就会出现故障，从而导致安全事故。因此，既要保证电池的工作温度，又要节能，需要一种高效节能的优化策略。本文根据电池的发热特性和牛顿冷却定律建立了集总热模型，并通过与AMESim建立的液冷系统进行对比验证了其准确性。此外，针对电池热管理系统的高非线性和时变性，提出了一种迭代动态规划（IDP）方法，用于在多维搜索空间中迭代确定最优值，以减少计算时间并提高实时性。以及动态规划（DP）的复杂性。因此，在 Matlab 和 AMESim 中进行的联合仿真结果验证了所提出的策略具有较高的冷却效率，与 PID 和 DP 相比，可以为冷却系统节省大量能源。
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