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Battery thermal management strategy for electric vehicles based on nonlinear model predictive control
Measurement ( IF 5.6 ) Pub Date : 2021-09-04 , DOI: 10.1016/j.measurement.2021.110115
Yan Ma 1, 2 , Hao Ding 2 , Hongyuan Mou 2 , Jinwu Gao 1, 2
Affiliation  

As the temperature has a great effect on the cycle life and capacity of power battery on electric vehicles (EVs), a practical battery thermal management (BTM) strategy is required to adjust the battery temperature within an appropriate range and reduce the temperature inconsistency in the battery module. To achieve the multiple objectives, a nonlinear model predictive control (NMPC) method is proposed to optimize the cooling process of battery module. Firstly, a lumped thermal model of single lithium-ion battery under air cooling is presented, which considers the change of internal resistance with temperature and the change of heat transfer coefficient with coolant velocity. Considering the temperature inconsistency in the battery module, a thermal model of the battery module is derived based on the law of conservation of energy and verified. Due to the nonlinearity, time-varying parameters and multiple constraints of the thermal management system, the NMPC method is designed. Particle swarm optimization is used to solve the nonlinear programming problem in NMPC method. The simulation results show that the NMPC method ensures that the battery works near the target temperature under different working conditions, the deviation is less than 0.5 K, and the temperature inconsistency in the battery module is less than 1.2 K. In addition, compared with the PID method, the air flow consumption is effectively reduced.



中文翻译:

基于非线性模型预测控制的电动汽车电池热管理策略

由于温度对电动汽车(EV)动力电池的循环寿命和容量有很大影响,因此需要一种实用的电池热管理(BTM)策略,将电池温度调节在合适的范围内,减少电池内部的温度不一致性。电池模块。为了实现多个目标,提出了一种非线性模型预测控制(NMPC)方法来优化电池模块的冷却过程。首先,提出了空冷下单节锂离子电池集总热模型,该模型考虑了内阻随温度的变化和传热系数随冷却液速度的变化。考虑到电池模块内部温度的不一致性,基于能量守恒定律推导出电池模块的热模型并进行验证。由于热管理系统的非线性、时变参数和多重约束,设计了NMPC方法。粒子群优化用于解决NMPC方法中的非线性规划问题。仿真结果表明,NMPC方法保证了电池在不同工况下工作在目标温度附近,偏差小于0.5 K,电池模块内温度不一致性小于1.2 K。 PID方式,有效降低风量消耗。

更新日期:2021-09-19
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