Energetic optimization of automotive thermal systems using mixed-integer programming and model predictive control

Donovan Esqueda-Merino, Alexandra Dubray-Demol, Sorin Olaru, E. Godoy, D. Dumur
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引用次数: 2

Abstract

One of the biggest shortcomings of Electric Vehicles (EV) is related to the range of their battery. This problem can become even more crucial while using some important features of the car, such as those regarding the thermal comfort of the cabin. While highly efficient systems such as heat pumps can be used to overcome this problem, their performance can yet be optimized if combined with some other thermal actuators. To this aim, this paper proposes a Mixed-Integer optimization strategy based on Model Predictive Control (MPC). The results give substantial gains using both linear and non-linear models.
基于混合整数规划和模型预测控制的汽车热力系统能量优化
电动汽车(EV)最大的缺点之一与电池的续航里程有关。当使用汽车的一些重要功能时,这个问题会变得更加重要,比如那些关于驾驶室热舒适性的功能。虽然热泵等高效系统可以用来克服这个问题,但如果与其他一些热致动器结合使用,它们的性能仍然可以得到优化。为此,提出了一种基于模型预测控制(MPC)的混合整数优化策略。使用线性和非线性模型的结果都得到了可观的收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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