论文标题
部分可观测时空混沌系统的无模型预测
Computationally Efficient Approach for Preheating of Battery Electric Vehicles before Fast Charging in Cold Climates
论文作者
论文摘要
本文在快速充电前调查电池预热，以便在寒冷的气候下驾驶电池电动汽车（BEV）。为了防止电池在低温下的性能降解，已经考虑了热管理（TM）系统，包括用于电池和机舱隔室加热的高压冷却液加热器（HVCH）。因此，已经以非线性程序（NLP）的形式制定了最佳控制问题（OCP），旨在最大程度地减少电池的总能耗。这里的主要重点是开发一种计算高效的方法，模仿最佳的预热行为，而不会显着增加总能耗。所提出的算法很简单，可以通过消除求解整个NLP的需求仅在总能源消耗增加1WH的成本中实现在车辆的低级电子控制单元中。
This paper investigates battery preheating before fast charging, for a battery electric vehicle (BEV) driving in a cold climate. To prevent the battery from performance degradation at low temperatures, a thermal management (TM) system has been considered, including a high-voltage coolant heater (HVCH) for the battery and cabin compartment heating. Accordingly, an optimal control problem (OCP) has been formulated in the form of a nonlinear program (NLP), aiming at minimising the total energy consumption of the battery. The main focus here is to develop a computationally efficient approach, mimicking the optimal preheating behavior without a noticeable increase in the total energy consumption. The proposed algorithm is simple enough to be implemented in a low-level electronic control unit of the vehicle, by eliminating the need for solving the full NLP in the cost of only 1Wh increase in the total energy consumption.
