基于优化的电池热管理,改进 CEP 车辆的再生制动性能

Dominik Rehm, Jonathan Krost, Martin Meywerk, Walter Czarnetzki
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引用次数: 0

摘要

近年来,由于包裹量不断增加,快递包裹服务行业(CEP 行业)经历了重大变化。与此同时,车队的电气化也带来了更多挑战。与内燃机车辆相比,电池电动 CEP 车辆的一大优势是能够在包裹递送过程中的频繁减速阶段再生车辆动能。如果电池处于低温状态,动力系统的最大再生功率就会受到电池内部化学反应速率降低的限制。一般来说,电池的最大充电功率取决于充电状态和电池温度。由于 CEP 运行期间的驾驶功率需求较低,因此电池的自热度也相对较低。如果不对电池进行主动调节,再生能量的潜力就会部分丧失,因为只要超过冷电池的极限,摩擦制动器就需要吸收动能。本文提出了一种基于优化的 CEP 车辆电池热管理策略。研究了在寒冷环境条件下电池加热成本与再生制动效益之间的权衡。为此,本文开发了一种非线性模型预测控制方法,根据即将到来的驾驶任务,通过选择性电池加热实现车辆整体效率的最大化。评估结果表明,整体效率的提高取决于电池加热系统的电力效率、环境条件、减速阶段的强度和频率以及车辆的使用行为。在可以准确预测驾驶周期和环境条件的前提下,环中模型模拟表明,使用电冷却液加热器最多可减少 3.3% 的能耗,使用环境热泵最多可减少 9.6% 的能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization-Based Battery Thermal Management for Improved Regenerative Braking in CEP Vehicles
The courier express parcel service industry (CEP industry) has experienced significant changes in the recent years due to increasing parcel volume. At the same time, the electrification of the vehicle fleets poses additional challenges. A major advantage of battery electric CEP vehicles compared to internal combustion engine vehicles is the ability to regenerate the kinetic energy of the vehicle in the frequent deceleration phases during parcel delivery. If the battery is cold, the maximum regenerative power of the powertrain is limited by a reduced chemical reaction rate inside the battery. In general, the maximum charging power of the battery depends on the state of charge and the battery temperature. Due to the low power demand for driving during CEP operation, the battery self-heating is comparably low. Without active conditioning of the battery, potential of regenerating energy is partially lost because the friction brake needs to absorb kinetic energy whenever the cold battery’s limit is exceeded. This paper proposes an optimization-based strategy for the battery thermal management of CEP vehicles. The tradeoff between the cost of battery heating and the benefit of regenerative braking is investigated under cold ambient conditions. For this purpose, a nonlinear model predictive control approach is developed to maximize the overall vehicle efficiency depending on the upcoming driving task by selective battery heating. The evaluation shows that the increase in overall efficiency depends on the electric efficiency of the battery heating system, the ambient conditions, the intensity and frequency of the deceleration phases, and the usage behavior of the vehicle. Based on the assumption that the driving cycle and ambient conditions can be accurately predicted, the model-in-the-loop simulation indicates a reduction in energy consumption of up to 3.3 % with an electric coolant heater and up to 9.6 % with an ambient heat pump.
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