基于卡尔曼滤波的纯电动汽车实时环境温度估计与牵引功率感知的座舱气候控制

Maryam Alizadeh, Sumedh Dhale, A. Emadi
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引用次数: 0

摘要

在本文中,提出了一种改进的气候控制系统,用于电池电动汽车(BEV)的暖通空调(HVAC)单元,以提高系统的效率,同时保持乘客所需的舱内温度。由于纯电动汽车的暖通空调使用完全依赖于电池供电,因此根据电池状态调整暖通空调控制以提高电池利用率至关重要。因此,我们提出的气候控制系统考虑了暖通空调模型的动力学,同时考虑了环境温度和路线行为对电力使用的重要性,这需要在客舱内提供舒适的气候。由于环境温度在估算所需的暖通空调功率方面起着至关重要的作用,因此有必要对其进行精确评估。为此,设计了卡尔曼滤波器,实现了高精度的实时温度估计。此外,考虑了行驶周期对牵引电机的影响,通过调整气候控制器在不同天气条件下的行为,提高车辆系统的整体性能和电池的健康状况。在MATLAB/Simulink®中进行了全面的仿真研究,以评估所提出的气候控制技术和基于卡尔曼滤波的环境温度估计的有效性。
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Real-Time Ambient Temperature Estimation Using Kalman Filter and Traction Power-Aware Cabin Climate Control in Battery Electric Vehicles
In this paper, an improved climate control system is presented for a Heating, Ventilation, and Air conditioning (HVAC) unit of a battery electric vehicle (BEV) to improve the system’s efficiency while maintaining the desired cabin temperature for the passengers. Since BEVs are entirely dependent on the battery power for HVAC usage, it is crucial to adapt the HVAC control according to the battery status to improve the battery usage. Therefore, our proposed climate control system has taken into account the dynamics of the HVAC model while considering the importance of the ambient temperature and route behavior on the power usage that is needed to provide a comfortable climate in the cabin. Since the ambient temperature has a critical role in estimating the required HVAC power, it is necessary to assess it precisely. Accordingly, a Kalman filter is designed to achieve high precision temperature estimation in real-time. Furthermore, the effect of the driving cycle on the traction motor is considered to improve the overall performance of the vehicle’s system and battery’s health by adjusting climate controller behavior in different weather conditions. A comprehensive simulation study in MATLAB/Simulink® is provided to evaluate the effectiveness of the proposed climate control technique and Kalman filter based ambient temperature estimation.
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