Impact of scaling laws of permanent magnet synchronous machines on the accuracy of energy consumption computation of electric vehicles

缩放比例 能源消耗 动力传动系统 功率(物理) 计算 能量(信号处理) 计算机科学 汽车工程 控制理论(社会学) 工程类 算法 数学 扭矩 电气工程 物理 几何学 统计 控制(管理) 量子力学 人工智能 热力学
作者
Ayoub Aroua,Walter Lhomme,Florian Verbelen,Mohamed N. Ibrahim,Alain Bouscayrol,Peter Sergeant,Kurt Stockman
出处
期刊:eTransportation [Elsevier]
卷期号:18: 100269-100269 被引量:1
标识
DOI:10.1016/j.etran.2023.100269
摘要

This paper compares the impact of two scaling methods of electric machines on the energy consumption of electric vehicles. The first one is the linear losses-to-power scaling method of efficiency maps, which is widely used in powertrain design studies. While the second is the geometric scaling method. Linear scaling assumes that the losses of a reference machine are linearly scaled according to the new desired power rating. This assumption is questionable and yet its impact on the energy consumption of electric vehicles remains unknown. Geometric scaling enables rapid and accurate recalculation of the parameters of the scaled machines based on scaling laws validated by finite element analysis. For this comparison, a reference machine design of 80 kW is downscaled with a power scaling factor of 0.58 and upscaled considering a power scaling of 1.96. For comparative purposes, optimal combinations of geometric scaling factors are determined. The scaled machines are derived to fit the driving requirements of two electric vehicles, namely a light-duty vehicle and a medium-duty truck. The comparison is performed for 9 standardized driving cycles. The results show that the maximal relative difference between linear and geometric scaling in terms of energy consumption is 3.5% for the case of the light-duty vehicle, compared with 1.2% for the case of the truck. The findings of this work provide evidence that linear scaling can continue to be used in system-level design studies with a relatively low impact on energy consumption. This is of high interest considering the simplicity of linear scaling and its potential for time-saving in the early development phases of electric vehicles.
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