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Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression
International Journal of Green Energy ( IF 3.1 ) Pub Date : 2020-05-13
Xinyou Lin, Guangji Zhang, Shenshen Wei, Yanli Yin

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.



中文翻译:

基于多元线性回归的双电机电动汽车能耗估算模型

电动汽车(EV)的行驶范围是阻碍其普及性的主要限制之一。大量研究致力于提高电动汽车的续驶里程,准确而有效的能耗估算在这些研究中起着至关重要的作用。但是,大多数电动汽车的能耗估算模型都是基于单电机电动汽车,这些模型不适用于由更复杂的传动机构和多种运行模式组成的双电机电动汽车。因此,提出了双电机电动汽车的能耗估算模型来估算电池电量。本文重点研究每种操作模式下的操作模式和系统效率。每种模式工作区域的限制可确保车辆动态性能,然后采用PSO算法优化两个电动机之间的转矩(速度)分配,以提高耦合驱动模式下的系统效率。最后,通过多元线性回归(MLR)建立能耗估算模型。结果表明,该模型在双电机电动汽车能耗估算中具有较高的精度。

更新日期:2020-05-13
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