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Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

机译:基于多线性回归的双电机电动车能耗估计模型

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摘要

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.
机译:电动车辆(EV)的驱动范围是阻碍其普遍性的主要限制之一。大量的研究已经致力于推动EV的范围改进,准确和效率的能耗估计在这些研究中起着至关重要的作用。然而,大多数EV的能耗估算模型基于单电机EV,这些型号不适用于双电机EV,由更复杂的传动机制和多种操作模式组成。因此,提出了一种用于双电机EV的能耗估计模型来估计电池功率。本文侧重于在每种操作模式下研究操作模式和系统效率。每个模式的工作区域的限制确保了车辆动态性能,然后采用PSO算法优化两个电动机之间的扭矩(速度)分布,以提高耦合驱动模式中的系统效率。最后,通过多元线性回归(MLR)建立能量消耗估计模型。结果表明,该模型具有高精度的双电机EV的能耗估计。

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