Design and optimization of the in-wheel motor driving electric vehicle based on the vibration energy transmission

拓扑优化 振动 拓扑(电路) 能量(信号处理) 正确性 电动汽车 控制理论(社会学) 键合图 计算机科学 工程类 数学 有限元法 结构工程 算法 声学 物理 功率(物理) 人工智能 电气工程 组合数学 统计 控制(管理) 量子力学
作者
Di Tan,Fan Song,Qiang Wang
出处
期刊:Journal of Vibration and Control [SAGE Publishing]
卷期号:: 107754631774525-107754631774525 被引量:3
标识
DOI:10.1177/1077546317745255
摘要

In order to solve the problems of the increasing unsprung mass and the influence of the road excitation on the in-wheel motor (IWM), this paper puts forward two kinds of improved topology schemes. The bond graph (BG) and mathematical models of original and improved topological schemes are developed by using the BG theory. Based on the mathematical model, the final topology scheme is determined by the analysis of vibration energy transfer characteristics for the three schemes. It is further proved that the vibration energy analysis method is effective and complete in revealing the change of the system force and motion through the comparison analysis of the three kinds of topology scheme related to vehicle force and ride comfort index of motion variable. Furthermore, the optimal design is carried out for the determined topology scheme, which is aimed at minimum vibration energy delivered to the vehicle body. The comparison results before and after optimization show that: after optimization, the vibration energy delivered to the vehicle body has significantly decreased in the whole frequency range, and the vibration energy delivered to other components also decreased, which proved the correctness of the optimization method; and the comparison results of ride comfort index before and after optimization validate the effectiveness of the parameter optimization design based on the energy method. Finally, a structure design is provided based on the determined topology scheme. This paper provides an idea and method for the vibration suppression of the IWN driving electric vehicle (EV), while it can also provide some theoretical guidance for the design and optimization of the IWN driving EV.

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