扭矩
行驶循环
计算机科学
稳健性(进化)
能源消耗
控制理论(社会学)
汽车工程
离散化
燃料效率
控制工程
工程类
电动汽车
数学
控制(管理)
数学分析
化学
功率(物理)
人工智能
量子力学
物理
电气工程
基因
热力学
生物化学
作者
Hao Chen,Peng Du,Yüan Wang,Dafeng Jin,Xiaomin Lian
标识
DOI:10.1177/0954407019899205
摘要
In-wheel motor-driven vehicle improves the overall performance with its torque vectoring system, which distributes the torque command of each motor. This paper proposes a novel torque allocation algorithm to dynamically optimize energy consumption of the vehicle. It splits the optimization problem into two sub-problems and obtains the executive torque of each side. The method also simplifies the solution by modification and discretization of feasible torque space, thus ensuring that there must be solvable and reducing online computational load. Two representative simulation cases—New European Driving Cycle and Fault Tolerance—have been selected and conducted through Cruise–Simulink co-simulation platform. The simulation verifies that the method decreases three energy consumption indices by 18.5%, 13.9%, and 14.7%, respectively, than those of the average allocation and coordinates all motors effectively based on vehicle’s operating status, which proves its practicability and robustness.
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