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首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Energy Management and Driving Strategy for In-Wheel Motor Electric Ground Vehicles With Terrain Profile Preview
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Energy Management and Driving Strategy for In-Wheel Motor Electric Ground Vehicles With Terrain Profile Preview

机译：带有地形剖面的轮毂电动地面车辆的能量管理和驾驶策略

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摘要

This paper presents a terrain-information- and actuator-efficiency-incorporated energy management and driving strategy (EMDS) for maximizing the travel distance of in-wheel motor, pure electric ground vehicles (EGVs). Minimization of energy consumption for a certain trip with terrain preview based on the operating efficiencies of in-wheel motors and a traffic model is essential to maximize the total travel distances of an EGV. Unlike conducting energy optimization under given vehicle speed profiles that are specified a priori in most literature, the optimally varied vehicle velocity and globally optimal in-wheel motor actuation torque distributions are simultaneously obtained to minimize the EGV energy consumption by employing the dynamic programming method for the first time. As a comparison, CarSim-matlab/Simulink co-simulation results based on a model predictive control design are displayed to not only validate that the energy optimization results from the EMDS design is a benchmark with the least power consumption, but also to show that the driving strategy derived from the EMDS can be potentially utilized as an energy-optimal speed reference for other real-time implementable methods.
机译：本文提出了一种结合了地形信息和执行器效率的能源管理和驾驶策略（EMDS），以最大程度地增加轮式电动机，纯电动地面车辆（EGV）的行驶距离。基于轮毂电机和交通模型的运行效率，通过地形预览来最大程度地减少特定行程的能量消耗，对于最大化EGV的总行驶距离至关重要。与在大多数文献中先验指定的给定车速曲线下进行能量优化不同，通过采用动态编程方法，可以同时获得最佳变化的车速和全局最优的轮内电动机驱动扭矩分布，以最大程度地降低EGV能耗。第一次。作为比较，显示了基于模型预测控制设计的CarSim-matlab / Simulink联合仿真结果，不仅可以验证EMDS设计的能源优化结果是功耗最低的基准，而且还可以证明EMDS得出的驱动策略可以潜在地用作其他实时可行方法的能量最佳速度参考。

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