基于神经网络和称重传感器的小型电动汽车耦合分布式驱动系统

T. Ogitsu, Tokunosuke Ikegami, S. Kato, H. Mizoguchi
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引用次数: 2

摘要

日本正面临着在人口稀少的城市提供一般公共交通系统的困难。本文提出了一种适用于此类城市的新型交通工具。该系统基于带有机械耦合器的小型电动汽车,设计用于连接安装在每个家庭的设备。不幸的是,该系统带来了一个问题,即如何提高耦合电动汽车驾驶员的可操作性。因此,本研究着手开发一种分布式驱动系统,以确保一组车辆保持与单个车辆相同的驾驶特性,而无论耦合车辆的数量如何。该系统通过使用神经网络的车辆模型在线学习和使用力计的反馈控制来抑制驾驶特性的波动。本文详细介绍了该系统的设计细节,并在两辆小型电动汽车上进行了评价实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Driving System for Coupled Small EV Using Neural Network and Load Cell
Japan is facing difficulties with providing general public transport systems in depopulated cities. This paper proposes a new means of transport for application to such cities. The system is based on small electric vehicles with mechanical couplers that are designed to attach to devices installed at each home. Unfortunately, this system incurs an issue of enhancing the operability for drivers of the coupled EVs. Therefore, this study set out to develop a distributed driving system that ensures that a group of vehicles maintains the same driving characteristics as those of a single vehicle, regardless of the number of coupled vehicles. This system suppresses fluctuations in the driving characteristics by means of online learning by the vehicle model using a neural network and by feedback control using a force gauge. This paper describes the details of this system and evaluation experiments using two small EVs.
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