A fuzzy Q-learning based assisted power management method for comfortable riding of pedelec

Cheng-Ting Liu, R. Hsu
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引用次数: 2

Abstract

In this study, a fuzzy logic controller with parameters tuned by Q-learning is proposed for the assisted power management of a pedelec. The pedelec is a human-electric hybrid vehicle driven by mainly the rider's pedal force with the assisted power from the electric motor. The proposed assisted power management (APM) method adaptively provides an appropriate assisted power (action) according to the environmental changes via the fuzzy inference coordinated Q-learning, i.e. fuzzy Q-learning. Simulations of the proposed method, hereafter abbreviated as FQLAPM, on a pedelec are performed, and the results exhibit better performance in comparing with other existent assisted power methods.
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基于模糊q学习的电动自行车舒适骑行辅助电源管理方法
本文提出了一种基于q学习的模糊控制器,用于电动汽车的辅助电源管理。pedelec是一种人-电混合动力汽车,主要依靠骑手的脚踏力和电动机的辅助动力驱动。提出的辅助功率管理(APM)方法通过模糊推理协调q -学习,即模糊q -学习,自适应地根据环境变化提供适当的辅助功率(动作)。本文对该方法(以下简称FQLAPM)在踏板上进行了仿真,结果表明,与现有的辅助电源方法相比,该方法具有更好的性能。
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