An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning

	An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning
	Yue Hu; Weimin Li; Hui Xu; Guoqing Xu
刊名	Energies
	2015
英文摘要	In order to realize the online learning of a hybrid electric vehicle (HEV) control strategy, a fuzzy Q-learning (FQL) method is proposed in this paper. FQL control strategies consists of two parts: The optimal action-value function Q(x,u) estimator network (QEN) and the fuzzy parameters tuning (FPT). A back propagation (BP) neural network is applied to estimate Q(x,u) as QEN. For the fuzzy controller, we choose a Sugeno-type fuzzy inference system (FIS) and the parameters of the FIS are tuned online based on Q*(x,u). The action exploration modifier (AEM) is introduced to guarantee all actions are tried. The main advantage of a FQL control strategy is that it does not rely on prior information related to future driving conditions and can self-tune the parameters of the fuzzy controller online. The FQL control strategy has been applied to a HEV and simulation tests have been done. Simulation results indicate that the parameters of the fuzzy controller are tuned online and that a FQL control strategy achieves good performance in fuel economy.
收录类别	SCI
原文出处	http://www.mdpi.com/1996-1073/8/10/11167/htm
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/6607]
专题	深圳先进技术研究院_集成所
作者单位	Energies
推荐引用方式 GB/T 7714	Yue Hu,Weimin Li,Hui Xu,et al. An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning[J]. Energies,2015.
APA	Yue Hu,Weimin Li,Hui Xu,&Guoqing Xu.(2015).An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning.Energies.
MLA	Yue Hu,et al."An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning".Energies (2015).