标题:A neural network fuzzy energy management strategy for hybrid electric vehicles based on driving cycle recognition
作者:Zhang Q.; Fu X.
作者机构:[Zhang, Q] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130025, China, School of Control Science and Engine 更多
通讯作者:Fu, X(fxl@sdu.edu.cn)
通讯作者地址:[Fu, X] Department of Physics, Changji CollegeChina;
来源:Applied Sciences (Switzerland)
出版年:2020
卷:10
期:2
DOI:10.3390/app10020696
关键词:Driving cycle recognition; Energy management strategy; Hybrid electric vehicle; Neural network fuzzy
摘要:Aiming at the problems inherent in the traditional fuzzy energy management strategy (F-EMS), such as poor adaptive ability and lack of self-learning, a neural network fuzzy energy management strategy (NNF-EMS) for hybrid electric vehicles (HEVs) based on driving cycle recognition (DCR) is designed. The DCR was realized by the method of neural network sample learning and characteristic parameter analysis, and the recognition results were considered as the reference input of the fuzzy controller with further optimization of the membership function, resulting in improvement in the poor pertinence of F-EMS driving cycles. The research results show that the proposed NNF-EMS can realize the adaptive optimization of fuzzy membership function and fuzzy rules under different driving cycles. Therefore, the proposed NNF-EMS has strong robustness and practicability under different driving cycles. © 2020 by the authors.
收录类别:SCOPUS
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081253922&doi=10.3390%2fapp10020696&partnerID=40&md5=6adfab819f5f9f496b75eb27b423b76a
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