@inproceedings{b7b45e0ae49d4645b7c1f1ec36ad857f,
title = "An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI",
abstract = "This paper proposes a new energy management based on equivalent consumption minimization strategy (ECMS) for hybrid electric vehicles. The aim is to impose SoC charge-sustainability and enhance the fuel economy. First, the equivalent factor (EF) of ECMS is derived from Pontryagin's Minimum Principle. Second, a new adaptation law using Fuzzy Proportional plus Integral (PI) controller is developed to adjust EF in real-time. Finally, simulations for two driving cycles using ECMS are compared with rule-based (RB) control strategy, indicating that the proposed adaptation law can provide a promising blend in terms of fuel economy and charge-sustainability. The results show that ECMS with Fuzzy PI adaptation of EF achieves significant improvement compared with RB in terms of fuel economy and is more robust than ECMS with constant EF.",
keywords = "Equivalent Consumption Minimization Strategy, Hybrid Electric Vehicle, equivalent factor, fuzzy PI",
author = "Fengqi Zhang and Junqiang Xi and Reza Langari",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Intelligent Vehicles Symposium, IV 2016 ; Conference date: 19-06-2016 Through 22-06-2016",
year = "2016",
month = aug,
day = "5",
doi = "10.1109/IVS.2016.7535426",
language = "English",
series = "IEEE Intelligent Vehicles Symposium, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "460--465",
booktitle = "2016 IEEE Intelligent Vehicles Symposium, IV 2016",
address = "United States",
}