An Adaptive Equivalent Consumption Minimization Strategy for Parallel Hybrid Electric Vehicle Based on Fuzzy PI Conference Paper

abstract

• 2016 IEEE. 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.

name of conference

• 2016 IEEE Intelligent Vehicles Symposium (IV)

authors

• Langari, Gholamreza

published proceedings

• 2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)

author list (cited authors)

• Zhang, F., Xi, J., & Langari, R.

citation count

• 21

complete list of authors

• Zhang, Fengqi||Xi, JunQiang||Langari, Reza

publication date

• January 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• 2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)  Journal

keywords

• Equivalent Consumption Minimization Strategy
• Equivalent Factor
• Fuzzy Pi
• Hybrid Electric Vehicle

Digital Object Identifier (DOI)

• 10.1109/ivs.2016.7535426

International Standard Book Number (ISBN) 13

• 9781509018215

start page

• 460

end page

• 465

volume

• 2016-August

URL

• http://dx.doi.org/10.1109/ivs.2016.7535426

user-defined tag

• 7 Affordable and Clean Energy