An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI

Fengqi Zhang; Junqiang Xi; Reza Langari

doi:10.1109/IVS.2016.7535426

An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI

Fengqi Zhang, Junqiang Xi, Reza Langari

School of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 Citations (Scopus)

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.

Original language	English
Title of host publication	2016 IEEE Intelligent Vehicles Symposium, IV 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	460-465
Number of pages	6
ISBN (Electronic)	9781509018215
DOIs	https://doi.org/10.1109/IVS.2016.7535426
Publication status	Published - 5 Aug 2016
Event	2016 IEEE Intelligent Vehicles Symposium, IV 2016 - Gotenburg, Sweden Duration: 19 Jun 2016 → 22 Jun 2016

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings
Volume	2016-August

Conference

Conference	2016 IEEE Intelligent Vehicles Symposium, IV 2016
Country/Territory	Sweden
City	Gotenburg
Period	19/06/16 → 22/06/16

Keywords

Equivalent Consumption Minimization Strategy
Hybrid Electric Vehicle
equivalent factor
fuzzy PI

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10.1109/IVS.2016.7535426

Cite this

Zhang, F., Xi, J., & Langari, R. (2016). An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI. In 2016 IEEE Intelligent Vehicles Symposium, IV 2016 (pp. 460-465). Article 7535426 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2016-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IVS.2016.7535426

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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.",

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Zhang, F, Xi, J & Langari, R 2016, An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI. in 2016 IEEE Intelligent Vehicles Symposium, IV 2016., 7535426, IEEE Intelligent Vehicles Symposium, Proceedings, vol. 2016-August, Institute of Electrical and Electronics Engineers Inc., pp. 460-465, 2016 IEEE Intelligent Vehicles Symposium, IV 2016, Gotenburg, Sweden, 19/06/16. https://doi.org/10.1109/IVS.2016.7535426

An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI. / Zhang, Fengqi; Xi, Junqiang; Langari, Reza.
2016 IEEE Intelligent Vehicles Symposium, IV 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 460-465 7535426 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

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An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on Fuzzy PI

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