Study of HEV power management control strategy based on driving pattern recognition

Zhen Wei; Z. Xu; Dunant Halim

doi:10.1016/j.egypro.2016.06.062

Study of HEV power management control strategy based on driving pattern recognition

Zhen Wei, Z. Xu, Dunant Halim

Research output: Journal Publication › Conference article › peer-review

23 Citations (Scopus)

52 Downloads (Pure)

Abstract

In this work, an optimized HEV power management fuzzy control strategy is proposed with the aim to further improve the fuel efficiency of the rule-based control strategy and overcome the drawbacks of the conventional control strategies. The driving pattern recognition method is used to classify the driving condition into one of the driving patterns to select proper control algorithm. The dynamic programming solution is used to design the fuzzy control strategies for each driving pattern. The simulation results indicate that by adopting the proposed strategy the fuel efficiency of HEV is improved, especially under complex driving conditions.

Original language	English
Pages (from-to)	847-853
Number of pages	7
Journal	Energy Procedia
Volume	88
DOIs	https://doi.org/10.1016/j.egypro.2016.06.062
Publication status	Published - 1 Jun 2016
Event	Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 - Fuzhou, China Duration: 15 Nov 2015 → 17 Nov 2015

Keywords

Driving cycle
Energy management
Fuzzy logic control
HEV

ASJC Scopus subject areas

General Energy

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10.1016/j.egypro.2016.06.062

1-s2.0-S1876610216301266-mainFinal published version, 678 KBLicence: CC BY-NC-ND

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title = "Study of HEV power management control strategy based on driving pattern recognition",

abstract = "In this work, an optimized HEV power management fuzzy control strategy is proposed with the aim to further improve the fuel efficiency of the rule-based control strategy and overcome the drawbacks of the conventional control strategies. The driving pattern recognition method is used to classify the driving condition into one of the driving patterns to select proper control algorithm. The dynamic programming solution is used to design the fuzzy control strategies for each driving pattern. The simulation results indicate that by adopting the proposed strategy the fuel efficiency of HEV is improved, especially under complex driving conditions.",

keywords = "Driving cycle, Energy management, Fuzzy logic control, HEV",

author = "Zhen Wei and Z. Xu and Dunant Halim",

note = "Publisher Copyright: {\textcopyright} 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.; Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 ; Conference date: 15-11-2015 Through 17-11-2015",

year = "2016",

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doi = "10.1016/j.egypro.2016.06.062",

language = "English",

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pages = "847--853",

journal = "Energy Procedia",

issn = "1876-6102",

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TY - JOUR

T1 - Study of HEV power management control strategy based on driving pattern recognition

AU - Wei, Zhen

AU - Xu, Z.

AU - Halim, Dunant

PY - 2016/6/1

Y1 - 2016/6/1

N2 - In this work, an optimized HEV power management fuzzy control strategy is proposed with the aim to further improve the fuel efficiency of the rule-based control strategy and overcome the drawbacks of the conventional control strategies. The driving pattern recognition method is used to classify the driving condition into one of the driving patterns to select proper control algorithm. The dynamic programming solution is used to design the fuzzy control strategies for each driving pattern. The simulation results indicate that by adopting the proposed strategy the fuel efficiency of HEV is improved, especially under complex driving conditions.

AB - In this work, an optimized HEV power management fuzzy control strategy is proposed with the aim to further improve the fuel efficiency of the rule-based control strategy and overcome the drawbacks of the conventional control strategies. The driving pattern recognition method is used to classify the driving condition into one of the driving patterns to select proper control algorithm. The dynamic programming solution is used to design the fuzzy control strategies for each driving pattern. The simulation results indicate that by adopting the proposed strategy the fuel efficiency of HEV is improved, especially under complex driving conditions.

KW - Driving cycle

KW - Energy management

KW - Fuzzy logic control

KW - HEV

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U2 - 10.1016/j.egypro.2016.06.062

DO - 10.1016/j.egypro.2016.06.062

M3 - Conference article

AN - SCOPUS:85007518493

SN - 1876-6102

VL - 88

SP - 847

EP - 853

JO - Energy Procedia

JF - Energy Procedia

T2 - Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015

Y2 - 15 November 2015 through 17 November 2015

ER -

Study of HEV power management control strategy based on driving pattern recognition

Abstract

Keywords

ASJC Scopus subject areas

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