Multi-objective optimisation of parallel hybrid electric vehicles based on fuzzy logic control

Wei Chen; Yunqing Zhang; Yuan Liang; Liping Chen; Jingzhou Yang

doi:10.1504/ijvas.2008.023579

Multi-objective optimisation of parallel hybrid electric vehicles based on fuzzy logic control

Wei Chen, Yunqing Zhang, Yuan Liang, Liping Chen, Jingzhou Yang

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The design of HEV control strategy is difficult owing to the large amount of inter-related design parameters and conflicting design objectives. This paper implements a Fuzzy Logic Controller to manage the energy distribution for a Parallel Hybrid Electric Vehicle (PHEV). In order to improve the performance of a PHEV, a multi-objective optimisation evolutionary algorithm is then applied to optimise the fuzzy membership function automatically according to known fuzzy control rules. In addition, Design of Experiment (DOE) technology is implemented to enhance the optimisation process. Simulation results reveal that the proposed multi-objective optimisation method can effectively improve FLC. Also offers sufficiently diverse solutions for the designer.

Original language	English
Pages (from-to)	236-250
Number of pages	15
Journal	International Journal of Vehicle Autonomous Systems
Volume	6
Issue number	3-4
DOIs	https://doi.org/10.1504/ijvas.2008.023579
State	Published - 2008

Keywords

FLC
Fuzzy logic control
Membership function
Multi-objective optimisation
PHEV
Simulation

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10.1504/ijvas.2008.023579

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title = "Multi-objective optimisation of parallel hybrid electric vehicles based on fuzzy logic control",

abstract = "The design of HEV control strategy is difficult owing to the large amount of inter-related design parameters and conflicting design objectives. This paper implements a Fuzzy Logic Controller to manage the energy distribution for a Parallel Hybrid Electric Vehicle (PHEV). In order to improve the performance of a PHEV, a multi-objective optimisation evolutionary algorithm is then applied to optimise the fuzzy membership function automatically according to known fuzzy control rules. In addition, Design of Experiment (DOE) technology is implemented to enhance the optimisation process. Simulation results reveal that the proposed multi-objective optimisation method can effectively improve FLC. Also offers sufficiently diverse solutions for the designer.",

keywords = "FLC, Fuzzy logic control, Membership function, Multi-objective optimisation, PHEV, Simulation",

author = "Wei Chen and Yunqing Zhang and Yuan Liang and Liping Chen and Jingzhou Yang",

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T1 - Multi-objective optimisation of parallel hybrid electric vehicles based on fuzzy logic control

AU - Chen, Wei

AU - Zhang, Yunqing

AU - Liang, Yuan

AU - Chen, Liping

AU - Yang, Jingzhou

PY - 2008

Y1 - 2008

N2 - The design of HEV control strategy is difficult owing to the large amount of inter-related design parameters and conflicting design objectives. This paper implements a Fuzzy Logic Controller to manage the energy distribution for a Parallel Hybrid Electric Vehicle (PHEV). In order to improve the performance of a PHEV, a multi-objective optimisation evolutionary algorithm is then applied to optimise the fuzzy membership function automatically according to known fuzzy control rules. In addition, Design of Experiment (DOE) technology is implemented to enhance the optimisation process. Simulation results reveal that the proposed multi-objective optimisation method can effectively improve FLC. Also offers sufficiently diverse solutions for the designer.

AB - The design of HEV control strategy is difficult owing to the large amount of inter-related design parameters and conflicting design objectives. This paper implements a Fuzzy Logic Controller to manage the energy distribution for a Parallel Hybrid Electric Vehicle (PHEV). In order to improve the performance of a PHEV, a multi-objective optimisation evolutionary algorithm is then applied to optimise the fuzzy membership function automatically according to known fuzzy control rules. In addition, Design of Experiment (DOE) technology is implemented to enhance the optimisation process. Simulation results reveal that the proposed multi-objective optimisation method can effectively improve FLC. Also offers sufficiently diverse solutions for the designer.

KW - FLC

KW - Fuzzy logic control

KW - Membership function

KW - Multi-objective optimisation

KW - PHEV

KW - Simulation

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DO - 10.1504/ijvas.2008.023579

M3 - Article

AN - SCOPUS:61849177461

SN - 1471-0226

VL - 6

SP - 236

EP - 250

JO - International Journal of Vehicle Autonomous Systems

JF - International Journal of Vehicle Autonomous Systems

IS - 3-4

ER -

Multi-objective optimisation of parallel hybrid electric vehicles based on fuzzy logic control

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