CUED Publications database

Research on novel fuzzy control strategy of hybrid electric vehicles based on feature selection genetic algorithm

Zhu, T and Wang, L and Na, X and Wu, T and Hu, W and Jiang, R (2021) Research on novel fuzzy control strategy of hybrid electric vehicles based on feature selection genetic algorithm. Sensors and Materials, 33. pp. 301-313. ISSN 0914-4935

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Abstract

We propose a novel fuzzy control strategy for hybrid electric vehicles (HEVs) based on the feature selection genetic algorithm of multivariate data, which greatly shortens the selection time of the optimal parameters of the traditional genetic algorithm. Firstly, we take the fuel consumption and emission of an HEV as the optimization index, and develop a novel fuzzy control method considering parameters of the fuzzy controller with high correlation with the objective function, in which the membership function parameter is optimized by the feature selection genetic algorithm. Finally, the performances of the fuzzy control strategy for an HEV and the novel fuzzy control strategy optimized by the feature selection genetic algorithm under the New European Driving Cycle (NEDC) and Urban Dynamometer Driving Schedule (UDDS) cycle conditions are analyzed and compared. The results show that the proposed fuzzy control can greatly improve the fuel economy and reduce the emission of HEVs.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div C > Applied Mechanics
Depositing User: Cron Job
Date Deposited: 03 Mar 2021 20:04
Last Modified: 06 Apr 2021 01:46
DOI: doi:10.18494/SAM.2021.3013