Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

Mei Lan Zhou; Deng Ke Lu; Wei Min Li; Hui Feng Xu

doi:10.4028/www.scientific.net/AMM.274.345

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 274Optimized Fuzzy Logic Control Strategy for...

Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

Abstract:

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

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Periodical:

Applied Mechanics and Materials (Volume 274)

Pages:

345-349

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.274.345

Citation:

Cite this paper

Online since:

January 2013

Authors:

Mei Lan Zhou, Deng Ke Lu, Wei Min Li, Hui Feng Xu

Keywords:

Energy Management Strategy (EMS), Fuzzy Logic Controller (FLC), Genetic Algorithm (GA), Parallel Hybrid Electric Vehicle (PHEV), State of Charge (SOC)

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