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Fuzzy energy management strategy for parallel HEV based on pigeon-inspired optimization algorithm

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Abstract

Improvements in fuel consumption and emissions of hybrid electric vehicle (HEV) heavily depend upon an efficient energy management strategy (EMS). This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle employing a quantum chaotic pigeon-inspired optimization (QCPIO) algorithm. In this approach, the torque of the engine and the motor is assigned by a fuzzy torque distribution controller which is based on the battery state of charge (SoC) and the required torque of the hybrid powertrain. The rules and membership functions of the fuzzy torque distribution controller are optimized simultaneously through the use of QCPIO algorithm. The simulation ground on ADVISOR demonstrates that this EMS improves fuel economy more effectually than original fuzzy and PSO_Fuzzy EMS.

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Authors and Affiliations

  1. School of Automation, Wuhan University of Technology, Wuhan, 430070, China

    JiaZheng Pei, YiXin Su & DanHong Zhang

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  1. JiaZheng Pei
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  2. YiXin Su
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  3. DanHong Zhang
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Correspondence to DanHong Zhang.

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Pei, J., Su, Y. & Zhang, D. Fuzzy energy management strategy for parallel HEV based on pigeon-inspired optimization algorithm. Sci. China Technol. Sci. 60, 425–433 (2017). https://doi.org/10.1007/s11431-016-0485-8

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  • DOI: https://doi.org/10.1007/s11431-016-0485-8

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