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Modeling and Control of Parallel Hybrid Electric Vehicle Using Sea-Lion Optimization

J. Leon Bosco Raj1,*, M. Marsaline Beno2

1 Department of EEE, St. Xavier’s Catholic College of Engineering, Chunkankadai, Anna University, Chennai, India
2 St. Xavier’s Catholic College of Engineering, Chunkankadai, Anna University, Chennai, India

* Corresponding Author: J. Leon Bosco Raj. Email: email

Intelligent Automation & Soft Computing 2023, 35(2), 1441-1454. https://doi.org/10.32604/iasc.2023.026211

Abstract

This paper develops a parallel hybrid electric vehicle (PHEV) proportional integral controller with driving cycle. To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles (HEVs) combine an electric motor (EM), a battery and an internal combustion engine (ICE). The electric motor assists the engine when accelerating, driving longer highways or climbing hills. This enables the use of a smaller, more efficient engine. It also makes use of the concept of regenerative braking to maximize energy efficiency. In a Hybrid Electric Vehicle (HEV), energy dissipated while braking is utilized to charge the battery. The proportional integral controller was used in this paper to analyze engine, motor performance and the New European Driving Cycle (NEDC) was used in the vehicle driving test using Matlab/Simulink. The proportional integral controllers were designed to track the desired vehicle speed and manage the vehicle’s energy flow. The Sea Lion Optimization (SLnO) methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.

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Cite This Article

J. Leon Bosco Raj and M. Marsaline Beno, "Modeling and control of parallel hybrid electric vehicle using sea-lion optimization," Intelligent Automation & Soft Computing, vol. 35, no.2, pp. 1441–1454, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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