Optimal Power Management of an Electric Vehicle with Dual-Energy Sources via Optimized Fuzzy Controller using Genetic Algorithm

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Abstract

In this paper a novel power management method for an electric vehicle (EV) equipped with two energy storage systems is presented. In this way, an optimized nonlinear controller based on fuzzy system is developed. The main stage to design a fuzzy controller is proper determination of fuzzy rules and membership functions that in this paper, the fuzzy rules and input and output membership functions of fuzzy controller are determined via mixed integer genetic algorithm (GA). The model of EV and optimized fuzzy controller as well as conventional fuzzy controller and optimized on/off controller are simulated in ADVISOR environment for the standard driving cycle EPA urban UDDS. Simulation results confirm a significant reduction in the consumed energy by the proposed optimal fuzzy controller in comparison with the conventional fuzzy and optimized on/off controllers.

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