A genetically optimized fuzzy control algorithm is used to realize the parallel hybrid system’s real-time energy distribution between the engine and the electric motor. This paper first adopts fuzzy control to improve the robustness and real-time performance of the entire system. Then, a membership function optimization method based on a genetic algorithm is proposed by simulating the working state of CYCUDDS. Simulation experiments show that compared with unoptimized fuzzy control, the improved fuzzy controller can improve the vehicle’s fuel economy and prevent continuous battery discharge, thereby improving battery endurance.
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Hybrid Electric Vehicle Energy Management Strategy based on Genetic Algorithm
Semantic Scholar · Engineering · 2024
Abstract
A genetically optimized fuzzy control algorithm is used to realize the parallel hybrid system’s real-time energy distribution between the engine and the electric motor. This paper first adopts fuzzy control to improve the robustness and real-time performance of the entire system. Then, a membership function optimization method based on a genetic algorithm is proposed by simulating the working state of CYCUDDS. Simulation experiments show that compared with unoptimized fuzzy control, the improved fuzzy controller can improve the vehicle’s fuel economy and prevent continuous battery discharge, thereby improving battery endurance.