Electric vehicle braking energy recovery control method integrating fuzzy control and improved firefly algorithm

• Published in: PloS one Vol. 20; no. 3; p. e0320537
• Main Authors: Xiong, Jinfeng, Song, Jingbin, Zhang, Zhiqiang
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 28.03.2025; Public Library of Science (PLoS)
• Subjects: Algorithms; Automobiles; Automobiles, Electric; Brakes; Braking; Braking systems; Control algorithms; Control methods; Control theory; Electric Power Supplies; Electric vehicles; Electricity; Energy consumption; Energy efficiency; Energy management; Energy recovery; Environmental impact; Equipment and supplies; Friction; Fuzzy control; Fuzzy Logic; Genetic algorithms; Heuristic methods; Methods; Models, Theoretical; Motor vehicles; Operating costs; Technological change; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0320537

Braking energy recovery is crucial for improving the energy efficiency and extending the range of electric vehicles. If a large amount of braking energy is wasted, it will lead to problems such as reduced range and increased battery burden for electric vehicles. Therefore, an electric vehicle braking energy recovery control model that integrates fuzzy control algorithm with genetic firefly algorithm is proposed. Experimental analysis showed that the decrease in the state of charge of the model was 12.44%, and the braking energy recovery rate reached 52.1% in practical applications. Based on the above data, the proposed method can effectively control the amount of energy recovery. In addition, when the system chip value was 10%, the total amount of recovered energy at the battery end was the highest. Conversely, the total amount of recovered energy at the battery end was relatively small. In summary, the designed electric vehicle braking energy recovery control model can effectively control the amount of braking energy recovery of electric vehicles, ensuring the maximum recovery while also considering the durability and driving stability of the vehicle battery. The method can effectively extend mileage range in the electric vehicle industry, promoting the development and technological innovation of the new energy industry.