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

Area of Science:

• Automotive Engineering
• Control Systems
• Energy Systems

Background:

• Inefficient braking energy dissipation in electric vehicles (EVs) leads to reduced driving range and increased battery strain.
• Optimizing braking energy recovery is essential for improving EV energy efficiency and performance.

Purpose of the Study:

• To develop an integrated control model for electric vehicle braking energy recovery.
• To enhance energy efficiency and extend the operational range of electric vehicles.

Main Methods:

• Integration of a fuzzy control algorithm with a genetic firefly algorithm for braking energy recovery control.
• Experimental analysis to evaluate the model's performance in practical applications.

Main Results:

• Achieved a braking energy recovery rate of 52.1% in practical applications.
• Demonstrated an effective control over the amount of energy recovered, with optimal recovery at a 10% system chip value.
• Observed a 12.44% decrease in the state of charge, indicating efficient energy management.

Conclusions:

• The designed model effectively controls braking energy recovery, maximizing energy capture while ensuring battery durability and driving stability.
• The proposed method significantly extends the mileage range of electric vehicles, contributing to advancements in the new energy sector.