Modeling and Evaluation of the Regenerative Performance of an All-Wheel-Drive Electric Vehicle under Vietnamese Driving Conditions

Abstract

The study presents a comprehensive analysis of the regenerative braking efficiency of an All-wheels-drive electric vehicle under different traffic conditions using specific simulation software. The proposed model evaluates energy recovery performance across non-rush hours, rush hours, and highway driving cycles in Vietnam, highlighting the influence of traffic density on regenerative braking effectiveness. The results indicate that the highest energy recovery occurs in non-rush hours, where frequent braking events enhance regenerative braking activation. A comparative assessment between low and high-regeneration braking modes shows that the efficiency gap varies significantly depending on traffic flow, with the high-regeneration braking mode consistently demonstrating superior performance. In highway conditions, energy recovery is notably lower due to stable cruising speeds and fewer braking instances. The findings of this research contribute to the advancement of energy-efficient electric vehicle technologies by providing a detailed evaluation of regenerative braking potential under Vietnam driving conditions. This study serves as a reference for optimizing vehicle control strategies and promoting sustainable transportation solutions. By understanding the impact of traffic patterns on regenerative braking efficiency, this research aids in enhancing energy recovery strategies, reducing overall energy consumption, and improving vehicle performance in real-world urban environments.