Unravelling Battery Consumption Patterns and Motor Performance in the NxGV Challenge Using MATLAB Analysis

Abstract

This research analyzes battery consumption patterns and motor performance in electric vehicles (EVs) competing in the Next Generation Vehicle (NxGV) Challenge using MATLAB analysis. Key parameters include vehicle weight, speed, battery capacity, and motor power. The study evaluates how these factors impact energy efficiency, driving range, and overall vehicle performance. A major focus is the relationship between battery capacity and motor performance, aiming to identify optimal configurations that maximize efficiency while maintaining competitive power output. MATLAB analysis assesses how variations in vehicle weight and speed influence energy consumption and motor efficiency under different race conditions. Additionally, this study compares the effectiveness of single-controller and dual-controller systems in managing motor performance and power distribution, highlighting the advantages of improved efficiency and reduced energy losses in dual-controller setups. The findings from this research will be directly applied in the upcoming NxGV Challenge, providing data-driven insights for optimizing battery usage and motor capability. Beyond the competition, the results contribute to the broader field of electric vehicle development, offering recommendations on vehicle design, battery management strategies, and motor selection. These insights have global relevance in advancing sustainable transportation by improving energy efficiency, extending battery life, and enhancing overall EV performance for both racing and commercial applications.