Modeling and performance analysis of an electric two-wheeler on various driving cycles and validation using a performance real-time target machine

Abstract

Compared with conventional two-wheelers, electric two-wheelers are gaining popularity owing to their potential to reduce emissions, their dependency on fossil fuels, and their enhanced economic benefits. However, the electric two-wheelers face key challenges such as inconsistent performance and driving range due to varying driving conditions. This study overcomes this challenge by developing a comprehensive system to investigate and predict the behavior of electric two-wheelers under various vehicle and battery parameters, driving conditions, and ambient conditions. The developed system, implemented in MATLAB Simulink, includes five subsections (the driving cycle, motor controller unit, electric motor, battery pack, and vehicle model) and evaluates the state of health, cell temperature, energy consumption, driving range, and state of charge. To validate the model, a simulation was conducted using a Speedgoat performance real-time target machine. An extensive evaluation is executed to validate the accuracy of the developed system against the real-time performance of an electric two-wheeler. For both simulated and standard driving cycles, the model offers an error of less than 1 %. The results of the analysis show that maintaining a mean speed between 18 km/h and 35 km/h results in the least energy consumption, a higher driving range, and a lower cell temperature. In addition, the research results show that driving aggressively consumes more energy. The results of this research indicate an innovative contribution toward the recognition and selection of appropriate electric two-wheelers.