Modeling and simulating an electric bicycle in MATLAB/Simulink

The use of electric bikes is growing rapidly, enabling individuals to extend their potential rangewhile also reducing their dependency on traditional modes of transport. To expedite the development of new electric bicycles in terms of performance, range, and control algorithms, it isbeneficial to have the capability to simulate the core components. Nuxon Mobility is a startup that expressed interest in such an model to explore the feasibility andexpedite their development timeline for their new electric bike. Their new electric bike offers adiverse range of features and an innovative new propulsion system that utilizes multiple motors.This thesis focuses on creating a simulation environment that is both modular and representsreal-life conditions as closely as possible, with the key components of a drive train that includesthe following, multiple BLDC motors, motor controllers, a lithium-ion battery pack, peripherals asan constant load, environmental forces and being able to utilize driving cycles like WLTP profiles.The scope of this project includes a review of relevant literature, with a primary focus on thecreation and verification of the simulation model. The model incorporated a simplified human torque input that relied on the requested speed,along with a limiting variable that determined the maximum force the rider could exert. A separate current controller for each motors enabled optimal power distribution between the front andrear motors, taking into account various terrains, inclines, and riding modes. The results demonstrated the model’s potential to execute a WLTP drive cycle, showcasing the energy consumptionassociated with it. Furthermore, it illustrated how a dual wheel drive electric bike could effectivelymanage power distribution between the wheels, adapting to different terrains and riding modes. The model successfully replicated all of the core dynamics of an electric bicycle, however somesimplifications were made to reduce the computational complexity, such as the motor controllersand modeled human torque input. These limitations serve as opportunities for future work thatcould include field oriented control, battery aging, more defined riding modes, custom drive cyclesand integrating Mathworks parallel computing addon, which was not available at the time of thisreport due to a ransomware attack aimed at Mathworks. The overall result showed that themodel offered great potential and has the possibility to be used for developing electric bicyclesby enabling performance evaluation, control and riding mode algorithm testing without the needfor physical hardware.