Electric Motorcycle Modelling with Parallel Regenerative Braking

Range anxiety is a big problem faced by electric vehicle owners. This anxiety stems from the lack of confidence of the owners in their electric vehicle ability to travel the required distance. For this paper, the study of electric motorcycles was chosen to tackle this challenge, by modelling an electric motorcycle with parallel regenerative braking system. This research was conducted to see the potential of regenerative braking to deal with the issue of range anxiety. This research was also done to build an electric motorcycle model that could act as a framework for all sorts of electric motorcycle. The implementation of regenerative braking system is applied to the rear wheels with the system taking 20% of the total brake load. This technology is expected to help improve the electric motorcycle’s efficiency while providing a reliable feedback and response. The performance of the braking strategy was studied using a model-based simulation software. Simulation was done by imposing velocity profiles to the model. Velocity profiles were obtained from World Motorcycle Test Cycle (WMTC) part 1 version 8 as well as on-road measurement. WMTC cycle is purely longitudinal movement while on-road cycle takes longitudinal and lateral movements into account. As for the motorcycle model, the data were gathered from existing electric motorcycle, electric motor, controller, and battery. The result shows that the use of regenerative braking could lower energy consumption by up to 5.66%. The result root mean square error (RMSE) of the model shows that the proposed electric model is valid enough.