Model Predictive Control for Cruise Control of An Electric Motorcycle under External Disturbances

This paper presents the development and real-time validation of a Model Predictive Control (MPC) strategy for cruise control in an electric motorcycle. The MPC controller is designed to track the reference speed while minimizing both speed error and control effort. The model inside the MPC is constructed based on the speed and acceleration dynamics of the motorcycle through state-space modeling. The designed MPC is then evaluated in a real-time environment using dSPACE Scalexio. To assess its disturbance handling capability, a high-frequency sine wave with an amplitude of 5 km/h is introduced into the vehicle’s longitudinal speed. Two test cases are conducted at cruise reference speeds of 30 km/h and 60 km/h, with the performance of the MPC controller compared against the Proportional-Integral (PI) controller, both with and without disturbance. The results demonstrate that the MPC has a better performance in terms of overshoot reduction and speed regulation, highlighting its potential as a reliable and efficient control solution for electric motorcycles.