The global automotive landscape is evolving rapidly, driven by increasingly stringent regulations aimed at reducing emissions and mitigating the impact of climate change. As a result, Battery Electric Vehicles (BEVs) are gaining prominence considered a cleaner and more efficient mode of transportation. However, several challenges, including limited range, energy consumption, and battery degradation, continue to hinder the widespread adoption of BEVs. This thesis addresses these challenges by focusing on the development of an optimization strategy based on Model Predictive Control (MPC) for BEVs. The primary objective is to enhance energy efficiency and extend battery life. It accomplishes this by optimizing the vehicle speed profile to minimize energy consumption and reduce battery degradation.