As the world strives in the pursue of carbon neutrality, Hybrid Electric Vehicles (HEVs) raised as one of the most promising solutions to reduce greenhouse gas emissions. In this context, an effective and reliable Energy Management System (EMS) becomes essential to fully exploit the hybrid potential since the presence of two energy sources (i.e. the fuel tank and the chemical battery) introduces an additional degree of freedom which has to be properly handled. To address this control problem, in the wide portfolio of techniques available, Artificial Intelligence (AI) represents nowadays the cutting-edge solution. Reinforcement Learning (RL) seems to be one of the most promising thanks to its peculiar structure, where an agent interacts directly with an environment, making decisions and receiving feedback in the form of rewards.