Global warming, limited fossil fuel resources, and the increasing price of oil have encouraged people to find a more efficient and cleaner solution for their mobility, the electrified transportation seems to satisfy this demand. Even a company like Ferrari, which has, among its distinctive features, the fact of having always designed the state-of-the-art for everything concerned with internal combustion engines, must dialogue with these new requests.
A Battery Electric Vehicles (BEVs) is the solution, proposed by Ferrari and most of the OEMs, because of their reputation for being fully green as well as more efficient than Internal Combustion Engine Vehicles (ICEVs).
The aim of this thesis is the modelling and control of an energy management system for a battery electric supercar, dealing with the problem of the range anxiety and taking in account the fact that, as any Ferrari supporter expects, the car is designed to guarantee a thrill. The core of the work was the understanding and the optimization of the energetic flow inside a BEV supercar, paying particular attention on the relationship between mechanical power, electrical power and efficiency. To do so, was first developed an environment which simulate the main components and the main power flow inside a BEV supercar, then various driving cycles and tests have been made, to better understand the relations between the electric motors, the battery and the vehicle. Once the data has been collected, was possible to design the best energy management system in order to have the highest mileage for a complete discharge of the battery.
First was designed an offline strategy with an high computational load, that was useful to derive rules and set a benchmark, then from the results obtained, was possible to understand the objects to minimize, so designing a suboptimal strategies, enough robust and with a lower computational load that can guarantee performances as close as possible to the optimal ones.