Equivalent lap time minimization strategies for a hybrid electric race car

The powertrain of the Formula 1 car is composed of an electrically turbocharged internal combustion engine and an electric motor used for boosting and regenerative braking. The energy management system that controls this hybrid electric power unit strongly influences the achievable lap time, as well as the fuel and battery consumption. Therefore, it is important to design robust feedback control algorithms that can run on the ECU in compliance with the sporting regulations, and are able to follow lap time optimal strategies while properly reacting to external disturbances. In this paper, we design feedback control algorithms inspired by equivalent consumption minimization strategies (ECMS) that adapt the optimal control policy implemented on the car in real-time. This way, we are able to track energy management strategies computed offline in a lap time optimal way using three PID controllers. We validate the presented control structure with numerical simulations and compare it to a previously designed model predictive control scheme.