Dynamic Modeling and Driving Cycle Prediction for a Racing Series Hybrid Car

This paper presents Noao, a plug-in series hybrid racing car equipped with an engine/generator set as range extender. To determine the velocity profile, i.e., performance of the car and its power profile, a dynamic model for this car is developed using pedal position as input. This value is easy to measure, representative for race cycles, and presents a novelty. The model is validated with the results from experiments. An analysis based on the map of Magny-Cours racing circuit and drivers pedal action on certain zones of the circuit is formulated and is used as a prediction tool to determine drivers inputs on other racing circuits and generate driving schedules. The results obtained from this analysis are essential to predict energy consumption of the system, estimate driving range, and inspect battery state-of-charge evolution of the car during races. Moreover, the generated driving cycle provides an optimum compromise between drivetime and energy consumption of the system.