Analysis of a Rule-Based Control Strategy for On-Board Energy Management of Hybrid Solar Vehicles

In the paper, the performances of a rule-based (RB) control strategy for a series Hybrid Solar Vehicle (HSV) are assessed via comparison with a batch genetic algorithm-based (GA) optimization. The RB strategy relies on heuristic rules defined by optimizing ICE start&stop strategy as function of average traction power and current solar irradiation. The comparison with the reference GA benchmark confirms the suitability of the proposed RB strategy for HSV on-board energy management. Extensive simulations were performed to test the influence of driving cycle features, power-prediction time-horizon and solar irradiation on HSV fuel economy. Such simulation analysis, beyond providing useful indications about correct implementation of the RB strategy, also demonstrates the potentialities offered by HSV powertrains in both urban and highway driving conditions.