Genetic Algorithms based optimization of intermittent ice scheduling on a Hybrid Solar Vehicle

Hybrid Solar Vehicles (HSV), derived by integration of Hybrid Electric Vehicles with Photo-Voltaic sources, may represent a valuable solution to face both energy saving and environmental issues, particularly in urban driving. This paper focuses on their management strategies, evidencing some significant differences with respect to the case of Hybrid Electric Vehicles. In order to develop a supervisory control for an HSV prototype under development at University of Salerno, a study on the performance achievable by an intermittent use of the ICE powering the electric generator is presented. The results obtained by the application of Genetic Algorithms (GA) to the optimal energy management of an HSV with series structure are discussed. The optimal powering strategy accounts for fuel mileage and state of charge, also considering solar contribution during parking mode and the effects of engine thermal transients on fuel consumption and HC emissions.