On the Use of Genetic Algorithm to Optimize the On-board Energy Management of a Hybrid Solar Vehicle

This paper deals with the development of a prototype of Hybrid Solar Vehicle (HSV) with series structure. This activity has been also conducted in the framework of the European Union funded Leonardo project “Energy Conversion Systems and Their Environmental Impact”, a project with research and educational objectives. A study on supervisory control for hybrid solar vehicles and some preliminary tests performed on the road are presented. Previous results obtained by a model for HSV optimal design have confirmed the relevant benefits of such vehicles with respect to conventional cars in case of intermittent use in urban driving (city-car), and that economical feasibility could be achieved in a near future. Due to the series-powertrain adopted for the HSV prototype, an intermittent use of the ICE (Internal Combustion Engine) powering the electric generator is possible, thus avoiding part-load low-efficient engine operations. The best ICE power trajectory is determined via genetic algorithm optimization accounting for fuel mileage as well as battery state of charge, also considering solar contribution during parking mode. The experimental set up used for data logging, real-time monitoring and control of the prototype is also presented, and the results obtained with different road tests discussed