The global interest in green vehicleshas been growing since it is letting out less pollution than normal internal combustion engines (ICE) and many people want to get into the ecological-friendly alternative mode of transport. The solar car is one of these types of green vehicles, which is powered by renewable energy with zero emissions. The solar car makes use of its solar panel that uses photovoltaic cells to convert sunlight into electricity to the batteries and to also power the electric motor. The state of solar cars is that it is almost exclusively for competition and when competing a strategy is needed to get the best placement. Having knowledge about how the car is behaving is a good basis for building a driving strategy. Therefore, a case study is made on World Solar Challenge (WSC) focused on the cars of JU Solar team with the use of datasets such as topographical data and solar irradiation. An optimization model is made that inputs these datasets and simulates a time period (an hour) and checks the set battery discharge rate (BDR or C rating). It is concluded that a safe BDR is between 8 to 9 % per hour (i.e. 0.08 to 0.09 C), relative to the full capacity of the battery. Results shows an improved mean speeds of the solar cars and improved finish times. The model also works very well for solar cars that are not meant for racing. Since it keeps a relatively stable state of charge for long term driving, that ensures battery longevity. With these results JU Solar team can use this model to improve their driving strategy but could also be used for economical driving for the future of commercial solar cars. This paper recommends to follow a simple procedure, to keep the BDR on 9% as long as the sun irradiation stays above 800 W/m2, and lower the BDR to 8% if irradiation goes below 800 W/m. Adjustments to increase the BDR for the end of the race is also recommended for optimal driving strategy.