The National Petroleum Council (a panel advising the US Energy Department) has just published a future fuels report stating that the internal combustion will remain the dominant power source for cars until at least 2050. The study says it will take a future “disruptive innovation” to replace the internal-combustion engine.
Last month, perhaps we saw a glimpse into the future as the University of Michigan Solar Car Team (UMSCT) won their 7th National Championship – this time by the largest margin of victory in the history of the American Solar Challenge. The American Solar Challenge is a competition to design, build, and drive solar-powered cars cross-country. This year, it began on Friday the 13th with a display day at Rochester Institute of Technology before setting off for an over 1,600 mile trek that ended in St. Paul, Minn. on July 21st.
Prior to the team’s American Solar Challenge win, UMSCT won the Formula Sun Grand Prix, a track event that is held on grand prix-style closed courses. The strategy applied during this three-day event is different than the one applied to the cross-country event and tests the limits of solar cars in handling curves, braking and acceleration.
At the Altair HTC in Detroit earlier in this year, the UMSCT presented “Minimizing Body and Chassis Weight on a Solar Powered Race Car Using Altair’s OptiStruct Solver.” During the presentation, the team described how, through the use of Altair’s optimization software, they were able to reduce the weight of their 2009 solar car Infinium by 90kg, resulting in Quantum, the 2011 car. It also was mentioned that the best cars on the starting line for the 2011 World Solar Challenge would be weighing in and ready to race at less than 227kg.
The World Solar Challenge , a 3,000 km race from Darwin to Adelaide through the Australian outback, attracts student and professional teams from across the world. These teams compete in vehicles that run solely on energy acquired directly from the sun, and all of the top teams competing have the very lightest cars through optimization.
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