An engineering team from University of California, Riverside envisions that energy-efficient cars of the future will not be defined by a trait, but from an ability to learn more sustainable habits.
The proposed hybrid energy management system is designed to advance the existing energy management systems that are key components of plug-in hybrid electric vehicles. This system is what manages the usage of fuel and electricity and proposes that each power source could be used in only the most efficient way. This system is set to make use of machine learning software to assess road and traffic conditions. When the new hybrid energy management system was tested on a 32-kilometer commute in Southern California, the intuitive system was able to provide a savings of 12%.
Beyond simply noting the historical behaviors of individual drivers, the engineers envision that the next step would be to build an entire cloud-based network where cars could learn from one another.
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