University of California in Riverside has received a one-year $95,000 grant from the California Energy Commission to develop algorithms that find the route requiring the least amount of energy for an electric car’s trip. The research will be done by the Center for Environmental Research and Technology, part of the university’s Bourns College of Engineering.
Researcher Guoyuan Wu will be the principal investigator, with co-investigators Matthew Barth, director of the center, and Kanok Boriboonsomsin, a research faculty member. Barth and Boriboonsomsin have done earlier research on the value of eco-routing for fossil-fuel vehicles.
Electric vehicles have an estimated range of 100 miles or greater, but testing has shown that range can vary widely with driving conditions, traffic congestion, road grade, and even air temperature. For example, the range of the all-electric Nissan LEAF may vary between 47 and 138 miles. Current GPS devices can find the shortest or fastest route, but they rarely take into account other factors that can minimize energy use or greenhouse gas emissions.
The research work is expected to collect energy consumption data from an electric vehicle driven under a variety of real-world driving conditions: varying vehicle speeds, traffic congestion levels, road types, road grades, and number of passengers. The team will organize the data into database tables to develop real-time energy consumption estimate models for the test electric vehicle.
Those models will then be integrated into a routing algorithm. The team expects to build the algorithm into an eco-routing navigation system resembling a small computer screen, and mounted on the dashboard, which will then undergo live testing in an electric vehicle.
Wu and colleagues expect systems like the one proposed under the grant can add an additional 10 percent to the range of electric vehicles. “It should really help cut down on what has become known as range anxiety,” says Wu.
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