Researchers Say Nav Tool Can Cut EV Energy Use 51%

Electric car drivers could lower their energy use in half by opting for the fastest route recommended by their in-car navigation system, according to researchers at the University of California, Riverside.

The team bases it conclusion on results of 100 real and 4,000 simulated trips around Riverside. They developed and used a nav tool that considers real-time traffic information, road type and road grade. Trips were between 19 and 23 miles long.

The researchers say their analytic tool could be used by EV drivers to more effectively assess their options, thereby reducing range anxiety.

The tool evaluated three types of routes suggested by the nav system: least time, least distance and least energy. Tests were conducted using a 2013 model Nissan Leaf electric sedan.

The researchers say taking the quickest route recommended by the nav system produced the most useful result: 25%-51% less energy in spite of as much as 19% longer travel distance.

Opting for the shortest route produced energy savings of 5%-25%, but the travel time in some cases doubled.

As expected, the lowest-energy route suggested by the nav system was the most efficient. But it ignored travel time and wasn't always practical. Results showed the option lengthened the route as much as 16% and in some cases also nearly tripled travel time.

The researchers say first-generation GPS-based nav systems usually attempt to minimize distance traveled. Newer systems focus on the least travel time. But that may involve traveling greater distances but at higher speeds conditions that can lower energy efficiency.

The team notes that a few EV models, such as electrified Ford Focus and Honda Fit small cars, offer an "eco-routing" option. But it says such systems don't appear to have the ability to consider such factors as road grade and type or real-time traffic data.

The analysis was conducted by three researchers at the university's Bourns College of Engineering Center for Environmental Research and Technology. The team consisted of Matthew Barth, the center's director; Kanok Boriboonsomsin, an associate research engineer; and Guoyuan Wu, an assistant research engineer.