Automakers have made considerable gains in overcoming range anxiety, which still deters some buyers from purchasing an electric vehicle.The industry average range is presently about 300 miles, while some premium models—such as the Mercedes-Benz EQS Saloon, Polestar 2, and Porsche Taycan 4S—reach or exceed 400 miles.
In November 2023, S&P Global Mobility published a report stating that customers’ main concern seemed to be pricing rather than range. Just 29% of respondents indicated they would be happy if a car had a minimum range of 300 miles despite the fact that 62% of respondents stated they were “waiting until vehicle technology improves before purchasing a new car.”
But what if the range parameters provided by the manufacturers aren’t entirely accurate? “These are generally generated by combining city and highway driving under “ideal” conditions,” says Lasse Lumiaho, Vaisala’s Product Manager for Road Weather. This makes logical from a business standpoint, but depending on the area in which they live, EVs’ vulnerability to range changes can turn off customers.
EV batteries: the “Goldilocks” principle
According to Lumiaho, the primary cause of discrepancies between manufacturer specifications and real EV range is the energy efficiency of the electric powertrain, as Automotive World reports. An electric vehicle’s efficiency can reach up to 95%, whereas a gasoline engine can only manage about 25% and a diesel engine 40%. This suggests that outside influences do have an impact on performance, and that impact is usually rather visible. Realizing this problem, an unnamed OEM approached to Vaisala looking for a solution.
Only testing that accounts for and measures several elements, including as weather, traffic and road topography, driving style, and vehicle structure, can determine an EV’s range. Any one of these could alter the true range possibilities.
Getting Rid of Questions
In order to improve its customers’ ability to estimate on-road range, Vaisala intended to make a unique meteorological dataset available to them. As stated by Lumiaho, “it all starts with the global cooperation of governments collecting weather measurements,” indicating that a significant amount of work was required. “Aerial aircraft, land-based stations, satellites, and radars collect atmospheric data.” This is combined with local numerical weather predictions for every nation and commercial data fusion carried out by private companies to improve accuracy and reduce delay. Next, Vaisala incorporates a second road weather model that takes seasonal road conditioning, traffic, road curvature, and other factors into consideration using the atmospheric data as an input.
