Battery degradation is a persistent concern for electric vehicle (EV) owners, often affecting range and leading to costly replacements.
However, a groundbreaking study from the SLAC-Stanford Battery Centre reveals that EV batteries might last up to 40% longer than previously estimated. The research highlights that traditional methods of testing battery life cycles fail to account for real-world driving conditions, significantly underestimating their longevity.
“We’ve not been testing EV batteries the right way,” noted one of the study’s authors, emphasising the discrepancy between lab simulations and the varied experiences of EVs on the road.
Unlike the predictable discharge and recharge cycles tested in laboratories, EV batteries endure diverse conditions.
These include short urban commutes, long highway journeys, stop-start traffic, and extended periods of inactivity. Charging habits also vary widely among users, from nightly top-ups to infrequent charging sessions.
To better simulate these conditions, researchers developed four discharge profiles based on driving data.
Over a two-year period, they tested 92 commercial lithium-ion batteries, discovering that the more realistic the profile, the greater the battery’s life expectancy.
Surprisingly, sharp accelerations and regenerative braking were found to reduce degradation, contradicting conventional assumptions. Allowing batteries to rest also proved beneficial.
The study highlights key differences in battery aging for private and commercial EVs. For high-usage vehicles like taxis and delivery vans, charge cycles are critical, whereas, for private users, the passage of time is a more significant factor.
Researchers suggest automakers could update battery management software to optimise performance and longevity based on these findings. Such adjustments may help mitigate concerns around degradation, improving consumer confidence in EV technology.
This research emphasises the need for a paradigm shift in how EV batteries are tested, aligning lab methods with real-world conditions to better predict and extend their lifespan.