A new study by UC San Diego researchers could transform workplace EV charging by using real driver data, enabling cost-effective and efficient networks to meet growing demand.
A new study from the University of California San Diego has unveiled a cutting-edge computational tool designed to help institutions create more effective electric vehicle (EV) charging networks. Published in the journal Renewable Energy, the study addresses the challenges faced by organizations looking to support the burgeoning number of employees switching to electric vehicles.
“Early EV adopters have tended to be wealthier homeowners who charge their vehicles with private home chargers. But that is not representative of the broader population who may yet switch to an EV,” co-first author Ryan Hanna, an assistant research scientist at UC San Diego, said in a news release.
Indeed, the study underscores a critical insight: many potential EV drivers are renters or live in multi-dwelling units without dedicated parking spaces, limiting their ability to install home chargers. Consequently, workplace charging is poised to become the second most prevalent mode of charging, behind residential charging.
Hanna and co-first author Jeff Myers collaborated with a team of researchers and UC San Diego leadership to conduct several comprehensive studies on campus. Notably, UC San Diego boasts the largest EV charging network of any academic institution in the Western world.
The research team collected anonymized behavioral data from more than 800 EV drivers, along with data from 439 charging stations across the campus, spanning from 2023 to 2024.
“We have demonstrated that using data from real EV drivers — rather than relying on idealized or regionally-averaged assumptions — can have a significant impact on the optimal design of a charging network,” Myers, a research associate with the UC San Diego Deep Decarbonization Initiative, said in the news release.
One of the remarkable findings from the study is that EV drivers tend to charge their vehicles more frequently than previously assumed. Specifically, drivers often plug in when their battery is still at 60%, a stark departure from existing planning models that do not fully capture this behavior.
This real-world data significantly affects planning and policy. Using insights from individual drivers’ behavior, the study estimates that workplace charging networks might need to be triple their current size to adequately meet demand.
This could have substantial financial implications but also emphasizes the importance of strategically managed charging policies. These policies can adjust charging times to meet both driver and grid needs, promoting efficient network use.
The researchers plan to make their computational model publicly accessible, allowing other institutions and businesses to leverage their findings.
“The study shows that if workplaces take the time to understand how their employees use their electric cars and charge them, they can create charging networks that are more cost-effective, more efficient and better for the environment,” added co-author Teevrat Garg, an associate professor of economics at UC San Diego’s School of Global Policy and Strategy.
Senior author David Victor, a professor of innovation and public policy at the School of Global Policy and Strategy and co-director of the Deep Decarbonization Initiative, emphasized the broader impact, adding, “This kind of tailored design could help organizations provide a better charging experience for their workers, support the shift to electric vehicles and contribute to sustainability goals by reducing emissions from commuting.”