Credit: UC San Diego
Innovative Approaches to Electric Vehicle Charging at Workplaces
A groundbreaking study from the University of California, San Diego has introduced a cutting-edge computational tool aimed at helping organizations design effective electric vehicle (EV) charging networks. This tool emphasizes the actual behaviors and charging habits of modern drivers.
Addressing Current Needs in EV Infrastructure
Published recently in the journal Renewable Energy, this research aims to assist businesses and institutions striving to support employees transitioning to electric vehicles.
“Historically, early adopters of EVs have been predominantly affluent homeowners equipped with private home chargers. However, this demographic does not reflect the broader community that may consider making the switch,” explained Ryan Hanna, Assistant Research Scientist at UC San Diego and co-first author alongside Jeff Myers, a research associate involved in the university’s Deep Decarbonization Initiative.
“It’s crucial to recognize that many potential EV users are renters or reside in multi-family units without designated parking spaces—individuals who can’t install personal chargers. These stakeholders require alternative options; forecasts suggest workplace charging will become increasingly prominent as a supporting mode of charging after residential options.”
Utilizing Real-World Data for Effective Network Design
The team engaged extensively with campus leadership overseeing parking and transportation services while analyzing several elements on site—which boasts one of the largest academic EV charging infrastructures globally. They collected anonymized data from over 800 EV users between 2023 and 2024 along with insights derived from 439 local charging stations.
This study advances beyond previous models relying on generalized data by integrating real-time behavioral patterns exhibited by actual drivers utilizing these networks.
“Our findings indicate that optimizing network design relies significantly on using driver-specific data instead of depending solely on idealized averages,” stated Myers, who holds a Master’s degree in Public Policy from UC San Diego’s School of Global Policy and Strategy as of 2023.
Changing Perspectives on Charging Frequencies
The research highlighted that many existing infrastructure planning strategies lack understanding concerning how drivers charge their vehicles when away from home. Insights gathered show that participants tended to plug-in once battery levels dropped below approximately 60%, contradicting previous assumptions about typical behaviors. This observation revealed frequent usage patterns previously underestimated by planners.
Basing conclusions on individual rather than national averages suggests potentially tripling network size requirements essential for fully accommodating workplace-specific charging demands—this discovery bears significant repercussions regarding costs associated with developing such infrastructures.
The Importance of Thoughtful Policies in Charging Management
This underscores not only effective workplace policies but also managed charging techniques—methods allowing dynamic adjustments aligned both with user needs and grid capabilities. If executed strategically, these practices can optimize resources while minimizing necessary station numbers identified throughout studies conducted thus far.
Accessible Tools for Institutions Seeking Improvement
The researchers plan to make their innovative computational model publicly accessible so various institutions—including universities or corporations—can craft tailored networks befitting employee needs economically effectively.
“The results assert that when employers invest time into understanding employee interactions with electric vehicles and their preferences regarding charge periods—they enable creation opportunities leading toward environmentally conscious designs more economically favorable,” noted Teevrat Garg, Associate Professor at UC San Diego’s School focused upon public policy analysis & strategy developments relevantly involved.” “Organizations can input collected rudimentary metrics reflecting motivational factors influencing worker behavior into our model resulting towards impactful operational benefits.”
Firms possessing an inability monitoring such specific dynamics still leverage general dataset trends applicable across average usage instances presented within shared frameworks appropriately outlined above.”
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- Your Citation Resource:
- Jeff Myers et al., Structuring Workplace And Destination-Based Evs Considering Behavioral Patterns Innovatively - Renewable Energy (2025). DOI:10.1016/j.RENENE.xxxxxxx”
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