Summary: UCLA researchers in the Department of Mechanical & Aerospace Engineering have developed a smart EV charging architecture that dynamically optimizes EV charging loads based on real-time grid capacity and limitations.
Background: The rapid increase in electric vehicle (EV) adoption creates a critical need for robust and accessible charging infrastructure, particularly in commercial parking spaces and residential garages. Current EV charging infrastructure does not dynamically adjust based on the local grid’s current capacity. Consequently, grid overload may result in decreased charging efficiency, power outages, and additional cost barriers for consumers. Additionally, charging stations tend to be centralized in specific urban locations that may hinder accessibility to certain populations. As EV adoption becomes more widespread and vehicles draw power within localized locations, the power grid experiences heavy stress. During peak hours or power shortages, operators lack the ability to dynamically manage this load, threatening local grid stability. As a result, there is a need for an intelligent charging architecture that enables efficient and dynamic EV charge load management.
Innovation: To address this growing concern, researchers at UCLA have developed a grid-friendly EV charging architecture designed to manage EV charging loads via variable power control. This invention actively controls and multiplexes current dispersed to multiple vehicles simultaneously, dynamically scaling power delivery based on real-time demand and limitations of the local power grid. When the grid is strained, the system can automatically adjust power distribution instead of shutting off power entirely, satisfying utility constraints while continuing to provide charge. By optimizing power distribution amongst multiple chargers, the system lowers average hardware and energy implementation costs. Additionally, EV charging operators gain flexible and granular control over energy output, enabling the support of more EVs. The invention seamlessly integrates into existing charging networks and stations, eliminating the need to replace current infrastructure and reducing cost barriers for adoption. Thus, this innovation bridges the gap between rising EV infrastructure demands and utility constraints, enabling a scalable solution for next-generation smart charging.
Potential Applications: ● Commercial parking structures ● Multi-unit dwellings ● Commercial fleet depots ● Charging network retrofitting
Advantages: ● Reduced CapEx ● Grid tesiliency & compliance ● Seamless integration ● Improved user experience ● Scalability
Development-To-Date: First successful demonstration complete.
Related Papers:
• R. Zahedi, R. L. Sheinberg, S. Narayana Gowda, J. Raj Chadha, K. SedghiSigarchi and R. Gadh, "Phased Planning of Heavy-Duty Electric Vehicle Charging Stations: An Optimization Framework Under Grid Capacity Constraints," in IEEE Access, vol. 14, pp. 18316-18331, 2026, doi: 10.1109/ACCESS.2026.3659818.
• Ahmadian, A., Sedghisigarchi, K., & Gadh, R. (2024). Empowering Dynamic Active and Reactive Power Control: A Deep Reinforcement Learning Controller for Three-Phase Grid-Connected Electric Vehicles. IEEE Access.
• Zhang, C., Sheinberg, R., Gowda, S. N., Sherman, M., Ahmadian, A., & Gadh, R. (2023). A novel large-scale EV charging scheduling algorithm considering V2G and reactive power management based on ADMM. Frontiers in Energy Research, 11, 107802.
• Khaki, B., Chu, C., & Gadh, R. (2019). Hierarchical distributed framework for EV charging scheduling using exchange problem. Applied Energy, 241, 461-471.
• Xiong, Y., Wang, B., Chu, C., & Gadh, R. (2018). Vehicle Grid Integration for Demand Response with Mixture User Model and Decentralized Optimization. Applied Energy, 231, 481-493.
• Xiong, Y., Khaki, B., Chu, C., & Gadh, R. (2018). Real-Time Bi-directional Electric Vehicle Charging Control with Distribution Grid Implementation. 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 1-5.
Reference: UCLA Case No. 2013-146
Patent: Power control apparatus and methods for electric vehicles (US 9,290,104)
Lead Inventor: Rajit Gadh