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Digital Twin Based Automated Battery
As Electric Vehicles (EVs) become essential for "smart city" transportation and autonomous fleets, their traditional Battery Management Systems (BMS) are proving inadequate. Current BMS are isolated and reactive, merely monitoring basic parameters. This project introduces the Digital Twin (DT) concept—a real-time virtual model of the physical battery—to create a truly predictive and automated solution. This DT-based automated BMS is essential for handling the high-energy demands of vehicle automation and integrating with "smart city" investments. It provides the live, predictive data needed for fleet-wide maintenance and automated coordination with the smart grid.
University:
Mineta Consortium for Transportation Mobility
Principal Investigator:
Woonki Na
PI Contact Information:
California State University Fresno
Dates:
January 2026 to March 2027
Implementation of Research Outcomes:
1. New Technologies and Software - Hybrid Digital Twin (DT) Model: A high-fidelity virtual model that integrates physics-based electrochemical equations with data-driven machine learning algorithms. - Real-Time Synchronization System: A data-processing architecture that continuously aligns the virtual model's state with the physical battery's current condition.
2. Advanced Control Processes - Adaptive Charging Protocols: A dynamic process that adjusts voltage and current limits based on the battery’s real-time degradation and age. - Dynamic Power Dispatch: An optimization process that intelligently limits power output to protect long-term battery health while maximizing driving range.
3. Validation and Testing Methods - High-Fidelity HILS Methodology: A Hardware-in-the-Loop simulation process that uses the Digital Twin to safely test physical BMS hardware against extreme scenarios, such as internal short circuits.
Impacts/Benefits of Implementation:
The implementation of this automated BMS provides three main benefits to the electric vehicle (EV) industry:
1. Longer Battery Life and Lower Costs - Smart Charging: The system changes how it charges based on the battery's age, which slows down wear and tear. - Better Resale Value: By accurately tracking the "State of Health," owners and regulators have a clear record of the battery's true remaining life.
2. Improved Safety and Reliability - Fire Prevention: The "Digital Twin" can spot tiny chemical changes and stop "thermal runaway" (battery fires) before they start. - Self-Healing: If one battery cell starts acting up, the system automatically re-balances the pack to keep the car running safely.
3. Impact on Rules and Policies - New Standards: This research creates a high-tech process for validating EV software, which can help governments set new safety and warranty laws. - Better Performance: Drivers get more range and more reliable power because the system adapts to the battery's specific condition.
Project Number:
2619
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Contact Us
San José State University One Washington Square, San Jose, CA 95192 Phone: 408-924-7560 Email: mineta-institute@sjsu.edu
