Research Themes
Battery Modeling and Characterization
We develop rapid characterization methods and high-fidelity electrical, electrochemical, and thermal models for practical battery diagnostics, estimation, and control.
Battery State Estimation and Fuel Gauging
We develop robust battery state-estimation and fuel-gauging methods that account for model uncertainty, sensor bias, measurement noise, temperature, aging, capacity uncertainty, and timing drift.
Battery Pack Design and Mission Optimization
We develop battery pack sizing, mission-analysis, and thermal-management tools that connect battery behavior to application-level performance and cost requirements.
Battery Health Diagnostics and Prognostics
We develop physics-informed and data-driven methods to detect degradation, diagnose battery health, quantify uncertainty, and predict state of health and remaining useful life under real-world operating conditions.
Battery Thermal Modeling, Management, and Safety
We develop thermal models, temperature-estimation methods, and control strategies to support safe, reliable, and high-performance battery operation under dynamic loading and environmental conditions.
Intelligent Charging and Charge Optimization
We develop intelligent charging and cell-balancing strategies that optimize charging time, energy efficiency, thermal stress, and battery longevity under practical operating constraints.
Battery Reuse, Refurbishment, and Second-Life Applications
We develop rapid battery health assessment and decision-support methods for sorting, refurbishment, reuse, and safe second-life deployment of retired batteries.
Battery Pack Testing and Experimental Platforms
We design experimental platforms and testing methodologies for accurate cell, module, and pack characterization under realistic electrical and thermal operating conditions.
BMS Validation and Performance Evaluation
We develop rigorous validation, benchmarking, and hardware-in-the-loop methods to evaluate the accuracy, robustness, and failure modes of battery management algorithms and systems.
Technology & Innovation Platforms
Integrated Battery Diagnostic System (iBDS)
BMSLab is developing the Integrated Battery Diagnostic System (iBDS), a modular platform for rapid and reliable assessment of battery health and performance. iBDS combines available battery metadata, optional BMS history, portable electrical testing, physics-informed modeling, and AI-enabled inference to support fast and explainable battery health assessment. Designed for field deployment, the platform supports applications ranging from EV module screening to consumer-electronics battery diagnostics and second-life decision making.
Advanced EIS Device
BMSLab is developing next-generation Electrochemical Impedance Spectroscopy (EIS) methods and technologies to address important sources of measurement bias and variability in battery testing. Our work combines advanced signal design, measurement correction, uncertainty analysis, and parameter estimation to improve the accuracy, repeatability, and interpretability of impedance measurements and strengthen their use in battery health diagnostics.