Focus: Battery Technology
Lab PI: Matthieu Dubarry
The electrochemical power sources laboratory (EPSL) main areas of research are:
Testing of batteries under representative conditions to assess durability in the field,
Battery diagnosis and prognosis using non-invasive and deployable techniques,
Battery packs modeling taking into consideration cell-to-cell variations and inhomogeneities,
Deployed systems state of charge and state of health monitoring,
Battery prototyping and electrode formulation optimization,
Transfer of knowledge from laboratory to real-life applications to facilitate battery engineering, cost estimate, control strategy, and decisions.
EPSL is well equipped for electrode preparation and assembly for different types of half-cells (coin cells, swageloks, PAT-cells) with 30 independent channels for testing. For larger full cells, the laboratory has more than 80 channels available with temperature chambers and state-of-the art safety procedures. Material characterization including x-ray diffraction as well as scanning and transmission electron microscopy, will be done in collaboration with the UHM Material Science Consortium for Research and Education.
Lab Partnerships and Funding
EPSL has been a partner with various research institutions in government, industry, and academia, in the US and abroad. Current and past funding sources include the Office of Naval Research, SAFT Batteries, the US DOE’s Office of Energy Efficiency and Renewable Energy (through the Idaho National Laboratory), the Department of Transportation (via the Electric Vehicle Transportation Center), the Air Force Research Laboratory (through the Hawai‘i Center for Advanced Transportation Technologies), and the Hawai‘i Renewable Energy Development Venture funds.
Current and Past Collaborations
- The assessment of the remaining useful life of deployed BESS from the characterization of representative usage and the consideration of intra- and extra-modular inhomogeneities (ONR/APRISES)
- The assessment of different strategies to track the optimal usage of EV batteries as grid support (DOT, ONR/APRISES)
- The development of tools, protocols, and approaches to improve batteries diagnosis and prognosis via non-invasive in-operando techniques (ONR/APRISES, SAFT)
- The optimization of battery electrodes to improve performance by tuning architecture (ONR/APRISES, Trevi Systems, University of Montreal, University of Nantes)
- 2008-2013: Evaluation of Commercial Li-ion cells based on composite electrode for plug-in electric vehicle (DOE/Idaho National Laboratory)
- 2000-2011: Data Collection and Analysis to Support HCATT Electric and Hybrid Vehicle Demonstration Program (HCATT)
- 2020, M. Dubarry, G. Baure, Perspective on Commercial Li-ion Battery Testing, Best Practices for Simple and Effective Protocols, Electronics, Vol. 9, Issue 1, Paper 152. (Open Access: PDF)
- 2019, A. Barai, K. Uddin, M. Dubarry, L. Somerville, A. McGordon, P. Jennings, I. Bloom, A comparison of methodologies for the non-invasive characterisation of commercial Li-ion cells, Progress in Energy and Combustion Science, Vol. 72, pp. 1-32. (Open Access: PDF)
- 2019, M. Dubarry, G. Baure, C. Pastor-Fernández, T.F. Yu, W.D. Widanage, J. Marco, Battery energy storage system modeling: A combined comprehensive approach, Journal of Energy Storage, Vol. 21, pp. 172-185. (Open Access: PDF)
- 2018, K. Uddin, M. Dubarry, M.B. Glick, The viability of vehicle-to-grid operations from a battery technology and policy perspective, Energy Policy, Vol. 113, pp. 342-347. (Open Access: PDF)
- 2017, M. Dubarry, A. Devie, K. Stein, M. Tun, M. Matsuura, R. Rocheleau, Battery Energy Storage System battery durability and reliability under electric utility grid operations: Analysis of 3 years of real usage, Journal of Power Sources, Vol. 338, pp. 65-73.
- 2017, M. Dubarry, M. Berecibar, A. Devie, D. Ansean, N. Omar, I. Villarreal, State of Health Battery Estimator Enabling Degradation Diagnosis: Model and Algorithm Description, Journal of Power Sources, Vol. 360, pp. 59-69.
- 2012, M. Dubarry, C. Truchot, B.Y. Liaw, Synthesize battery degradation modes via a diagnostic and prognostic model, Journal of Power Sources, Vol. 219, pp. 204-216.