This report is intended to address the failure mode analysis gap by developing a classification system that is practical for both technical and non-technical stakeholders.
Research Papers
Insights from EPRI's BESS failure incident database
BESS failure: study identifies opportunities for battery analytics to prevent incidents
There is currently no public resource that categorizes BESS incidents by cause of failure. The joint report from EPRI, PNNL & TWAICE fills this gap by analyzing aggregated failure data. Understanding how and why BESS fail is a major priority to the energy industry. Learning from failure incidents will improve prevention and mitigation measures. The report classifies failure events and provides recommendations for future development.
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Non-destructive electrode potential and open-circuit voltage aging estimation for lithium-ion batteries
In this publication we extend a state-of-the-art electrode open circuit potential model for blend electrodes and inhomogeneous lithiation. We introduce a bi-level optimization algorithm to estimate the open parameters of the electrode model using measurements conducted on the full-cell level with state-of-the-art testing equipment.
Mechanistic cycle aging model for the open-circuit voltage curve of lithium-ion batteries
Cycling lithium-ion batteries causes capacity fade, but also changes the shape of the open-circuit voltage (OCV) curve, due to loss of active material (LAM) and loss of lithium inventory (LLI). To model this change, we recently proposed a novel empirical calendar aging model that is parameterized on component states of health (s) instead of capacity fade only.
Mechanistic calendar aging model for lithium-ion batteries
In this work we present a novel mechanistic calendar aging model for a commercial lithium-ion cell with NCA cathode and silicon-graphite anode. The mechanistic calendar aging model is a semi-empirical aging model that is parameterized on component states of health, instead of capacity.