BESS failure analysis
Research Papers

Insights from EPRI's BESS failure incident database

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.

from TWAICE
No items found.
Download the content

twaicetech

TWAICE helped me to learn more about: Insights from EPRI's BESS failure incident database read article here:

www.twaice.com/research/insights-from-epris-bess-failure-incident-database

#thinktwaice

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.

‍

Download the infographic here:

Featured Resources · Webinar

Product Webinar: What’s New with TWAICE Energy Analytics (Winter '24 Edition)

Discover the latest product features designed to optimize BESS management & operations, engage in a live Q&A, and get exclusive insights into what’s coming up.

Sign up

Related Resources

Lithium-ion battery cells degradation
RESEARCH PAPER

Modeling Particle Versus SEI Cracking in Lithium-Ion Battery Degradation

This work identifies and systematically compares three different SEI interaction theories, and applies them to experimental degradation data from a commercial lithium-ion cell. It shows that SEI delamination without any cracking of the active particles, and SEI microcracking, where cycling only affects SEI growth during the cycle itself, are both unlikely candidates.
Battery material
RESEARCH PAPER

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.
Battery development
RESEARCH PAPER

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.