OMB Individually Reported
Enhancing the circularity: Cost effective battery de-energization, disassembly, and pre-processing (CEBDDP)
Low riskExact public inventory row
Description
Predict state of health and state of function of spent batteries
Detailed example
Prediction of battery state of health
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Improved ability for prediction to enable potential reuse of batteries, towards reducing costs of batteries
Audit / financial statement impact
Will serve as basis for decisions on use of end-of-first life batteries
Controls / human review
ATO: Not reported; PIA: Not published