Machine Learning Model Extends Retired EV Battery Life and Cuts Carbon Intensity by 14.3%
bioengineer.orgResearchers used machine learning to decide when retired electric vehicle batteries should leave their first life in commercial fleets and move into second life storage. Instead of retiring every pack after a fixed 30 months, the model tracks cell degradation and lets each battery run until it hits an 80 percent state of health threshold. On a fleet of 20 BAIC EU500 vans with CATL NCM packs, that approach added about 5 months of service on average and lowered life cycle carbon intensity from 97.3 to 83.4 grams of CO2e per kWh, a 14.3 percent reduction. Second life uses like PV paired stationary storage gave the strongest carbon benefit. The authors project large mitigation potential in China and the EU as EV retirements ramp up, but the numbers fall once grids clean up. The study is limited to one vehicle model and one battery chemistry, so more data is needed before applying the framework to LFP packs or mixed fleets.
