Immediate remaining capacity estimation of heterogeneous second-life lithium-ion batteries via deep generative transfer learning

This work proposes a novel deep generative transfer learning algorithm to estimate the relative remaining capacity of second-life batteries using minimal field data, enabling safe and sustainable reuse under data scarce and heterogeneous conditions.