LiPM: Foundation Model for Lithium-Ion Battery Analysis
Published in KDD, 2025
LiPM is a pretrained foundation model designed for heterogeneous lithium-ion battery datasets and irregular sampling protocols. It combines a mix-masked autoencoder for electrochemical consistency, a Coulombic Integration Regression objective that encodes charge conservation, and a dual-scale temporal encoder for local irregular timestamps and long-range dynamics. Pretraining across eight battery datasets enables transfer to different battery types, partial charge-discharge segments, and downstream analysis tasks.
Recommended citation: Juren Li, Yang Yang, Hanchen Su, Jiayu Liu, Youmin Chen, Jianfeng Zhang, and Lujia Pan. LiPM: Foundation Model for Lithium-Ion Battery Analysis. KDD 2025.
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