The work presents a model that predicts battery degradation using field-accessible data without historical cycling information. It combines a mixture of expert’s network with features from partial charging curves and relaxation voltage to classify degradation modes and predict long-term trajectories under uncertain future conditions.
- Xinghao Huang
- Shengyu Tao
- Xuan Zhang
