Battery health and remaining life model

The brief

EV makers and battery-swap companies need to know how healthy each battery is. Predict a battery's capacity fade and remaining life from its charge and discharge cycles, compare ensemble models, and explain which conditions age it fastest. Good looks like: features from cycle curves, evaluation on batteries the model has not seen, and clear explanations.

What you will build

1. Explore the charge and discharge cycles
2. Engineer features from each cycle
3. Train and compare ensemble models
4. Test on held-out batteries
5. Explain ageing factors with SHAP

Free, open data to build it with

• NASA battery dataset ↗ Kaggle (NASA PCoE)

Check each dataset's licence before you publish your work. Your mentor gives your team its own version of the brief (data, scope or region), so every team's project is its own.