Umeshexe/Battery-Health-Management-System ? reverse-engineered prompt

Build me a notebook based project that predicts the state of health of an EV lithium ion battery over a long horizon, ideally up to the next 100 cycles, using the Toyota battery dataset or a similar battery dataset.

I want it to train a few different models, like LSTM, RNN, and some basic machine learning models, then compare how well they forecast battery health. Please also add explainable AI so I can see which features matter most for the prediction, since this is meant to be an interpretable project and not just a black box.

Make it easy to run in Jupyter Notebook, with clear data loading, preprocessing, training, evaluation, and plots for the predicted versus actual battery health. If you need to look up current docs or best practices for the libraries, go ahead. I’d also like the notebook to be clean enough that I can use it for a minor project presentation or report.