Detecting Electric Vehicle Battery Failure via Dynamic-VAE

In this note, we describe a battery failure detection pipeline backed up by deep learning models. We first introduce a large-scale Electric vehicle (EV) battery dataset including cleaned battery-charging data from hundreds of vehicles. We then formulate battery failure detection as an outlier detection problem, and propose a new algorithm named Dynamic-VAE based on dynamic system and variational autoencoders. We validate the performance of our proposed algorithm against several baselines on our released dataset and demonstrated the effectiveness of Dynamic-VAE.