Case Study: a global automaker and e-mobility provider achieves predictive EV charger and battery maintenance with Expleo

Making predictive maintenance chargers and high-voltage batteries for EVs a reality

The global automaker service provider, a leader in e-mobility, sought to leverage its vehicle data to launch a new predictive maintenance service for EV chargers and batteries. Their challenge was that the low sampling rate of the data made traditional time-series analysis tools unusable for predicting failures. They engaged Expleo to find a solution.

Expleo combined its automotive engineering and data science expertise to develop an innovative machine learning pipeline. This solution used existing error codes as weak signals to classify failures, achieving nearly 100% accuracy for on-board charger predictions and similar results for batteries. This efficient and interpretable methodology enabled a new predictive maintenance offering for the client, saving time, reducing costs, and increasing end-customer satisfaction.