Big Brother Is Watching You: Leveraging Artificial Intelligence for Automated Fuel Cell Monitoring (Technical Report)

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In this technical report, we present our second-generation digital twin model for monitoring of fuel cells. This digital twin combines two data-driven machine learning models: a stationary model for stationary cell voltage prediction and a degradation model for degradation correction. This combination of both models results in a precise probabilistic prediction of the cell voltage over time.Furthermore, we present a web-based framework for automated fuel cell monitoring in real time. This framework allows training a digital twin on existing data and subsequently applying the twin to automatically check new data for anomalies.