NIO Europe & Monolith Start Collaboration on AI-Driven EV Battery Testing

Monolith, an artificial intelligence (AI) software provider, has been chosen by China's NIO to collaborate on AI-driven anomaly detection in the company’s electric vehicle (EV) batteries. NIO will use Monolith’s Anomaly Detector AI software to monitor performance from data generated in the field.

These learnings will build a basis for comparing test-bench results and will be integrated into further verification activities.

NIO’s battery swap technology presents a unique opportunity to discover new insights into real-world, daily usage of batteries.

With Anomaly Detector, NIO and Monolith engineers can recognise abnormalities in cross-channel results at an unprecedented rate based on complex system relationships.

Battery test data anomalies can now be found rapidly and more efficiently by automating the inspection of raw test data to look for potential errors or abnormalities across hundreds of test channels.

Frank Kindermann, Head of Battery System Europe at NIO, says: “NIO's partnership with Monolith exemplifies our commitment to delivering a premium user experience. 98% of our users across the five key European markets opt for Battery as a Service (BaaS). BaaS allows NIO users in Europe to flexibly charge or swap their batteries as needed, enhancing convenience and cost efficiency."

Dr. Richard Ahlfeld, CEO and Founder of Monolith, adds: “Monolith’s deep-learning algorithms allow for automatic detection of battery issues, such as spontaneous discharge and thermal runaway, making it easier to analyse complex real-world data quickly. This capability not only saves time and resources but also enhances battery safety. As a leader in software-defined vehicles, NIO is the ideal partner to leverage this advanced technology, driving innovation in battery performance and safety.” 

UK-based Monolith's software is trusted by the world’s top engineering teams including Siemens, Honeywell, and the BMW Group to develop better quality products in half the time