The partners plan to bring together Monolith's AI platform and Cammotive's comprehensive real-world battery data. According to the initiator, the collaboration will enhance the validation of test data and help engineers detect complex failure characteristics during battery development in electric vehicles.
Specifically, we plan to implement a “hybrid modeling technique for anomaly detection in the battery testing process.” This approach benefits from combining physics-based simulation with machine learning methods to identify battery problems that are difficult to detect with traditional rule-based detection systems. Their hope is that the success of monoliths in laboratory environments leads to more accuracy and insight into real-world scenarios. This is to reduce reliance on physical testing and streamline your workflow.
“The partnership with Cammotive has the potential to make EV battery development faster and more efficient, as training machine learning models using robust, real-world data really makes AI effective.
Cammotive Director Bruce Campbell added: “In partnership with Monolith, Cammotive offers the ability to significantly improve the battery testing process. Monolith's AI technology allows us to produce higher quality results while using cutting-edge testing facilities more efficiently. Customers.”
Heading towards the end of last year, Monolith has also joined a partnership with Chinese EV manufacturer NIO. We also used artificial intelligence and machine learning to test and improve electric vehicle batteries more efficiently. Their partnership could begin in Europe and eventually expand to China.
Monolithai.com
