UK-based artificial intelligence company Monolith has announced a collaboration with CamMotive, a specialist in electric powertrain testing, to bring AI-powered tools to electric vehicle (EV) battery development. The partnership aims to improve the accuracy and scalability of battery testing by integrating machine learning with real-world data from CamMotive’s testing operations.
The companies are introducing a hybrid modelling approach for anomaly detection in EV battery testing. This method blends physics-based simulations with data-driven algorithms to detect complex battery issues often missed by conventional systems. According to Monolith, the initiative is intended to accelerate development timelines, enhance performance insights, and lower costs.
“Our partnership with CamMotive has the potential to make EV battery development faster and more efficient,” said Dr. Richard Ahlfeld, CEO and Founder of Monolith. “Training machine learning models with robust, real-world data is what makes AI truly effective, as it means engineers can find reliable ways to save time, achieve performance gains and reduce costs.”
CamMotive expects the collaboration to improve its ability to deliver detailed battery diagnostics. “Partnering with Monolith gives CamMotive the ability to significantly improve our battery testing process,” said Bruce Campbell, Director of CamMotive. “Monolith’s AI technology allows us to use our state-of-the-art test facility more efficiently while generating higher-quality results. The insights we gain through this collaboration will help us detect potential issues earlier, streamline workflows, and enable our engineers to focus on delivering valuable data analysis for our customers.”
Monolith previously partnered with Chinese electric carmaker Nio to deploy its AI platform for battery testing in Europe, with possible future expansion to China.