Monolith and CamMotive Join Forces to Drive Faster, More Accurate EV Battery Testing with AI

Monolith, artificial intelligence (AI) software provider to the world’s most innovative engineering teams, has joined forces with e-powertrain development and UK-based testing services provider CamMotive to provide engineers with the tools to run more efficient, insightful, and scalable battery tests through applied AI.

Bringing together Monolith’s cutting-edge AI platform and CamMotive’s comprehensive, real-world battery data, the collaboration will enhance test data validation, helping engineers detect complex failure characteristics during electric vehicle battery development.

The partnership is implementing a ‘hybrid’ modelling technique for anomaly detection in the battery testing process. It combines physics-based simulations and machine learning methods to identify issues that may not be detected by traditional rule-based detection systems.

Building on Monolith’s successful deployments in laboratory environments, CamMotive is providing operational test data to evaluate how these models can achieve greater accuracy and insights across real-world scenarios.

Dr. Richard Ahlfeld, CEO and Founder of Monolith, said: “Our partnership with CamMotive has the potential to make EV battery development faster and more efficient. 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.”

Bruce Campbell, Director of CamMotive, said: “Partnering with Monolith gives CamMotive the ability to significantly improve our battery testing process. 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.”

Driving efficiencies in battery testing represents the core objective of Monolith and CamMotive’s collaboration. CamMotive is exploring the integration of an advanced AI toolkit to reduce reliance on physical testing and streamline workflows, using the Monolith platform to support earlier fault detection and smarter testing reviews. Simultaneously, the depth and detail of CamMotive’s battery data set will serve to further enhance Monolith’s battery-model performance.

Monolith is democratising AI for engineering, with its objective to cut engineers’ product development cycle in half by 2026. Its platform gives domain experts the power to leverage existing, valuable testing datasets for their product development. The platform analyses and learns from this information, using it to generate accurate, reliable predictions that enable engineering teams to reduce costly, time-intensive prototype testing programmes.

Integrating highly effective innovations such as the ‘Next Test Recommender’ tool and the pioneering AI-powered ‘Anomaly Detector’ functionality, Monolith provides engineers with intelligent solutions to develop higher-quality products in half the time.

To learn more, visit www.monolithai.com and www.cammotive.com.