Cambridge EnerTech’s

Battery Intelligence

Using Machine Learning and Artificial Intelligence to Optimise Battery Development from Materials to Manufacturing

25-26 June 2025

As the battery market rapidly expands, the need to extend battery longevity becomes increasingly critical. For OEMs, battery pack manufacturers, and electric fleet managers, the key to enhancing battery life lies in harnessing data. By leveraging machine learning and advanced analytics, the true potential of battery data can be unlocked—enabling more accurate predictions, real-time monitoring, and continuous improvement of battery lifespan. As AI becomes more disruptive in the battery technology space, predictive intelligence and data analytics will play pivotal roles in achieving higher efficiency and operational reliability. The Battery Intelligence conference will gather industry and academic thought leaders to explore how battery intelligence can drive significant and continuous improvements in battery performance.

Coverage will include, but is not limited to:

Industry and Academic Perspectives
Intelligent Chemistry and Materials
Intelligent Manufacturing
Data Strategy, Security, and Traceability
Machine Learning for Batteries
Diagnostic, Predictive, and Prescriptive Analytics

The deadline for priority consideration is 13 December 2024.

All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge EnerTech’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.

Opportunities for Participation: