As the battery market continues its rapid growth, extending battery longevity has become a top priority. For OEMs, battery pack manufacturers, and electric fleet operators, the path to longer-lasting batteries lies in data-driven insights. By harnessing machine learning and advanced analytics, organizations can unlock the full potential of battery data, enabling precise performance predictions, real-time health monitoring, and continuous optimization. With AI emerging as a transformative force in battery technology, predictive intelligence and data analytics are set to play a central role in boosting efficiency, reliability, and lifespan. The Battery Intelligence conference will bring together leading voices from industry and academia to explore how data-driven strategies are shaping the future of battery performance and innovation.
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 May 23, 2025.
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: