Coverage will include, but is not limited to:
- AI for Battery Management Systems (BMS) — Predictive analytics, intelligent control, and state estimation for enhanced battery life, performance, and safety.
- AI in Battery Design & Materials Discovery — Accelerated material prediction, synthesis optimization, and novel battery chemistry development.
- AI for Battery Manufacturing & Quality Control — AI-driven process monitoring, defect detection, and quality assurance in battery production.
- Cost-Benefit Analysis of AI — Quantify the economic impact, ROI, and efficiency gains from AI implementation in energy systems and battery applications.
- Predictive AI for Battery Degradation — Models for predicting battery lifespan, optimizing usage, and facilitating second-life applications and recycling.
- AI for Energy Storage System (ESS) Optimization — Intelligent management of distributed battery energy storage systems, including charge/discharge and integration with renewables.
- AI & Data Analytics for Energy Efficiency — AI for optimizing energy consumption in various sectors.
- Ethical AI, Regulations & Policy in Energy — Responsible AI development, data privacy, and policy frameworks for intelligent energy systems.
The deadline for priority consideration is 7 November 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: