About Workshop
Explore cutting-edge techniques in battery performance optimization and degradation analysis through machine learning, and gain hands-on experience in predicting battery lifetime and enhancing reliability in energy storage systems
Aim
The aim of this workshop is to equip participants with the knowledge and practical skills to leverage machine learning techniques for analyzing battery lifetime, predicting performance degradation, and optimizing the reliability of energy storage systems.
What Participants Will Learn
- Introduce machine learning for battery lifetime and degradation analysis.
- Explore data collection, feature extraction, and model development.
- Provide hands-on experience with battery performance prediction.
- Optimize battery performance and enhance storage system reliability.
Structure
📅 Day 1 — Battery Fundamentals and Degradation Data
- Battery systems overview: battery types, working principles, and lifecycle behavior
- Battery degradation basics: capacity fade, cycle aging, and failure mechanisms
- Battery data analysis: cycle, voltage, capacity data cleaning and visualization
📅 Day 2 — Machine Learning for Battery Lifetime Prediction
- ML in battery analytics: role of AI in health monitoring and lifetime estimation
- Feature engineering and modeling: extracting useful parameters for prediction
- Lifetime prediction: remaining useful life and capacity loss using regression models
📅 Day 3 — Interpretation, Optimization, and Research Insights
- Model interpretation: feature importance and degradation-driving factors
- Model improvement: tuning, validation, and prediction comparison
- Research applications: graphs, insights, and research-ready battery case study
Important Dates
Workshop Dates
2026-04-16
05: 30 PM
05: 30 PM
What You Will Gain
Outcomes
- Understanding machine learning techniques for battery lifetime and degradation analysis.
- Proficiency in data collection, feature extraction, and model development for battery performance.
- Ability to predict battery lifetime and optimize performance using machine learning models.
- Enhanced skills in improving the reliability of energy storage systems through data-driven insights.