Optimizing Cycle Life Testing: Hybrid (Physics + ML) Modeling Approach for Real-world Applications
Join us for an insightful joint webinar hosted by oorja and Customized Energy Solutions (CES), where we discuss oorja’s advanced hybrid (physics + ML) modeling techniques for optimizing battery cycle life testing requirements, test protocols, and getting reliable life predictions according to the real-world use case.
Agenda Highlights
- The Importance and Background of Accelerated Life Testing: Understand the need and background for accelerated life testing, requirements, and optimization strategies to streamline testing and ensure rapid yet reliable assessments of battery durability.
- Validation Cases: Learn from real-world case studies demonstrating the successful implementation and validation of optimized testing protocols.
- Hybrid Modeling for Cycle Life Prediction: Explore how combining physics-based modeling and machine learning techniques enhances the accuracy and efficiency of cycle life predictions.
- Design of Experiments (DoE) Test Case Matrix: Learn how to effectively construct extensive DoE matrices to enhance predictive modeling accuracy and reliability.
Reserve your spot to gain cutting-edge insights and practical strategies from leading battery experts!
Meet The Speakers
Prajakta brings extensive expertise in customer success and engagement, honed over years of experience. She has an M.Tech in Microelectronics from IIT Bombay. At oorja, she leads customer engagement, ensuring clients receive exceptional support and value from our solutions.
Experienced R&D Services team lead at Customised Energy Solutions with a demonstrated history of working in the energy storage industry. During this time, he has developed his skills in the energy storage domain by building knowledge in li-ion, lead acid and sodium-ion technologies, and experience in research, product development, engineering, design, testing, analysis, data processing, telemetry and conducting trainings.