Join us for an insightful webinar as we explore a new revolutionary hybrid simulation technique that reduces accelerated battery cycler testing time by up to 50%. Pure physics-based simulation struggles to model Li-ion battery degradation due to its multi-physics nature, non-linear behavior, and microstructural changes. Additionally, testing a battery under typical automotive conditions to predict a 10-year lifespan may require up to 2 years of continuous testing. Accelerated aging tests, while useful, may not perfectly replicate real-world conditions, leading to prediction errors of up to 20% when applied to actual field performance.
During the webinar, we will explore how a minimal amount of data can be used to obtain degradation and design parameters that allow for better prediction of battery and cell behavior under real-world operating conditions and drive cycles, saving time and cost during the design of the battery pack.
Topic Area
- Time Savings: Up to 50% reduction in accelerated testing time.
- Enhanced Reliability: Integrating physics-based models and machine learning.
- Streamlined Analysis: Effortless data handling and real-world applicability.
- Driving Innovation: Optimizing battery development processes for real-world scenarios.
Registration Procedure
This event is free of charge: registration is required to attend.
It uses a web platform that does not require local software installation. You can join the session via: Mac, PC, or any mobile device.
Registered participants will receive the link and credentials to participate at the email address provided during registration.
You can ask questions and participate in the discussion via the chat function in the web platform.
SUBSCRIBE NOW
