Battery Aging Simulation Solutions Blog Series

June 29, 2020

Across many industries, more and more companies are utilizing batteries as the primary source of energy for their products. When designing these products, one of the most important tasks is predicting and maximizing battery life to inform decisions on product warranty and create added value for customers. Popular methods of understanding battery aging usually rely heavily on physical testing, which is expensive or prohibitively time-consuming.

In our Battery Aging blog series, we explain how multi-physics simulation provides the ideal solution to accurately predict battery aging in real-world scenarios. Topics include:

Using Simulation to Reduce Battery Testing Time and Cost

Learn how simulation tools that use a physics-based approach to modeling Li-ion cells enable engineers to decrease testing time and costs. Click here to read the blog.

Battery-Aging-for-Real-World-Applications-and-Industries

Using GT-AutoLion and GT-SUITE to Predict Battery Aging for Real World Applications

Learn how to predict battery lifetime and make confident battery warranty decisions by combining a minimal amount of available data with physics-based simulation software. Click here to read more.

Predicting-System-Performance-with-Aged-Battery

Predicting System Performance with Aged Li-ion Batteries Using GT-AutoLion and GT-SUITE

In this blog, you’ll learn how to predict not only how Li-ion batteries degrade over time, but how that affects system-level performance by combining GT-AutoLion and GT-SUITE.

Hybrid and Electric Vehicle Simulation

How to Reduce Battery Charging Time While Maximizing Battery Life

Learn how different charging protocols impact the tradeoff between reducing the time required to charge a battery and maximizing the life of a battery. Click here to read more!

Electric Bus

Virtual Calibration of Fast Charging Strategies in GT-AutoLion

In this blog, you’ll learn how GT-AutoLion enables engineers to explore, calibrate, and make robust decisions for fast charging algorithms early in a development cycle.