Cycle Life

Cycle life, the number of charge-discharge cycles a battery can endure before failure, is a critical parameter for battery performance and longevity. Current research focuses on accurately predicting cycle life using various approaches, including physics-based models, machine learning algorithms (like recurrent neural networks and gradient boosting regressors), and hybrid methods combining both. These models leverage early-cycle data to forecast the entire capacity degradation curve, providing more robust and interpretable predictions than simple point estimates. Accurate cycle life prediction is crucial for optimizing battery design, management, and resource allocation, improving the safety and efficiency of battery-powered systems.