Predictive Battery Lifetime Modeling at NREL

Research output: NRELPresentation


Battery lifetime models are used to extrapolate data from accelerated aging tests to simulate degradation in real-world applications such as electric vehicles and battery energy storage systems. Methods developed at NREL utilize both expert domain-knowledge and machine-learning to identify models, using statistical methods such as cross-validation and bootstrap resampling to interrogate model performance and quantify uncertainty. These models can be utilized in systems level simulations to predict battery performance or technoeconomic models to estimate the lifetime cost of battery systems.
Original languageAmerican English
Number of pages38
StatePublished - 2021

NREL Publication Number

  • NREL/PR-5700-80161


  • battery lifetime
  • graphite
  • lithium iron phosphate
  • lithium-ion
  • machine learning
  • non-linear models


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