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Battery Life Predictive Model

National Renewable Energy Laboratory

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Technology Marketing Summary

Batteries are one of the leading cost drivers of any electric vehicle project. Current practices require that batteries be oversized by design in order to meet the battery warrantee’s end-of-life (EOL) power and energy requirements. This quickly increases the cost of electric vehicles and can price them out of the realm of consideration for most users. NREL scientists have developed a software model that analyzes the performance of batteries over a lifetime of use in real world environmental and loading scenarios. This model allows users to simulate the lifetime performance requirements of a battery and minimize the size and cost of a battery that is needed to meet user requirements. NREL is seeking partners and/or licensees to further develop, test, and support the software for widespread distribution.


The battery life predictive model provides a method to estimate capacity fade and resistance growth of a battery under real world usage cycles and temperature conditions. The model uses an extensive database of previous Department of Energy (DOE) experiments and a series of empirical models to produce accurate estimates of battery life under real world conditions. The model requires performance inputs from past experiments for operating temperature, voltage, depth of discharge and the number of cycles per day and analyzes the effect of those inputs on battery performance based on a user defined driving requirements profile. The model will output the increase in battery resistance and the reduction in capacity over time or a given number of cycles.

Most currently available models allow the designer to only analyze battery life for a few limited scenarios that closely correspond to experimentally tested conditions. This limitation does not provide a true “real world” simulation of the factors that affect battery performance. NREL’s Battery Life Predictive Model has the unique ability to allow the user to change multiple constraints at once to get an accurate simulation of the desired operating scenario. NREL’s model targets users looking to run performance/life/cost tradeoff analyses or determine the appropriate battery that must be used in an application to meet end of life performance goals. The model also enables users to fit specific scenarios and perform business case analyses.

  • Enables users to adjust a wide variety of inputs to simulate real world battery usage conditions.
  • Uses a large database of DOE test results, combined with physically justified empirical models to predict battery life.
Applications and Industries
  • Battery performance tradeoff analysis (“what if” analysis).
  • Determining battery size requirements to meet end of life goals.
  • Warranty, second use analysis.
  • Could be developed into an on board power management program.
Technology Status
Technology IDDevelopment StageAvailabilityPublishedLast Updated
NREL SWR: 10-15Development - Algorithm development and initial coding are complete. The application would require the development of a user interface.Available - The Battery Life Predictive Model is currently available for licensing or partnership opportunities.08/03/201008/03/2010

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To: Jean Schulte<>