Genetic Modeling of Battery Performance

Abstract

A state-of-the-art, first-principles lithium-ion cell model has been used to describe the changes in the performance of a 50- Ah cell during the first 7563 cycles of its life. This model was fit to the life test database using a genetic adaptation algorithm that provided degradation trends for nine different parameters that described the processes most likely to undergo change during the life of the cell. Based on the model trending, most of the capacity degradation seen in this cell arises from the net loss of lithium that can reversibly cycle between the anode and cathode. The model also indicates that increasing lithium diffusion resistance and increasing surface layer polarization on the cathode are contributing to the diminished the changeability of the cell, along with the observed decrease in cathode capacity. Thus, the cathode appears to be changing more than the anode during the cycling.

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Document Details

Document Type
Technical Report
Publication Date
Jul 10, 2009
Accession Number
ADA515077

Entities

People

  • Albert H. Zimmerman

Organizations

  • The Aerospace Corporation

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Cellular Structures
  • Chemistry
  • Databases
  • Detectors
  • Energy
  • Failure Mode And Effect Analysis
  • Genetic Algorithms
  • Genetic Code
  • Life Tests
  • Lithium Ion Batteries
  • Materials
  • Mechanics
  • Metal Oxides
  • Microelectromechanical Systems
  • Reliability
  • Resistance

Fields of Study

  • Materials science

Readers

  • Battery Technology and Engineering
  • Computational Modeling and Simulation
  • Systems Analysis and Design

Technology Areas

  • Biotechnology