Synthetic vs. Real Driving Cycles: A Comparison of Electric Vehicle Battery Degradation

Abstract

Automobile dependency and the inexorable proliferation of electric vehicles (EVs) compels accurate predictions of cycle life across multiple usage conditions and for multiple lithium-ion battery systems. Synthetic driving cycles have been essential in accumulating data on EV battery lifetimes. However, since battery deterioration is path-dependent, the representability of synthetic cycles must be questioned. Hence, this work compared three different synthetic driving cycles to real driving data in terms of mimicking actual EV battery degradation. It was found that the average current and charge capacity during discharge were important parameters in determining the appropriate synthetic profile, and traffic conditions have a significant impact on cell lifetimes. In addition, a stage of accelerated capacity fade was observed and shown to be induced by an increased loss of lithium inventory (LLI) resulting from irreversible Li plating. New metrics, the ratio of the loss of activematerial at the negative electrode (LAMNE) to the LLI and the plating threshold, were proposed as possible predictors for a stage of accelerated degradation. The results presented here demonstrated tracking properties, such as capacity loss and resistance increase, were insufficient in predicting cell lifetimes, supporting the adoption of metrics based on the analysis of degradation modes.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2019
Accession Number
AD1104877

Entities

People

  • George Baure
  • Matthieu Dubarry

Organizations

  • University of Hawaiʻi at Mānoa

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Chemical Kinetics
  • Chemistry
  • Computer Simulations
  • Detection
  • Electric Vehicles
  • Energy
  • Energy Storage
  • Experimental Data
  • High Voltage
  • Land Transportation
  • Lithium Ion Batteries
  • Materials
  • Research Facilities
  • Simulations
  • Stress Tests
  • Vehicles
  • X-Ray Computed Tomography

Readers

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