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Systems and methods for estimation and prediction of battery health and performance

  • US 10,209,314 B2
  • Filed: 11/21/2016
  • Issued: 02/19/2019
  • Est. Priority Date: 11/21/2016
  • Status: Active Grant
First Claim
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1. A computer-implemented method for analyzing energy storage device information, comprising:

  • a feature extraction module configured for;

    receiving input data including passive information collected from passive measurements of a battery and active information collected from active measurements of a response of the battery to a stimulus signal applied to the battery;

    performing geometric-based parameter identification responsive to the input data relative to an electrical equivalent circuit model to develop geometric parameters;

    performing optimization-based parameter identification responsive to the input data relative to the electrical equivalent circuit model to develop optimized parameters; and

    performing a decision fusion algorithm for combining the geometric parameters and the optimized parameters to develop new internal battery parameters including at least a constant phase element exponent, electrolyte resistance, and charge transfer resistance;

    a state estimation module for updating an internal state model of the battery responsive to the new internal battery parameters;

    a health estimation module for processing the internal state model to determine a present battery health including one or both of a state-of-health (SOH) estimation and a state-of-charge (SOC) estimation for the battery; and

    a communication module for communicating one or more of the SOH estimation and the SOC estimation to a user, a related computing system, or a combination thereof.

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