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This work addresses the parameter identification issues for the nonlinear fractional-order model with colored noise. Fractional-order circuit representation precisely characterizes lithium-ion battery electrochemical dynamics. Parameter estimates are generated via auxiliary model gradient descent (AM-GD), resolving unmeasurable system states. Furthermore, incorporating a forgetting factor accelerates convergence dynamics. Finally, the simulation examples test the effectiveness of the proposed algorithm.

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An Auxiliary Model Gradient Algorithm with Forgetting Factor for Parameter Estimation of Nonlinear Fractional Order Models in Colored Noise

  • 会议论文

  • 发表日期：

    2026年

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  • Naishuo Yan,
  • Yan Ji,
  • Wen Zheng

摘要

This work addresses the parameter identification issues for the nonlinear fractional-order model with colored noise. Fractional-order circuit representation precisely characterizes lithium-ion battery electrochemical dynamics. Parameter estimates are generated via auxiliary model gradient descent (AM-GD), resolving unmeasurable system states. Furthermore, incorporating a forgetting factor accelerates convergence dynamics. Finally, the simulation examples test the effectiveness of the proposed algorithm.