Joint dynamics and efficient initialization techniques for potentials and currents in the P2D battery model.

Area of Science:

• Computational Physics
• Mathematical Modeling

Background:

• Physics-based pseudo-two-dimensional (P2D) models are often solved using iterative methods like Newton's or shooting methods.
• Effective application of these iterative methods requires transforming boundary value problems into initial value problems.
• Initial parameter guesses significantly influence the convergence rate of these iterative solutions.

Purpose of the Study:

• To develop an analytically derived linear solution for initializing parameters in P2D models.
• To enhance the convergence speed and computational efficiency of P2D model simulations.
• To provide a practical and easily implementable method for parameter initialization.

Main Methods:

• Derivation of a linear analytical solution for initial parameter estimation.
• Application of the derived solution to P2D model initialization.
• Evaluation of the proposed method's impact on convergence and performance.

Main Results:

• The proposed analytical linear solution provides an effective approximate guess for initial conditions.
• This approach demonstrably enhances the convergence speed of iterative solvers for P2D models.
• The method offers a computationally efficient and straightforward alternative to traditional initialization techniques.

Conclusions:

• The analytically derived linear solution is a practical and efficient method for initializing P2D models.
• Implementing this approach can lead to faster and more robust simulations.
• This technique offers a valuable improvement for researchers utilizing P2D modeling.