Surface Lithium Concentration Estimation Without PDE Battery Models
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Solution Overview
Problem
Current lithium ion battery models, particularly equivalent circuit models, struggle with accuracy and interpretability due to their data-driven nature lacking physical meaning, and electrochemical models are hindered by complexity, making it difficult to estimate surface lithium concentration and reduce model complexity for wide application.
Innovation Solution
A real-time estimation method for surface lithium concentration of electrode active materials in lithium ion batteries, which models the diffusion process as a superposition of first-order transient and transitory processes, allowing direct calculation of surface lithium concentration from average lithium concentration and transient variables, avoiding the solution of high-order partial differential equations, and uses data-driven parameter estimation for diffusion performance parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrochemical models are used to accurately describe internal state changes, then model accuracy is improved, but model complexity increases
Solution Approach 1:
The patent segments the complex electrochemical model into a simplified equivalent circuit model with physically meaningful elements. The model divides the battery into discrete components (electrode active materials, electrolytes, separators) with identifiable parameters, allowing accurate description of internal states without full electrochemical complexity. This segmentation enables practical application while maintaining measurement precision for surface lithium concentration estimation.
2Ease of operation
If equivalent circuit models are used for practical applications, then ease of operation is improved, but model accuracy deteriorates
Solution Approach 1:
The patent changes the parameters of the equivalent circuit model by introducing physically meaningful elements that represent actual battery components and processes. Instead of purely empirical circuit elements, the model uses parameters related to electrode active materials, lithium ion diffusion, and electrochemical reactions. This parameter transformation maintains ease of operation while significantly improving model accuracy for describing internal battery states.
3Ease of manufacture
If data-driven models are used to fit external characteristics, then ease of manufacture is improved, but interpretability deteriorates
Solution Approach 1:
The patent introduces physically meaningful circuit elements as intermediaries between data-driven fitting and physical interpretation. These elements serve as mediators that connect external electrical characteristics to internal battery states, providing both the ease of data-driven implementation and the interpretability of physical models. The circuit elements represent actual physical processes, enabling lossless interpretation of model parameters.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides a flexible and accurate real-time estimation of surface lithium concentration applicable to various electrode materials, reducing model complexity and enhancing the universality and practicality of lithium ion battery models.
Implementation Method 1
The patent models the diffusion process as a superposition of first-order transient and transitory processes, allowing direct calculation of surface lithium concentration from average lithium concentration and transient variables
Data Source
AI summary
Provided is a real-time estimation method for a surface lithium concentration of an electrode active material of a lithium ion battery. The method comprises: obtaining an electric current sequence and a temperature sequence of a battery port and a basic parameter of an electrode active material, and calculating a surface lithium concentration, the average lithium concentration and an initial value of a transient variable of the electrode active material in a diffusion process; at the beginning of the current time period, calculating a surface reaction ion flux and a diffusion coefficient of the electrode active material and a time constant of the transient variable of lithium in the active material in the diffusion process; at the end of the current time period, calculating the transient variable of the active material in the diffusion process and the average lithium concentration of the active material.