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An interpretable capacity prediction method for lithium-ion battery considering environmental interference.

Zijiang Yang^1,2, Hongquan Zhang^3,4

¹College of Electronic Engineering, Heilongjiang University, Harbin, 150080, China.

Scientific Reports

|August 17, 2024

Summary

This summary is machine-generated.

This study introduces an interpretable method for lithium-ion battery (LIB) capacity prediction, enhancing accuracy and understanding even with environmental interference. The IM-EI model offers robust and precise LIB performance insights.

Keywords:

Belief rule base Capacity prediction Environmental interference Interpretability Lithium-ion battery

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Area of Science:

Electrochemistry
Materials Science
Artificial Intelligence

Background:

Accurate lithium-ion battery (LIB) capacity prediction is vital for safe operation and lifespan extension.
Environmental interference can significantly degrade prediction accuracy.
Model interpretability is crucial for user trust and decision-making in LIB management.

Purpose of the Study:

To develop an interpretable method for predicting LIB capacity that accounts for environmental interference.
To enhance both the precision and interpretability of LIB capacity prediction models.

Main Methods:

Introduced an interpretable method considering environmental interference (IM-EI).
Utilized Spearman correlation coefficients, interpretability principles, and a belief rule base (BRB) with interpretability constraints.
Incorporated dynamic attribute reliability to mitigate environmental interference effects.

Main Results:

The IM-EI model demonstrated superior interpretability and prediction precision compared to existing models.
The model maintained good precision and robustness even under environmental interference conditions.

Conclusions:

The proposed IM-EI method effectively addresses environmental interference in LIB capacity prediction.
The study highlights the importance of interpretability alongside accuracy for practical LIB applications.