Why parameter identification of battery model is essential?
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Parameter identification of battery models is crucial due to its impact on accuracy and performance. Various methods like Bayesian inference , recursive least squares (RLS) , bounded varying forgetting factor recursive least square approach , and hybrid optimization techniques like particle swarm optimizer (PSO) and genetic algorithm (GA) are employed to determine accurate parameters. These methods help in estimating internal behaviors, optimizing coefficients, enhancing model precision, and improving sensitivity analysis. Accurate parameter identification ensures reliable battery management, precise voltage curve reconstruction, and effective analysis of battery behaviors under different conditions. It aids in obtaining optimal values for coefficients, state of charge estimation, and overall model accuracy, which are essential for efficient battery design, operation, and performance evaluation.
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| Papers (5) | Insight |
|---|---|
1 Citations | Parameter identification of the battery model is essential to accurately predict terminal voltage and internal parameters, enhancing the model's precision and effectiveness in applications like vanadium redox flow batteries. |
| Parameter identification of the battery model is crucial to enhance accuracy in state of charge estimation and overall model precision, as demonstrated in the research paper. | |
| Parameter identification of battery models is crucial for accurate equivalent circuit modeling, ensuring performance prediction and optimization in various applications, as highlighted in the research paper. | |
| Parameter identification of battery models is crucial for accurate estimation of internal behavior, aiding in battery design and management by determining parameter distributions and global sensitivity for optimal performance. | |
| Parameter identification of battery model is crucial for model-based battery management systems to optimize performance. The proposed online method ensures accurate parameter estimation for effective battery monitoring. |
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