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A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation
Mohammad Aljaidi1, Pradeep Jangir2,3,4,5, Sunilkumar P Agrawal6
1Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa, 13110, Jordan. mjaidi@zu.edu.jo.
Scientific Reports
|January 10, 2025
Summary
A new QUATRE-EMS algorithm optimizes proton exchange membrane fuel cell (PEMFC) parameters, significantly reducing errors and runtime. This advancement improves PEMFC accuracy and efficiency for power systems.
Area of Science:
- Electrochemical energy conversion and storage.
- Renewable energy systems and power management.
Background:
- Proton exchange membrane fuel cells (PEMFCs) offer low-emission, reliable power generation as alternatives to diesel systems.
- Optimizing PEMFC parameters is complex due to nonlinear models, hindering efficient performance.
- Accurate PEMFC modeling is crucial for their application in backup power and grid stabilization.
Purpose of the Study:
- To introduce a novel optimization algorithm, QUasi-Affine TRansformation Evolution with Evolution Matrix and Selection (QUATRE-EMS), for PEMFC parameter determination.
- To enhance the accuracy and efficiency of PEMFC stack performance prediction.
- To validate the effectiveness of QUATRE-EMS against existing optimization algorithms.
Main Methods:
- Development and application of the QUATRE-EMS algorithm to optimize uncertain parameters in various PEMFC stack references.
- Defining the optimization objective function as the sum of squared errors (SSE) between actual and predicted voltage data.
- Comparative analysis of QUATRE-EMS against state-of-the-art differential evolution variants (LSHADE, MadDE, CS-DE, etc.) using statistical metrics.
Main Results:
- QUATRE-EMS achieved a significantly lower average SSE of 0.078492, outperforming existing algorithms by 15%.
- The algorithm demonstrated up to 20% improvement in accuracy, with the lowest average absolute error, relative error, and mean bias error.
- QUATRE-EMS exhibited superior computational efficiency, reducing runtime by 50% compared to other methods.
Conclusions:
- The QUATRE-EMS algorithm is highly effective and practical for optimizing PEMFC stack parameters.
- This method significantly enhances the accuracy of predicting performance for diverse PEMFC stack references (e.g., BCS500W, NedStackPS6, SR12).
- QUATRE-EMS offers a computationally efficient solution for improving PEMFC modeling and application in power systems.
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