Using Limited-Memory Broyden-Fletcher-Goldfarb-Shanno and Emperor Penguin Algorithm to Minimize the Cell Voltage of Solid Oxide Fuel Cells

Ramiz İlker Tuna; Faruk Ayata; Ebubekir Seyyarer

Makale detayları

Using Limited-Memory Broyden-Fletcher-Goldfarb-Shanno and Emperor Penguin Algorithm to Minimize the Cell Voltage of Solid Oxide Fuel Cells

Yazarlar:

Ramiz İlker Tuna | Faruk Ayata | Ebubekir Seyyarer

Yayıncı:

Gazi University

Ana Başlıklar:

Mühendislik

Dergi:

Politeknik Dergisi Vol.28 Issue 1, pp.251-259

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001339483

pISSN:

2147-9429

Anahtar kelimeler:

Özet:

 Optimization methods are widely used in various industrial, scientific, and engineering applications to determine the most efficient planning strategy, determine the best distribution of a financial portfolio, design a logistics network in the most efficient way possible, or achieve the best performance of an artificial intelligence model. In this study, the aim is to minimize the cell voltage of solid oxide fuel cells to improve their performance and energy efficiency. In the optimization studies carried out with the L-BFGS-B algorithm and Emperor Penguin algorithm, the values of temperature T, oxygen pressure pO2, hydrogen pressure pH2, and water vapor pressure pH2O are calculated for minimum voltage while the input values of Faraday constant, Gas constant, Activation polarization coefficient, Reverse current density, and Electrode thickness are fixed. For both optimization methods, the optimum temperature value is calculated as 1000 K, the optimum oxygen pressure value as 1.0, the optimum hydrogen pressure value as 0.000001, and the optimum water vapor pressure value as 0.000001. The minimum cell voltage was calculated as 0.6486 for both optimization methods, but the L-BFGS-B algorithm reached the result in 6 iterations and 0.0046 seconds, while the Emperor Penguin algorithm reached it in 44 iterations and 0.01 seconds. According to the analysis results, although the cell voltage values of the two methods are the same, it can be seen that the L-BFGS-B algorithm is more successful in terms of iteration and time.

 Optimization methods are widely used in various industrial, scientific, and engineering applications to determine the most efficient planning strategy, determine the best distribution of a financial portfolio, design a logistics network in the most efficient way possible, or achieve the best performance of an artificial intelligence model. In this study, the aim is to minimize the cell voltage of solid oxide fuel cells to improve their performance and energy efficiency. In the optimization studies carried out with the L-BFGS-B algorithm and Emperor Penguin algorithm, the values of temperature T, oxygen pressure pO2, hydrogen pressure pH2, and water vapor pressure pH2O are calculated for minimum voltage while the input values of Faraday constant, Gas constant, Activation polarization coefficient, Reverse current density, and Electrode thickness are fixed. For both optimization methods, the optimum temperature value is calculated as 1000 K, the optimum oxygen pressure value as 1.0, the optimum hydrogen pressure value as 0.000001, and the optimum water vapor pressure value as 0.000001. The minimum cell voltage was calculated as 0.6486 for both optimization methods, but the L-BFGS-B algorithm reached the result in 6 iterations and 0.0046 seconds, while the Emperor Penguin algorithm reached it in 44 iterations and 0.01 seconds. According to the analysis results, although the cell voltage values of the two methods are the same, it can be seen that the L-BFGS-B algorithm is more successful in terms of iteration and time.

 Optimization methods are widely used in various industrial, scientific, and engineering applications to determine the most efficient planning strategy, determine the best distribution of a financial portfolio, design a logistics network in the most efficient way possible, or achieve the best performance of an artificial intelligence model. In this study, the aim is to minimize the cell voltage of solid oxide fuel cells to improve their performance and energy efficiency. In the optimization studies carried out with the L-BFGS-B algorithm and Emperor Penguin algorithm, the values of temperature T, oxygen pressure pO2, hydrogen pressure pH2, and water vapor pressure pH2O are calculated for minimum voltage while the input values of Faraday constant, Gas constant, Activation polarization coefficient, Reverse current density, and Electrode thickness are fixed. For both optimization methods, the optimum temperature value is calculated as 1000 K, the optimum oxygen pressure value as 1.0, the optimum hydrogen pressure value as 0.000001, and the optimum water vapor pressure value as 0.000001. The minimum cell voltage was calculated as 0.6486 for both optimization methods, but the L-BFGS-B algorithm reached the result in 6 iterations and 0.0046 seconds, while the Emperor Penguin algorithm reached it in 44 iterations and 0.01 seconds. According to the analysis results, although the cell voltage values of the two methods are the same, it can be seen that the L-BFGS-B algorithm is more successful in terms of iteration and time.

 Optimizasyon yöntemleri çeşitli endüstriyel, bilimsel ve mühendislik uygulamalarında, en verimli planlama stratejisi belirlemek, bir finansal portföyün en iyi dağılımını belirlemek, bir lojistik ağın en verimli şekilde tasarlanması veya bir yapay zekâ modelinin en iyi performansını elde etmek için yaygın olarak kullanılmaktadır. Bu çalışmada ise katı oksit yakıt pillerinin hücre gerilimini minimuma indirerek pillerin performansını arttırmak ve enerji verimliliğini iyileştirmek amaçlanmaktadır. Bu kapsamda L-BFGS-B algoritması ve İmparator Penguen algoritması ile yapılan optimizasyon çalışmalarında Faraday sabiti, Gaz sabiti, Aktivasyon polarizasyonu katsayısı, Ters akım yoğunluğu, Elektrot kalınlığı girdi değerler sabitlenerek sıcaklık T, oksijen basıncı pO2, hidrojen basıncı pH2 ve su buharı basıncı pH2Onın minimum gerilim için değerleri hesaplanmaktadır. İki optimizasyon yöntemi için de optimum sıcaklık değeri 1000 K, optimum oksijen basıncı değeri 1.0, optimum hidrojen basıncı değeri 0.000001 ve optimum su buharı basıncı değeri de 0.000001 olarak hesaplanmaktadır. İki optimizasyon yönteminde de minimum hücre gerilimi 0.6486 olarak hesaplanmış ancak L-BFGS-B algoritması sonuca 6 iterasyon ve 0.0046 saniye de ulaşmış; İmparator Penguen algoritması ise 44 iterasyon ve 0,01 saniye de ulaşmıştır. Analiz sonuçlarına göre iki yöntemin de hücre gerilim değerleri aynı olmasına rağmen iterasyon ve süre bakımından L-BFGS-B algoritmasının daha başarılı olduğu görülmektedir.

Makale detayları

Using Limited-Memory Broyden-Fletcher-Goldfarb-Shanno and Emperor Penguin Algorithm to Minimize the Cell Voltage of Solid Oxide Fuel Cells

Yazarlar:

Ramiz İlker Tuna | Faruk Ayata | Ebubekir Seyyarer

Yayıncı:

Gazi University

Ana Başlıklar:

Mühendislik

Dergi:

Politeknik Dergisi Vol.28 Issue 1, pp.251-259

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001339483

pISSN:

2147-9429

solid oxide fuel cells

cell voltage

L-BFGS-B

Emperor PenguinKatı oksit yakıt pilleri

Hücre gerilimi

L-BFGS-B

İmparator penguen

Sayı

Makale detayları

Yazarlar: Ramiz İlker Tuna | Faruk Ayata | Ebubekir Seyyarer

Yayıncı: Gazi University

Ana Başlıklar: Mühendislik

Dergi: Politeknik Dergisi Vol.28 Issue 1, pp.251-259

Belge Tipi: Makale

Yayın Tarihi: 1/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001339483

pISSN: 2147-9429

Sayı

Yazarlar:

Ramiz İlker Tuna | Faruk Ayata | Ebubekir Seyyarer

Yayıncı:

Gazi University

Ana Başlıklar:

Mühendislik

Dergi:

Politeknik Dergisi Vol.28 Issue 1, pp.251-259

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001339483

pISSN:

2147-9429