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Otomobil Koltuklarını Isıtmak İçin Yeniden Tasarlanan Standart Otomobil Klima Sisteminin Performansının Bulanık Mantık ile Modellenmesi

Year 2017, Volume: 5 Issue: 3, 82 - 94, 01.10.2017
https://doi.org/10.21541/apjes.335093

Abstract

Bu çalışma, deneysel bir çalışmadan elde edilen
veriler kullanılarak taşıt koltuklarının ısıtılması için değiştirilen bir taşıt
kliması sisteminin performansının bulanık mantık modelini sunar. Deneyler
sırasında 500 dev/dak değerinden 1600 dev/dak değerine kadar 100 dev/dak
aralıklarla değişen kompresör devirlerine karşılık koltuk oturak ve sırt
sıcaklıkları 15 dakika boyunca kaydedilmiştir. Bulanık mantık yönteminde, giriş
parametreleri kompresör devri ve zaman olarak seçilmişken çıkış parametreleri
olarak koltuk sırt ve oturak sıcaklıkları seçilmiştir. Bulanıklaştırma işlemi
için on iki hız seviyesi ve on zaman seviyesi belirlenmiştir. Çıkış için yedi
sırt sıcaklığı ve on bir oturak sıcaklığı seçilmiştir. Sistemin giriş ve
çıkışının ilişkisini tanımlayan toplamda 120 gözetim kuralı saptanmıştır.
Toplamda 4320 sırt ve oturak sıcaklık verisi ayrıca bulanık mantık ile
bulunmuştur. Bulanık mantık ve deneysel sonuçların birbirleri ile
karşılaştırılmasında "determinasyon katsayısı" kullanılmıştır.
Deneysel çalışmanın ara değerleri bulanık mantık modeli ile de tahmin
ettirilmiştir. Canlı denekten koltuğa gerçekleşen ısı transferi nedeniyle ısıl
süreç içerisinde koltuk yüzeylerindeki azami sıcaklık değeri 5inci ve 10uncu
dakikalar arasında gerçekleşmiştir. En yüksek sıcaklık değerleri 1600 dev/dak
değerinde elde edilirken en düşük sıcaklık değerleri 500 dev/dak değerinde elde
edilmiştir. Deneysel veriler ile model sonuçları arasındaki korelasyon tatmin
edicidir. Sonuç olarak bulanık mantık taşıt ısıl konfor sistemlerinde hızlı
karar alma için uygun bir araç olarak bulunmuştur. Model gelecekte bir akıllı
araç klima sistemine adapte edilmek için değiştirilebilir. İlk de
fa sunulan bu
deneysel veriler ile Bulanık Mantık uygulama sonuçları gelecek çalışmalar için
referans teşkil etmektedir.

References

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  • [2] B. Hamed, and F. Alami, “Adaptive Hierarchical Fuzzy controller for HVAC Systems in Low Energy Buildings” APJES, vol. 3, no 2, pp. 01-07, 2015
  • [3] S. Akıncıoğlu, F. Mendi, A. Çiçek, and G. Akıncıoğlu, “Prediction Of Thrust Forces And Hole Diameters Using Artificial Neural Networks In Drilling Of AISI D2 Tool Steel With Cemented Carbide Tools”, APJES, vol. 1, no2, pp. 11-20, 2013
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  • [14] M. Kılıç, and S.M. Akyol, “Experimental Investigation Of Thermal Comfort And Air Quality In An Automobile Cabin During The Cooling Period”, Heat and Mass Transfer, vol. 48, no 8, pp. 1375-1384, August 2012
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  • [16] M. Kilic, and O. Kaynakli, “An Experimental Investigation On Interior Thermal Conditions And Human Body Temperatures During Cooling Period In Automobile” Heat and Mass Transfer, vol. 47, no 4, pp. 407–418, April 2011
  • [17] İ. Atmaca, and A. Yiğit, “Predicting the effect of relative humidity on skin temperature and skin wettedness”, Journal Of Thermal Biology, vol. 31, no 5, pp. 442-452, July 2006
  • [18] T.G. Cengiz, and F.C. Babalık, “An On-The-Road Experiment Into The Thermal Comfort Of Car Seats”, Applied Ergonomics, vol. 38, no 3, pp. 337-347, May 2007
  • [19] F.C. Babalık, and T.G. Cengiz, “Comfort Investigation By Measurements At Seat Driver Contact Points For Acclimated Seats” 11. Ulusal Ergonomi Congress, İstanbul, Turkey, 2004.
  • [20] Ö. Kaynaklı, and R. Yamankaradeniz, “Simulation Of Thermal Comfort Conditions By Instant Energy Balance Model", Fırat Üniversitesi Fen ve Müh. Bil. Dergisi, vol. 15, no 4, pp. 601-612, 2003
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  • [22] Z. Yılmaz, and Ş. Ocak, “Determination of Anemia via Fuzzy Logic”, 1.Mühendislik ve Teknoloji Symposium, Ankara, Turkey, 2008.
  • [23] Y.Ş. Murat, and N. Uludağ, “Route Choice Modelling In Urban Transportation Networks Using Fuzzy Logic And Logistic Regression Methods” JSIR, vol. 67, no 1, pp. 19-27, January 2008

Modeling of Performance of a Standard Vehicle Air Conditioning System Re-Designed for Heating Vehicle Seats via Fuzzy Logic

Year 2017, Volume: 5 Issue: 3, 82 - 94, 01.10.2017
https://doi.org/10.21541/apjes.335093

Abstract

Fuzzy Logic model of a vehicle seat heating
system was constituted by using data obtained from a previous experimental work
of ours. A standard vehicle air conditioning system was modified in order to
pump heat to the surfaces of a vehicle seat. Collected data were used to
constitute the fuzzy logic model and test it. In the Fuzzy Logic method, input
parameters were selected as compressor speed (rpm) and time (s) while output
parameters were back and seating surface temperatures (oC) of the
vehicle seat. Back and seating temperatures were recorded for 15 minutes for
compressor speeds ranging from 500 rpm to 1600 rpm with 100 rpm intervals. Twelve
levels of revolution and ten levels of time were selected and determined for
the fuzzyfication process. As output fuzzy levels seven back temperature levels
and eleven seat temperature levels were determined. Totally 120 supervision
rules that define relation between system input and output and detect behaviors
of fuzzy logic supervision were determined. Data that were measured at every 5
seconds for 12 different rotation speed speeds which yield totally 4320 points
for back and seating surfaces were also found by Fuzzy Logic. Determination
coefficient was used for the comparison of experimental and fuzzy logic results.
Additionally surface temperatures were estimated with fuzzy logic for
intermediate values of the experimental study. As a conclusion, fuzzy logic is
found a proper tool for rapid decision making in vehicle thermal comfort systems.

References

  • [1] M. Mupit, and A.A. Shafie, “Experimental Study of Automated Car Power Window with Preset Position”, APJES, vol. 3, no 1, pp. 21-28, 2015
  • [2] B. Hamed, and F. Alami, “Adaptive Hierarchical Fuzzy controller for HVAC Systems in Low Energy Buildings” APJES, vol. 3, no 2, pp. 01-07, 2015
  • [3] S. Akıncıoğlu, F. Mendi, A. Çiçek, and G. Akıncıoğlu, “Prediction Of Thrust Forces And Hole Diameters Using Artificial Neural Networks In Drilling Of AISI D2 Tool Steel With Cemented Carbide Tools”, APJES, vol. 1, no2, pp. 11-20, 2013
  • [4] A. Guler, M.E. Berberler, and U.G. Nuriyev, “A New Genetic Algorithm for the 0-1 Knapsack Problem”, APJES, vol. 4, no 3, pp. 09-14, 2016
  • [5] S. Öztürk, C. Karakuzu, M. Kuncan, and A. Erdil, “Fuzzy Neural Network Controller As A Real Time Controller Using Pso”, APJES, vol. 5, no 1, pp. 15-22, 2017
  • [6] T.E. Kalaycı, “Construction And Implementation Of X3d Framework For Three Dimensional Graphics Software Using Artificial Intelligence Techniques”, MSc Thesis, Ege Üniversitesi, İzmir, Turkey, 2006.
  • [7] Ç. Elmas, “Artificial Intelligence Applications”, Seçkin Yayıncılık Publication, Ankara, Turkey, 2011.
  • [8] Ö. Hasgül, and A.S. Anagün, “Artificial Neural Network Usage In Analysis Of Experimental Results And An Application For Concrete Duration Test”, V. Ulusal Üretim Araştırmaları Symposium, İstanbul, Turkey, 2005.
  • [9] Ş. Ünal, T. Yımaz, E. Cihan, and O. Büyükalaca, “Coefficient of Performance Variation with the Mass Flow Rate for the Ejector Cooling System”. Çukurova Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 28, no 1, pp. 61-76, 2013.
  • [10] Ö. Solmaz, “Investigation of dynamic performance of a vehicle air-conditioning system driven by solar energy (PV)” Ph.D thesis, Selcuk University, Konya, Turkey, 2013.
  • [11] D. Erzurumlu, “Efficiency of air-conditioning system used in agricultural tractors on tractor performance and specific fuel comsumption”, MSc Thesis, Çukurova Üniversitesi, Adana, Turkey, 2010.
  • [12] A. Alkan, and M. Hosoz, “Experimental Performance Of An Automobile Air Conditioning System Using A Variable Capacity Compressor For Two Different Types Of Expansion Devices”, International Journal of Vehicle Design, vol. 52, no 1-4, pp. 160-176
  • [13] K. Öngel, and H. Mergen, , “Review of literature about the effects of thermal comfort parameters on human body”, Medical Journal of Suleyman Demirel University, vol. 16, no 1, pp. 21-25, 2009
  • [14] M. Kılıç, and S.M. Akyol, “Experimental Investigation Of Thermal Comfort And Air Quality In An Automobile Cabin During The Cooling Period”, Heat and Mass Transfer, vol. 48, no 8, pp. 1375-1384, August 2012
  • [15] Yiğit A, Atmaca İ. “Investigation of experimental change andcomparison with empirical results”. TTMD VIII. Uluslararası Yapıda Tesisat Teknolojisi Sempozyumu, İstanbul, Turkey, 12-14 May 2008.
  • [16] M. Kilic, and O. Kaynakli, “An Experimental Investigation On Interior Thermal Conditions And Human Body Temperatures During Cooling Period In Automobile” Heat and Mass Transfer, vol. 47, no 4, pp. 407–418, April 2011
  • [17] İ. Atmaca, and A. Yiğit, “Predicting the effect of relative humidity on skin temperature and skin wettedness”, Journal Of Thermal Biology, vol. 31, no 5, pp. 442-452, July 2006
  • [18] T.G. Cengiz, and F.C. Babalık, “An On-The-Road Experiment Into The Thermal Comfort Of Car Seats”, Applied Ergonomics, vol. 38, no 3, pp. 337-347, May 2007
  • [19] F.C. Babalık, and T.G. Cengiz, “Comfort Investigation By Measurements At Seat Driver Contact Points For Acclimated Seats” 11. Ulusal Ergonomi Congress, İstanbul, Turkey, 2004.
  • [20] Ö. Kaynaklı, and R. Yamankaradeniz, “Simulation Of Thermal Comfort Conditions By Instant Energy Balance Model", Fırat Üniversitesi Fen ve Müh. Bil. Dergisi, vol. 15, no 4, pp. 601-612, 2003
  • [21] M. Tektaş, “Preparation Of Education Simulators Of Web Based Artificial Intelligence Techniques”, Marmara Üniversitesi BAP Komisyonu Başkanlığı Proje Raporu, İstanbul, Türkiye, pp. 76-90, 2010
  • [22] Z. Yılmaz, and Ş. Ocak, “Determination of Anemia via Fuzzy Logic”, 1.Mühendislik ve Teknoloji Symposium, Ankara, Turkey, 2008.
  • [23] Y.Ş. Murat, and N. Uludağ, “Route Choice Modelling In Urban Transportation Networks Using Fuzzy Logic And Logistic Regression Methods” JSIR, vol. 67, no 1, pp. 19-27, January 2008
There are 23 citations in total.

Details

Subjects Engineering
Journal Section Articles
Authors

Ali Ateş

Kevser Dinçer

Eyüb Canlı

Sadık Ata

Publication Date October 1, 2017
Submission Date August 17, 2017
Published in Issue Year 2017 Volume: 5 Issue: 3

Cite

IEEE A. Ateş, K. Dinçer, E. Canlı, and S. Ata, “Modeling of Performance of a Standard Vehicle Air Conditioning System Re-Designed for Heating Vehicle Seats via Fuzzy Logic”, APJES, vol. 5, no. 3, pp. 82–94, 2017, doi: 10.21541/apjes.335093.