Öz
Due to continuous increase of energy consumption in personal and business life, the battery industry, the emergence of more advanced technologies are needed. In this respect, for a battery user, expected to be a priority, the energy needed, the duration of time needed to provide. However accurate and precise knowledge of the state-ofcharge is one of the most important components of a battery management system. In this study, estimation of battery state of charge parameter using genetic expression programming is investigated. To estimate the state-of-charge, which is the most important component of battery management system, estimation methods and battery models in the literature are summarized. In the simulation, the variables of battery current, battery terminal voltage and the time are assigned as inputs. With this process, new specific state-of-charge data and are mathematical discharge equations are obtained for each Lithium-Ion, battery types. Hence, it is intended to reach an accurate and precise state-of-charge estimation due to battery types.
Anahtar Kelimeler
State of Charge SOC Genetic Programming Genetic Expression Programming Genetic Algorithm
Kaynakça
- Casacca, M.A., Salameh, Z.M., 1992, Determination of lead–acid battery capacity via mathematical modeling techniques, IEEE Trans. Energy Conv., 7, 3, 442–446.
- Kutluay, K., Çadırcı, Y., Özkazanç Y. and Çadırcı I., 2005, A new online state-of-charge estimation and monitoring system for sealed lead–acid batteries in telecommunication power supplies, IEEE Trans. Industrial Electronics, 52, 5, 131513
- Chiasson J. and Vairamohan, B., 2005, Estimating the state of charge of a battery, IEEE Trans. Control Systems Technology, 13, 3, 465–470.
- Bhangu, B.S., Bently, P., Stone, D.A. and Bingham, C.M., 2005, Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles, IEEE Trans Vehicular Technol, 54,3, 783-794.
- Barbarisi, O.,Vasca, F. and Glielmo, L., 2006, State of charge Kalman filter estimator for automotive batteries, Control Engineering Practice, 14, 267-275.
- Santhanagopalan, S., White, R.E., 2006, Online estimation of the state of charge of a lithium ion cell, J. Power Sources, 161, 1346–1355.
- Avgın, MS, 2012, Batarya Şarj Doluluk Durumu Model Parametresinin GEP ile Tahmin Edilmesi, KSÜ. Fen Bil. Ens., Elektrik Elektronik Mühendisliği ABD, Yüksek Lisans Tezi, 87 s.
- Dell, R.M., Rand D.J. , 2001, Understanding Batteries, Royal Society of Chemisty, UK.
- Linden, D., 1995, Handbook of Batteries, McGraw-Hill, New-York.
- Sauer, D. U., Karden, E, Fricke B., Holger Blanke, Marc Thele,Oliver Bohlen, Julia Schiffer, Jochen Bernhard Gerschler, Rudi Kaiser, ―Charging performance of automotive batteries—An underestimated factor influencing lifetime and reliable battery operation‖ Journal of Power Sources Vol.168 22–30,(2007).
- Salameh, Z.M., Casacca, M.A. and Lynch, W.A., 1992, A mathematical model for lead-acid batteries, IEEE Trans. Energy Conversion, 7, 93–
- Schweighofer, B., Raab, K.M., and Brasseur, G., 200 Modelling of highpower automotive batteries by the use of an automated test system.IEEE Transactions on Instrumentation and Measurement, 52, 1087-1091.
- Ferreira, C., Gene Expression Programming in Problem Solving, WSC6 Tutorial, 2001.
- Ferreira, C., Analyzıng The Founder Effect In Sımulated Evolutionary Processes Using Gene Expression Programming, Soft Computing Systems: Design, Management And Applications, 153-163, IOS Pres, Netherlands, 2002
Öz
Artış gösteren kişisel ve iş yaşamındaki enerji tüketimine bağlı olarak, batarya sektöründe daha gelişmiş teknolojilerin ortaya çıkmasına ihtiyaç duyulmaktadır. Bu noktada öncelikli olarak bir bataryadan beklenen, ihtiyaç duyulan enerjiyi, ihtiyaç duyulan zaman süresince sağlamasıdır. Bunun yanında şarj doluluk durumu bilgisinin doğru ve kesin olarak bilinmesi de batarya yönetim sisteminin en önemli unsurlarından biridir. Bu çalışmada, lityum-ion (Li-Ion) akü yönetim sisteminin en önemli unsurlarından birisi olan batarya doluluk durumunu için genetik ifade programlama algoritması ile kestirimi incelenmiştir. Kestirim çalışmasında giriş değerleri olarak atanan batarya akımı, batarya çıkış voltajı ve zaman değişkenleri ile çıkış değeri olarak batarya türlerine özel şarj doluluk durumu verileri elde edilmiştir. Lityum-İon aküler için matematiksel deşarj denklemleri oluşturulmuş ve böylece pil türüne özel deşarj bilgileriyle daha doğru ve kesin SOC tahmini yapılabilmesi amaçlanmıştır.
Anahtar Kelimeler
Şarj Doluluk Durumu SOC Genetik Programlama Genetik İfade Programlama Genetik Algoritma.
Kaynakça
- Casacca, M.A., Salameh, Z.M., 1992, Determination of lead–acid battery capacity via mathematical modeling techniques, IEEE Trans. Energy Conv., 7, 3, 442–446.
- Kutluay, K., Çadırcı, Y., Özkazanç Y. and Çadırcı I., 2005, A new online state-of-charge estimation and monitoring system for sealed lead–acid batteries in telecommunication power supplies, IEEE Trans. Industrial Electronics, 52, 5, 131513
- Chiasson J. and Vairamohan, B., 2005, Estimating the state of charge of a battery, IEEE Trans. Control Systems Technology, 13, 3, 465–470.
- Bhangu, B.S., Bently, P., Stone, D.A. and Bingham, C.M., 2005, Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles, IEEE Trans Vehicular Technol, 54,3, 783-794.
- Barbarisi, O.,Vasca, F. and Glielmo, L., 2006, State of charge Kalman filter estimator for automotive batteries, Control Engineering Practice, 14, 267-275.
- Santhanagopalan, S., White, R.E., 2006, Online estimation of the state of charge of a lithium ion cell, J. Power Sources, 161, 1346–1355.
- Avgın, MS, 2012, Batarya Şarj Doluluk Durumu Model Parametresinin GEP ile Tahmin Edilmesi, KSÜ. Fen Bil. Ens., Elektrik Elektronik Mühendisliği ABD, Yüksek Lisans Tezi, 87 s.
- Dell, R.M., Rand D.J. , 2001, Understanding Batteries, Royal Society of Chemisty, UK.
- Linden, D., 1995, Handbook of Batteries, McGraw-Hill, New-York.
- Sauer, D. U., Karden, E, Fricke B., Holger Blanke, Marc Thele,Oliver Bohlen, Julia Schiffer, Jochen Bernhard Gerschler, Rudi Kaiser, ―Charging performance of automotive batteries—An underestimated factor influencing lifetime and reliable battery operation‖ Journal of Power Sources Vol.168 22–30,(2007).
- Salameh, Z.M., Casacca, M.A. and Lynch, W.A., 1992, A mathematical model for lead-acid batteries, IEEE Trans. Energy Conversion, 7, 93–
- Schweighofer, B., Raab, K.M., and Brasseur, G., 200 Modelling of highpower automotive batteries by the use of an automated test system.IEEE Transactions on Instrumentation and Measurement, 52, 1087-1091.
- Ferreira, C., Gene Expression Programming in Problem Solving, WSC6 Tutorial, 2001.
- Ferreira, C., Analyzıng The Founder Effect In Sımulated Evolutionary Processes Using Gene Expression Programming, Soft Computing Systems: Design, Management And Applications, 153-163, IOS Pres, Netherlands, 2002
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Mühendislik |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 25 Ekim 2014 |
| Gönderilme Tarihi | 28 Mart 2014 |
| Yayımlandığı Sayı | Yıl 2014Cilt: 17 Sayı: 1 |