Journals / Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi / 2019 / Cilt: 12 Sayı: 3

The Design of Autonomous Thermal Management System For An Internal Combustion Engine Using Fractional Order PID Controller

Kesir Dereceli PID Denetleyici Kullanarak İçten Yanmalı Motorlarda Otonom Termal Yönetim Sistemi Tasarımı

Ali Rıza Kaleli(SAMSUN ÜNİVERSİTESİ)0000-0002-3234-5922
Pages
1640–1650
Publication Date
2019-12-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In the steady state operating conditions, engine output temperature tracking error is 0,0248 and the tracking error is obtained 2.108 ℃, in variable temperature conditions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the fractional order PID type controller is designed an independent cooling system for internal combustion engines.
📊
Key Findings & Data:Nonlinear optimization technique is used to determine the controller parameters in the proposed strategy.
💡
Conclusion & Impact:In the steady state operating conditions, engine output temperature tracking error is 0,0248 and the tracking error is obtained 2.108 ℃, in variable temperature conditions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:içten yanmalı motorlar · termal yönetim sistemi · kesir dereceli PID

Abstract

In this study, the fractional order PID type controller is designed an independent cooling system for internal combustion engines. Nonlinear optimization technique is used to determine the controller parameters in the proposed strategy. The system is named as autonomous engine cooling system and it provides a superior performance in terms of optimal thermal management compared to conventional systems. Fistly, the mathematical model of engine thermal system is derived. Next, in order to adjust cooling system electromechanical components, the proposed control strategy is tested both steady and transient engine operating conditions. In the steady state operating conditions, engine output temperature tracking error is 0,0248 and the tracking error is obtained 2.108 ℃, in variable temperature conditions.

Özet

Bu çalışmada, kesir dereceli PID (FOPID) tipi kontrolcülerin içten yanmalı motorlarda bağımsız soğutma sistemi için tasarımı gerçekleştirilmiştir. Önerilen kontrol stratejisinde kontrolcü parametrelerinin belirlenmesinde doğrusal olamayan optimizasyon tekniği kullanılmıştır. Otonom motor soğutma şeklinde isimlendirilen bu sistem, geleneksel sisteme göre optimal ısı yönetimi bakımından üstün bir performans sağlar. Tasarımda öncelikle soğutma sisteminin matematiksel modeli elde edilmiştir. Sonrasında soğutma sistemi bileşenleri için önerilen kontrol stratejisi hem sabit ve hem de geçici motor çalışma koşulları için test edilmiştir. Sabit çalışma koşullarında kontolcü sayesinde motor çıkış sıcaklığını izeleme hatası 0,0248 ve değişken koşullarda ise sıcaklık izleme hatası ise 2,108 elde edilmiştir.

🔖

Cite This Article

Kaleli, A. R. (2019). The Design of Autonomous Thermal Management System For An Internal Combustion Engine Using Fractional Order PID Controller. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Cilt: 12 Sayı: 3, 1640–1650. https://doi.org/10.18185/erzifbed.644767

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (27)

  1. Allen, D. J., & Lasecki, M. P. (2001). Thermal Management Evolution and Controlled Coolant Flow. https://doi.org/10.4271/2001-01-1732
  2. Bequette, B. W. (2019, September 2). Process control practice and education: Past, present and future. Computers and Chemical Engineering, Vol. 128, pp. 538–556. https://doi.org/10.1016/j.compchemeng.2019.06.011
  3. Boudjehem, B., & Boudjehem, D. (2013). Fractional order controller design for desired response. Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering. https://doi.org/10.1177/0959651812456647
  4. Büche, D., Stoll, P., Dornberger, R., & Koumoutsakos, P. (2002). Multiobjective evolutionary algorithm for the optimization of noisy combustion processes. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 32(4), 460–473. https://doi.org/10.1109/TSMCB.2002.804372
  5. Castiglione, T., Pizzonia, F., & Bova, S. (2016). A Novel Cooling System Control Strategy for Internal Combustion Engines. https://doi.org/10.4271/2016-01-0226
  6. Chiara, F., & Canova, M. (2013). A review of energy consumption, management, and recovery in automotive systems, with considerations of future trends. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 227(6), 914–936. https://doi.org/10.1177/0954407012471294
  7. Choi, K.-W., Kim, K.-B., & Lee, K.-H. (2009). Effect of New Cooling System in a Diesel Engine on Engine Performance and Emission Characteristics. SAE International Journal of Engines, 2(1), 77–82. https://doi.org/10.4271/2009-01-0177
  8. Dumlu, A., & Ayten, K. K. (2018). Bir Otonom Elektrikli Tekerlekli Sandalyenin Hesaplamalı Tork Kontrol Yöntemiyle Yörünge Kontrolünün Gerçekleştirilmesi. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi. https://doi.org/10.18185/erzifbed.382359
  9. Eberth, J. F., Wagner, J. R., Afshar, B. A., & Foster, R. C. (2004). Modeling and Validation of Automotive “Smart” Thermal Management System Architectures. https://doi.org/10.4271/2004-01-0048
  10. Fleming, P. J., & Purshouse, R. C. (2002). Evolutionary algorithms in control systems engineering: A survey. Control Engineering Practice, 10(11), 1223–1241. https://doi.org/10.1016/S0967-0661(02)00081-3
  11. Hakariya, M., Toda, T., & Sakai, M. (2017). The New Toyota Inline 4-Cylinder 2.5L Gasoline Engine. https://doi.org/10.4271/2017-01-1021
  12. Jafari, S., Dunne, J. F., Langari, M., Yang, Z., Pirault, J.-P., Long, C. A., & Thalackottore Jose, J. (2016). A review of evaporative cooling system concepts for engine thermal management in motor vehicles. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 231(8), 1126–1143. https://doi.org/10.1177/0954407016674606
  13. Jander, B. S., & Baar, R. (2017). Modeling Thermal Engine Behavior Using Artificial Neural Network. https://doi.org/10.4271/2017-01-0534
  14. John, H. (1988). Internal combustion engine fundamentals. McGraw-Hill Science.
  15. Li, H., & Chen, Y. (2008). A fractional order proportional and derivative (FOPD) controller tuning algorithm. 2008 Chinese Control and Decision Conference, 4059–4063. IEEE.
  16. Özdemir, M. T., Öztürk, D., Eke, I., Çelik, V., & Lee, K. Y. (2015). Tuning of Optimal Classical and Fractional Order PID Parameters for Automatic Generation Control Based on the Bacterial Swarm Optimization. IFAC-PapersOnLine, 48(30), 501–506. https://doi.org/10.1016/j.ifacol.2015.12.429
  17. Pang, H. H., & Brace, C. J. (2004). Review of engine cooling technologies for modern engines. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 218(11), 1209–1215. https://doi.org/10.1243/0954407042580110
  18. Podlubny, I. (1999). Fractional-order systems and PIλDμ-controllers. IEEE Transactions on Automatic Control. https://doi.org/10.1109/9.739144
  19. Postalcıoğlu, S., & Köktürk, Ç. (2019). Bilgisayar Destekli DC Motor Hız Denetimi. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi. https://doi.org/10.18185/erzifbed.510259
  20. Shah, P., & Agashe, S. (2016). Review of fractional PID controller. Mechatronics. https://doi.org/10.1016/j.mechatronics.2016.06.005
  21. Sheng, W., & Bao, Y. (2013). Fruit fly optimization algorithm based fractional order fuzzy-PID controller for electronic throttle. Nonlinear Dynamics, 73(1–2), 611–619. https://doi.org/10.1007/s11071-013-0814-y
  22. Tao, X., & Wagner, J. R. (2016). An Engine Thermal Management System Design for Military Ground Vehicle - Simultaneous Fan, Pump and Valve Control. SAE International Journal of Passenger Cars - Electronic and Electrical Systems. https://doi.org/10.4271/2016-01-0310
  23. Tepljakov, A., Petlenkov, E., Belikov, J., & Finajev, J. (2013). Fractional-order controller design and digital implementation using FOMCON toolbox for MATLAB. 2013 IEEE Conference on Computer Aided Control System Design (CACSD), 340–345. IEEE.
  24. Wang, T., & Wagner, J. R. (2015). A Smart Engine Cooling System - Experimental Study of Integrated Actuator Transient Behavior. https://doi.org/10.4271/2015-01-1604
  25. Will, F., & Boretti, A. (2011). A New Method to Warm Up Lubricating Oil to Improve the Fuel Efficiency During Cold Start. SAE International Journal of Engines, 4(1), 175–187. https://doi.org/10.4271/2011-01-0318
  26. Xu, Z., Zhang, Y., Di, H., & Shen, T. (2019). Combustion variation control strategy with thermal efficiency optimization for lean combustion in spark-ignition engines. Applied Energy. https://doi.org/10.1016/j.apenergy.2019.113329
  27. Zamani, M., Karimi-Ghartemani, M., Sadati, N., & Parniani, M. (2009). Design of a fractional order PID controller for an AVR using particle swarm optimization. Control Engineering Practice, 17(12), 1380–1387. https://doi.org/10.1016/j.conengprac.2009.07.005