Research Article
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Year 2021, Volume: 10 Issue: 3, 126 - 134, 09.11.2021
https://doi.org/10.18245/ijaet.824507

Abstract

Thanks

International Mediterranean Science and Engineering Congress (IMSEC 2020) komite üyelerine bu çalışmayı derginizde makale yayını olarak seçtikleri için teşekkür ederiz.

References

  • Tafreshi, R., Ebrahimi, B., Mohammadpour, J., Franchek, M.A., Grigoriadis, K. and Masudi, H., "Linear Dynamic Parameter-Varying Sliding Manifold for Air–Fuel Ratio Control in Lean-burn Engines", IET Control Theory & Applications, vol.7 issue 10, pp.1319-1329, 2013.
  • Wang, P., Zhu, C. and Gao, J., "Feedforward Model Predictive Control of Fuel-Air Ratio for Lean-burn Spark-Ignition Gasoline Engines of Passenger Cars", IEEE Access, vol.7, pp.73961-73969, 2019.
  • Kumar, M. and Shen, T., "In-cylinder Pressure-based Air-Fuel Ratio Control for Lean Burn Operation Mode of SI Engines", Energy, vol.120, pp.106-116, 2017.
  • Ebrahimi, B., Tafreshi, R., Masudi, H., Franchek, M., Mohammadpour, J. and Grigoriadis, K., "A Parameter-Varying Diltered PID Strategy for Air–Fuel Ratio Control of Spark Ignition Engines", Control Engineering Practice, vol.20 issue 8, pp.805-815, 2012.
  • Jiao, X., Zhang, J., Shen, T. and Kako, J., "Adaptive Air–Fuel Ratio Control Scheme and Its Experimental Validations for Port‐Injected Spark Ignition Engines", International Journal of Adaptive Control and Signal processing, vol.29, issue 1, pp.41-63, 2015.
  • Meng, L., Wang, X., Zeng, C. and Luo, J., "Adaptive Air-Fuel Ratio Regulation for Port-Injected Spark-Ignited Engines Based on a Generalized Predictive Control Method", Energies, vol.12 issue 1, pp.173, 2019.
  • Na, J., Chen, A.S., Huang, Y., Agarwal, A., Lewis, A., Herrmann, G., Burke, R. and Brace, C., "Air-Fuel Ratio Control of Spark Ignition Engines with Unknown System Dynamics Estimator: Theory and Experiments", IEEE Transactions on Control Systems Technology, vol. 99, pp.1-8. 2019.
  • Ebrahimi, B., Tafreshi, R., Mohammadpour, J., Franchek, M., Grigoriadis, K. and Masudi, H., "Second-order Sliding Mode Strategy for Air–Fuel Ratio Control of Lean-Burn SI Engines", IEEE Transactions on Control Systems Technology, vol.22, issue 4, pp.1374-1384, 2013.
  • Wu, H.M. and Tafreshi, R., "Fuzzy Sliding‐mode Strategy for Air–Fuel Ratio Control of Lean‐Burn Spark Ignition Engines", Asian Journal of Control, vol.20, issue 1, pp.149-158, 2018.
  • Zope, R.A., Mohammadpour, J., Grigoriadis, K.M. and Franchek, M., "Air-fuel ratio control of spark ignition engines with TWC using LPV techniques", In Dynamic Systems and Control Conference, vol. 48920, pp. 897-903, 2009.
  • Zope, R., Mohammadpour, J., Grigoriadis, K. and Franchek, M., "Robust fueling strategy for an SI engine modeled as an linear parameter varying time-delayed system", In Proceedings of the 2010 American Control Conference, IEEE, pp. 4634-4639, 2010.
  • Wu, H. M., & Tafreshi, R., "Air–fuel ratio control of lean-burn SI engines using the LPV-based fuzzy technique", IET Control Theory & Applications, vol.12, issue 10, pp.1414-1420, 2018.
  • Wati, D. A. R., & Hidayat, R., "Genetic algorithm-based PID parameters optimization for air heater temperature control", In 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems-IEEE, pp. 30-34, 2013.
  • Nagaraj, B., Subha, S., & Rampriya, B., "Tuning algorithms for PID controller using soft computing techniques", International Journal of Computer Science and Network Security, vol.8, issue 4, pp.278-281, 2008.
  • Wang, F., Chen, Z., & Song, G., "Monitoring of multi-bolt connection looseness using entropy-based active sensing and genetic algorithm-based least square support vector machine", Mechanical Systems and Signal Processing, vol.136, 106507, 2020.
  • Wen, Q., Liu, G., Wu, W., & Liao, S., "Genetic algorithm-based operation strategy optimization and multi-criteria evaluation of distributed energy system for commercial buildings", Energy Conversion and Management, vol. 226, 113529, 2020.
  • Qin, L., Huang, W., Du, Y., Zheng, L., & Jawed, M. K., "Genetic algorithm-based inverse design of elastic gridshells", Structural and Multidisciplinary Optimization, pp. 1-17, 2020.
  • Köse, E., Abaci, K., Kizmaz, H., Aksoy, S., and Yalçin, M. A., "Sliding mode control based on genetic algorithm for WSCC systems include of SVC", Elektronika ir Elektrotechnika, vol.19 issue 4, pp. 25-28, 2013.
  • Zhang, F., Grigoriadis, K. M., Franchek, M. A., & Makki, I. H., "Linear parameter-varying lean burn air-fuel ratio control for a spark ignition engine", Transactions of the ASME, vol. 129, pp. 404-414, 207.
  • Holland, J. H., "Adaptation in Natural and Artificial Systems", Mich. Univ. Press. Ann Arbor, MI, USA, 1975.
  • https://www.sciencemag.org/news/modern-humans-lost-dna-when-they-left-afri ca-mating-neandertals-brought-some-back, 10/2017
  • https://tr.pinterest.com/pin/706502260268183167/
  • https://www.worldwildlife.org/stories/an-end-to-great-barrier-reef-dumping-is-imminent/01/2015
  • https://www.helsinki.fi/en/researchgroups/population-genetics-and-biodiversity
  • https://becominghuman.ai/understanding-genetic-algorithms-a-use-case-in-organizational-field-2087c30fb61e/2/12/ 2017
  • https://evolution.berkeley.edu/evolibrary/article/0_0_0/mutations_04
  • https://courses.lumenlearning.com/boundless-biology/chapter/population-genetics/
  • Amin, A. A., & Mahmood-ul-Hasan, K., "Robust active fault-tolerant control for internal combustion gas engine for air–fuel ratio control with statistical regression-based observer model", Measurement and Control, vol. 52, pp. 1179-1194, 2019.

Lean-burn air-fuel ratio control using genetic algorithm-based PI controller

Year 2021, Volume: 10 Issue: 3, 126 - 134, 09.11.2021
https://doi.org/10.18245/ijaet.824507

Abstract

Maximizing the fuel economy while lowering exhaust emissions highly depend on precise air-fuel ratio (AFR) control. The major challenge in the control of AFR is the time-varying delay, which is an inherent reason for performance degradation and instability. For analysis, the time delay is approximated by Padé approximation, leading to a non-minimum phase system that exhibits the difficulty of controlling due to its zeroes in the right half side of the s-plane. Moreover, dealing with uncertainties in fuel-path dynamics and minimizing the effect of external disturbances are key goals in the minimization of harmful emissions and maximization of fuel economy. This study puts forward an AFR control strategy in lean-burn spark-ignition (SI) engines by proposing a genetic algorithm (GA)-based proportional-integral (PI) control technique. The proposed PI controller aims at dealing with the aforementioned design challenges. The PI controller gains, namely, proportional (K_p), integral (K_i) gains are obtained with the proposed GA algorithm based on minimization of an objective function. The GA-based PI controller’s performance is analyzed with several methods in time-domain study. According to the obtained results, it has been revealed that the proposed GA-based PI controller improves the reference air-fuel ratio tracking performance in the existence of the time-varying delays in the closed-loop system, exhibiting good disturbance rejection properties, and is robust against system uncertainties. Thus, it can be effectively used for the accurate regulation of AFR under various operating conditions in SI engines.

References

  • Tafreshi, R., Ebrahimi, B., Mohammadpour, J., Franchek, M.A., Grigoriadis, K. and Masudi, H., "Linear Dynamic Parameter-Varying Sliding Manifold for Air–Fuel Ratio Control in Lean-burn Engines", IET Control Theory & Applications, vol.7 issue 10, pp.1319-1329, 2013.
  • Wang, P., Zhu, C. and Gao, J., "Feedforward Model Predictive Control of Fuel-Air Ratio for Lean-burn Spark-Ignition Gasoline Engines of Passenger Cars", IEEE Access, vol.7, pp.73961-73969, 2019.
  • Kumar, M. and Shen, T., "In-cylinder Pressure-based Air-Fuel Ratio Control for Lean Burn Operation Mode of SI Engines", Energy, vol.120, pp.106-116, 2017.
  • Ebrahimi, B., Tafreshi, R., Masudi, H., Franchek, M., Mohammadpour, J. and Grigoriadis, K., "A Parameter-Varying Diltered PID Strategy for Air–Fuel Ratio Control of Spark Ignition Engines", Control Engineering Practice, vol.20 issue 8, pp.805-815, 2012.
  • Jiao, X., Zhang, J., Shen, T. and Kako, J., "Adaptive Air–Fuel Ratio Control Scheme and Its Experimental Validations for Port‐Injected Spark Ignition Engines", International Journal of Adaptive Control and Signal processing, vol.29, issue 1, pp.41-63, 2015.
  • Meng, L., Wang, X., Zeng, C. and Luo, J., "Adaptive Air-Fuel Ratio Regulation for Port-Injected Spark-Ignited Engines Based on a Generalized Predictive Control Method", Energies, vol.12 issue 1, pp.173, 2019.
  • Na, J., Chen, A.S., Huang, Y., Agarwal, A., Lewis, A., Herrmann, G., Burke, R. and Brace, C., "Air-Fuel Ratio Control of Spark Ignition Engines with Unknown System Dynamics Estimator: Theory and Experiments", IEEE Transactions on Control Systems Technology, vol. 99, pp.1-8. 2019.
  • Ebrahimi, B., Tafreshi, R., Mohammadpour, J., Franchek, M., Grigoriadis, K. and Masudi, H., "Second-order Sliding Mode Strategy for Air–Fuel Ratio Control of Lean-Burn SI Engines", IEEE Transactions on Control Systems Technology, vol.22, issue 4, pp.1374-1384, 2013.
  • Wu, H.M. and Tafreshi, R., "Fuzzy Sliding‐mode Strategy for Air–Fuel Ratio Control of Lean‐Burn Spark Ignition Engines", Asian Journal of Control, vol.20, issue 1, pp.149-158, 2018.
  • Zope, R.A., Mohammadpour, J., Grigoriadis, K.M. and Franchek, M., "Air-fuel ratio control of spark ignition engines with TWC using LPV techniques", In Dynamic Systems and Control Conference, vol. 48920, pp. 897-903, 2009.
  • Zope, R., Mohammadpour, J., Grigoriadis, K. and Franchek, M., "Robust fueling strategy for an SI engine modeled as an linear parameter varying time-delayed system", In Proceedings of the 2010 American Control Conference, IEEE, pp. 4634-4639, 2010.
  • Wu, H. M., & Tafreshi, R., "Air–fuel ratio control of lean-burn SI engines using the LPV-based fuzzy technique", IET Control Theory & Applications, vol.12, issue 10, pp.1414-1420, 2018.
  • Wati, D. A. R., & Hidayat, R., "Genetic algorithm-based PID parameters optimization for air heater temperature control", In 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems-IEEE, pp. 30-34, 2013.
  • Nagaraj, B., Subha, S., & Rampriya, B., "Tuning algorithms for PID controller using soft computing techniques", International Journal of Computer Science and Network Security, vol.8, issue 4, pp.278-281, 2008.
  • Wang, F., Chen, Z., & Song, G., "Monitoring of multi-bolt connection looseness using entropy-based active sensing and genetic algorithm-based least square support vector machine", Mechanical Systems and Signal Processing, vol.136, 106507, 2020.
  • Wen, Q., Liu, G., Wu, W., & Liao, S., "Genetic algorithm-based operation strategy optimization and multi-criteria evaluation of distributed energy system for commercial buildings", Energy Conversion and Management, vol. 226, 113529, 2020.
  • Qin, L., Huang, W., Du, Y., Zheng, L., & Jawed, M. K., "Genetic algorithm-based inverse design of elastic gridshells", Structural and Multidisciplinary Optimization, pp. 1-17, 2020.
  • Köse, E., Abaci, K., Kizmaz, H., Aksoy, S., and Yalçin, M. A., "Sliding mode control based on genetic algorithm for WSCC systems include of SVC", Elektronika ir Elektrotechnika, vol.19 issue 4, pp. 25-28, 2013.
  • Zhang, F., Grigoriadis, K. M., Franchek, M. A., & Makki, I. H., "Linear parameter-varying lean burn air-fuel ratio control for a spark ignition engine", Transactions of the ASME, vol. 129, pp. 404-414, 207.
  • Holland, J. H., "Adaptation in Natural and Artificial Systems", Mich. Univ. Press. Ann Arbor, MI, USA, 1975.
  • https://www.sciencemag.org/news/modern-humans-lost-dna-when-they-left-afri ca-mating-neandertals-brought-some-back, 10/2017
  • https://tr.pinterest.com/pin/706502260268183167/
  • https://www.worldwildlife.org/stories/an-end-to-great-barrier-reef-dumping-is-imminent/01/2015
  • https://www.helsinki.fi/en/researchgroups/population-genetics-and-biodiversity
  • https://becominghuman.ai/understanding-genetic-algorithms-a-use-case-in-organizational-field-2087c30fb61e/2/12/ 2017
  • https://evolution.berkeley.edu/evolibrary/article/0_0_0/mutations_04
  • https://courses.lumenlearning.com/boundless-biology/chapter/population-genetics/
  • Amin, A. A., & Mahmood-ul-Hasan, K., "Robust active fault-tolerant control for internal combustion gas engine for air–fuel ratio control with statistical regression-based observer model", Measurement and Control, vol. 52, pp. 1179-1194, 2019.
There are 28 citations in total.

Details

Primary Language English
Subjects Mechanical Engineering
Journal Section Article
Authors

Serdar Coşkun 0000-0002-7080-0340

Ercan Köse 0000-0001-9814-6339

Publication Date November 9, 2021
Submission Date November 11, 2020
Published in Issue Year 2021 Volume: 10 Issue: 3

Cite

APA Coşkun, S., & Köse, E. (2021). Lean-burn air-fuel ratio control using genetic algorithm-based PI controller. International Journal of Automotive Engineering and Technologies, 10(3), 126-134. https://doi.org/10.18245/ijaet.824507
AMA Coşkun S, Köse E. Lean-burn air-fuel ratio control using genetic algorithm-based PI controller. International Journal of Automotive Engineering and Technologies. November 2021;10(3):126-134. doi:10.18245/ijaet.824507
Chicago Coşkun, Serdar, and Ercan Köse. “Lean-Burn Air-Fuel Ratio Control Using Genetic Algorithm-Based PI Controller”. International Journal of Automotive Engineering and Technologies 10, no. 3 (November 2021): 126-34. https://doi.org/10.18245/ijaet.824507.
EndNote Coşkun S, Köse E (November 1, 2021) Lean-burn air-fuel ratio control using genetic algorithm-based PI controller. International Journal of Automotive Engineering and Technologies 10 3 126–134.
IEEE S. Coşkun and E. Köse, “Lean-burn air-fuel ratio control using genetic algorithm-based PI controller”, International Journal of Automotive Engineering and Technologies, vol. 10, no. 3, pp. 126–134, 2021, doi: 10.18245/ijaet.824507.
ISNAD Coşkun, Serdar - Köse, Ercan. “Lean-Burn Air-Fuel Ratio Control Using Genetic Algorithm-Based PI Controller”. International Journal of Automotive Engineering and Technologies 10/3 (November 2021), 126-134. https://doi.org/10.18245/ijaet.824507.
JAMA Coşkun S, Köse E. Lean-burn air-fuel ratio control using genetic algorithm-based PI controller. International Journal of Automotive Engineering and Technologies. 2021;10:126–134.
MLA Coşkun, Serdar and Ercan Köse. “Lean-Burn Air-Fuel Ratio Control Using Genetic Algorithm-Based PI Controller”. International Journal of Automotive Engineering and Technologies, vol. 10, no. 3, 2021, pp. 126-34, doi:10.18245/ijaet.824507.
Vancouver Coşkun S, Köse E. Lean-burn air-fuel ratio control using genetic algorithm-based PI controller. International Journal of Automotive Engineering and Technologies. 2021;10(3):126-34.