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A fuzzy logic map-based knock control for spark ignition engines

Author

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  • Pla, Benjamí n
  • Bares, Pau
  • Jiménez, Irina
  • Guardiola, Carlos
  • Zhang, Yahui
  • Shen, Tielong

Abstract

Knock control represents one of the most critical aspects to reach optimal thermal efficiency in spark ignition engines, and its research is crucially important because it determines thermal efficiency, engine durability, and power density, as well as noise and emission performance. In this paper, a spark advance control based on a map learning technique is combined with a knock estimator to maximize the engine efficiency while keeping the knock probability below a desired limit. The proposed controller is experimentally validated on a production spark ignition gasoline engine test bench, and compared with a conventional spark advance controller in both, steady and transient conditions. From experimental results, a benefit in terms of thermal efficiency, control stability and engine security are achieved. The results show that the proposed method is capable of regulating the knock probability to a target percentage with low spark advance and thermal efficiency dispersion than the conventional controller.

Suggested Citation

  • Pla, Benjamí n & Bares, Pau & Jiménez, Irina & Guardiola, Carlos & Zhang, Yahui & Shen, Tielong, 2020. "A fuzzy logic map-based knock control for spark ignition engines," Applied Energy, Elsevier, vol. 280(C).
  • Handle: RePEc:eee:appene:v:280:y:2020:i:c:s0306261920314719
    DOI: 10.1016/j.apenergy.2020.116036
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    References listed on IDEAS

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    1. Shen, Xun & Zhang, Yahui & Shen, Tielong & Khajorntraidet, Chanyut, 2017. "Spark advance self-optimization with knock probability threshold for lean-burn operation mode of SI engine," Energy, Elsevier, vol. 122(C), pages 1-10.
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    4. Zhen, Xudong & Wang, Yang & Xu, Shuaiqing & Zhu, Yongsheng & Tao, Chengjun & Xu, Tao & Song, Mingzhi, 2012. "The engine knock analysis – An overview," Applied Energy, Elsevier, vol. 92(C), pages 628-636.
    5. Guardiola, C. & Pla, B. & Bares, P. & Barbier, A., 2018. "An analysis of the in-cylinder pressure resonance excitation in internal combustion engines," Applied Energy, Elsevier, vol. 228(C), pages 1272-1279.
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    Cited by:

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    2. Christian Farinango-Herrera & Joshebet Zambrano-Ramón & Edgar Vicente Rojas-Reinoso, 2024. "Thermographic Analysis of Exhaust Gas and Emissions by Varying Catalyst Behaviour and Injection Parameters," Energies, MDPI, vol. 17(6), pages 1-28, March.
    3. Danail D. Stratiev & Angel Dimitriev & Dicho Stratiev & Krassimir Atanassov, 2023. "Modeling the Production Process of Fuel Gas, LPG, Propylene, and Polypropylene in a Petroleum Refinery Using Generalized Nets," Mathematics, MDPI, vol. 11(17), pages 1-17, September.
    4. Cao, Jiale & Li, Tie & Huang, Shuai & Chen, Run & Li, Shiyan & Kuang, Min & Yang, Rundai & Huang, Yating, 2023. "Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning," Applied Energy, Elsevier, vol. 352(C).

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