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A control-oriented real-time semi-empirical model for the prediction of NOx emissions in diesel engines

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  • d’Ambrosio, Stefano
  • Finesso, Roberto
  • Fu, Lezhong
  • Mittica, Antonio
  • Spessa, Ezio

Abstract

The present work describes the development of a fast control-oriented semi-empirical model that is capable of predicting NOx emissions in diesel engines under steady state and transient conditions. The model takes into account the maximum in-cylinder burned gas temperature of the main injection, the ambient gas-to-fuel ratio, the mass of injected fuel, the engine speed and the injection pressure. The evaluation of the temperature of the burned gas is based on a three-zone real-time diagnostic thermodynamic model that has recently been developed by the authors.

Suggested Citation

  • d’Ambrosio, Stefano & Finesso, Roberto & Fu, Lezhong & Mittica, Antonio & Spessa, Ezio, 2014. "A control-oriented real-time semi-empirical model for the prediction of NOx emissions in diesel engines," Applied Energy, Elsevier, vol. 130(C), pages 265-279.
    • Handle: RePEc:eee:appene:v:130:y:2014:i:c:p:265-279
    DOI: 10.1016/j.apenergy.2014.05.046
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    References listed on IDEAS

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    1. Roy, Sumit & Banerjee, Rahul & Bose, Probir Kumar, 2014. "Performance and exhaust emissions prediction of a CRDI assisted single cylinder diesel engine coupled with EGR using artificial neural network," Applied Energy, Elsevier, vol. 119(C), pages 330-340.
    2. Beatrice, Carlo & Napolitano, Pierpaolo & Guido, Chiara, 2014. "Injection parameter optimization by DoE of a light-duty diesel engine fed by Bio-ethanol/RME/diesel blend," Applied Energy, Elsevier, vol. 113(C), pages 373-384.
    3. Asprion, Jonas & Chinellato, Oscar & Guzzella, Lino, 2013. "A fast and accurate physics-based model for the NOx emissions of Diesel engines," Applied Energy, Elsevier, vol. 103(C), pages 221-233.
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    Cited by:

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    2. Stefano d’Ambrosio & Alessandro Ferrari & Alessandro Mancarella & Salvatore Mancò & Antonio Mittica, 2019. "Comparison of the Emissions, Noise, and Fuel Consumption Comparison of Direct and Indirect Piezoelectric and Solenoid Injectors in a Low-Compression-Ratio Diesel Engine," Energies, MDPI, vol. 12(21), pages 1-16, October.
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    5. Roberto Finesso & Gilles Hardy & Claudio Maino & Omar Marello & Ezio Spessa, 2017. "A New Control-Oriented Semi-Empirical Approach to Predict Engine-Out NOx Emissions in a Euro VI 3.0 L Diesel Engine," Energies, MDPI, vol. 10(12), pages 1-26, November.
    6. Srivastava, Vivek & Schaub, Joschka & Pischinger, Stefan, 2023. "Model-based closed-loop control strategies for flex-fuel capability," Applied Energy, Elsevier, vol. 350(C).
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    10. Bolan Liu & Xiaowei Ai & Pan Liu & Chuang Zhang & Xingqi Hu & Tianpu Dong, 2015. "Fuel Economy Improvement of a Heavy-Duty Powertrain by Using Hardware-in-Loop Simulation and Calibration," Energies, MDPI, vol. 8(9), pages 1-14, September.
    11. Aleksandra Banasiewicz & Paweł Śliwiński & Pavlo Krot & Jacek Wodecki & Radosław Zimroz, 2023. "Prediction of NOx Emission Based on Data of LHD On-Board Monitoring System in a Deep Underground Mine," Energies, MDPI, vol. 16(5), pages 1-16, February.
    12. Di Battista, D. & Cipollone, R., 2016. "Experimental and numerical assessment of methods to reduce warm up time of engine lubricant oil," Applied Energy, Elsevier, vol. 162(C), pages 570-580.
    13. Alessandro Falai & Daniela Anna Misul, 2023. "Data-Driven Model for Real-Time Estimation of NOx in a Heavy-Duty Diesel Engine," Energies, MDPI, vol. 16(5), pages 1-17, February.
    14. Liu, Yintong & Li, Liguang & Ye, Junyu & Wu, Zhijun & Deng, Jun, 2015. "Numerical simulation study on correlation between ion current signal and NOX emissions in controlled auto-ignition engine," Applied Energy, Elsevier, vol. 156(C), pages 776-782.
    15. Kumar, Madan & Tsujimura, Taku & Suzuki, Yasumasa, 2018. "NOx model development and validation with diesel and hydrogen/diesel dual-fuel system on diesel engine," Energy, Elsevier, vol. 145(C), pages 496-506.
    16. Seungha Lee & Youngbok Lee & Gyujin Kim & Kyoungdoug Min, 2017. "Development of a Real-Time Virtual Nitric Oxide Sensor for Light-Duty Diesel Engines," Energies, MDPI, vol. 10(3), pages 1-21, March.

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