IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v156y2015icp149-158.html
   My bibliography  Save this article

Combustion-response mapping procedure for internal-combustion engine emissions

Author

Listed:
  • Korakianitis, T.
  • Imran, S.
  • Chung, N.
  • Ali, Hassan
  • Emberson, D.R.
  • Crookes, R.J.

Abstract

This paper describes a new method to predict emissions in internal combustion (IC) engines. The method couples a multi-dimensional engine modeling program with pre-integrated non-equilibrium chemical kinetics reaction results. Prior to engine simulation, detailed chemical kinetics reactions of air/fuel mixture at different temperatures, pressures, and compositions, are calculated using SENKIN, a subprogram in the CHEMKIN-II computer package. The reaction results are decoupled from their chemical eigenvalue (order of about 10-10s), then integrated and saved in physical time scale (order of about 10-5s) in a database file. In the database reaction results of different initial conditions (temperature, pressure, and species composition) are stored in different zones; the zones are indexed using their respective reaction conditions. Fluid dynamics and thermal dynamics of the movement of piston and valves, and spray droplets interaction are simulated by KIVA-3V. Instead of calculating directly the non-equilibrium chemical reactions of the air/fuel mixture, reaction results are obtained from the database file via an interpolating subroutine, which returns temperature, heat release, and species concentrations after reaction to the main program. The approach avoids direct time consuming calculation of detailed chemical reactions as well as the errors introduced by coupling the physical and chemical processes. Emissions are predicted accurately since reaction of air/fuel mixture is calculated using the detailed chemical kinetics mechanism. The approach is applied to model a Caterpillar 3401 direct injection compression ignition (CI) diesel engine. In addition we carried out experimental tests on a Toledo 1500 SI gasoline engine, and those results are compared with the proposed computational approach. In all cases the predicted results agree well with the experimental data.

Suggested Citation

  • Korakianitis, T. & Imran, S. & Chung, N. & Ali, Hassan & Emberson, D.R. & Crookes, R.J., 2015. "Combustion-response mapping procedure for internal-combustion engine emissions," Applied Energy, Elsevier, vol. 156(C), pages 149-158.
  • Handle: RePEc:eee:appene:v:156:y:2015:i:c:p:149-158
    DOI: 10.1016/j.apenergy.2015.06.039
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915007977
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.06.039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Prasad, B.V.V.S.U. & Sharma, C.S. & Anand, T.N.C. & Ravikrishna, R.V., 2011. "High swirl-inducing piston bowls in small diesel engines for emission reduction," Applied Energy, Elsevier, vol. 88(7), pages 2355-2367, July.
    2. D'Errico, G. & Cerri, T. & Pertusi, G., 2011. "Multi-objective optimization of internal combustion engine by means of 1D fluid-dynamic models," Applied Energy, Elsevier, vol. 88(3), pages 767-777, March.
    3. Kegl, Breda, 2011. "Influence of biodiesel on engine combustion and emission characteristics," Applied Energy, Elsevier, vol. 88(5), pages 1803-1812, May.
    4. Payri, F. & Olmeda, P. & Martín, J. & García, A., 2011. "A complete 0D thermodynamic predictive model for direct injection diesel engines," Applied Energy, Elsevier, vol. 88(12), pages 4632-4641.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Payri, Francisco & Olmeda, Pablo & Arnau, Francisco J. & Dombrovsky, Artem & Smith, Les, 2014. "External heat losses in small turbochargers: Model and experiments," Energy, Elsevier, vol. 71(C), pages 534-546.
    2. Payri, F. & Olmeda, P. & Martín, J. & García, A., 2011. "A complete 0D thermodynamic predictive model for direct injection diesel engines," Applied Energy, Elsevier, vol. 88(12), pages 4632-4641.
    3. Khan, Shahanwaz & Panua, Rajsekhar & Bose, Probir Kumar, 2019. "The impact of combustion chamber configuration on combustion and emissions of a single cylinder diesel engine fuelled with soybean methyl ester blends with diesel," Renewable Energy, Elsevier, vol. 143(C), pages 335-351.
    4. Benajes, Jesús & Olmeda, Pablo & Martín, Jaime & Blanco-Cavero, Diego & Warey, Alok, 2017. "Evaluation of swirl effect on the Global Energy Balance of a HSDI Diesel engine," Energy, Elsevier, vol. 122(C), pages 168-181.
    5. Doppalapudi, A.T. & Azad, A.K. & Khan, M.M.K., 2021. "Combustion chamber modifications to improve diesel engine performance and reduce emissions: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    6. Varatharajan, K. & Cheralathan, M., 2012. "Influence of fuel properties and composition on NOx emissions from biodiesel powered diesel engines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3702-3710.
    7. Richard Fiifi Turkson & Fuwu Yan & Mohamed Kamal Ahmed Ali & Bo Liu & Jie Hu, 2016. "Modeling and Multi-Objective Optimization of Engine Performance and Hydrocarbon Emissions via the Use of a Computer Aided Engineering Code and the NSGA-II Genetic Algorithm," Sustainability, MDPI, vol. 8(1), pages 1-15, January.
    8. Mofid, Hossein & Jazayeri-Rad, Hooshang & Shahbazian, Mehdi & Fetanat, Abdolvahhab, 2019. "Enhancing the performance of a parallel nitrogen expansion liquefaction process (NELP) using the multi-objective particle swarm optimization (MOPSO) algorithm," Energy, Elsevier, vol. 172(C), pages 286-303.
    9. Serrano, J. & Jiménez-Espadafor, F.J. & López, A., 2019. "Analysis of the effect of the hydrogen as main fuel on the performance of a modified compression ignition engine with water injection," Energy, Elsevier, vol. 173(C), pages 911-925.
    10. Theotokatos, Gerasimos & Guan, Cong & Chen, Hui & Lazakis, Iraklis, 2018. "Development of an extended mean value engine model for predicting the marine two-stroke engine operation at varying settings," Energy, Elsevier, vol. 143(C), pages 533-545.
    11. Serrano, J. & Jiménez-Espadafor, F.J. & Lora, A. & Modesto-López, L. & Gañán-Calvo, A. & López-Serrano, J., 2019. "Experimental analysis of NOx reduction through water addition and comparison with exhaust gas recycling," Energy, Elsevier, vol. 168(C), pages 737-752.
    12. Channappagoudra, Manjunath & Ramesh, K. & Manavendra, G., 2019. "Comparative study of standard engine and modified engine with different piston bowl geometries operated with B20 fuel blend," Renewable Energy, Elsevier, vol. 133(C), pages 216-232.
    13. José Javier López & Oscar A. de la Garza & Joaquín De la Morena & Simón Martínez-Martínez, 2021. "Influence of Cavitation in Common-Rail Diesel Nozzles on the Soot Formation Process through Measuring Soot Emissions," Energies, MDPI, vol. 14(19), pages 1-11, October.
    14. Edward Roper & Yaodong Wang & Zhichao Zhang, 2022. "Numerical Investigation of the Application of Miller Cycle and Low-Carbon Fuels to Increase Diesel Engine Efficiency and Reduce Emissions," Energies, MDPI, vol. 15(5), pages 1-20, February.
    15. Soudagar, Manzoore Elahi M. & Mujtaba, M.A. & Safaei, Mohammad Reza & Afzal, Asif & V, Dhana Raju & Ahmed, Waqar & Banapurmath, N.R. & Hossain, Nazia & Bashir, Shahid & Badruddin, Irfan Anjum & Goodar, 2021. "Effect of Sr@ZnO nanoparticles and Ricinus communis biodiesel-diesel fuel blends on modified CRDI diesel engine characteristics," Energy, Elsevier, vol. 215(PA).
    16. Torregrosa, A.J. & Broatch, A. & García, A. & Mónico, L.F., 2013. "Sensitivity of combustion noise and NOx and soot emissions to pilot injection in PCCI Diesel engines," Applied Energy, Elsevier, vol. 104(C), pages 149-157.
    17. Benajes, J. & Martín, J. & Novella, R. & Thein, K., 2016. "Understanding the performance of the multiple injection gasoline partially premixed combustion concept implemented in a 2-Stroke high speed direct injection compression ignition engine," Applied Energy, Elsevier, vol. 161(C), pages 465-475.
    18. Kumar, R. Sathish & Sivakumar, S. & Joshuva, A. & Deenadayalan, G. & Vishnuvardhan, R., 2021. "Bio-fuel production from Martynia annua L. seeds using slow pyrolysis reactor and its effects on diesel engine performance, combustion and emission characteristics," Energy, Elsevier, vol. 217(C).
    19. Zhang, Qiang & Ogren, Ryan M. & Kong, Song-Charng, 2016. "A comparative study of biodiesel engine performance optimization using enhanced hybrid PSO–GA and basic GA," Applied Energy, Elsevier, vol. 165(C), pages 676-684.
    20. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:156:y:2015:i:c:p:149-158. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.