| Peer-Reviewed

Algorithm for Determining the Knock Resistance of Pipeline Natural Gases

Received: 15 July 2020     Accepted: 18 August 2020     Published: 3 September 2020
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Abstract

A next-generation algorithm to calculate the PKI methane number is reported. The algorithm is suitable for a wide range of fuel compositions encountered in natural gas pipelines, including admixture of hydrogen and carbon monoxide from renewable sources. Comparison with measurements of knock in a commercial engine shows that the algorithm allows sharp distinction between fuel compositions that do or do not cause engine knock under given operating conditions. Moreover, the algorithm presented here demonstrates superior performance as compared to the existing methods from MWM and AVL. The methane numbers calculated using the PKI MN algorithm for a wide range of fuel compositions are within the uncertainty of the experimental knock measurements. In contrast, methods that are currently used do not predict the knock behavior of the measured gas compositions reliably. A major benefit of the algorithm presented here is that it consists of a simple polynomial equation that can be easily integrated into real-time gas-quality sensing equipment to calculate the PKI MN for assessment of pipeline gas quality or into engine management systems to allow next-generation feed-forward, fuel-adaptive control. In contrast, the current methods such as AVL and MWM need dedicated (and for AVL, proprietary) solvers that iteratively calculate the methane number. Furthermore, given the experimentally verified reliability and ease of implementation of the PKI MN algorithm, we assert that it is an excellent, open-source candidate for international standards for specifying the knock resistance of gaseous fuels.

Published in International Journal of Energy and Power Engineering (Volume 9, Issue 4)
DOI 10.11648/j.ijepe.20200904.11
Page(s) 41-48
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Pipeline Gas, Natural Gas, Methane Number, Engine Knock, Algorithm

References
[1] J. B. Heywood., International Combustion Engine fundamentals, McGraw-Hill, 1989.
[2] M. Leiker, W. Cartelliere, H. Christoph, U. Pfeifer, M. Rankl,, “Evaluation of Anti-Knock Property of Gaseous Fuels by Means of the Methane Number and Its Practical Application”, ASME paper 72-DGP-4, April 1972.
[3] California Alternative Fuels for Motor Vehicle Regulations Appendix D: Methane Number and fuel composition, https://www.arb.ca.gov/regact/cng-lpg/appd.pdf
[4] Gary Choquette, “Analysis and estimation of stoichiometric air-fuel ratio and methane number for natural gas”, 23rd Gas Machinery Conference, Nashville, USA, October 5-8, 2014.
[5] G. W. Sorge, R. J. Kakoczki, and J. E. Peffer, “Method for determining knock resistance rating for non-commercial grade natural gas”, US Patent 6,061,637, May 9, 2000.
[6] R. T. Smith, G. W. Sorge, and J. R. Zurlo, “Systems and Methods for Engine Control Incorporating Fuel Properties”, European Patent EP 2 963 270 A1, 25th May 2015.
[7] EN16726: 2014 - Annex A.
[8] C. Rahmouni, G. Brecq, M. Tazerout, O. Le Corre, (2004) Knock rating of gaseous fuels in single cylinder spark ignition engine, Fuel 83 (3) 327-336.
[9] “Gas Methane Number Calculation MWM method”, April 2013 (documentation Euromot MWM tool).
[10] Methane number calculation of natural gas mixtures, http://mz.dgc.eu./
[11] http://www.cumminswestport.com/fuel-quality-calculator
[12] https://www.wartsila.com/products/marine-oil-gas/gas-solutions/methane-number-calculator
[13] https://www.dnvgl.com/oilgas/natural-gas/fitness-for-purpose-of-lng-pki-methane-number-calculator.html
[14] https://www.dnvgl.com/oilgas/natural-gas/fitness-for-purpose-for-pipeline-gas.html
[15] GasCalc Software, http://www.eon.com/en/business-areas/technical-sercices/gascalc-software.html
[16] EUROMOT position paper, “Methane number as a parameter for gas quality specifications”, 2012.
[17] Callahan, T. J., Ryan III, T. W., Buckingham, J. P., Kakockzi, R. J. and Sorge, G., ICE-Vol. 27-4, 1996, Fall Technical Conference Vol. 4, pp. 59-64, ASME.
[18] Gersen, S., Essen, M., Levinsky, H., and Dijk, G., "Characterizing Gaseous Fuels for Their Knock Resistance based on the Chemical and Physical Properties of the Fuel," SAE Int. J. Fuels Lubr. 9 (1): 1-13, 2016, doi: 10.4271/2015-01-9077.
[19] G. van Dijk, M. van Essen and S. Gersen, “A Feed-Forward Fuel-Adaptive Gas Engine Control Approach Based on a Knock-Prediction Algorithm”, 17th Conference „The Working Process of the Internal Combustion Engine“, Graz, Austria, September 26-27, 2019.
[20] K. Portin and D. Högberg, “Gas Online Quality Measurement for Optimized Engine Control”, CIMAC, paper no. 109, 2019.
[21] Martijn Van Essen, Sander Gersen, Gerco Van Dijk, Maurice Van Erp, En Howard Levinsky. Algorithm for Determining the Knock Resistance of LNG. International Journal of Energy and Power Engineering. Vol. 8, No. 2, 2019, pp. 18-27. doi: 10.11648/j.ijepe.20190802.12.
[22] S. Gersen, M. van Essen, H. Darmeveil, H. Hashemi, C. T. Rasmussen, J. M. Christensen and P. Glarborg, “Experimental and Modeling Investigation of the Effect of H2S Addition to Methane on the Ignition and Oxidation at High Pressure”, Energy Fuels 2017, 31, 2175−2182, DOI: 10.1021/acs.energyfuels.6b02140.
[23] Essen, M., Gersen, S., Dijk, G., Mundt, T. et al., "The Effect of Humidity on the Knock Behavior in a Medium BMEP Lean-Burn High-Speed Gas Engine," SAE Int. J. Fuels Lubr. 9 (3): 2016, doi: 10.4271/2016-01-9075.
[24] Martijn van Essen, Sander Gersen, Gerco van Dijk, Liming Dai, Howard Levinsky, Peter van Wesenbeeck, “The knock propensity of CO2 containing natural gases”, SAE paper, to be submitted.
Cite This Article
  • APA Style

    Sander Gersen, Martijn van Essen, Gerco van Dijk, Howard Levinsky. (2020). Algorithm for Determining the Knock Resistance of Pipeline Natural Gases. International Journal of Energy and Power Engineering, 9(4), 41-48. https://doi.org/10.11648/j.ijepe.20200904.11

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    ACS Style

    Sander Gersen; Martijn van Essen; Gerco van Dijk; Howard Levinsky. Algorithm for Determining the Knock Resistance of Pipeline Natural Gases. Int. J. Energy Power Eng. 2020, 9(4), 41-48. doi: 10.11648/j.ijepe.20200904.11

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    AMA Style

    Sander Gersen, Martijn van Essen, Gerco van Dijk, Howard Levinsky. Algorithm for Determining the Knock Resistance of Pipeline Natural Gases. Int J Energy Power Eng. 2020;9(4):41-48. doi: 10.11648/j.ijepe.20200904.11

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  • @article{10.11648/j.ijepe.20200904.11,
      author = {Sander Gersen and Martijn van Essen and Gerco van Dijk and Howard Levinsky},
      title = {Algorithm for Determining the Knock Resistance of Pipeline Natural Gases},
      journal = {International Journal of Energy and Power Engineering},
      volume = {9},
      number = {4},
      pages = {41-48},
      doi = {10.11648/j.ijepe.20200904.11},
      url = {https://doi.org/10.11648/j.ijepe.20200904.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20200904.11},
      abstract = {A next-generation algorithm to calculate the PKI methane number is reported. The algorithm is suitable for a wide range of fuel compositions encountered in natural gas pipelines, including admixture of hydrogen and carbon monoxide from renewable sources. Comparison with measurements of knock in a commercial engine shows that the algorithm allows sharp distinction between fuel compositions that do or do not cause engine knock under given operating conditions. Moreover, the algorithm presented here demonstrates superior performance as compared to the existing methods from MWM and AVL. The methane numbers calculated using the PKI MN algorithm for a wide range of fuel compositions are within the uncertainty of the experimental knock measurements. In contrast, methods that are currently used do not predict the knock behavior of the measured gas compositions reliably. A major benefit of the algorithm presented here is that it consists of a simple polynomial equation that can be easily integrated into real-time gas-quality sensing equipment to calculate the PKI MN for assessment of pipeline gas quality or into engine management systems to allow next-generation feed-forward, fuel-adaptive control. In contrast, the current methods such as AVL and MWM need dedicated (and for AVL, proprietary) solvers that iteratively calculate the methane number. Furthermore, given the experimentally verified reliability and ease of implementation of the PKI MN algorithm, we assert that it is an excellent, open-source candidate for international standards for specifying the knock resistance of gaseous fuels.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Algorithm for Determining the Knock Resistance of Pipeline Natural Gases
    AU  - Sander Gersen
    AU  - Martijn van Essen
    AU  - Gerco van Dijk
    AU  - Howard Levinsky
    Y1  - 2020/09/03
    PY  - 2020
    N1  - https://doi.org/10.11648/j.ijepe.20200904.11
    DO  - 10.11648/j.ijepe.20200904.11
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 41
    EP  - 48
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20200904.11
    AB  - A next-generation algorithm to calculate the PKI methane number is reported. The algorithm is suitable for a wide range of fuel compositions encountered in natural gas pipelines, including admixture of hydrogen and carbon monoxide from renewable sources. Comparison with measurements of knock in a commercial engine shows that the algorithm allows sharp distinction between fuel compositions that do or do not cause engine knock under given operating conditions. Moreover, the algorithm presented here demonstrates superior performance as compared to the existing methods from MWM and AVL. The methane numbers calculated using the PKI MN algorithm for a wide range of fuel compositions are within the uncertainty of the experimental knock measurements. In contrast, methods that are currently used do not predict the knock behavior of the measured gas compositions reliably. A major benefit of the algorithm presented here is that it consists of a simple polynomial equation that can be easily integrated into real-time gas-quality sensing equipment to calculate the PKI MN for assessment of pipeline gas quality or into engine management systems to allow next-generation feed-forward, fuel-adaptive control. In contrast, the current methods such as AVL and MWM need dedicated (and for AVL, proprietary) solvers that iteratively calculate the methane number. Furthermore, given the experimentally verified reliability and ease of implementation of the PKI MN algorithm, we assert that it is an excellent, open-source candidate for international standards for specifying the knock resistance of gaseous fuels.
    VL  - 9
    IS  - 4
    ER  - 

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Author Information
  • DNV-GL Oil & Gas, Groningen, The Netherlands

  • DNV-GL Oil & Gas, Groningen, The Netherlands

  • DNV-GL Oil & Gas, Groningen, The Netherlands

  • DNV-GL Oil & Gas, Groningen, The Netherlands

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