IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v165y2016icp676-684.html
   My bibliography  Save this article

A comparative study of biodiesel engine performance optimization using enhanced hybrid PSO–GA and basic GA

Author

Listed:
  • Zhang, Qiang
  • Ogren, Ryan M.
  • Kong, Song-Charng

Abstract

Efficient optimization algorithms are critical to the development of new engine technology. In this study, experimental investigations were carried out on optimizing the performance of a four-cylinder, turbocharged, direct-injection diesel engine running with soy biodiesel. An effective hybrid particle swarm optimization (PSO) and genetic algorithm (GA) method using a small population was developed and tested to optimize five operating parameters, including EGR rate, pilot timing, pilot ratio, main injection timing, and injection pressure. Based on the measured engine performance and emissions, results show that the new hybrid algorithm can significantly speed up the optimization process and achieve a superior optimum as compared to the basic GA method. The new hybrid PSO–GA method is expected to perform as an effective tool for rapid engine performance optimization.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:165:y:2016:i:c:p:676-684
    DOI: 10.1016/j.apenergy.2015.12.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915016177
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.12.044?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. Wei, Zhongbao & Li, Xiaolu & Xu, Lijun & Cheng, Yanting, 2013. "Comparative study of computational intelligence approaches for NOx reduction of coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 683-692.
    2. Wong, Ka In & Wong, Pak Kin & Cheung, Chun Shun & Vong, Chi Man, 2013. "Modeling and optimization of biodiesel engine performance using advanced machine learning methods," Energy, Elsevier, vol. 55(C), pages 519-528.
    3. Molina, S. & Guardiola, C. & Martín, J. & García-Sarmiento, D., 2014. "Development of a control-oriented model to optimise fuel consumption and NOX emissions in a DI Diesel engine," Applied Energy, Elsevier, vol. 119(C), pages 405-416.
    4. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2014. "Self-adaptable hierarchical clustering analysis and differential evolution for optimal integration of renewable distributed generation," Applied Energy, Elsevier, vol. 133(C), pages 388-402.
    5. 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.
    6. Ganesan, T. & Elamvazuthi, I. & Ku Shaari, Ku Zilati & Vasant, P., 2013. "Swarm intelligence and gravitational search algorithm for multi-objective optimization of synthesis gas production," Applied Energy, Elsevier, vol. 103(C), pages 368-374.
    7. Lešnik, Luka & Vajda, Blaž & Žunič, Zoran & Škerget, Leopold & Kegl, Breda, 2013. "The influence of biodiesel fuel on injection characteristics, diesel engine performance, and emission formation," Applied Energy, Elsevier, vol. 111(C), pages 558-570.
    8. Suh, Hyun Kyu, 2011. "Investigations of multiple injection strategies for the improvement of combustion and exhaust emissions characteristics in a low compression ratio (CR) engine," Applied Energy, Elsevier, vol. 88(12), pages 5013-5019.
    9. Donateo, Teresa & Tornese, Federica & Laforgia, Domenico, 2013. "Computer-aided conversion of an engine from diesel to methane," Applied Energy, Elsevier, vol. 108(C), pages 8-23.
    10. Asad, Usman & Kumar, Raj & Zheng, Ming & Tjong, Jimi, 2015. "Ethanol-fueled low temperature combustion: A pathway to clean and efficient diesel engine cycles," Applied Energy, Elsevier, vol. 157(C), pages 838-850.
    11. Gonca, Guven & Sahin, Bahri & Parlak, Adnan & Ust, Yasin & Ayhan, Vezir & Cesur, İdris & Boru, Barış, 2015. "Theoretical and experimental investigation of the Miller cycle diesel engine in terms of performance and emission parameters," Applied Energy, Elsevier, vol. 138(C), pages 11-20.
    12. Li, Y.G. & Pilidis, P., 2010. "GA-based design-point performance adaptation and its comparison with ICM-based approach," Applied Energy, Elsevier, vol. 87(1), pages 340-348, January.
    13. Yang, Jun & He, Lifu & Fu, Siyao, 2014. "An improved PSO-based charging strategy of electric vehicles in electrical distribution grid," Applied Energy, Elsevier, vol. 128(C), pages 82-92.
    14. Varuvel, Edwin Geo & Mrad, Nadia & Tazerout, Mohand & Aloui, Fethi, 2012. "Experimental analysis of biofuel as an alternative fuel for diesel engines," Applied Energy, Elsevier, vol. 94(C), pages 224-231.
    15. Basu, M., 2014. "Fuel constrained economic emission dispatch using nondominated sorting genetic algorithm-II," Energy, Elsevier, vol. 78(C), pages 649-664.
    16. Tompkins, B.T. & Song, H. & Bittle, J.A. & Jacobs, T.J., 2012. "Efficiency considerations for the use of blended biofuel in diesel engines," Applied Energy, Elsevier, vol. 98(C), pages 209-218.
    17. Molina, S. & García, A. & Pastor, J.M. & Belarte, E. & Balloul, I., 2015. "Operating range extension of RCCI combustion concept from low to full load in a heavy-duty engine," Applied Energy, Elsevier, vol. 143(C), pages 211-227.
    18. Tesfa, B. & Mishra, R. & Zhang, C. & Gu, F. & Ball, A.D., 2013. "Combustion and performance characteristics of CI (compression ignition) engine running with biodiesel," Energy, Elsevier, vol. 51(C), pages 101-115.
    19. Labecki, L. & Cairns, A. & Xia, J. & Megaritis, A. & Zhao, H. & Ganippa, L.C., 2012. "Combustion and emission of rapeseed oil blends in diesel engine," Applied Energy, Elsevier, vol. 95(C), pages 139-146.
    20. Martinez-Rojas, Marcela & Sumper, Andreas & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search," Applied Energy, Elsevier, vol. 88(12), pages 4678-4686.
    21. Roy, Murari Mohon & Wang, Wilson & Bujold, Justin, 2013. "Biodiesel production and comparison of emissions of a DI diesel engine fueled by biodiesel–diesel and canola oil–diesel blends at high idling operations," Applied Energy, Elsevier, vol. 106(C), pages 198-208.
    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. Alejos Altamirano, Carlos Alberto & Yokoyama, Lídia & de Medeiros, José Luiz & de Queiroz Fernandes Araújo, Ofélia, 2016. "Ethylic or methylic route to soybean biodiesel? Tracking environmental answers through life cycle assessment," Applied Energy, Elsevier, vol. 184(C), pages 1246-1263.
    2. Bendu, Harisankar & Deepak, B.B.V.L. & Murugan, S., 2017. "Multi-objective optimization of ethanol fuelled HCCI engine performance using hybrid GRNN–PSO," Applied Energy, Elsevier, vol. 187(C), pages 601-611.
    3. Lotfan, S. & Ghiasi, R. Akbarpour & Fallah, M. & Sadeghi, M.H., 2016. "ANN-based modeling and reducing dual-fuel engine’s challenging emissions by multi-objective evolutionary algorithm NSGA-II," Applied Energy, Elsevier, vol. 175(C), pages 91-99.
    4. Shyang-Chyuan Fang & Bwo-Ren Ke & Chen-Yuan Chung, 2017. "Minimization of Construction Costs for an All Battery-Swapping Electric-Bus Transportation System: Comparison with an All Plug-In System," Energies, MDPI, vol. 10(7), pages 1-20, June.
    5. Wang, Xi & Henshaw, Paul & Ting, David S.-K., 2021. "Exergoeconomic analysis for a thermoelectric generator using mutation particle swarm optimization (M-PSO)," Applied Energy, Elsevier, vol. 294(C).
    6. Krishnamoorthi, M. & Malayalamurthi, R., 2018. "Engine characteristics analysis of chaulmoogra oil blends and corrosion analysis of injector nozzle using scanning electron microscopy/energy dispersive spectroscopy," Energy, Elsevier, vol. 165(PB), pages 1292-1319.
    7. Sultana, U. & Khairuddin, Azhar B. & Sultana, Beenish & Rasheed, Nadia & Qazi, Sajid Hussain & Malik, Nimra Riaz, 2018. "Placement and sizing of multiple distributed generation and battery swapping stations using grasshopper optimizer algorithm," Energy, Elsevier, vol. 165(PA), pages 408-421.
    8. Manh-Hai Pham & T-A-Tho Vu & Duc-Quang Nguyen & Viet-Hung Dang & Ngoc-Trung Nguyen & Thu-Huyen Dang & The Vinh Nguyen, 2019. "Study on Selecting the Optimal Algorithm and the Effective Methodology to ANN-Based Short-Term Load Forecasting Model for the Southern Power Company in Vietnam," Energies, MDPI, vol. 12(12), pages 1-19, June.
    9. Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.

    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. Tan, Pi-qiang & Ruan, Shuai-shuai & Hu, Zhi-yuan & Lou, Di-ming & Li, Hu, 2014. "Particle number emissions from a light-duty diesel engine with biodiesel fuels under transient-state operating conditions," Applied Energy, Elsevier, vol. 113(C), pages 22-31.
    2. Aldhaidhawi, Mohanad & Chiriac, Radu & Badescu, Viorel, 2017. "Ignition delay, combustion and emission characteristics of Diesel engine fueled with rapeseed biodiesel – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 178-186.
    3. Tauzia, Xavier & Maiboom, Alain & Karaky, Hassan, 2017. "Semi-physical models to assess the influence of CI engine calibration parameters on NOx and soot emissions," Applied Energy, Elsevier, vol. 208(C), pages 1505-1518.
    4. Tamilselvan, P. & Nallusamy, N. & Rajkumar, S., 2017. "A comprehensive review on performance, combustion and emission characteristics of biodiesel fuelled diesel engines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1134-1159.
    5. Wang, Yifeng & Yao, Mingfa & Li, Tie & Zhang, Weijing & Zheng, Zunqing, 2016. "A parametric study for enabling reactivity controlled compression ignition (RCCI) operation in diesel engines at various engine loads," Applied Energy, Elsevier, vol. 175(C), pages 389-402.
    6. Pachiannan, Tamilselvan & Zhong, Wenjun & Rajkumar, Sundararajan & He, Zhixia & Leng, Xianying & Wang, Qian, 2019. "A literature review of fuel effects on performance and emission characteristics of low-temperature combustion strategies," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    7. Zareh, Parvaneh & Zare, Ali Asghar & Ghobadian, Barat, 2017. "Comparative assessment of performance and emission characteristics of castor, coconut and waste cooking based biodiesel as fuel in a diesel engine," Energy, Elsevier, vol. 139(C), pages 883-894.
    8. Daho, Tizane & Vaitilingom, Gilles & Ouiminga, Salifou K. & Piriou, Bruno & Zongo, Augustin S. & Ouoba, Samuel & Koulidiati, Jean, 2013. "Influence of engine load and fuel droplet size on performance of a CI engine fueled with cottonseed oil and its blends with diesel fuel," Applied Energy, Elsevier, vol. 111(C), pages 1046-1053.
    9. Eko Supriyanto & Jayan Sentanuhady & Ariyana Dwiputra & Ari Permana & Muhammad Akhsin Muflikhun, 2021. "The Recent Progress of Natural Sources and Manufacturing Process of Biodiesel: A Review," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
    10. Rami Y. Dahham & Haiqiao Wei & Jiaying Pan, 2022. "Improving Thermal Efficiency of Internal Combustion Engines: Recent Progress and Remaining Challenges," Energies, MDPI, vol. 15(17), pages 1-60, August.
    11. Tripathi, Shweta & Subramanian, K.A., 2017. "Experimental investigation of utilization of Soya soap stock based acid oil biodiesel in an automotive compression ignition engine," Applied Energy, Elsevier, vol. 198(C), pages 332-346.
    12. Yu, Xunzhao & Zhu, Ling & Wang, Yan & Filev, Dimitar & Yao, Xin, 2022. "Internal combustion engine calibration using optimization algorithms," Applied Energy, Elsevier, vol. 305(C).
    13. Khandal, S.V. & Banapurmath, N.R. & Gaitonde, V.N. & Hiremath, S.S., 2017. "Paradigm shift from mechanical direct injection diesel engines to advanced injection strategies of diesel homogeneous charge compression ignition (HCCI) engines- A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 369-384.
    14. Can, Özer & Öztürk, Erkan & Yücesu, H. Serdar, 2017. "Combustion and exhaust emissions of canola biodiesel blends in a single cylinder DI diesel engine," Renewable Energy, Elsevier, vol. 109(C), pages 73-82.
    15. Bendu, Harisankar & Deepak, B.B.V.L. & Murugan, S., 2017. "Multi-objective optimization of ethanol fuelled HCCI engine performance using hybrid GRNN–PSO," Applied Energy, Elsevier, vol. 187(C), pages 601-611.
    16. Serrano, J.R. & Climent, H. & Piqueras, P. & Angiolini, E., 2014. "Analysis of fluid-dynamic guidelines in diesel particulate filter sizing for fuel consumption reduction in post-turbo and pre-turbo placement," Applied Energy, Elsevier, vol. 132(C), pages 507-523.
    17. Gonca, Guven & Dobrucali, Erinc, 2016. "Theoretical and experimental study on the performance of a diesel engine fueled with diesel–biodiesel blends," Renewable Energy, Elsevier, vol. 93(C), pages 658-666.
    18. Chattopadhyay, Soham & Sen, Ramkrishna, 2013. "Fuel properties, engine performance and environmental benefits of biodiesel produced by a green process," Applied Energy, Elsevier, vol. 105(C), pages 319-326.
    19. Li, Yangtao & Khajepour, Amir & Devaud, Cécile & Liu, Kaimin, 2017. "Power and fuel economy optimizations of gasoline engines using hydraulic variable valve actuation system," Applied Energy, Elsevier, vol. 206(C), pages 577-593.
    20. Han, Weiqiang & Li, Bolun & Pan, Suozhu & Lu, Yao & Li, Xin, 2018. "Combined effect of inlet pressure, total cycle energy, and start of injection on low load reactivity controlled compression ignition combustion and emission characteristics in a multi-cylinder heavy-d," Energy, Elsevier, vol. 165(PB), pages 846-858.

    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:165:y:2016:i:c:p:676-684. 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.