IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v147y2018icp1299-1310.html
   My bibliography  Save this article

Turbocharger turbine rotor tip leakage loss and mass flow model valid up to extreme off-design conditions with high blade to jet speed ratio

Author

Listed:
  • Serrano, José Ramón
  • Navarro, Roberto
  • García-Cuevas, Luis Miguel
  • Inhestern, Lukas Benjamin

Abstract

Due to the power consumption restriction of the turbocharger compressor, common turbine maps are rather narrow. To extrapolate them, reliable physical submodels are needed that are valid for broad ranges. Plenty of research has been done referring to tip leakage losses in axial and traditional radial turbomachinery. However, less effort has been put into the tip leakage analysis of radial turbocharger turbines, whose characteristics including high rotational speed and geometry are rather different. Commonly developed tip leakage loss models in radial turbines are mainly based on correlations with the rotational speed, while in axial turbomachinery they are mainly based on blade loading assumptions. Wide range computational fluid dynamics (CFD) data of a medium sized automotive turbine have been used to analyze tip leakage mass flow under extremely diverse running conditions. To be able to fit a model in a broad range of the map, blade loading and rotational speed have to be considered. A novel tip clearance model has been derived from the Navier Stokes Equations. The model owns a dependency on the rotational speed and the blade loading. With this approach CFD data have been fitted in a very good quality to model the tip leakage mass flow rate and tip leakage losses.

Suggested Citation

  • Serrano, José Ramón & Navarro, Roberto & García-Cuevas, Luis Miguel & Inhestern, Lukas Benjamin, 2018. "Turbocharger turbine rotor tip leakage loss and mass flow model valid up to extreme off-design conditions with high blade to jet speed ratio," Energy, Elsevier, vol. 147(C), pages 1299-1310.
  • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:1299-1310
    DOI: 10.1016/j.energy.2018.01.083
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218301014
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.01.083?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. Galindo, J. & Fajardo, P. & Navarro, R. & García-Cuevas, L.M., 2013. "Characterization of a radial turbocharger turbine in pulsating flow by means of CFD and its application to engine modeling," Applied Energy, Elsevier, vol. 103(C), pages 116-127.
    2. Zhu, Sipeng & Deng, Kangyao & Liu, Sheng, 2015. "Modeling and extrapolating mass flow characteristics of a radial turbocharger turbine," Energy, Elsevier, vol. 87(C), pages 628-637.
    3. Serrano, José Ramón & Tiseira, Andrés & García-Cuevas, Luis Miguel & Inhestern, Lukas Benjamin & Tartoussi, Hadi, 2017. "Radial turbine performance measurement under extreme off-design conditions," Energy, Elsevier, vol. 125(C), pages 72-84.
    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. Wei, Jiangshan & Xue, Yingxian & Yang, Mingyang & Deng, Kangyao & Wang, Cuicui & Wu, Xintao, 2021. "A reduced-order model of twin-entry nozzleless radial turbine based on flow characteristics," Energy, Elsevier, vol. 214(C).
    2. Serrano, José Ramón & Piqueras, Pedro & De la Morena, Joaquín & Gómez-Vilanova, Alejandro & Guilain, Stéphane, 2021. "Methodological analysis of variable geometry turbine technology impact on the performance of highly downsized spark-ignition engines," Energy, Elsevier, vol. 215(PB).
    3. José Galindo & Andrés Tiseira & Roberto Navarro & Lukas Benjamin Inhestern & Juan David Echavarría, 2022. "Numerical Analysis of the Effects of Different Rotor Tip Gaps in a Radial Turbine Operating at High Pressure Ratios Reaching Choked Flow," Energies, MDPI, vol. 15(24), pages 1-30, December.
    4. Tüchler, Stefan & Chen, Zhihang & Copeland, Colin D., 2018. "Multipoint shape optimisation of an automotive radial compressor using a coupled computational fluid dynamics and genetic algorithm approach," Energy, Elsevier, vol. 165(PA), pages 543-561.
    5. Xue, Yingxian & Yang, Mingyang & Martinez-Botas, Ricardo F. & Romagnoli, Alessandro & Deng, Kangyao, 2019. "Loss analysis of a mix-flow turbine with nozzled twin-entry volute at different admissions," Energy, Elsevier, vol. 166(C), pages 775-788.
    6. Rong Huang & Jimin Ni & Houchuan Fan & Xiuyong Shi & Qiwei Wang, 2023. "Investigating a New Method-Based Internal Joint Operation Law for Optimizing the Performance of a Turbocharger Compressor," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    7. Wang, Zhiqi & Xie, Baoqi & Xia, Xiaoxia & Yang, Huya & Zuo, Qingsong & Liu, Zhipeng, 2022. "Energy loss of radial inflow turbine for organic Rankine cycle using mixture based on entropy production method," Energy, Elsevier, vol. 245(C).
    8. Serrano, José Ramón & Arnau, Francisco José & García-Cuevas, Luis Miguel & Inhestern, Lukas Benjamin, 2019. "An innovative losses model for efficiency map fitting of vaneless and variable vaned radial turbines extrapolating towards extreme off-design conditions," Energy, Elsevier, vol. 180(C), pages 626-639.

    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. Kim, Jeong Ho & Kim, Tong Seop, 2019. "A new approach to generate turbine map data in the sub-idle operation regime of gas turbines," Energy, Elsevier, vol. 173(C), pages 772-784.
    2. José Galindo & Andrés Tiseira & Roberto Navarro & Lukas Benjamin Inhestern & Juan David Echavarría, 2022. "Numerical Analysis of the Effects of Different Rotor Tip Gaps in a Radial Turbine Operating at High Pressure Ratios Reaching Choked Flow," Energies, MDPI, vol. 15(24), pages 1-30, December.
    3. Tregenza, Owen & Olshina, Noam & Hield, Peter & Manzie, Chris & Hulston, Chris, 2022. "A comparison of turbine mass flow models based on pragmatic identification data sets for turbogenerator model development," Energy, Elsevier, vol. 247(C).
    4. Serrano, José Ramón & Arnau, Francisco José & García-Cuevas, Luis Miguel & Inhestern, Lukas Benjamin, 2019. "An innovative losses model for efficiency map fitting of vaneless and variable vaned radial turbines extrapolating towards extreme off-design conditions," Energy, Elsevier, vol. 180(C), pages 626-639.
    5. Salameh, Georges & Chesse, Pascal & Chalet, David, 2019. "Mass flow extrapolation model for automotive turbine and confrontation to experiments," Energy, Elsevier, vol. 167(C), pages 325-336.
    6. Liu, Zheng & Copeland, Colin, 2018. "New method for mapping radial turbines exposed to pulsating flows," Energy, Elsevier, vol. 162(C), pages 1205-1222.
    7. Sakellaridis, Nikolaos F. & Raptotasios, Spyridon I. & Antonopoulos, Antonis K. & Mavropoulos, Georgios C. & Hountalas, Dimitrios T., 2015. "Development and validation of a new turbocharger simulation methodology for marine two stroke diesel engine modelling and diagnostic applications," Energy, Elsevier, vol. 91(C), pages 952-966.
    8. Inhestern, Lukas Benjamin & Peitsch, Dieter & Paniagua, Guillermo, 2024. "Flow irreversibility and heat transfer effects on turbine efficiency," Applied Energy, Elsevier, vol. 353(PA).
    9. Ma, Zetai & Xie, Wenping & Xiang, Hanchun & Zhang, Kun & Yang, Mingyang & Deng, Kangyao, 2023. "Thermodynamic analysis of power recovery of marine diesel engine under high exhaust backpressure by additional electrically driven compressor," Energy, Elsevier, vol. 266(C).
    10. Zhao, Rongchao & Li, Weihua & Zhuge, Weilin & Zhang, Yangjun & Yin, Yong & Wu, Yonghui, 2018. "Characterization of two-stage turbine system under steady and pulsating flow conditions," Energy, Elsevier, vol. 148(C), pages 407-423.
    11. Andrés Omar Tiseira Izaguirre & Roberto Navarro García & Lukas Benjamin Inhestern & Natalia Hervás Gómez, 2020. "Design and Numerical Analysis of Flow Characteristics in a Scaled Volute and Vaned Nozzle of Radial Turbocharger Turbines," Energies, MDPI, vol. 13(11), pages 1-19, June.
    12. Afrouzi, Hamid Hassanzadeh & Ahmadian, Majid & Moshfegh, Abouzar & Toghraie, Davood & Javadzadegan, Ashkan, 2019. "Statistical analysis of pulsating non-Newtonian flow in a corrugated channel using Lattice-Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    13. Wang, Chongming & Xu, Hongming & Herreros, Jose Martin & Wang, Jianxin & Cracknell, Roger, 2014. "Impact of fuel and injection system on particle emissions from a GDI engine," Applied Energy, Elsevier, vol. 132(C), pages 178-191.
    14. Powell, D. & Ebrahimi, A. & Nourbakhsh, S. & Meshkahaldini, M. & Bilton, A.M., 2018. "Design of pico-hydro turbine generator systems for self-powered electrochemical water disinfection devices," Renewable Energy, Elsevier, vol. 123(C), pages 590-602.
    15. Zhang, Guangchao & Lv, Kai & Xie, Yudong & Wang, Yong & Shan, Kunshan, 2023. "Performance study of a control valve with energy harvesting based on a modified passive model," Energy, Elsevier, vol. 285(C).
    16. Rong Huang & Jimin Ni & Houchuan Fan & Xiuyong Shi & Qiwei Wang, 2023. "Investigating a New Method-Based Internal Joint Operation Law for Optimizing the Performance of a Turbocharger Compressor," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    17. Mahabadipour, Hamidreza & Srinivasan, Kalyan Kumar & Krishnan, Sundar Rajan & Subramanian, Swami Nathan, 2018. "Crank angle-resolved exergy analysis of exhaust flows in a diesel engine from the perspective of exhaust waste energy recovery," Applied Energy, Elsevier, vol. 216(C), pages 31-44.
    18. Deligant, Michael & Sauret, Emilie & Danel, Quentin & Bakir, Farid, 2020. "Performance assessment of a standard radial turbine as turbo expander for an adapted solar concentration ORC," Renewable Energy, Elsevier, vol. 147(P3), pages 2833-2841.
    19. Bontempo, R. & Cardone, M. & Manna, M. & Vorraro, G., 2017. "A statistical approach to the analysis of the surge phenomenon," Energy, Elsevier, vol. 124(C), pages 502-509.
    20. 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.

    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:energy:v:147:y:2018:i:c:p:1299-1310. 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.journals.elsevier.com/energy .

    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.