IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14519-d963749.html
   My bibliography  Save this article

Simulation Optimization of an Industrial Heavy-Duty Truck Based on Fluid–Structure Coupling

Author

Listed:
  • Xinyu Song

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Fang Cao

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Weifeng Rao

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Peiwen Huang

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

Abstract

In order to realize the sustainable development of the field of automotive industrial engineering and reduce the emissions of heavy-duty trucks (HDTs), a simulation analysis method that combined fluid–structure coupling and a discrete phase model was proposed in this study. The pressure, velocity, and other parameters of an HDT air filter and its cartridge were analyzed by using CFX and the Static Structure module in the ANSYS software. The results showed that under six different flow rates, the error between the simulation results and the test results was basically less than 3% (the maximum error was 3.4%), and the pressure distribution of the fluid in the air filter was very uneven, leading to a severe deformation of 3.51 mm in the filter element. In order to reduce the pressure drop of the air filter and the deformation of the filter element, the position of the air inlet duct, the height of the filter element, and the number of folds of the air filter were optimized in this study. The optimization results showed that when the rated flow was 840 m 3 /h, compared with the original structure, the pressure drop of the air filter was reduced by 445 Pa, the maximum deformation of the filter element was reduced by 54.1% and the average deformation is reduced by 39.8%. After the optimization, the structural parameters of the air filter were as follows: the position of the air inlet moved down 126 mm along the shell, the filter height was 267 mm, and the pleat number of the filter element was 70. The simulation method and optimization design method of an air filter based on fluid–structure interaction presented in this study can be used to reduce the pressure drop, improve the engine performance, and reduce the amount of harmful emissions.

Suggested Citation

  • Xinyu Song & Fang Cao & Weifeng Rao & Peiwen Huang, 2022. "Simulation Optimization of an Industrial Heavy-Duty Truck Based on Fluid–Structure Coupling," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14519-:d:963749
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14519/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/21/14519/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tadeusz Dziubak & Mirosław Karczewski, 2022. "Experimental Study of the Effect of Air Filter Pressure Drop on Internal Combustion Engine Performance," Energies, MDPI, vol. 15(9), pages 1-32, April.
    Full references (including those not matched with items on IDEAS)

    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. Tadeusz Dziubak & Mirosław Karczewski, 2022. "Experimental Studies of the Effect of Air Filter Pressure Drop on the Composition and Emission Changes of a Compression Ignition Internal Combustion Engine," Energies, MDPI, vol. 15(13), pages 1-31, June.
    2. Serdar Halis & Hamit Solmaz & Seyfi Polat & H. Serdar Yücesu, 2023. "Numerical Investigation of a Reactivity-Controlled Compression Ignition Engine Fueled with N-Heptane and Iso-Octane," Sustainability, MDPI, vol. 15(13), pages 1-17, July.
    3. Jufang Zhang & Xiumin Yu & Zezhou Guo & Yinan Li & Jiahua Zhang & Dongjie Liu, 2022. "Study on Combustion and Emissions of a Spark Ignition Engine with Gasoline Port Injection Plus Acetone–Butanol–Ethanol (ABE) Direct Injection under Different Speeds and Loads," Energies, MDPI, vol. 15(19), pages 1-22, September.
    4. Adrian Irimescu & Bianca Maria Vaglieco & Simona Silvia Merola & Vasco Zollo & Raffaele De Marinis, 2023. "Conversion of a Small-Size Passenger Car to Hydrogen Fueling: Evaluating the Risk of Backfire and the Correlation to Fuel System Requirements through 0D/1D Simulation," Energies, MDPI, vol. 16(10), pages 1-13, May.
    5. Gabriele D’Antuono & Davide Lanni & Enzo Galloni & Gustavo Fontana, 2023. "Numerical Modeling and Simulation of a Spark-Ignition Engine Fueled with Ammonia-Hydrogen Blends," Energies, MDPI, vol. 16(6), pages 1-14, March.
    6. Ziyang Wang & Masahiro Mae & Shoma Nishimura & Ryuji Matsuhashi, 2024. "Vehicular Fuel Consumption and CO 2 Emission Estimation Model Integrating Novel Driving Behavior Data Using Machine Learning," Energies, MDPI, vol. 17(6), pages 1-16, March.

    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:gam:jsusta:v:14:y:2022:i:21:p:14519-:d:963749. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.