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Possibility of Energy Recovery from Airflow around an SUV-Class Car Based on Wind Tunnel Testing

Author

Listed:
  • Paweł Ruchała

    (Aerodynamics Department, Łukasiewicz Research Network—Institute of Aviation, Al. Krakowska 110/114, 02-256 Warszawa, Poland)

  • Olga Orynycz

    (Department of Production Management, Faculty of Engineering Management, Bialystok University of Technology, Wiejska Street 45A, 15-351 Bialystok, Poland)

  • Wit Stryczniewicz

    (Aerodynamics Department, Łukasiewicz Research Network—Institute of Aviation, Al. Krakowska 110/114, 02-256 Warszawa, Poland)

  • Karol Tucki

    (Department of Production Engineering, Institute of Mechanical Engineering, Warsaw University of Life Sciences, Nowoursynowska Street 164, 02-787 Warsaw, Poland)

Abstract

For many years, technological progress has been observed in the field of minimizing energy consumption by devices and increasing the efficiency of energy generation from freely available sources. Energy harvesting (EH) is one of the ways to increase the energy available in vehicles. The manuscript presents the results of a series of laboratory tests carried out in a wind tunnel using a 1:10 scale model of an SUV. The aim of the tests was to measure the air velocity in the footsteps of the car. The speed field has been identified at more than 188,000 points in the space behind or next to the car, considering the symmetry of the vehicle. The total energy was aggregated for 2760 points in a vertical plane perpendicular to the plane of symmetry. From the tests carried out, it was found that the highest speed was achieved just behind the trunk of the car, at a distance of about 20% of the length of the car. Interestingly, the speed in this area was higher than the speed of the car.

Suggested Citation

  • Paweł Ruchała & Olga Orynycz & Wit Stryczniewicz & Karol Tucki, 2023. "Possibility of Energy Recovery from Airflow around an SUV-Class Car Based on Wind Tunnel Testing," Energies, MDPI, vol. 16(19), pages 1-16, October.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6965-:d:1254322
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    References listed on IDEAS

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    1. Maosong Fan & Mengmeng Geng & Kai Yang & Mingjie Zhang & Hao Liu, 2023. "State of Health Estimation of Lithium-Ion Battery Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 16(8), pages 1-14, April.
    2. Zuo, Jianyong & Dong, Liwei & Yang, Fan & Guo, Ziheng & Wang, Tianpeng & Zuo, Lei, 2023. "Energy harvesting solutions for railway transportation: A comprehensive review," Renewable Energy, Elsevier, vol. 202(C), pages 56-87.
    3. Ning Ma & Huaixian Yin & Kai Wang, 2023. "Prediction of the Remaining Useful Life of Supercapacitors at Different Temperatures Based on Improved Long Short-Term Memory," Energies, MDPI, vol. 16(14), pages 1-14, July.
    4. Mustafa Ergin Şahin & Frede Blaabjerg & Ariya Sangwongwanich, 2022. "A Comprehensive Review on Supercapacitor Applications and Developments," Energies, MDPI, vol. 15(3), pages 1-26, January.
    5. Pan, Hongye & Qi, Lingfei & Zhang, Zutao & Yan, Jinyue, 2021. "Kinetic energy harvesting technologies for applications in land transportation: A comprehensive review," Applied Energy, Elsevier, vol. 286(C).
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