IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i9p2224-d1388805.html
   My bibliography  Save this article

Improving the Fuel Economy and Energy Efficiency of Train Cab Climate Systems, Considering Air Recirculation Modes

Author

Listed:
  • Ivan Panfilov

    (Department of Theoretical and Applied Mechanics, Agribusiness Faculty, Don State Technical University, Gagarin, 1, 344003 Rostov-on-Don, Russia)

  • Alexey N. Beskopylny

    (Department of Transport Systems, Faculty of Roads and Transport Systems, Don State Technical University, Gagarin, 1, 344003 Rostov-on-Don, Russia)

  • Besarion Meskhi

    (Department of Life Safety and Environmental Protection, Faculty of Life Safety and Environmental Engineering, Don State Technical University, Gagarin, 1, 344003 Rostov-on-Don, Russia)

Abstract

Current developments in vehicles have generated great interest in the research and optimization of heating, ventilation, and air conditioning (HVAC) systems as a factor to reduce fuel consumption. One of the key trends for finding solutions is the intensive development of electric transport and, consequently, additional requirements for reducing energy consumption and modifying climate systems. Of particular interest is the optimal functioning of comfort and life support systems during air recirculation, i.e., when there is a complete or partial absence of outside air supply, in particular to reduce energy consumption or when the environment is polluted. This work examines numerical models of airfields (temperature, speed, and humidity) and also focuses on the concentration of carbon dioxide and oxygen in the cabin, which is a critical factor for ensuring the health of the driver and passengers. To build a mathematical model, the Navier–Stokes equations with energy, continuity, and diffusion equations are used to simulate the diffusion of gases and air humidity. In the Ansys Fluent finite volume analysis package, the model is solved numerically using averaged RANS equations and k-ω turbulence models. The cabin of a mainline locomotive with two drivers, taking into account their breathing, is used as a transport model. The problem was solved in a nonstationary formulation for the design scenario of summer and winter, the time of stabilization of the fields was found, and graphs were constructed for different points in time. A comparative analysis of the uniformity of fields along the height of the cabin was carried out with different locations of deflectors, and optimal configurations were found. Energy efficiency values of the climate system operation in recirculation operating modes were obtained. A qualitative assessment of the driver’s blowing directions under different circulation and recirculation modes is given from the point of view of the concentration of carbon dioxide in the breathing area. The proposed solution makes it possible to reduce electricity consumption from 3.1 kW to 0.6 kW and in winter mode from 11.6 kW to 3.9 kW and save up to 1.5 L/h of fuel. The conducted research can be used to develop modern energy-efficient and safe systems for providing comfortable climate conditions for drivers and passengers of various types of transport.

Suggested Citation

  • Ivan Panfilov & Alexey N. Beskopylny & Besarion Meskhi, 2024. "Improving the Fuel Economy and Energy Efficiency of Train Cab Climate Systems, Considering Air Recirculation Modes," Energies, MDPI, vol. 17(9), pages 1-26, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2224-:d:1388805
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/9/2224/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/9/2224/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ivan Panfilov & Alexey N. Beskopylny & Besarion Meskhi, 2023. "Numerical Simulation of Heat Transfer and Spread of Virus Particles in the Car Interior," Mathematics, MDPI, vol. 11(3), pages 1-18, February.
    2. Ivan Cvok & Igor Ratković & Joško Deur, 2020. "Optimisation of Control Input Allocation Maps for Electric Vehicle Heat Pump-based Cabin Heating Systems," Energies, MDPI, vol. 13(19), pages 1-23, October.
    3. Daniele Basciotti & Dominik Dvorak & Imre Gellai, 2020. "A Novel Methodology for Evaluating the Impact of Energy Efficiency Measures on the Cabin Thermal Comfort of Electric Vehicles," Energies, MDPI, vol. 13(15), pages 1-16, July.
    4. Hemmati, S. & Doshi, N. & Hanover, D. & Morgan, C. & Shahbakhti, M., 2021. "Integrated cabin heating and powertrain thermal energy management for a connected hybrid electric vehicle," Applied Energy, Elsevier, vol. 283(C).
    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. Ivan Cvok & Igor Ratković & Joško Deur, 2021. "Multi-Objective Optimisation-Based Design of an Electric Vehicle Cabin Heating Control System for Improved Thermal Comfort and Driving Range," Energies, MDPI, vol. 14(4), pages 1-24, February.
    2. Gian Luca Patrone & Elena Paffumi & Marcos Otura & Mario Centurelli & Christian Ferrarese & Steffen Jahn & Andreas Brenner & Bernd Thieringer & Daniel Braun & Thomas Hoffmann, 2022. "Assessing the Energy Consumption and Driving Range of the QUIET Project Demonstrator Vehicle," Energies, MDPI, vol. 15(4), pages 1-21, February.
    3. Alexander Wahl & Christoph Wellmann & Björn Krautwig & Patrick Manns & Bicheng Chen & Christof Schernus & Jakob Andert, 2022. "Efficiency Increase through Model Predictive Thermal Control of Electric Vehicle Powertrains," Energies, MDPI, vol. 15(4), pages 1-21, February.
    4. Ivan Cvok & Igor Ratković & Joško Deur, 2020. "Optimisation of Control Input Allocation Maps for Electric Vehicle Heat Pump-based Cabin Heating Systems," Energies, MDPI, vol. 13(19), pages 1-23, October.
    5. Haibo Wu & Xingwang Tang & Sichuan Xu & Jiangbin Zhou, 2022. "Research on Energy Saving of PHEV Air Conditioning System Based on Reducing Air Backflow in Underhood," Energies, MDPI, vol. 15(9), pages 1-15, April.
    6. Ivan Panfilov & Alexey N. Beskopylny & Besarion Meskhi, 2023. "Numerical Simulation of Heat Transfer and Spread of Virus Particles in the Car Interior," Mathematics, MDPI, vol. 11(3), pages 1-18, February.
    7. Qian Zhang & Shaopeng Tian, 2023. "Energy Consumption Prediction and Control Algorithm for Hybrid Electric Vehicles Based on an Equivalent Minimum Fuel Consumption Model," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    8. Zhang, Nan & Lu, Yiji & Ouderji, Zahra Hajabdollahi & Yu, Zhibin, 2023. "Review of heat pump integrated energy systems for future zero-emission vehicles," Energy, Elsevier, vol. 273(C).
    9. Ju Yeong Kwon & Jung Kyung Kim & Hyunjin Lee & Dongchan Lee & Da Young Ju, 2023. "A Comprehensive Overview of Basic Research on Human Thermal Management in Future Mobility: Considerations, Challenges, and Methods," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    10. Francesco Mocera & Aurelio Somà & Salvatore Martelli & Valerio Martini, 2023. "Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications," Energies, MDPI, vol. 16(18), pages 1-36, September.
    11. Ma, Yan & Ma, Qian & Liu, Yongqin & Gao, Jinwu & Chen, Hong, 2024. "Two-level optimization strategy for vehicle speed and battery thermal management in connected and automated EVs," Applied Energy, Elsevier, vol. 361(C).
    12. Ma, Jing & Sun, Yongfei & Zhang, Shiang, 2023. "Experimental investigation on energy consumption of power battery integrated thermal management system," Energy, Elsevier, vol. 270(C).
    13. Simone Lombardi & Manfredi Villani & Daniele Chiappini & Laura Tribioli, 2020. "Cooling System Energy Consumption Reduction through a Novel All-Electric Powertrain Traction Module and Control Optimization," Energies, MDPI, vol. 14(1), pages 1-22, December.
    14. Amir Ansari & Hamidreza Abediasl & Mahdi Shahbakhti, 2024. "Ambient Temperature Effects on Energy Consumption and CO 2 Emissions of a Plug-in Hybrid Electric Vehicle," Energies, MDPI, vol. 17(14), pages 1-21, July.
    15. Adam Wróblewski & Arkadiusz Macek & Aleksandra Banasiewicz & Sebastian Gola & Maciej Zawiślak & Anna Janicka, 2023. "CFD Analysis of the Forced Airflow and Temperature Distribution in the Air-Conditioned Operator’s Cabin of the Stationary Rock Breaker in Underground Mine under Increasing Heat Flux," Energies, MDPI, vol. 16(9), pages 1-18, April.
    16. Dominik Dvorak & Daniele Basciotti & Imre Gellai, 2020. "Demand-Based Control Design for Efficient Heat Pump Operation of Electric Vehicles," Energies, MDPI, vol. 13(20), pages 1-18, October.
    17. Kwon Joong Son, 2024. "Model Characterization of High-Voltage Layer Heater for Electric Vehicles through Electro–Thermo–Fluidic Simulations," Energies, MDPI, vol. 17(12), pages 1-13, June.

    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:jeners:v:17:y:2024:i:9:p:2224-:d:1388805. 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.