IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i12p2121-d122778.html
   My bibliography  Save this article

Effect on Vehicle Turbocharger Exhaust Gas Energy Utilization for the Performance of Centrifugal Compressors under Plateau Conditions

Author

Listed:
  • Hong Zhang

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Hang Zhang

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Zhuo Wang

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

Abstract

This paper is focused on the performance of centrifugal compressors for vehicle turbochargers operating at high altitude. The reasons for turbocharged diesel engine power loss increases and bad economy performance caused by exhaust gas energy utilization are investigated. The atmosphere’s impact on the turbocharger centrifugal compressor’s energy distribution characteristics under the plateau is discussed. The key parameters that affect compressor characteristics are concluded in a theoretical method. A simulation calculation model is established to accurately predict compressor performance at high altitude. By comparing the experimental results, the calculation results are validated. The details of the internal flow fields analysis, including critical parameters of a compressor operating at high altitude, are analyzed. The results show that with the increase of altitude from 0 m to 4500 m, the peak efficiency of the compressor is reduced by 2.4%, while the peak pressure ratio is increased by 7%. The main influence characters of the plateau environment on the turbocharger centrifugal compressor performance, such as blade loads, exergy utilization and entropy distribution are concluded. The key factors for compressor performance and compressor energy flow control design method operated at high altitude are obtained.

Suggested Citation

  • Hong Zhang & Hang Zhang & Zhuo Wang, 2017. "Effect on Vehicle Turbocharger Exhaust Gas Energy Utilization for the Performance of Centrifugal Compressors under Plateau Conditions," Energies, MDPI, vol. 10(12), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2121-:d:122778
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/12/2121/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/12/2121/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mamat, Aman M.I. & Romagnoli, Alessandro & Martinez-Botas, Ricardo F., 2014. "Characterisation of a low pressure turbine for turbocompounding applications in a heavily downsized mild-hybrid gasoline engine," Energy, Elsevier, vol. 64(C), pages 3-16.
    2. Saidur, R. & Rezaei, M. & Muzammil, W.K. & Hassan, M.H. & Paria, S. & Hasanuzzaman, M., 2012. "Technologies to recover exhaust heat from internal combustion engines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5649-5659.
    3. Zou, Yuan & Liu, Teng & Liu, Dexing & Sun, Fengchun, 2016. "Reinforcement learning-based real-time energy management for a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 171(C), pages 372-382.
    4. Xiong, Rui & Tian, Jinpeng & Mu, Hao & Wang, Chun, 2017. "A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries," Applied Energy, Elsevier, vol. 207(C), pages 372-383.
    5. Xiong, Rui & Yu, Quanqing & Wang, Le Yi & Lin, Cheng, 2017. "A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter," Applied Energy, Elsevier, vol. 207(C), pages 346-353.
    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. Yi Dong & Jianmin Liu & Yanbin Liu & Xinyong Qiao & Xiaoming Zhang & Ying Jin & Shaoliang Zhang & Tianqi Wang & Qi Kang, 2020. "A RBFNN & GACMOO-Based Working State Optimization Control Study on Heavy-Duty Diesel Engine Working in Plateau Environment," Energies, MDPI, vol. 13(1), pages 1-24, January.
    2. Rui Xiong & Suleiman M. Sharkh & Xi Zhang, 2018. "Research Progress on Electric and Intelligent Vehicles," Energies, MDPI, vol. 11(7), pages 1-5, July.
    3. Beichuan Hong & Varun Venkataraman & Andreas Cronhjort, 2021. "Numerical Analysis of Engine Exhaust Flow Parameters for Resolving Pre-Turbine Pulsating Flow Enthalpy and Exergy," Energies, MDPI, vol. 14(19), pages 1-24, September.
    4. Salvo, Orlando de & Vaz de Almeida, Flávio G., 2019. "Influence of technologies on energy efficiency results of official Brazilian tests of vehicle energy consumption," Applied Energy, Elsevier, vol. 241(C), pages 98-112.

    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. Aijuan Li & Wanzhong Zhao & Xibo Wang & Xuyun Qiu, 2018. "ACT-R Cognitive Model Based Trajectory Planning Method Study for Electric Vehicle’s Active Obstacle Avoidance System," Energies, MDPI, vol. 11(1), pages 1-21, January.
    2. Zhao, Rongchao & Zhuge, Weilin & Zhang, Yangjun & Yin, Yong & Zhao, Yanting & Chen, Zhen, 2016. "Parametric study of a turbocompound diesel engine based on an analytical model," Energy, Elsevier, vol. 115(P1), pages 435-445.
    3. Li, Jianwei & Xiong, Rui & Mu, Hao & Cornélusse, Bertrand & Vanderbemden, Philippe & Ernst, Damien & Yuan, Weijia, 2018. "Design and real-time test of a hybrid energy storage system in the microgrid with the benefit of improving the battery lifetime," Applied Energy, Elsevier, vol. 218(C), pages 470-478.
    4. Yang, Ruixin & Xiong, Rui & He, Hongwen & Mu, Hao & Wang, Chun, 2017. "A novel method on estimating the degradation and state of charge of lithium-ion batteries used for electrical vehicles," Applied Energy, Elsevier, vol. 207(C), pages 336-345.
    5. Xiaogang Wu & Siyu Lv & Jizhong Chen, 2017. "Determination of the Optimum Heat Transfer Coefficient and Temperature Rise Analysis for a Lithium-Ion Battery under the Conditions of Harbin City Bus Driving Cycles," Energies, MDPI, vol. 10(11), pages 1-17, October.
    6. Pasini, Gianluca & Lutzemberger, Giovanni & Frigo, Stefano & Marelli, Silvia & Ceraolo, Massimo & Gentili, Roberto & Capobianco, Massimo, 2016. "Evaluation of an electric turbo compound system for SI engines: A numerical approach," Applied Energy, Elsevier, vol. 162(C), pages 527-540.
    7. Xiaogang Wu & Wenwen Shi & Jiuyu Du, 2017. "Multi-Objective Optimal Charging Method for Lithium-Ion Batteries," Energies, MDPI, vol. 10(9), pages 1-18, August.
    8. Lin, Cheng & Yu, Quanqing & Xiong, Rui & Wang, Le Yi, 2017. "A study on the impact of open circuit voltage tests on state of charge estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 205(C), pages 892-902.
    9. Zhu, Sipeng & Liu, Sheng & Qu, Shuan & Deng, Kangyao, 2017. "Thermodynamic and experimental researches on matching strategies of the pre-turbine steam injection and the Miller cycle applied on a turbocharged diesel engine," Energy, Elsevier, vol. 140(P1), pages 488-505.
    10. Zhao, Rongchao & Li, Weihua & Zhuge, Weilin & Zhang, Yangjun & Yin, Yong, 2017. "Numerical study on steam injection in a turbocompound diesel engine for waste heat recovery," Applied Energy, Elsevier, vol. 185(P1), pages 506-518.
    11. Mu, Hao & Xiong, Rui & Zheng, Hongfei & Chang, Yuhua & Chen, Zeyu, 2017. "A novel fractional order model based state-of-charge estimation method for lithium-ion battery," Applied Energy, Elsevier, vol. 207(C), pages 384-393.
    12. Yan Bao & Yu Luo & Weige Zhang & Mei Huang & Le Yi Wang & Jiuchun Jiang, 2018. "A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System," Energies, MDPI, vol. 11(1), pages 1-21, January.
    13. Di Battista, D. & Mauriello, M. & Cipollone, R., 2015. "Waste heat recovery of an ORC-based power unit in a turbocharged diesel engine propelling a light duty vehicle," Applied Energy, Elsevier, vol. 152(C), pages 109-120.
    14. Chen, Zeyu & Xiong, Rui & Lu, Jiahuan & Li, Xinggang, 2018. "Temperature rise prediction of lithium-ion battery suffering external short circuit for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 213(C), pages 375-383.
    15. He, Hongwen & Guo, Xiaoguang, 2018. "Multi-objective optimization research on the start condition for a parallel hybrid electric vehicle," Applied Energy, Elsevier, vol. 227(C), pages 294-303.
    16. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    17. Xiong, Rui & Li, Linlin & Li, Zhirun & Yu, Quanqing & Mu, Hao, 2018. "An electrochemical model based degradation state identification method of Lithium-ion battery for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 219(C), pages 264-275.
    18. Hong Zhang & Zhuang Xing & Jiajian Song & Qiangqiang Yang, 2018. "Development and Test Application of an Auxiliary Power-Integrated System," Energies, MDPI, vol. 11(1), pages 1-18, January.
    19. Mingjie Zhao & Junhui Shi & Cheng Lin & Junzhi Zhang, 2018. "Application-Oriented Optimal Shift Schedule Extraction for a Dual-Motor Electric Bus with Automated Manual Transmission," Energies, MDPI, vol. 11(2), pages 1-16, February.
    20. Rujian Fu & Xuan Zhou & Hengbin Fan & Douglas Blaisdell & Ajay Jagadale & Xi Zhang & Rui Xiong, 2017. "Comparison of Lithium-Ion Anode Materials Using an Experimentally Verified Physics-Based Electrochemical Model," Energies, MDPI, vol. 10(12), pages 1-20, December.

    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:10:y:2017:i:12:p:2121-:d:122778. 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.