IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i16p4747-d608506.html
   My bibliography  Save this article

Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms

Author

Listed:
  • Sascha Krysmon

    (Institute for Combustion Engines, RWTH Aachen University, 52074 Aachen, Germany)

  • Frank Dorscheidt

    (Institute for Combustion Engines, RWTH Aachen University, 52074 Aachen, Germany)

  • Johannes Claßen

    (Institute for Combustion Engines, RWTH Aachen University, 52074 Aachen, Germany)

  • Marc Düzgün

    (Institute for Combustion Engines, RWTH Aachen University, 52074 Aachen, Germany)

  • Stefan Pischinger

    (Institute for Combustion Engines, RWTH Aachen University, 52074 Aachen, Germany)

Abstract

The combination of different propulsion and energy storage systems for hybrid vehicles is changing the focus in the field of powertrain calibration. Shorter time-to-market as well as stricter legal requirements regarding the validation of Real Driving Emissions (RDE) require the adaptation of current procedures and the implementation of new technologies in the powertrain development process. In order to achieve highest efficiencies and lowest pollutant emissions at the same time, the layout and calibration of the control strategies for the powertrain and the exhaust gas aftertreatment system must be precisely matched. An optimal operating strategy must take into account possible trade-offs in fuel consumption and emission levels, both under highly dynamic engine operation and under extended environmental operating conditions. To achieve this with a high degree of statistical certainty, the combination of advanced methods and the use of virtual test benches offers significant potential. An approach for such a combination is presented in this paper. Together with a Hardware-in-the-Loop (HiL) test bench, the novel methodology enables a targeted calibration process, specifically designed to address calibration challenges of hybridized powertrains. Virtual tests executed on a HiL test bench are used to efficiently generate data characterizing the behavior of the system under various conditions with a statistically based evaluation identifying white spots in measurement data, used for calibration and emission validation. In addition, critical sequences are identified in terms of emission intensity, fuel consumption or component conditions. Dedicated test scenarios are generated and applied on the HiL test bench, which take into account the state of the system and are adjusted depending on it. The example of one emission calibration use case is used to illustrate the benefits of using a HiL platform, which achieves approximately 20% reduction in calibration time by only showing differences of less than 2% for fuel consumption and emission levels compared to real vehicle tests.

Suggested Citation

  • Sascha Krysmon & Frank Dorscheidt & Johannes Claßen & Marc Düzgün & Stefan Pischinger, 2021. "Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms," Energies, MDPI, vol. 14(16), pages 1-27, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4747-:d:608506
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/16/4747/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/16/4747/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ilya Kulikov & Sergey Korkin & Andrey Kozlov & Alexey Terenchenko & Kirill Karpukhin & Ulugbek Azimov, 2021. "Component-in-the-Loop Testing of Automotive Powertrains Featuring All-Wheel-Drive," Energies, MDPI, vol. 14(7), pages 1-18, April.
    2. Federico Millo & Francesco Accurso & Alessandro Zanelli & Luciano Rolando, 2019. "Numerical Investigation of 48 V Electrification Potential in Terms of Fuel Economy and Vehicle Performance for a Lambda-1 Gasoline Passenger Car," Energies, MDPI, vol. 12(15), pages 1-21, August.
    3. Timothy Bodisco & Ali Zare, 2019. "Practicalities and Driving Dynamics of a Real Driving Emissions (RDE) Euro 6 Regulation Homologation Test," Energies, MDPI, vol. 12(12), pages 1-19, June.
    4. Kangjin Kim & Wonyong Chung & Myungsoo Kim & Charyung Kim & Cha-Lee Myung & Simsoo Park, 2020. "Inspection of PN, CO 2 , and Regulated Gaseous Emissions Characteristics from a GDI Vehicle under Various Real-World Vehicle Test Modes," Energies, MDPI, vol. 13(10), pages 1-17, May.
    5. Ali Ashtari & Eric Bibeau & Soheil Shahidinejad, 2014. "Using Large Driving Record Samples and a Stochastic Approach for Real-World Driving Cycle Construction: Winnipeg Driving Cycle," Transportation Science, INFORMS, vol. 48(2), pages 170-183, May.
    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. Gloria Pignatta & Navid Balazadeh, 2022. "Hybrid Vehicles as a Transition for Full E-Mobility Achievement in Positive Energy Districts: A Comparative Assessment of Real-Driving Emissions," Energies, MDPI, vol. 15(8), pages 1-18, April.
    2. Frank Dorscheidt & Stefan Pischinger & Johannes Claßen & Stefan Sterlepper & Sascha Krysmon & Michael Görgen & Martin Nijs & Pawel Straszak & Abdelrahman Mahfouz Abdelkader, 2021. "Development of a Novel Gasoline Particulate Filter Loading Method Using a Burner Bench," Energies, MDPI, vol. 14(16), pages 1-21, August.

    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. Kazimierz Lejda & Artur Jaworski & Maksymilian Mądziel & Krzysztof Balawender & Adam Ustrzycki & Danylo Savostin-Kosiak, 2021. "Assessment of Petrol and Natural Gas Vehicle Carbon Oxides Emissions in the Laboratory and On-Road Tests," Energies, MDPI, vol. 14(6), pages 1-19, March.
    2. S. M. Ashrafur Rahman & I. M. Rizwanul Fattah & Hwai Chyuan Ong & Fajle Rabbi Ashik & Mohammad Mahmudul Hassan & Md Tausif Murshed & Md Ashraful Imran & Md Hamidur Rahman & Md Akibur Rahman & Mohammad, 2021. "State-of-the-Art of Establishing Test Procedures for Real Driving Gaseous Emissions from Light- and Heavy-Duty Vehicles," Energies, MDPI, vol. 14(14), pages 1-32, July.
    3. Branislav Šarkan & Marek Jaśkiewicz & Przemysław Kubiak & Dariusz Tarnapowicz & Michal Loman, 2022. "Exhaust Emissions Measurement of a Vehicle with Retrofitted LPG System," Energies, MDPI, vol. 15(3), pages 1-22, February.
    4. Andrzej Ziółkowski & Paweł Fuć & Piotr Lijewski & Aleks Jagielski & Maciej Bednarek & Władysław Kusiak, 2022. "Analysis of Exhaust Emissions from Heavy-Duty Vehicles on Different Applications," Energies, MDPI, vol. 15(21), pages 1-21, October.
    5. José I. Huertas & Michael Giraldo & Luis F. Quirama & Jenny Díaz, 2018. "Driving Cycles Based on Fuel Consumption," Energies, MDPI, vol. 11(11), pages 1-13, November.
    6. Danilo Engelmann & Yan Zimmerli & Jan Czerwinski & Peter Bonsack, 2021. "Real Driving Emissions in Extended Driving Conditions," Energies, MDPI, vol. 14(21), pages 1-19, November.
    7. Cui, Yuepeng & Xu, Hao & Zou, Fumin & Chen, Zhihui & Gong, Kuangmin, 2021. "Optimization based method to develop representative driving cycle for real-world fuel consumption estimation," Energy, Elsevier, vol. 235(C).
    8. Danijel Pavković & Mihael Cipek & Filip Plavac & Juraj Karlušić & Matija Krznar, 2022. "Internal Combustion Engine Starting and Torque Boosting Control System Design with Vibration Active Damping Features for a P0 Mild Hybrid Vehicle Configuration," Energies, MDPI, vol. 15(4), pages 1-24, February.
    9. Karol Tucki, 2021. "A Computer Tool for Modelling CO 2 Emissions in Driving Tests for Vehicles with Diesel Engines," Energies, MDPI, vol. 14(2), pages 1-30, January.
    10. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    11. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
    12. Jacek Pielecha & Kinga Skobiej & Maciej Gis & Wojciech Gis, 2022. "Particle Number Emission from Vehicles of Various Drives in the RDE Tests," Energies, MDPI, vol. 15(17), pages 1-20, September.
    13. Hongli Liu & Weiguo Yun & Bin Li & Mengling Dai & Yangyuhang Wang, 2023. "A Quantitative Study on Driving Behavior Economy Based on Big Data from the Pure Electric Bus," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    14. Cui, Yuepeng & Zou, Fumin & Xu, Hao & Chen, Zhihui & Gong, Kuangmin, 2022. "A novel optimization-based method to develop representative driving cycle in various driving conditions," Energy, Elsevier, vol. 247(C).
    15. Björnsson, Lars-Henrik & Karlsson, Sten, 2015. "Plug-in hybrid electric vehicles: How individual movement patterns affect battery requirements, the potential to replace conventional fuels, and economic viability," Applied Energy, Elsevier, vol. 143(C), pages 336-347.
    16. Kinga Skobiej & Jacek Pielecha, 2022. "Analysis of the Exhaust Emissions of Hybrid Vehicles for the Current and Future RDE Driving Cycle," Energies, MDPI, vol. 15(22), pages 1-21, November.
    17. Huiyong Yang & Lei Zhang & Jingping Liu & Jianqin Fu & Dazi Shen & Zhipeng Yuan, 2023. "Development and Validation of a Variable Displacement Variable Compression Ratio Miller Cycle Technology on an Automotive Gasoline Engine," Energies, MDPI, vol. 16(11), pages 1-17, June.
    18. Maksymilian Mądziel, 2023. "Vehicle Emission Models and Traffic Simulators: A Review," Energies, MDPI, vol. 16(9), pages 1-31, May.
    19. Federico Millo & Fabrizio Gullino & Luciano Rolando, 2020. "Methodological Approach for 1D Simulation of Port Water Injection for Knock Mitigation in a Turbocharged DISI Engine," Energies, MDPI, vol. 13(17), pages 1-21, August.

    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:14:y:2021:i:16:p:4747-:d:608506. 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.