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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
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    References listed on IDEAS

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    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.
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    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.

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