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Efficiency Increase through Model Predictive Thermal Control of Electric Vehicle Powertrains

Author

Listed:
  • Alexander Wahl

    (Teaching and Research Area Mechatronics in Mobile Propulsion, Faculty of Mechanical Engineering, RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany)

  • Christoph Wellmann

    (Teaching and Research Area Mechatronics in Mobile Propulsion, Faculty of Mechanical Engineering, RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany)

  • Björn Krautwig

    (Teaching and Research Area Mechatronics in Mobile Propulsion, Faculty of Mechanical Engineering, RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany)

  • Patrick Manns

    (Chair of Thermodynamics of Mobile Energy Conversion Systems, Faculty of Mechanical Engineering, RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany)

  • Bicheng Chen

    (Chair of Thermodynamics of Mobile Energy Conversion Systems, Faculty of Mechanical Engineering, RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany)

  • Christof Schernus

    (FEV Europe GmbH, Neuenhofstr. 181, 52078 Aachen, Germany)

  • Jakob Andert

    (Teaching and Research Area Mechatronics in Mobile Propulsion, Faculty of Mechanical Engineering, RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany)

Abstract

Battery electric vehicles (BEVs) are currently enjoying rising sales figures. However, BEVs still have problems with customer acceptance, partly due to limited driving ranges. To improve the situation, this paper introduces a novel approach utilising temperature-dependent efficiencies using an economic model predictive control approach (MPC) in combination with an active grille shutter in order to accelerate the heating of the permanent magnet synchronous machine. The measurements of temperature-dependent component efficiencies on a powertrain test bench are presented and analysed in detail in the speed/torque range. Thermal models based on the lumped parameter thermal network approach were developed and validated as part of the system-level validation against a US06 wind tunnel measurement. After the build-up and implementation of the MPC, various simulations were conducted. For the investigations, three driving cycles were considered at component start temperatures of 20–80 °C. The results show that using the MPC with the grille shutter can save 0.69–2.02% energy at the HV level compared to the rule-based control with a shutter, of which up to 1.02% is due to temperature-dependent efficiencies. Comparing the MPC with the grille shutter to a vehicle without a shutter, savings of 2.8–4.2% were achieved, while up to 1.67% was achieved due to temperature effects in the powertrain.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1476-:d:751462
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    References listed on IDEAS

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    1. Ye Yang & Zhongfu Tan & Yilong Ren, 2020. "Research on Factors That Influence the Fast Charging Behavior of Private Battery Electric Vehicles," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    2. Mariusz Baranski & Wojciech Szelag & Wieslaw Lyskawinski, 2020. "Analysis of the Partial Demagnetization Process of Magnets in a Line Start Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 13(21), pages 1-20, October.
    3. 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).
    4. Cedric De Cauwer & Wouter Verbeke & Thierry Coosemans & Saphir Faid & Joeri Van Mierlo, 2017. "A Data-Driven Method for Energy Consumption Prediction and Energy-Efficient Routing of Electric Vehicles in Real-World Conditions," Energies, MDPI, vol. 10(5), pages 1-18, May.
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    6. Ziwen Ling & Christopher R. Cherry & Yi Wen, 2021. "Determining the Factors That Influence Electric Vehicle Adoption: A Stated Preference Survey Study in Beijing, China," Sustainability, MDPI, vol. 13(21), pages 1-22, October.
    7. Caiyang Wei & Theo Hofman & Esin Ilhan Caarls & Rokus van Iperen, 2019. "Integrated Energy and Thermal Management for Electrified Powertrains," Energies, MDPI, vol. 12(11), pages 1-24, May.
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    Cited by:

    1. Shantanu Pardhi & Sajib Chakraborty & Dai-Duong Tran & Mohamed El Baghdadi & Steven Wilkins & Omar Hegazy, 2022. "A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology, Hydrogen, Energy and Thermal Management Solutions," Energies, MDPI, vol. 15(24), pages 1-55, December.
    2. Wahl, Alexander & Wellmann, Christoph & Monissen, Christian & Andert, Jakob, 2023. "Active temperature control of electric drivetrains for efficiency increase," Applied Energy, Elsevier, vol. 338(C).

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