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A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Author

Listed:
  • Kiyoung Kim

    (Department of Mechanical Engineering, Seoul National University, Seoul 08826, Korea)

  • Namdoo Kim

    (Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL 60439, USA)

  • Jongryeol Jeong

    (Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL 60439, USA)

  • Sunghwan Min

    (Hyundai Motor Company, 772-1 Jangduk-dong, Hwasung-si 445706, Gyunggi-do, Korea)

  • Horim Yang

    (Hyundai Motor Company, 772-1 Jangduk-dong, Hwasung-si 445706, Gyunggi-do, Korea)

  • Ram Vijayagopal

    (Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL 60439, USA)

  • Aymeric Rousseau

    (Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL 60439, USA)

  • Suk Won Cha

    (Department of Mechanical Engineering, Seoul National University, Seoul 08826, Korea
    Institute of Advanced Machines and Design, Seoul National University, Seoul 08826, Korea)

Abstract

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

Suggested Citation

  • Kiyoung Kim & Namdoo Kim & Jongryeol Jeong & Sunghwan Min & Horim Yang & Ram Vijayagopal & Aymeric Rousseau & Suk Won Cha, 2021. "A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm," Energies, MDPI, vol. 14(11), pages 1-15, May.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3147-:d:563892
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    References listed on IDEAS

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    1. Bradley, Thomas H. & Frank, Andrew A., 2009. "Design, demonstrations and sustainability impact assessments for plug-in hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 115-128, January.
    2. Piotr Wróblewski & Wojciech Drożdż & Wojciech Lewicki & Jakub Dowejko, 2021. "Total Cost of Ownership and Its Potential Consequences for the Development of the Hydrogen Fuel Cell Powered Vehicle Market in Poland," Energies, MDPI, vol. 14(8), pages 1-25, April.
    3. Kyuhyun Sim & Ram Vijayagopal & Namdoo Kim & Aymeric Rousseau, 2019. "Optimization of Component Sizing for a Fuel Cell-Powered Truck to Minimize Ownership Cost," Energies, MDPI, vol. 12(6), pages 1-13, March.
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    Cited by:

    1. Shantanu Pardhi & Mohamed El Baghdadi & Oswin Hulsebos & Omar Hegazy, 2022. "Optimal Powertrain Sizing of Series Hybrid Coach Running on Diesel and HVO for Lifetime Carbon Footprint and Total Cost Minimisation," Energies, MDPI, vol. 15(19), pages 1-28, September.
    2. Liu, Xinglong & Zhao, Fuquan & Hao, Han & Liu, Zongwei, 2023. "Comparative analysis for different vehicle powertrains in terms of energy-saving potential and cost-effectiveness in China," Energy, Elsevier, vol. 276(C).
    3. Ju, Fei & Du, Wei & Zhuang, Weichao & Li, Bingbing & Wang, Tao & Wang, Weiwei & Ma, Huijie, 2024. "Profit-effective component sizing for electric delivery trucks with dual motor coupling powertrain," Energy, Elsevier, vol. 296(C).
    4. Pier Giuseppe Anselma, 2022. "Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health," Energies, MDPI, vol. 15(5), pages 1-25, February.
    5. Andyn Omanovic & Norbert Zsiga & Patrik Soltic & Christopher Onder, 2021. "Optimal Degree of Hybridization for Spark-Ignited Engines with Optional Variable Valve Timings," Energies, MDPI, vol. 14(23), pages 1-21, December.

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