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Real Driving Cycle Simulation of a Hybrid Bus by Means of a Co-Simulation Tool for the Prediction of Performance and Emissions

Author

Listed:
  • Andrea Massimo Marinoni

    (Politecnico di Milano, Department of Energy, Via Lambruschini 4A, 20156 Milano, Italy)

  • Angelo Onorati

    (Politecnico di Milano, Department of Energy, Via Lambruschini 4A, 20156 Milano, Italy)

  • Giacomo Manca Di Villahermosa

    (FPT Motorenforschung AG, 9320 Arbon, Switzerland)

  • Simon Langridge

    (FPT Motorenforschung AG, 9320 Arbon, Switzerland)

Abstract

This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity.

Suggested Citation

  • Andrea Massimo Marinoni & Angelo Onorati & Giacomo Manca Di Villahermosa & Simon Langridge, 2023. "Real Driving Cycle Simulation of a Hybrid Bus by Means of a Co-Simulation Tool for the Prediction of Performance and Emissions," Energies, MDPI, vol. 16(12), pages 1-29, June.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:12:p:4736-:d:1172059
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    References listed on IDEAS

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    1. Vittorio Usai & Silvia Marelli, 2021. "Steady State Experimental Characterization of a Twin Entry Turbine under Different Admission Conditions," Energies, MDPI, vol. 14(8), pages 1-17, April.
    2. Liu, Jinlong & Dumitrescu, Cosmin E., 2019. "Single and double Wiebe function combustion model for a heavy-duty diesel engine retrofitted to natural-gas spark-ignition," Applied Energy, Elsevier, vol. 248(C), pages 95-103.
    3. Finesso, Roberto & Spessa, Ezio & Venditti, Mattia, 2014. "Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle," Applied Energy, Elsevier, vol. 134(C), pages 573-588.
    4. Millo, Federico & Giacominetto, Paolo Ferrero & Bernardi, Marco Gianoglio, 2012. "Analysis of different exhaust gas recirculation architectures for passenger car Diesel engines," Applied Energy, Elsevier, vol. 98(C), pages 79-91.
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