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

Andrea Massimo Marinoni (), Angelo Onorati, Giacomo Manca Di Villahermosa and Simon Langridge
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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

Energies, 2023, vol. 16, issue 12, 1-29

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.

Keywords: hybrid diesel modeling; 1D co-simulation; fast simulation method; hybrid bus; driving cycle prediction; steady state map; 1D model validation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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