Applied Sciences (Sep 2021)

0D/1D Thermo-Fluid Dynamic Modeling Tools for the Simulation of Driving Cycles and the Optimization of IC Engine Performances and Emissions

  • Andrea Marinoni,
  • Matteo Tamborski,
  • Tarcisio Cerri,
  • Gianluca Montenegro,
  • Gianluca D’Errico,
  • Angelo Onorati,
  • Emanuele Piatti,
  • Enrico Ernesto Pisoni

DOI
https://doi.org/10.3390/app11178125
Journal volume & issue
Vol. 11, no. 17
p. 8125

Abstract

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The prediction of internal combustion engine performance and emissions in real driving conditions is getting more and more important due to the upcoming stricter regulations. This work aims at introducing and validating a new transient simulation methodology of an ICE coupled to a hybrid architecture vehicle, getting closer to real-time calculations. A one-dimensional computational fluid dynamic software has been used and suitably coupled to a vehicle dynamics model in a user function framework integrated within a Simulink® environment. A six-cylinder diesel engine has been modeled by means of the 1D tool and cylinder-out emissions have been compared to experimental data. The measurements available have been used also to calibrate the combustion model. The developed 1D engine model has been then used to perform driving cycle simulations considering the vehicle dynamics and the coupling with the energy storage unit in the hybrid mode. The map-based approach along with the vehicle simulation tool has also been used to perform the same simulation and the two results are compared to evaluate the accuracy of each approach. In this framework, to achieve the best simulation performance in terms of computational time over simulated time ratio, the 1D engine model has been used in a configuration with a very coarse mesh. Results have shown that despite the high mesh spacing used the accuracy of the wave dynamics prediction was not affected in a significant way, whereas a remarkable speed-up factor was achieved. This means that a crank angle resolution approach to the vehicle simulation is a viable and accurate strategy to predict the engine emission during any driving cycle with a computation effort compatible with the tight schedule of a design process.

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