Applied Sciences (Mar 2022)

1D and Map-Based Modeling Approaches for Railway Compression Ignition Engine in NRTC Application

  • Giuseppe Di Luca,
  • Massimiliano Muccillo,
  • Giovanni Giardiello,
  • Alfredo Gimelli,
  • Gabriele Di Blasio

DOI
https://doi.org/10.3390/app12052665
Journal volume & issue
Vol. 12, no. 5
p. 2665

Abstract

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Internal combustion engine-driven railway vehicles play an important role in the sector even today, due to the incomplete electrification of railway routes. However, stringent COP26 environmental rules are driving manufacturers and the scientific community to study more complex or alternative propulsion systems. Therefore, the design of new powertrains is becoming more challenging. Affordable, along with robust, development tools are fundamental for their development and optimization. In this framework, numerical simulation can represent an effective instrument to face these requirements. The proposed study assesses the accuracy of different modelling approaches for the same engine. In particular, a detailed 1D model, a simplified 1D model and a map-based model are compared. Although studies on engine simulation are available in the technical literature, the novelty introduced with this work is the assessment of accuracy and computational times of the engine models, considered by performing the new emission standard Non-Road Transient Cycle (NRTC), which is applied to a specific field such as Heavy Duty (HD) Compression Ignition (CI) engines for railway applications. This study provides new and quantitative results rarely available in the specific literature. The results show that the simplest model, despite its lower accuracy, maintains good predictive results in terms of cumulative fuel consumption and cumulative nitric oxide (NOx) emissions over the cycle considered. In particular, the difference in terms of fuel consumption for the map-based model is within 5% compared with the more detailed models. Moreover, the computational effort required by the simplest model is three orders of magnitude lower compared with the more detailed model. Therefore, as the simulation run-time is the priority, the simplest modeling approach is suitable for the evaluation of the global performance, in view of a more complex systems simulation, such as a hybrid powertrain.

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