Development of a Fully Physical Vehicle Model for Off-Line Powertrain Optimization: A Virtual Approach to Engine Calibration

Millo, Federico; Piano, Andrea; Zanelli, Alessandro; Boccardo, Giulio; Rimondi, Marcello; Fuso, Rocco

doi:10.4271/2021-24-0004

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…As highlighted in previous works 32,33 the calculation of ICE performance and emissions by a map-based approach, relying on look-up tables, is very fast but not predictive, since it does not allow a crank angle resolved solution of the engine thermodynamic cycles and cannot calculate the pollutant emissions from each combustion event. Additionally, this approach completely disregards the engine dynamics in transients: during a read driving cycle, the virtual engine represented by a map behaves like a simple sequence of steady-state points, with an of instantaneous transition from one to another.…”

Section: Discussionmentioning

confidence: 99%

RDE cycle simulation by 0D/1D models to investigate IC engine performance and cylinder-out emissions

Marinoni

Onorati

Montenegro

et al. 2022

International Journal of Engine Research

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In this work, the development and application of advanced predictive 0D/1D methodologies to simulate Real Driving Emission (RDE) cycles are described. Firstly, the 1D simulation model is validated on a map of steady state operating points, which allows to use successively the very same model, with its calibration, during an RDE cycle simulation, considering the sequence of varying loads, and rotational speeds. In particular, the validated 1D model is used to simulate a typical RDE transient cycle of approximately 1 h and 45 min. The test case investigated is a modern plug-in hybrid passenger car engine, in which the thermal power unit consists of a 1 L three-cylinder, turbocharged gasoline engine. The experimental and simulated RDE cycle is characterized by a sensibly varying Internal Combustion Engine (ICE) operation, allowing to evaluate engine performance and cylinder out emissions. To speed up the calculation and significantly lower the Central Processing Unit (CPU)/real time ratio a dedicated numerical solver for fast simulation has been implemented and tested, while keeping the fidelity of the results. A predictive 0D, multi-zone model for Spark Ignition (SI) combustion has been applied, together with emission sub-models for the calculation of the main pollutants. Both instantaneous and cumulative emissions have been evaluated. The results of the simulations have been compared to the experimental data of RDE cycles, showing a good predictiveness of the models and the high potential of 0D/1D simulation codes as design tools, in the new scenario of demanding testing procedures. This approach can be applied for any engine configuration operating under any transient condition.

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Section: Discussionmentioning

confidence: 99%

RDE cycle simulation by 0D/1D models to investigate IC engine performance and cylinder-out emissions

Marinoni

Onorati

Montenegro

et al. 2022

International Journal of Engine Research

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“…Wasserburger et al propose a methodology in [44,45] for generating test cycles from engine-operating points and using these as input values for an optimization algorithm that adjusts the calibration of specific functions to optimize vehicle emissions. Moreover, offline powertrain models use nearest neighbor clustering algorithms to frontload the engine base calibration in [46], and a methodology for model-based smooth calibration is presented in [47]. The investigation of neural networks is the main topic in [48] for developing models for the optimization of baseline calibration.…”

Section: State-of-the-art-novel Methods For Vehicle Calibrationmentioning

confidence: 99%

Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

Krysmon,

Pischinger,

Claßen

et al. 2024

Future Transportation

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Further reducing greenhouse gas and pollutant emissions from road vehicles is a major task for the automotive industry. Stricter regulations regarding emissions and fleet fuel consumption require the continuous development of new powertrains and methods. In particular, the combination of hybrid powertrains on the technical side and the focus on real driving emissions (RDE) on the legislative side pose significant challenges to the vehicle calibration process. Against this background, new test methods and environments are being investigated to counteract the high number of interactions between hybrid drive systems and quasi-infinite test conditions due to RDE. Complementary to new test environments, innovative methods for data analysis are needed that allow the exploitation of the complete potential of measurement data. The application of such a method in the field of emission calibration is presented in this paper. For this purpose, a clustering method (HDBSCAN) is applied to critical sequences from emission tests. Within this presentation, the clustering process is based on a single signal only. This paper shows how signals of various characteristics can be processed with dynamic time warping and generically structured with the clustering method used. Here, 959 single events are automatically categorized into 24 clusters. This provides a new basis for system evaluation, enabling the automatic identification, categorization, and prioritization of calibration weaknesses. Using twelve signals of different characteristics, the generic usability of the clustering method is demonstrated.

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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

et al. 2023

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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.

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Development of a Fully Physical Vehicle Model for Off-Line Powertrain Optimization: A Virtual Approach to Engine Calibration

Cited by 4 publications

References 22 publications

RDE cycle simulation by 0D/1D models to investigate IC engine performance and cylinder-out emissions

RDE cycle simulation by 0D/1D models to investigate IC engine performance and cylinder-out emissions

Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

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

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