Investigation of powertrains in hybrid vehicles

Briguiet, Gabriel de Oliveira Franco; Lopes, Pedro Henrique Lameirão Machado; Rodrigues, Gustavo Simão; Lopes, Elias Dias Rossi

doi:10.4271/2020-36-0137

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…The particle size evolution is also affected by two chemistry-dominated phenomena, namely surface growth and oxidation, leading to increase and reduction of the particle size, respectively. In equation (10), the overall source term Õsoot, i for the generic section i is computed as the sum of individual source terms as in equation (11). Each one is related to a specific contribution: particle inception, coagulation, condensation, surface growth, and oxidation.…”

Section: Sectional Soot Methodsmentioning

confidence: 99%

“…To achieve the target, engine manufacturers take advantage of different techniques such as downsizing together with turbocharging (leading to an increase of specific power), 1,2 gasoline direct injection (GDI), 3 complex fuel injection strategies (to exploit charge stratification benefits), 4,5 variable valve timing, 6,7 innovative combustion and ignition processes, 8,9 and water injection. 10 Moreover, the possibility to hybridize vehicles cannot be ignored, which currently is a widespread solution as described in Franco Briguiet et al, 11 Seibel et al, 12 and Smirnov et al 13 However, most of these technologies are simultaneously ''pain and delight'' for designers. In fact, besides undoubted benefits, they introduce drawbacks which cannot be neglected.…”

Section: Introductionmentioning

confidence: 99%

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Modeling of gaseous emissions and soot in 3D-CFD in-cylinder simulations of spark-ignition engines: A methodology to correlate numerical results and experimental data

Berni

Pessina

Paltrinieri

et al. 2022

International Journal of Engine Research

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In order to reduce development costs and time-to market, 1D and 3D CFD tools can support engine design providing reliable estimations of the tailpipe emissions. In particular, 3D-CFD in-cylinder simulations can evaluate formation of both soot and gaseous pollutants inside the combustion chamber. The main issue in such kind of simulations is the validation against experimental findings. In fact, the complexity of the emission measurements does not allow a straightforward one-to-one comparison between numerical and experimental results. Therefore the present paper aims at providing, on the one hand, a robust numerical framework for both gaseous and solid emissions, on the other hand a dedicated post-processing for a fair comparison between simulations and experiments. From a numerical standpoint, a simplified approach is dedicated to gaseous emissions, while a more detailed one is reserved to soot modeling. The latter is based on the Sectional Method, whose reaction rates are tabulated following 0D chemical kinetic simulations of a purposely designed surrogate in a constant pressure reactor. Simulations and experiments proposed in the present analysis are referred to a high-performance turbocharged direct-injection spark-ignition engine operated at part-load and low rpms. On equal performance, revving speed and mean mixture quality, different injection timings are investigated. The developed numerical approach and post-processing ensure a good agreement between simulations and experiments.

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Section: Sectional Soot Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling of gaseous emissions and soot in 3D-CFD in-cylinder simulations of spark-ignition engines: A methodology to correlate numerical results and experimental data

Berni

Pessina

Paltrinieri

et al. 2022

International Journal of Engine Research

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“…Start-stop technology is an integral part of efforts to improve vehicle energy efficiency and reduce the negative impact of road transport on the natural environment. Since the 2010s, this technology has gained popularity and is now standard equipment in many new cars, with ongoing development and refinement to ensure even greater efficiency and effectiveness [16,17].…”

Section: Introductionmentioning

confidence: 99%

Quantifying Emissions in Vehicles Equipped with Energy-Saving Start-Stop Technology: THC and NOx Modeling Insights

Mądziel

2024

Preprint

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Creating accurate emission models capable of capturing the variability and dynamics of modern propulsion systems is crucial for future mobility planning. This paper presents a methodology for creating THC and NOx emission models for vehicles equipped with start-stop technology. A key aspect of this endeavor is to find techniques that accurately replicate the engine stop stages when there are no emissions. To this end, several machine learning techniques were tested using the Python programming language. Random forest and gradient boosting methods demonstrated the best predictive capabilities for THC and NOx emissions, achieving R2 scores of approximately 0.9 for both cold and hot engine emissions. Additionally, recommendations for effective modeling of such emissions from vehicles are presented in the paper.

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“…Startstop technology is an integral part of efforts to improve vehicle energy efficiency and reduce the negative impact of road transportation on the natural environment. Since the 2010s, this technology has gained popularity and is now standard equipment in many new cars, with ongoing development and refinement to ensure even greater efficiency and effectiveness [16,17].…”

Section: Introductionmentioning

confidence: 99%

Quantifying Emissions in Vehicles Equipped with Energy-Saving Start–Stop Technology: THC and NOx Modeling Insights

Mądziel

2024

Energies

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Creating accurate emission models capable of capturing the variability and dynamics of modern propulsion systems is crucial for future mobility planning. This paper presents a methodology for creating THC and NOx emission models for vehicles equipped with start–stop technology. A key aspect of this endeavor is to find techniques that accurately replicate the engine’s stop stages when there are no emissions. To this end, several machine learning techniques were tested using the Python programming language. Random forest and gradient boosting methods demonstrated the best predictive capabilities for THC and NOx emissions, achieving R2 scores of approximately 0.9 for engine emissions. Additionally, recommendations for effective modeling of such emissions from vehicles are presented in the paper.

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Investigation of powertrains in hybrid vehicles

Cited by 3 publications

References 12 publications

Modeling of gaseous emissions and soot in 3D-CFD in-cylinder simulations of spark-ignition engines: A methodology to correlate numerical results and experimental data

Modeling of gaseous emissions and soot in 3D-CFD in-cylinder simulations of spark-ignition engines: A methodology to correlate numerical results and experimental data

Quantifying Emissions in Vehicles Equipped with Energy-Saving Start-Stop Technology: THC and NOx Modeling Insights

Quantifying Emissions in Vehicles Equipped with Energy-Saving Start–Stop Technology: THC and NOx Modeling Insights

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