Remote Sensing Measurements and Simulations for Real Driving Emission Characterization of Vehicles

Plogmann, Justin; Gubser, Ariane; Eggenschwiler, Panayotis Dimopoulos

doi:10.1007/978-3-658-37011-4_23

Cited by 2 publications

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“…To provide additional insights on the exhaust plume dispersion downstream a realistic vehicle and how this affects an on-road RES measurement, in the present work, a parameter study deepening and extending the one by [18] was carried out to relate various properties of the exhaust plume to the given circumstances. Since the parameter study led to numerous simulations, this was another reason URANS was chosen instead of LES or hybrid LES/RANS [19].…”

Section: Introductionmentioning

confidence: 99%

URANS Simulations of Vehicle Exhaust Plumes with Insight on Remote Emission Sensing

et al. 2023

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Remote Emission Sensing (RES) is a measurement method based on absorption spectroscopy for the determination of pollutant concentrations. The absorption of the exhaust plume of a vehicle is measured from the roadside without intervention by means of a light/laser barrier during a short measurement (∼0.5 s) and concentration ratios of pollutants (e.g., NOx to CO2) are estimated. Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations of exhaust plumes in vehicle wakes are performed using the k-ω SST turbulence model with focus on pollutant dispersion. The simulation setup has been validated by a comparison with experimentally obtained drag coefficients. The resulting concentration fields represent the pollutants available for measurements by a RES device. The influence of the characteristics of the RES device on the measurement is assessed. In addition, investigations involve several environmental and vehicle related parameters. The results demonstrate that due to strong turbulence, mixing is enhanced and the exhaust plumes rapidly disperse in the near vehicle wakes. Results show that emission characteristics of a vehicle are contained downstream for approximately half the vehicle length, regardless of different vehicle configurations, driving and ambient parameters. Further downstream dispersion of pollutants results in concentrations that are less than 1/100 of the pollutant concentration in the vehicle’s exhaust tailpipe implying that RES devices have to measure at a high sampling frequency. Therefore, reliable determination of the concentration ratios of pollutant at high vehicle velocities requires the RES device to operate in the order of 1000 Hz sampling frequency. Ultimately, the numerical simulations not only help to understand exhaust plume dispersion, but provide a very useful tool to minimize RES uncertainties.

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Section: Introductionmentioning

confidence: 99%

URANS Simulations of Vehicle Exhaust Plumes with Insight on Remote Emission Sensing

et al. 2023

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A Consistent Dual-Mesh Framework for Hybrid LES/RANS Simulations of Vehicle Exhaust Plumes: Implications for Remote Emission Sensing

Plogmann,

Dimopoulos Eggenschwiler,

Pierce

et al. 2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">Remote emission sensing (RES) is a non-intrusive measurement method based on absorption spectroscopy, which allows for the determination of pollutant concentrations in vehicle exhaust plumes. By measuring the absorption of the exhaust plume from the roadside using a light/laser barrier, concentration ratios of pollutants, such as nitrogen oxides to carbon dioxide, can be estimated. Computational fluid dynamics (CFD) has been employed to simulate vehicle exhaust plumes due to uncertainties in RES capabilities.</div><div class="htmlview paragraph">In a previous study, Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations were conducted to investigate the dispersion of vehicle exhaust plumes under various ambient/driving conditions and provide insights for RES applications. However, the accuracy of these simulations can be further improved. Therefore, this study focuses on enhancing the simulation accuracy by employing large eddy simulations (LES).</div><div class="htmlview paragraph">The computational cost of LES approximately scales with <i>Re</i><sup>1<i>.</i>8</sup> in wall-bounded flows, making it impractical for this application given that the computational mesh has to be substantially refined in the near-wall region. To overcome this challenge, a consistent hybrid LES/RANS dual-mesh approach is adopted. The hybrid turbulence modeling framework is extended to account for a species- and temperature-dependent (density-varying) flow to accurately simulate the vehicle exhaust plume.</div><div class="htmlview paragraph">To ensure consistency between the RANS and averaged LES solutions, additional drift terms are introduced in the corresponding equations. The results demonstrate that the hybrid LES/RANS solver leads to significantly improved consistency in comparison to the standalone RANS and LES results. This turbulence-modeling framework is not only very promising for industrial flow simulations but also provides valuable guidance for the future development of RES devices.</div><div class="htmlview paragraph">This work highlights the potential of hybrid LES/RANS simulations in enhancing the accuracy of vehicle exhaust plume dispersion predictions, which is crucial for optimizing RES measurements. The findings pave the way for further advancements in RES technology and contribute to the ongoing development of efficient and accurate emission monitoring systems.</div></div>

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Remote Sensing Measurements and Simulations for Real Driving Emission Characterization of Vehicles

Cited by 2 publications

References 3 publications

URANS Simulations of Vehicle Exhaust Plumes with Insight on Remote Emission Sensing

URANS Simulations of Vehicle Exhaust Plumes with Insight on Remote Emission Sensing

A Consistent Dual-Mesh Framework for Hybrid LES/RANS Simulations of Vehicle Exhaust Plumes: Implications for Remote Emission Sensing

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