Quantitative study of vehicle CO2 emission at various temperatures and road loads

Wang, Yachao; Zhao, Hongbin; Yin, Hong; Yang, Zhen; Hao, Lijun; Tan, Jianwei; Wang, Xin; Zhang, Mengzhu; Li, Jiachen; Lyu, Liqun; Wang, Huaiyu; Wang, Chongyao; Tan, Dan; Ge, Yunshan

doi:10.1016/j.fuel.2022.123911

Cited by 19 publications

(3 citation statements)

References 34 publications

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“…When the torque is higher than 20 Nm, the CO 2 emission increases sharply. Under such conditions, more fuel is delivered into combustion chamber of gasoline engines, result in more CO, which is confirmed in the bench test [44]. Small torque operation may be a good option for GDI vehicles to reduce CO 2 emissions, being consistent with the conditions of small acceleration.…”

Section: Real-world Co 2 Emission Rate Distributionssupporting

confidence: 59%

Real-World Pipe-Out Emissions from Gasoline Direct Injection Passenger Cars

et al. 2022

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The analysis of real-world emissions is necessary to reduce the emissions of vehicles during on-road driving. In this paper, the matrix of gasoline direct injection passenger cars is applied to analyze the real-world emissions. The results show that high acceleration and high speed conditions are major conditions for the particulate number emissions, and the particulate number emissions are positively correlated with torque and throttle opening. The catalyst temperature and saturation are important factors that affect nitrogen oxide emission. The nitrogen oxide emissions of low speed and low torque conditions cannot be ignored in real-world driving. The carbon dioxide emissions are positively correlated with acceleration, torque and throttle opening. Once the vehicles are in the acceleration condition, the carbon dioxide emissions increase rapidly. The vehicles with higher average emission factors are more susceptible to driving behaviors, and the differences in the emission factors are more obvious, leading to an increase in the difficulty of emission control.

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Section: Real-world Co 2 Emission Rate Distributionssupporting

confidence: 59%

Real-World Pipe-Out Emissions from Gasoline Direct Injection Passenger Cars

et al. 2022

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“…Some measures have been taken by governments to reduce the emission of pollutants into the atmosphere. The Paris Agreement, signed during the United Nations Framework Convention on Climate Change (UNFCCC) in 2016, provides for a reduction in and adaptation of greenhouse gas emissions [ 41 ]. To meet environmental requirements, a catalytic converter is used by cars to transform polluting gases into non-polluting substances: (i) Hydrocarbons are transformed into carbon dioxide (CO 2 ) and water (H 2 O); (ii) carbon monoxide is transformed into carbon dioxide; (iii) NOx is reduced in nitrogen and oxygen.…”

Section: Fundamentals Of Vehicular Emissionsmentioning

confidence: 99%

A TinyML Soft-Sensor Approach for Low-Cost Detection and Monitoring of Vehicular Emissions

Andrade

Silva

et al. 2022

Sensors

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Vehicles are the major source of air pollution in modern cities, emitting excessive levels of CO2 and other noxious gases. Exploiting the OBD-II interface available on most vehicles, the continuous emission of such pollutants can be indirectly measured over time, although accuracy has been an important design issue when performing this task due the nature of the retrieved data. In this scenario, soft-sensor approaches can be adopted to process engine combustion data such as fuel injection and mass air flow, processing them to estimate pollution and transmitting the results for further analyses. Therefore, this article proposes a soft-sensor solution based on an embedded system designed to retrieve data from vehicles through their OBD-II interface, processing different inputs to provide estimated values of CO2 emissions over time. According to the type of data provided by the vehicle, two different algorithms are defined, and each follows a comprehensive mathematical formulation. Moreover, an unsupervised TinyML approach is also derived to remove outliers data when processing the computed data stream, improving the accuracy of the soft sensor as a whole while not requiring any interaction with cloud-based servers to operate. Initial results for an embedded implementation on the Freematics ONE+ board have shown the proposal’s feasibility with an acquisition frequency equal to 1Hz and emission granularity measure of gCO2/km.

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“…Wang et al conducted tests on CO 2 emissions from two gasoline vehicles under four distinct environmental temperatures. The results showed that the CO 2 emission deteriorated under cold ambient temperatures because of the increased internal resistance [21]. Zhu et al (2022) used a machine learning model to confirm that engine load percent and engine speed were the most dominant factors affecting vehicular carbon emissions based on PEMS data [22].…”

Section: Introductionmentioning

confidence: 99%

Exhaust Emissions from Gasoline Vehicles with Different Fuel Detergency and the Prediction Model Using Deep Learning

Zhang,

Chen,

Xie

et al. 2023

Sensors

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Enhancing gasoline detergency is pivotal for enhancing fuel efficiency and mitigating exhaust emissions in gasoline vehicles. This study investigated gasoline vehicle emission characteristics with different gasoline detergency, explored synergistic emission reduction potentials, and developed versatile emission prediction models. The results indicate that improved fuel detergency leads to a reduction of 5.1% in fuel consumption, along with decreases of 3.2% in total CO2, 55.4% in CO, and 15.4% in HC emissions. However, during low-speed driving, CO2 and CO emissions reductions are limited, and HC emissions worsen. A synergistic emission reduction was observed, particularly with CO exhibiting a pronounced reduction compared to HC. The developed deep-learning-based vehicle emission model for different gasoline detergency (DPVEM-DGD) enables accurate emission predictions under various fuel detergency conditions. The Pearson correlation coefficients (Pearson’s r) between predicted and measured values of CO2, CO, and HC emissions before and after adding detergency agents are 0.913 and 0.934, 0.895 and 0.915, and 0.931 and 0.969, respectively. The predictive performance improves due to reduced peak emissions resulting from improved fuel detergency. Elevated gasoline detergency not only reduces exhaust emissions but also facilitates more refined emission management to a certain extent.

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Quantitative study of vehicle CO2 emission at various temperatures and road loads

Cited by 19 publications

References 34 publications

Real-World Pipe-Out Emissions from Gasoline Direct Injection Passenger Cars

Real-World Pipe-Out Emissions from Gasoline Direct Injection Passenger Cars

A TinyML Soft-Sensor Approach for Low-Cost Detection and Monitoring of Vehicular Emissions

Exhaust Emissions from Gasoline Vehicles with Different Fuel Detergency and the Prediction Model Using Deep Learning

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