Browse Topic: Exhaust emissions

Items (17,348)
A cold start occurs when the engine is cranked after being off for a long time, enough for its temperature to drop down to the cold ambient levels. Cold start in an engine is a critical phase as it is characterized by elevated emissions. During a cold start, exhaust components such as catalytic converter do not operate in its optimal temperature zone leading to reduced efficiency in emission control. New regulations for engine emissions are becoming stringent for this condition, hence it is important to accurately determine cold start condition in an engine to optimize the emissions control strategy. Accurate engine off time calculation plays a crucial role in cold start detection, emissions control and On-Board Diagnostics (OBD-II) decision making. This engine off time if greater than 6 hours indicates one of the conditions to confirm a cold start. Other conditions such as Ambient temperature and coolant temperature along with the engine off time confirms a cold start. This paper
MUTHA, MAYURESHTalawadekar, PradnyaKale, Upendra
In Diesel engine exhaust after treatment system (ATS), Nitrogen Oxides (NOx) emissions control is achieved via Selective Catalytic Reduction (SCR) in which AdBlue or Diesel Exhaust Fluid (DEF) plays vital role. But AdBlue freezes below -11°C due to which in cold climate conditions system performance becomes critical as it affects efficiency as well as overall performance leading to safety and compliance with emission standards issue. So, it is essential to have a probabilistic thermal model which can predict the AdBlue temperature as per ambient temperature conditions. The present paper focuses on developing Bayesian Network (BN) based algorithm for AdBlue system by modelling probability of key factors influencing on its performance including AdBlue temperature, Ambient temperature, Coolant temperature, Coolant flow, Vehicle operating conditions etc. The BN Model predicts and ensures continuous learning and improvement of the system, based on operational data. Methodology proposed in
Thakur, ShivamSalunke, Omkar
Cabin air quality plays a crucial role in ensuring passenger comfort, health and driving experience. There have been growing concerns over poor cabin air quality resulting from multiple factors, including infiltration of external pollutants such as particulate matter, volatile organic compounds, emissions from vehicle interior materials, microbial contamination and inadequate ventilation. Therefore, maintaining optimal air quality inside vehicle cabin has become a critical aspect of vehicle climate control systems. Additionally, high humidity levels inside the cabin contribute to mold growth and fogging of windows, further compromising both air quality and visibility. This review explores such factors contributing to poor cabin air quality, where the severity of these issues ranges from mild discomfort and allergic reactions to long-term respiratory ailments. To mitigate these challenges, automotive manufacturers and researchers have implemented various air purification and filtration
Sharma, Shrutika
As the automotive industry explores alternative powertrain options to curb emissions, it is pertinent to refine existing technologies to improve efficiency. The Exhaust Gas Recirculation (EGR) system is one of the pivotal components in emission control strategies for Internal Combustion Engines (ICE). The EGR cooler is crucial in thermal management strategies, as it lowers the temperature of recirculated exhaust gases before feeding it along with fresh air, thereby reducing nitrogen oxides (NOx) emissions. Precise estimation of the EGR cooler outlet temperature is crucial for effective emission control. However, conventional Engine Control Unit (ECU) models fall short, as they often show discrepancies when compared to real-world test data. These models rely on empirical relationships that struggle to capture precisely the transient effect, and real time variation in operating conditions. To address these limitations and improve the accuracy of ECU based model, various signal processing
Kumar, AmitKumar, RamanManojdharan, ArjungopalChalla, KrishnaKramer, Markus
Ducted fuel injection (DFI) was tested for the first time on a production multi-cylinder engine. Design-of-experiments (DoE) testing was carried out for DFI with a baseline ultra-low sulfur diesel (ULSD) fuel as well as three fuels with lower lifecycle carbon dioxide (CO2) emissions: renewable diesel, neat biodiesel (from soy), and a 50/50 blend by volume of biodiesel with renewable diesel denoted B50R50. For all fuels tested, DFI enabled simultaneous reductions of engine-out emissions of soot and nitrogen oxides (NOx) with late injection timings. DoE data were used to develop individual calibrations for steady-state testing with each fuel using the ISO 8178 eight-mode off-road test cycle. Over the ISO 8178 test, DFI with a five-duct configuration and B50R50 fuel reduced soot and NOx by 87% and 42%, respectively, relative to the production engine calibration. Soot reductions generally decreased with increasing engine load. Hydrocarbon and carbon monoxide emissions tended to increase
Ogren, Ryan M.Baumgard, Kirby J.Radhakrishna, VishnuKempin, Robert C.Mueller, Charles J.
The current work is the second installment of a two-part study designed to understand the impact of high-power cold-start events for plug-in electric vehicles (PHEVs) on tailpipe emissions. In part 1, tailpipe emissions and powertrain signals of a modern PHEV measured over three drive cycles identified that high-power cold-start events generated the highest amounts of gaseous and particulate emissions. The trends in emissions data and powertrain performance were specific to the P2-type hybrid topology used in the study. In this second part of the study, the effects of different PHEV hardware configurations are determined. Specifically, the tailpipe emissions of three production plug-in hybrid vehicles, operated over the US06 drive cycle, are characterized. The approach compared the tailpipe emissions of the test vehicles on the basis of the hybrid topologies and corresponding engine operational characteristics during a high-power cold-start event. Analysis of test results showed
Chakrapani, VarunO’Donnell, RyanFataouraie, MohammadWooldridge, Margaret
With the escalating rate of urbanization in China, the urban construction sector is encountering numerous challenges, including issues such as traffic congestion and environmental pollution. To enhance traffic efficiency and offer planning guidance for urban development, this study focuses on the fully or partial opening of community entrances. VISSIM is utilized to examine the community opening and simulate the internal road network, while also employing the SPSS data analysis tool for supplementary analysis. The objective of this method is to compare and analyze the traffic conditions and environmental impact of the community before and after its opening with different automobiles. Through the establishment of a comprehensive evaluation system, the study calculates and analyzes the average vehicle speed, noise levels, energy consumption, and carbon dioxide emissions before and after the opening of the community. Finally, several recommendations are proposed to enhance community
Li, MengyuanZhuo, ChenxuXiong, SiminXu, Lihao
In recent years, the greenhouse effect has become a major challenge for sustainable development, with carbon dioxide emissions playing a significant role. In 2022, China’s carbon dioxide emissions reached 12,667,430 tons [1], the highest globally, with the transportation sector contributing about 8% of this, and road transportation accounting for 90% of the sector’s emissions. To promote green development, the Chinese government emphasizes efficient resource use, energy conservation, and emissions reduction, aiming to build a strong transport system by 2035. Understanding carbon emissions in expressway construction is crucial for green development. Studies on highway carbon emissions focus on emissions from road construction and vehicle operation. For example, Chen et al. used a “bottom-up” method to account for emissions during construction, while Tu et al. created a vehicle carbon emission model during operation. With the expanding highway network, maintenance has become essential
You, ShutingXu, ZihengGao, YihanZhang, ZhishuoLi, Zihao
The demand for alternate fuel continues to grow steadily, while energy sources are being researched and explored every year. Considering the energy demand and fuel cost this research was initiated to identify better sources for fuel production. Also the emission released into the atmosphere causes significant influence in the global market in terms of pollution, which was also a prime motive toward this research analysis. A green biodiesel, fatty acid alkyl ester, has attracted much attention as an environmentally friendly diesel fuel. This is due to several advantages, especially that fatty acid alkyl ester is renewable, biodegradable, and has less toxic properties as a fuel. In this article, cottonseed (Gossypium hirsutum) biodiesel and algal (Stoechospermum marginatum) biodiesel was prepared with a yield of 94% and 85%, respectively. Single-stage transesterification was performed since the free fatty acid percentage was within the limit. The performance characteristics in terms of
Godwin, John J.Hariram, V.Muthiya, Solomon JenorisSambandam, PadmanabhanPrathik, S. J.Santhosh, K.Baskar, S.Boopathi, D.
The nvPM Mission Emissions Estimation Methodology (MEEM) was previously developed to estimate nonvolatile particulate matter (nvPM) emissions from ground certification data using the publicly available data from the International Civil Aviation Organization (ICAO) Aircraft Engine Emissions Databank (EEDB). In order to potentially improve the accuracy of nvPM emissions estimation and to enhance its usefulness to modelers, the method was revised to make use of fuel flow correlations and similar altitude corrections as used in the Boeing Fuel Flow Method 2 (BFFM2). The new fuel flow approach allows for improved trade-off-type assessments between nvPM and gaseous emissions—i.e., less relative uncertainties when assessing results from the two methods. Like the former MEEM, the new method, MEEM2, can be used with just publicly available data such as nvPM emissions indices (EI) from the EEDB as well as predicted fuel flows from publicly available aircraft performance models. MEEM2 has been
Ahrens, DeniseKim, BrianMéry, YoannZelina, JosephDudebout, RudolphMiake-Lye, Richard C.
Air pollution is a significant long-term public health issue, with on-road traffic emissions being a primary contributor, especially in urban areas. Remote emission sensing (RES) is an innovative method for large-scale monitoring of vehicle emissions. It not only enables accurate detection of pollutants from vehicles under real-world driving conditions but also offers actionable insights to optimize engine performance. The point sampling-based RES technique involves sampling the vehicle exhaust plume along the roadside with a sampling line and using exhaust analyzers. In this method, the sampling line is placed alongside the road for sample extraction. Thus, the sampling position and knowledge regarding the spread of the exhaust plumes are crucial. Other modern RES systems utilize laser absorption spectroscopy to measure the pollutants in vehicle exhaust. For accurate absorption measurements, the laser’s height must align with the height of the exhaust plume, and the absorption length
Imtiaz, Hafiz HashimLiu, YingjieSchaffer, PaulKupper, MartinBergmann, Alexander
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