國立虎尾科技大學 |

Gasoline Engine-Out Particulate Matter Characterization and Control & Low-Cost Particulate Matter Light Scattering Sensing = = Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Gasoline Engine-Out Particulate Matter Characterization and Control & Low-Cost Particulate Matter Light Scattering Sensing =/
Reminder of title:	Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan.
remainder title:	Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan.
Author:	Chen, Weiqi.
Description:	1 online resource (287 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
Contained By:	Dissertations Abstracts International85-06B.
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798381177695

Gasoline Engine-Out Particulate Matter Characterization and Control & Low-Cost Particulate Matter Light Scattering Sensing = = Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan.
Chen, Weiqi.

Gasoline Engine-Out Particulate Matter Characterization and Control & Low-Cost Particulate Matter Light Scattering Sensing =Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan.Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan. - 1 online resource (287 pages)

Source: Dissertations Abstracts International, Volume: 85-06, Section: B.

Thesis (Ph.D.)--University of Minnesota, 2023.

Includes bibliographical references

Particulate matter (PM) consists of minuscule solid or liquid airborne particles. Among these particles, fine particles like PM2.5 (particles with a diameter of 2.5 micrometers or smaller) are particularly concerning due to their ability to deeply penetrate the lungs and even enter the bloodstream and contribute to various adverse health effects, including an increased risk of heart disease, lung cancers, and other health issues. The engine combustion process of fossil fuels is a significant contributor to PM2.5 pollution in many urban areas. Furthermore, recent advancements in low-cost light-scattering PM sensors present a cost-effective solution for real-time spatiotemporal PM monitoring. Despite their benefits, these sensors have limitations in data quality due to relaxed quality control and their sensitivity to environmental conditions affecting light scattering. Therefore, this dissertation is driven by two primary objectives: Part 1 aims to mitigate Engine-out PM emissions by reducing their formation in the combustion chamber and improving filtration within the aftertreatment system. On the other hand, Part 2 is dedicated to evaluating and improving low-cost light-scattering PM sensor technology and exploring its diverse applications.In Part 1 Chapter 2, we investigated how combustion strategy and ethanol content affect particle properties in emissions from a lean burn gasoline direct injection (GDI) engine. GDI engines, increasingly used in light-duty vehicles for higher power and fuel efficiency, tend to produce elevated PM emissions. Different combustion strategies and fuel properties (like volatility and aromaticity) influence PM emission rates and characteristics. We measured particle number, size, mass concentration, effective density, and mass-mobility exponent for a GDI engine fueled with E10, E30, and E50, and operated in three combustion modes: stoichiometric, lean homogeneous, and lean stratified. Key findings include lower particle number and higher effective density with stoichiometric operation using E10, while lean homogeneous operation resulted in the smallest particles and lowest effective density. Lean stratified operation produced the highest particle concentrations and effective densities between lean homogeneous and stoichiometric conditions. Ethanol content changes influenced mass and number concentrations and effective density differently based on the combustion mode.In Part 1 Chapters 3-4, we focus on enhancing PM filtration control in gasoline particulate filters (GPFs) within aftertreatment systems, particularly for gasoline direct injection (GDI) engines that emit higher PM levels. GPFs use deep-bed filtration through ceramic walls in a honeycomb channel structure for effective PM emission control. The increasingly stringent global PM emissions regulations have amplified the demand for GPFs. Chapter 3 introduces a rapid screening method using wafer-based nanoscale membranes to improve GPF performance. It explores the use of artificial aerosols to synthesize nano-scale membranes resembling soot cake in diesel particulate filters (DPFs), enhancing GPF performance. The experiments show that membranes with larger aggregate sizes or under lower face velocity yield significantly improved performance.Chapter 4 delves into a theoretical study, while Chapter 3 focuses on experimental investigation. In Chapter 4, an analytical filter model is developed to understand efficiency and pressure drop under engine conditions, aiming to reduce development costs for meeting emission regulations and engine performance targets. The study treats the deep bed regime as two co-existing filters with different geometries based on natural morphologies, dynamically considering changes in pore size distribution and soot dendrite growth during loading. Model validation using 12 sets of experimental filter loading data demonstrates reasonable predictions for filter efficiency and pressure drop during deep-bed loading for various GPF wall-flow filters and operating conditions. The model was also used to examine the impact of porosity, mean pore size, and pore size distribution on filter loading performance, suggesting strategies for future filter optimization.Part 2 addresses the second objective of the dissertation, focusing on low-cost light-scattering PM sensors. In Chapter 6, the study describes the development of sensor test systems, including a lab-simulated environmental chamber, a field test sensor chamber, and a sensor data acquisition platform. The lab environmental chamber can simulate various environmental conditions for sensor performance assessment, including RH, temperature, aerosol types, and concentrations. Conversely, the field sensor chamber is designed to protect sensors in outdoor environments while ensuring precise sampling. The data acquisition platform involves the development of a custom printed circuit board (PCB) design and a dedicated sensor website, essential for extensive data collection, wireless transmission, and online storage capabilities.Chapter 7 begins by presenting a thorough assessment of sensor performance by conducting side-by-side experiments with gravimetric filter method (Federal Reference Methods (FRMs)) as reference to examine the dynamic response of more than 10 different popular low-cost light-scattering core sensors under diverse conditions in both controlled laboratory settings and the real-world outdoor environment. When measuring atmospheric salt particles, it was found that the low-cost sensors generally provide accurate readings within the 30% to 70% RH range but exhibit a significant spike after surpassing the deliquescence relative humidity (DRH). When environment shifts from wet to dry conditions, it was observed that sensor bias is more pronounced compared to the increasing RH conditions. Moreover, the behavior of the sensor was observed to demonstrate a strong dependency on both concentrations and particle composition. Based on the analysis, the performance ranking for all the tested sensors is provided.Following the performance assessment, Chapter 7 demonstrated various methods for improving sensor performance, including 1) Utilizing calibrations employing a multivariable nonlinear model that incorporates RH level and differentiate the models for different concentration levels and RH hysteresis; 2) implementing sensor accessory/addon, specifically, a silica dryer was affixed to the sensor inlet to mitigate the RH impact; 3) and exploring different sensing theories to enhance sensor lower detectable size limit. Moving to Chapter 8, the dissertation delved into exploring the various potential applications of low-cost light-scattering PM sensors. These applications included spatiotemporal measurements and filtration applications. By exploring these applications, the advantages of low-cost sensors compared to traditional reference instruments were highlighted, and the insights into the opportunities associated with the deployment of these sensors were provided.The main body of this dissertation comprises the eight studies below. Among them, (Chen et al., 2023a, 2023b, 2021b, 2021a; Ye et al., 2022) have been published, one is presently under review, and two are in preparation.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381177695Subjects--Topical Terms:

557493
Mechanical engineering.
Subjects--Index Terms:

Engine emission controlIndex Terms--Genre/Form:

554714
Electronic books.

Gasoline Engine-Out Particulate Matter Characterization and Control & Low-Cost Particulate Matter Light Scattering Sensing = = Qi you fa dong ji pai fang ke li wu de te xing yu kong zhi ji di cheng ben ke li wu guang san she chuan gan.
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500 $a Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
500 $a Advisor: Pui, David Y. H.;Kittelson, David B.
502 $a Thesis (Ph.D.)--University of Minnesota, 2023.
504 $a Includes bibliographical references
520 $a Particulate matter (PM) consists of minuscule solid or liquid airborne particles. Among these particles, fine particles like PM2.5 (particles with a diameter of 2.5 micrometers or smaller) are particularly concerning due to their ability to deeply penetrate the lungs and even enter the bloodstream and contribute to various adverse health effects, including an increased risk of heart disease, lung cancers, and other health issues. The engine combustion process of fossil fuels is a significant contributor to PM2.5 pollution in many urban areas. Furthermore, recent advancements in low-cost light-scattering PM sensors present a cost-effective solution for real-time spatiotemporal PM monitoring. Despite their benefits, these sensors have limitations in data quality due to relaxed quality control and their sensitivity to environmental conditions affecting light scattering. Therefore, this dissertation is driven by two primary objectives: Part 1 aims to mitigate Engine-out PM emissions by reducing their formation in the combustion chamber and improving filtration within the aftertreatment system. On the other hand, Part 2 is dedicated to evaluating and improving low-cost light-scattering PM sensor technology and exploring its diverse applications.In Part 1 Chapter 2, we investigated how combustion strategy and ethanol content affect particle properties in emissions from a lean burn gasoline direct injection (GDI) engine. GDI engines, increasingly used in light-duty vehicles for higher power and fuel efficiency, tend to produce elevated PM emissions. Different combustion strategies and fuel properties (like volatility and aromaticity) influence PM emission rates and characteristics. We measured particle number, size, mass concentration, effective density, and mass-mobility exponent for a GDI engine fueled with E10, E30, and E50, and operated in three combustion modes: stoichiometric, lean homogeneous, and lean stratified. Key findings include lower particle number and higher effective density with stoichiometric operation using E10, while lean homogeneous operation resulted in the smallest particles and lowest effective density. Lean stratified operation produced the highest particle concentrations and effective densities between lean homogeneous and stoichiometric conditions. Ethanol content changes influenced mass and number concentrations and effective density differently based on the combustion mode.In Part 1 Chapters 3-4, we focus on enhancing PM filtration control in gasoline particulate filters (GPFs) within aftertreatment systems, particularly for gasoline direct injection (GDI) engines that emit higher PM levels. GPFs use deep-bed filtration through ceramic walls in a honeycomb channel structure for effective PM emission control. The increasingly stringent global PM emissions regulations have amplified the demand for GPFs. Chapter 3 introduces a rapid screening method using wafer-based nanoscale membranes to improve GPF performance. It explores the use of artificial aerosols to synthesize nano-scale membranes resembling soot cake in diesel particulate filters (DPFs), enhancing GPF performance. The experiments show that membranes with larger aggregate sizes or under lower face velocity yield significantly improved performance.Chapter 4 delves into a theoretical study, while Chapter 3 focuses on experimental investigation. In Chapter 4, an analytical filter model is developed to understand efficiency and pressure drop under engine conditions, aiming to reduce development costs for meeting emission regulations and engine performance targets. The study treats the deep bed regime as two co-existing filters with different geometries based on natural morphologies, dynamically considering changes in pore size distribution and soot dendrite growth during loading. Model validation using 12 sets of experimental filter loading data demonstrates reasonable predictions for filter efficiency and pressure drop during deep-bed loading for various GPF wall-flow filters and operating conditions. The model was also used to examine the impact of porosity, mean pore size, and pore size distribution on filter loading performance, suggesting strategies for future filter optimization.Part 2 addresses the second objective of the dissertation, focusing on low-cost light-scattering PM sensors. In Chapter 6, the study describes the development of sensor test systems, including a lab-simulated environmental chamber, a field test sensor chamber, and a sensor data acquisition platform. The lab environmental chamber can simulate various environmental conditions for sensor performance assessment, including RH, temperature, aerosol types, and concentrations. Conversely, the field sensor chamber is designed to protect sensors in outdoor environments while ensuring precise sampling. The data acquisition platform involves the development of a custom printed circuit board (PCB) design and a dedicated sensor website, essential for extensive data collection, wireless transmission, and online storage capabilities.Chapter 7 begins by presenting a thorough assessment of sensor performance by conducting side-by-side experiments with gravimetric filter method (Federal Reference Methods (FRMs)) as reference to examine the dynamic response of more than 10 different popular low-cost light-scattering core sensors under diverse conditions in both controlled laboratory settings and the real-world outdoor environment. When measuring atmospheric salt particles, it was found that the low-cost sensors generally provide accurate readings within the 30% to 70% RH range but exhibit a significant spike after surpassing the deliquescence relative humidity (DRH). When environment shifts from wet to dry conditions, it was observed that sensor bias is more pronounced compared to the increasing RH conditions. Moreover, the behavior of the sensor was observed to demonstrate a strong dependency on both concentrations and particle composition. Based on the analysis, the performance ranking for all the tested sensors is provided.Following the performance assessment, Chapter 7 demonstrated various methods for improving sensor performance, including 1) Utilizing calibrations employing a multivariable nonlinear model that incorporates RH level and differentiate the models for different concentration levels and RH hysteresis; 2) implementing sensor accessory/addon, specifically, a silica dryer was affixed to the sensor inlet to mitigate the RH impact; 3) and exploring different sensing theories to enhance sensor lower detectable size limit. Moving to Chapter 8, the dissertation delved into exploring the various potential applications of low-cost light-scattering PM sensors. These applications included spatiotemporal measurements and filtration applications. By exploring these applications, the advantages of low-cost sensors compared to traditional reference instruments were highlighted, and the insights into the opportunities associated with the deployment of these sensors were provided.The main body of this dissertation comprises the eight studies below. Among them, (Chen et al., 2023a, 2023b, 2021b, 2021a; Ye et al., 2022) have been published, one is presently under review, and two are in preparation.
520 $a 颗粒物（PM）由微小的固体或液体空气悬浮颗粒组成。在这些颗粒中，细颗粒如PM2.5（直径为2.5微米或更小的颗粒）尤其令人担忧，因为它们能够深入渗透到肺部，甚至进入血液，导致各种不良健康效应，包括增加心脏病、肺癌和其他健康问题的风险。化石燃料的发动机燃烧过程是许多城市地区PM2.5污染的重要原因。此外，近年来低成本的光散射PM传感器的进步为实时时空PM监测提供了经济有效的解决方案。尽管具有优势，但由于放松的质量控制和对光散射影响的环境条件的敏感性，这些传感器在数据质量方面存在限制。因此，这篇论文的主要目标有两个：第一部分旨在通过在燃烧室中减少PM的形成和改善后处理系统内的过滤来减轻发动机排放的PM。另一方面，第二部分致力于评估和改进低成本光散射PM传感器技术，并探索其多样化的应用。在第一部分第2章中，我们研究了燃烧策略和乙醇含量如何影响燃烧汽油直喷（GDI）发动机排放的颗粒特性。GDI发动机在轻型车辆中越来越多地用于提高动力和燃油效率，往往产生较高的PM排放。不同的燃烧策略和燃料性质（如挥发性和芳香性）影响PM排放速率和特性。我们对使用E10、E30和E50燃料的GDI发动机进行了测量，分别在化学计量、稀薄均质和稀薄分层三种燃烧模式下进行了操作。关键发现包括在使用E10进行化学计量操作时，颗粒数较低且有效密度较高，而在稀薄均质操作下产生的颗粒最小，有效密度最低。稀薄分层操作产生了介于稀薄均质和化学计量条件之间的最高颗粒浓度和有效密度。乙醇含量的变化影响了质量和数量浓度以及根据燃烧模式而异的有效密度。在第一部分第3-4章中，我们专注于提高汽油颗粒过滤器（GPFs）在后处理系统中的PM过滤控制，特别是对于排放较高PM水平的汽油直喷（GDI）发动机。GPFs通过陶瓷壁进行深层过滤，呈蜂窝通道结构，以实现有效的PM排放控制。全球日益严格的PM排放法规加大了对GPFs的需求。第3章介绍了一种使用基于晶片的纳米膜的快速筛选方法，以提高GPF性能。它探讨了使用人工气溶胶合成类似柴油颗粒过滤器（DPFs）中烟灰层的纳米膜，增强了GPF性能。实验表明，具有较大聚集尺寸或在较低面速下的膜明显改善了性能。第4章深入研究理论研究，而第3章专注于实验研究。在第4章中，开发了一个分析过滤器模型，以了解在发动机条件下的效率和压降，旨在减少满足排放法规和发动机性能目标的开发成本。该研究将深层床层视为两个共存的具有不同几何形态的过滤器，根据自然形态动态考虑孔径分布和负载过程中烟灰树枝的增长。使用12组实验过滤器负载数据的模型验证显示，对于各种GPF壁流过滤器和操作条件，在深层床层负载期间，对过滤器效率和压降的合理预测。该模型还用于研究孔隙率、平均孔径和孔径分布对过滤器负载性能的影响，并提出了未来过滤器优化的策略。第2部分解决了论文的第二个目标，重点关注低成本光散射PM传感器。在第6章中，研究描述了传感器测试系统的开发，包括实验室模拟环境室、野外测试传感器室和传感器数据采集平台。实验室环境室可以模拟各种环境条件，用于传感器性能评估，包括相对湿度、温度、气溶胶类型和浓度。相反，野外传感器室旨在在户外环境中保护传感器，同时确保精确取样。数据采集平台涉及开发定制的印刷电路板（PCB）设计和专用传感器网站，对于广泛的数据收集、无线传输和在线存储功能至关重要。第7章首先通过与重力法过滤方法（联邦参考方法（FRMs））进行并行实验，评估了10多种不同热门低成本光散射核心传感器在受控实验室环境和现实世界户外环境中不同条件下的动态响应。在测量大气盐颗粒时，发现低成本传感器通常在30%至70%相对湿度范围内提供准确读数，但在超过湿度解凝相对湿度（DRH）后显示出显著的峰值。当环境从湿润转变为干燥条件时，观察到传感器偏差与湿度增加的情况相比更为显著。此外，观察到传感器的行为对浓度和颗粒组成都表现出较强的依赖性。基于分析，提供了所有测试传感器的性能排名。在性能评估之后，第7章展示了改善传感器性能的各种方法，包括1）使用多变量非线性模型进行校准，该模型结合湿度水平，并区分不同浓度水平和湿度滞后的模型；2）实施传感器附件/附加件，具体而言，将硅胶干燥器固定在传感器进口以减轻湿度影响；3）并探索不同的感测理论以提高传感器的最低可检测尺寸限制。转至第8章，论文深入研究了低成本光散射PM传感器的各种潜在应用。这些应用包括时空测量和过滤应用。通过探索这些应用，突出了低成本传感器相对于传统参考仪器的优势，并提供了与这些传感器部署相关的机会的见解。
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650 4 $a Mechanical engineering. $3 557493
650 4 $a Particle physics. $3 1335339
650 4 $a Environmental engineering. $3 557376
653 $a Engine emission control
653 $a Filtration
653 $a Gasoline particulate filter
653 $a Light-scattering sensing
653 $a Membrane filter
653 $a Particulate matter
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880 1 0 $6 245-01/$1 $a Gasoline Engine-Out Particulate Matter Characterization and Control & Low-Cost Particulate Matter Light Scattering Sensing = $b 汽油发动机排放颗粒物的特性与控制及低成本颗粒物光散射传感.
880 3 1 $6 246-02/$1 $a 汽油发动机排放颗粒物的特性与控制及低成本颗粒物光散射传感.