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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Transportation Fuel Resiliency: Case Study of Tampa Bay

Here, this case study presents findings from an analysis of the emergency preparation and response for Hurricane Irma, the most recent hurricane impacting the Tampa Bay region. The Tampa Bay region, in particular, is considered one of the most vulnerable areas in the United States to hurricanes and severe tropical weather. A particular vulnerability stems from how all petroleum fuel comes to the area by marine transport through Port Tampa Bay, which can be (and has been in the past) impacted by hurricanes and tropical storms. The case study discussed in this paper covers previous fuel challenges, vulnerabilities, and lessons learned by key Tampa Bay public agency fleets during the past 10 years (mainly as a result of the most recent 2017 Hurricane Irma) to explore ways to improve the area’s resilience to natural disasters. Some of the strategies for fuel-supply resiliency include maintaining emergency fuel supply, prioritizing fuel use, strategically placing the assets around the region to help with recovery, investing in backup generators (including generators powered by alternative fuels), planning for redundancies in fuel supply networks, developing more efficient communication procedures between public fleets, hurricane preparedness-planning, and upgrading street drainage systems to reduce the threat of local flooding.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Dynamic Ride-Matching for Large-Scale Transportation Systems

Efficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem’s network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Toward Human-Centric Transportation and Energy Metrics: Influence of Mode, Vehicle Occupancy, Trip Distance, and Fuel Economy

Traditional metrics measuring transportation and energy outcomes can be augmented to better represent impacts on people's lives and systems-level performance. In this context, this study introduces two novel metrics: road capacity (as number of people traveling and accessing services) and energy intensity (as energy use for people traveling and accessing services). Current national-level distributions of available data in the United States for factors contributing to the two new integrated metrics are used as context to evaluate potential outcomes. These factors include vehicle occupancy, mode share, fuel economy, and trip distance. Variations in input values provide insights on how these factors shape efficiencies in road capacity and energy intensity. Parametric sensitivity analysis indicates that the impact of each input depends upon the metric being evaluated. For the human-centered road capacity mobility metric, increasing vehicle occupancy has the largest effect – twice that of increasing mode share for bike, walk, and transit. For the energy intensity mobility metric, the effect of improving fuel economy is the largest. However, when the focus is on accessibility (instead of mobility), for both metrics the effect of lowering average trip distance is the largest. Additionally, a novel interactive tool to visualize the results for various parameter combinations makes the metrics practitioner ready. The findings suggest that the diffusion of new human-centric metrics that benchmark outcomes associated with road capacity and energy may be significant in motivating new sustainable transportation investments and efficient utilization of infrastructure, mobility assets, and services.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

ASPIRES: Airport Shuttle Planning and Improved Routing Event-driven Simulation

Most of the existing traffic simulation packages require significant calibration work to be able to reflect reality. To evaluate special operations including emerging technologies, a microscopic simulation that tracks detailed interactions of all the elements of the traffic systems is usually needed. This type of simulation is usually computationally demanding. This work developed an Airport Shuttle Planning and Improved Routing Event-driven Simulation (ASPIRES) package to simulate and evaluate current, potential, and future airport shuttle operations. Here, the simulation was driven by data and thus did not require much calibration effort. The discrete-event simulation nature of ASPIRES makes the simulation computationally efficient. Simulating 1 day of shuttle operations takes less than 2s. The study site of this work is the Dallas/Fort Worth International Airport in the U.S. The shuttle service that connects the five terminals of the airport and the rental car center was studied. Travel times, dwell times, and passenger arrivals were simulated using empirical distributions derived mainly from real data to capture the stochastic nature of the rental car center shuttle bus operations. Data on bus miles traveled, bus energy consumption, passenger wait times, and passengers left behind at stops were collected to study the trade-off between energy use and passenger experience. Electric bus and on-demand bus operations were also included. The simulation outputs can show passengers statistics at terminals, shuttles statistics, and charging station statistics. ASPIRES cannot be used to model a generic traffic system but is well-suited for fleet systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

How Time Inefficient and Uncertain are Paratransit Trips Compared to Car Trips

The Americans with Disabilities Act (ADA) stipulates that paratransit mobility be comparable to public transit. However, with just under 5% of the population relying on public transportation, transit is not a representative benchmark. To highlight this inequality, we compare trip times by paratransit to counterfactual car-based travel. Using 2.5 years of demand data from the Denver Regional Transportation District's Access-a-Ride service, we compare paratransit trip times to counterfactual car-based trips for the same origin-destination pairs, controlling for various trip characteristics. Compared to car travel, the findings indicate high variability and uncertainty associated with paratransit trip times. For the same origin-destination pairs, the mean paratransit trip time is almost twice that of the mean car travel time, with a standard deviation for paratransit trip time fourfold that of the standard deviation for car trip time. For perspective, traveling an average of 10 mi during the 7-8 a.m. morning peak can take about 16 min by car with almost no variability, while that same trip can take an average of 25 min by paratransit, with 5% of trips being outside the 95% confidence interval and thus unpredictable. Paratransit trip time inefficiency tends to be particularly worse for females; older adults; those making trips between 9 and 11 a.m.; cash-paying customers; those making shorter trips; and those traveling during inclement weather, including cold temperatures. These findings suggest a need to re-assess using public transit as a benchmark for paratransit supply as regulated by the ADA.

accessible transportation and mobility↗
DOE OSTI2023

Mobility Energy Productivity and Equity: E-Bike Impacts for Low-Income Essential Workers in Denver

New mobility technologies such as electrified and shared mobility, combined with polices and incentive programs, are emerging to help address sustainability and equity issues in transportation planning. However, it can be difficult to understand the impacts of novel mobility trends and emerging modes on energy-efficient access. This is owing to a lack of (1) open-source tools enabling rapid data collection, and (2) open-source metrics that consider multimodal, multiactivity access and mobility within the contexts of sustainability and equity. Here, this paper addresses the topic of improving evaluation of transportation modes and incentive programs by integrating an open-source platform for tracking human travel data—the Open Platform for Agile Trip Heuristics (OpenPATH)—with a mobility metric that quantifies the efficiency of a region’s transportation system: Mobility Energy Productivity (MEP). Integration is demonstrated in the context of pilot programs in Colorado, where low-income essential workers were provided with electric bikes (e-bikes). OpenPATH-informed MEP calculations showed that several locations in downtown Denver provided comparable time-, cost-, and energy-efficient access to opportunities using e-bikes compared with driving. Additionally, providing e-bikes to low-income essential workers was found to be meaningful, as they utilized e-bikes the most to commute, despite driving still being their most utilized mode and the mode with highest MEP scores in Denver. We show how data collected from open-source tools coupled with robust metrics such as MEP can help evaluate the impacts of emerging mobility options. This could support developing policies to incentivize novel modes to achieve greater levels of sustainable, equitable, and efficient access.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. Here this paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from (0.217, 0.0848) to (o.011, 0.0407) (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from (0.25, 0.29) to (0.60, 0.74) (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. Finally, the results can be used to understand and improve the state of the art in the travel diary creation field.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Substitution or Shared Utilization? Intrahousehold Vehicle Use in Mixed-Powertrain Households

While previous research has focused heavily on understanding the factors deriving alternative fuel vehicle adoption rates, there remains a significant gap in understanding how households distribute mileage across different powertrains. This study utilizes data from the 2022 Next Generation National Household Travel Survey to investigate vehicle miles traveled within a sample of 150 plug-in electric vehicle (PEV)-owning households (in which at least one battery electric vehicle is present), characterizing how different powertrains are integrated into daily mobility. Leveraging a Seemingly Unrelated Regression (SUR) framework the study jointly models the utilization of PEVs, hybrid electric vehicles (HEV), and internal combustion engine vehicles (ICEVs) while accounting for household-level substitution effects. The results provide evidence of an asymmetric substitution effect. In households with mixed-powertrain configurations, the ICEV captures a substantially higher share of household miles (compared with the PEV), acting as a utility sponge. Conversely, the model identifies specific socioeconomic and geographic cohorts that prioritize PEV as the primary household workhorse, indicating a systematic sorting effect. Although the sample size limits broader generalizability, these findings suggest that PEVs are used for frequent, specific routine-intensive roles, whereas the ICEV remains a specialized utility vehicle. These insights highlight distinct intrahousehold vehicle use behaviors that are often obscured by aggregate fleetwide statistics.

25 ENERGY STORAGE↗
DOE OSTI2017

Instantaneous and cycle optimization of fuel usage on a dual fuel vehicle leveraging gasoline and natural gas

Recent increases in natural gas supply have led to a desire to leverage this fuel in the transportation sector. Dual fuel engines provide a platform on which to use natural gas efficiently; these engines, however, require new hardware and new control strategies to properly utilize two fuels simultaneously. This paper explores the impact of implementing dual fuel capabilities on a sedan and demonstrates that a dual fuel E10 and compressed natural gas engine is able to improve the average engine efficiency by up to 6.5% compared to a single fuel engine on standard drive cycles. An optimal control technique is also developed, and the proposed approach allows factors including fuel cost and fuel availability to be taken into account. Optimization at each time instant is investigated and contrasted with optimization over the entire cycle. Cycle optimization is shown to have particular value for cases in which the level in one fuel tank is low.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Analytic study of the conditions required for longitudinal stability of dual-wing aircraft

Recent studies of new, fuel-efficient transport aircraft have considered designs, which make use of two principal lifting surfaces to provide the required lift as well as trim and static stability. Such designs include open tandem-wings as well as closed joined and box-wings. As a group, these aircraft can be termed dual-wing designs. Our study developed a new analytic model, which takes into account the downwash from the two main wings and is sensitive to three important design variables: the relative areas of each wing, the streamwise separation of the wings, and the center of gravity position. This model was used to better understand trends in the dual-wing geometry on the stability, maneuverability, and lift-to-drag ratio of the aircraft. Dual-wing aircraft have been shown to have reduced the induced drag compared to the conventional designs. In addition, further drag reductions can be realized as the horizontal tail can be removed if the dual-wings have sufficient streamwise stagger to provide the moments necessary for trim and longitudinal stability. As both wings in a dual-wing system carry a significant fraction of the total lift, trends in such designs that led to longitudinal stability can differ from those of the conventional aircraft and have not been the subject of detailed investigation. Results from the analytic model showed that the longitudinal stability required either a reduction of the fore wing area or shifting the center of gravity forward from the midpoint of both wings' aerodynamic centers. Additionally, for wing configurations of approximately equal fore and aft wing areas, increasing the separation between the two wings decreased the stability of the aircraft. The source of this unusual behavior was the asymmetric distribution of downwash upstream and downstream of the wing. These relationships between dual-wing geometry and stability will provide initial guidance on the conceptual design of dual-wing aircraft and aid in the understanding of the results of more complex studies of such designs, furthering the development of future transport aircraft.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Reactivity-controlled compression ignition drive cycle emissions and fuel economy estimations using vehicle system simulations

In-cylinder blending of gasoline and diesel to achieve reactivity-controlled compression ignition has been shown to reduce NO X and soot emissions while maintaining or improving brake thermal efficiency as compared with conventional diesel combustion. The reactivity-controlled compression ignition concept has an advantage over many advanced combustion strategies in that the fuel reactivity can be tailored to the engine speed and load, allowing stable low-temperature combustion to be extended over more of the light-duty drive cycle load range. In this paper, a multi-mode reactivity-controlled compression ignition strategy is employed where the engine switches from reactivity-controlled compression ignition to conventional diesel combustion when speed and load demand are outside of the experimentally determined reactivity-controlled compression ignition range. The potential for reactivity-controlled compression ignition to reduce drive cycle fuel economy and emissions is not clearly understood and is explored here by simulating the fuel economy and emissions for a multi-mode reactivity-controlled compression ignition–enabled vehicle operating over a variety of US drive cycles using experimental engine maps for multi-mode reactivity-controlled compression ignition, conventional diesel combustion, and a 2009 port-fuel injected gasoline engine. Drive cycle simulations are completed assuming a conventional mid-size passenger vehicle with an automatic transmission. Multi-mode reactivity-controlled compression ignition fuel economy simulation results are compared with the same vehicle powered by a representative 2009 port-fuel injected gasoline engine over multiple drive cycles. Finally, engine-out drive cycle emissions are compared with conventional diesel combustion, and observations regarding relative gasoline and diesel tank sizes needed for the various drive cycles are also summarized.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Invited Review: A review of deterministic effects in cyclic variability of internal combustion engines

Here we review developments in the understanding of cycle to cycle variability in internal combustion engines, with a focus on spark-ignited and premixed combustion conditions. Much of the research on cyclic variability has focused on stochastic aspects, that is, features that can be modeled as inherently random with no short term predictability. In some cases, models of this type appear to work very well at describing experimental observations, but the lack of predictability limits control options. Also, even when the statistical properties of the stochastic variations are known, it can be very difficult to discern their underlying physical causes and thus mitigate them. Some recent studies have demonstrated that under some conditions, cyclic combustion variations can have a relatively high degree of low dimensional deterministic structure, which implies some degree of predictability and potential for real time control. These deterministic effects are typically more pronounced near critical stability limits (e.g. near tipping points associated with ignition or flame propagation) such during highly dilute fueling or near the onset of homogeneous charge compression ignition. We review recent progress in experimental and analytical characterization of cyclic variability where low dimensional, deterministic effects have been observed. We describe some theories about the sources of these dynamical features and discuss prospects for interactive control and improved engine designs. In conclusion, taken as a whole, the research summarized here implies that the deterministic component of cyclic variability will become a pivotal issue (and potential opportunity) as engine manufacturers strive to meet aggressive emissions and fuel economy regulations in the coming decades.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Reaction-space analysis of homogeneous charge compression ignition combustion with varying levels of fuel stratification under positive and negative valve overlap conditions

Full-cycle computational fluid dynamics simulations with gasoline chemical kinetics were performed to determine the impact of breathing and fuel injection strategies on thermal and compositional stratification, combustion and emissions during homogeneous charge compression ignition combustion. The simulations examined positive valve overlap and negative valve overlap strategies, along with fueling by port fuel injection and direct injection. The resulting charge mass distributions were analyzed prior to ignition using ignition delay as a reactivity metric. The reactivity stratification arising from differences in the distributions of fuel–oxygen equivalence ratio (Φ FO ), oxygen molar fraction (χ O2 ) and temperature (T) was determined for three parametric studies. In the first study, the reactivity stratification and burn duration for positive valve overlap valve events with port fuel injection and early direct injection were nearly identical and were dominated by wall-driven thermal stratification. nitrogen oxide (NO) and carbon monoxide (CO) emissions were negligible for both injection strategies. In the second study, which examined negative valve overlap valve events with direct injection and port fuel injection, reactivity stratification increased for direct injection as the Φ FO and T distributions associated with direct fuel injection into the hot residual gas were positively correlated; however, the latent heat absorbed from the hot residual gas by the evaporating direct injection fuel jet reduced the overall thermal and reactivity stratification. These stratification effects were offsetting, resulting in similar reactivity stratification and burn durations for the two injection strategies. The higher local burned gas temperatures with direct injection resulted in an order of magnitude increase in NO, while incomplete combustion of locally over-lean regions led to a sevenfold increase in CO emissions compared to port fuel injection. The final study evaluated positive valve overlap and negative valve overlap valve events with direct injection. Furthermore, relative to positive valve overlap, the negative valve overlap condition had a wider reactivity stratification, a longer burn duration and higher NO and CO emissions associated with reduced fuel–air mixing.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Parallel methodology to capture cyclic variability in motored engines

Numerical prediction of of cycle-to-cycle variability (CCV) in SI engines is extremely challenging for two key reasons: (i) high-fidelity methods such as large eddy simulation (LES) are require to accurately capture the in-cylinder turbulent flowfield, and (ii) CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. In this study, a new methodology is proposed to dissociate this long time-scale problem into several shorter time-scale problems, which can considerably reduce the computational time without sacrificing the fidelity of the simulations. The strategy is to perform multiple single-cycle simulations in parallel by effectively perturbing the simulation parameters such as the initial and boundary conditions. It is shown that by perturbing the initial velocity field effectively based on the intensity of the in-cylinder turbulence, the mean and variance of the in-cylinder flowfield is captured reasonably well. Adding perturbations in the initial pressure field and the boundary pressure improves the predictions. It is shown that this new approach is able to give accurate predictions of the flowfield statistics in less than one-tenth of time required for the conventional approach of simulating consecutive engine cycles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Nanostructure and burning mode of light-duty diesel particulate with conventional diesel, biodiesel, and intermediate blends

The nanostructure of diesel particulates has been shown to impact its oxidation rate and burnout trajectory. Additionally, this nanostructure can evolve during the oxidation process, furthering its influence on the burnout process. For this study, exhaust particulates were generated on a light-duty diesel engine with conventional diesel fuel, biodiesel, and intermediate blends of the two at a single load-speed point. Despite the singular engine platform and operating point, the different fuels created particulates with varied nanostructure, thereby greatly expanding the window for observing nanostructure evolution and oxidation. The physical and chemical properties of the particulates in the nascent state and at partial oxidation states were measured in a laboratory reactor and by high-resolution transmission electron microscopy as a function of the degree of oxidation in O 2 . X-ray photoacoustic spectroscopy analysis, thermal desorption, and solvent extraction of the nascent particulate samples reveal a significant organic content in the biodiesel-derived particulates, likely accounting for differences in the nanostructure. This study reports the nanoscale structural changes in the particulate with biofuel blend level and during O 2 oxidation as observed by high-resolution transmission electron microscopy and quantitated by fringe analysis and Brunnauer–Emmet–Teller total surface area measurements. It was observed that initial fuel-related differences in the lamella lengths, spacing, and curvature disappear when the particulate reaches approximately 50% burnout. Specifically, the initial ordered, fullerenic, and amorphous nanostructures converge during the oxidation process and the surface areas of these particulates appear to grow through these complex changes in internal particle structure. The specific surface area, measured at several points along the burnout trajectory, did not match the shrinking core projection and in contrast suggested that internal porosity was increasing. Thus, the appropriate burnout model for these particulates is significantly different from the standard shrinking core assumption, which does not account for any internal structure. An alternative burnout model is supported by high-resolution transmission electron microscopy image analysis.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Evolution of deep-bed filtration of engine exhaust particulates with trapped mass

Micro-scale filtration experiments were performed on cordierite filter samples using particulate matter (PM) generated by a spark-ignition direct-injection (SIDI) engine fueled with tier II EEE certification gasoline. Size-resolved mass and number concentrations were obtained from several engine operating conditions. The resultant mass-mobility relationships showed weak dependence on the operating condition. An integrated particle size distribution (IPSD) method was used estimate the PM mass concentration in the exhaust stream from the SIDI engine and a heavy duty diesel (HDD) engine. The average estimated mass concentration between all conditions was ~77****** % of the gravimetric measurements performed on Teflon filters. Despite the relatively low elemental carbon fraction (~0.4 to 0.7), the IPSD mass for stoichiometric SIDI exhaust was ~83±38 % of the gravimetric measurement. Identical cordierite filter samples with properties representative of diesel particulate filters were sequentially loaded with PM from the different SIDI engine operating conditions, in order of increasing PM mass concentration. Simultaneous particle size distribution measurements upstream and downstream of the filter sample were used to evaluate filter performance evolution and the instantaneous trapped mass within the filter for two different filter face velocities. The evolution of filtration performance for the different samples was sensitive only to trapped mass, despite using PM from a wide range of operating conditions. Higher filtration velocity resulted in a more rapid shift in the most penetrating particle size towards smaller mobility diameters.

33 ADVANCED PROPULSION SYSTEMS↗