Characterization of a Lightly Loaded Underfloor Catalyzed Gasoline Particulate Filter in a Turbocharged Light Duty Truck.

A test program to characterize the benefits and challenges of applying a European series production catalyzed gasoline particulate filter (GPF) to a U.S. Tier 2 turbocharged light duty truck (3.5L Ecoboost Ford F150) in the underfloor location was initiated at the U.S. Environmental Protection Agency. The turbos and underfloor location keep the GPF relatively cool and minimize passive regeneration relative to other configurations. This study characterizes the relatively cool GPF in a lightly loaded state, approximately 0.1 to 0.4 g/L of soot loading, using four test cycles: 60 mph steady state, 4-phase FTP, HWFET, and US06. Measurements include GPF temperature, soot loading, GPF pressure drop, brake thermal efficiency (BTE), CO2, PM mass, elemental carbon (EC), filter-collected organic carbon (OC), CO, THC, and NOx emissions. The lightly loaded underfloor GPF achieves 85-99% reduction in PM mass, 98.5-100.0% reduction in EC, and 65-91% reduction in filter-collected OC, depending on test cycle. The smallest reductions in PM and EC occur in the US06 cycle due to mild GPF regeneration caused by GPF inlet temperature exceeding 500°C. EC dominates filter-collected OC without a GPF, while OC dominates EC with a GPF. Composite cycle CO, THC, and NOx emissions are reduced by the washcoat on the GPF but the low temperature location of the GPF does not make best use of the catalyzed washcoat. Cycle average pressure drop across the GPF ranged from 1.25 kPa in the 4-phase FTP to 4.64 kPa in the US06 but did not affect BTE or CO2 emissions in a measurable way in any test cycle.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines.

Effects of fuels, engine load and exhaust after-treatment on diesel engine SVOC emissions and development of SVOC profiles for receptor modeling.

Diesel exhaust emissions contain numerous semivolatile organic compounds (SVOCs) for which emission information is limited, especially for idling conditions, new fuels and the new after-treatment systems. This study investigates exhaust emissions of particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs (NPAHs), and sterane and hopane petroleum biomarkers from a heavy-duty (6.4 L) diesel engine at various loads (idle, 600 and 900 kPa BMEP), with three types of fuel (ultra-low sulfur diesel or ULSD, Swedish low aromatic diesel, and neat soybean biodiesel), and with and without a diesel oxidation catalyst (DOC) and diesel particulate filter (DPF). Swedish diesel and biodiesel reduced emissions of PM2.5, Σ15PAHs, Σ11NPAHs, Σ5Hopanes and Σ6Steranes, and biodiesel resulted in the larger reductions. However, idling emissions increased for benzo[k]fluoranthene (Swedish diesel), 5-nitroacenaphthene (biodiesel) and PM2.5 (biodiesel), a significant result given the attention to exposures from idling vehicles and the toxicity of high-molecular-weight PAHs and NPAHs. The DOC + DPF combination reduced PM2.5 and SVOC emissions during DPF loading (>99% reduction) and DPF regeneration (83-99%). The toxicity of diesel exhaust, in terms of the estimated carcinogenic risk, was greatly reduced using Swedish diesel, biodiesel fuels and the DOC + DPF. PAH profiles showed high abundances of three and four ring compounds as well as naphthalene; NPAH profiles were dominated by nitro-naphthalenes, 1-nitropyrene and 9-nitroanthracene. Both the emission rate and the composition of diesel exhaust depended strongly on fuel type, engine load and after-treatment system. The emissions data and chemical profiles presented are relevant to the development of emission inventories and exposure and risk assessments.

Composition and Integrity of PAHs, Nitro-PAHs, Hopanes and Steranes In Diesel Exhaust Particulate Matter.

Diesel exhaust particulate matter contains many semivolatile organic compounds (SVOCs) of environmental and health significance. This study investigates the composition, emission rates, and integrity of 25 SVOCs, including polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs (NPAHs), and diesel biomarkers hopanes and steranes. Diesel engine particulate matter (PM), generated using an engine test bench, three engine conditions, and ultra-low sulfur diesel (ULSD), was collected on borosilicate glass fiber filters. Under high engine load, the PM emission rate was 0.102 g/kWh, and emission rate of ΣPAHs (10 compounds), ΣNPAHs (6 compounds), Σhopanes (2 compounds), and Σsteranes (2 compounds) were 2.52, 0.351, 0.02 ~ 2 and 1µg/kWh, respectively. Storage losses were evaluated for three cases: conditioning filters in clean air at 25 °C and 33% relative humidity (RH) for 24 h; storing filter samples (without extraction) wrapped in aluminum foil at 4 °C for up to one month; and storing filter extracts in glass vials capped with Teflon crimp seals at 4 °C for up to six months. After conditioning filters for 24 h, 30% of the more volatile PAHs were lost, but lower volatility NPAHs, hopanes and steranes showed negligible changes. Storing wrapped filters and extracts at 4 °C for up to one month did not lead to significant losses, but storing extracts for five months led to significant losses of PAHs and NPAHs; hopanes and steranes demonstrated greater integrity. These results suggest that even relatively brief filter conditioning periods, needed for gravimetric measurements of PM mass, and extended storage of filter extracts can lead to underestimates of SVOC concentrations. Thus, SVOC sampling and analysis protocols should utilize stringent criteria and performance checks to identify and limit possible biases occurring during filter and extract processing.

Gaseous and Particulate Emissions from Diesel Engines at Idle and under Load: Comparison of Biodiesel Blend and Ultralow Sulfur Diesel Fuels.

Diesel exhaust emissions have been reported for a number of engine operating strategies, after-treatment technologies, and fuels. However, information is limited regarding emissions of many pollutants during idling and when biodiesel fuels are used. This study investigates regulated and unregulated emissions from both light-duty passenger car (1.7 L) and medium-duty (6.4 L) diesel engines at idle and load and compares a biodiesel blend (B20) to conventional ultralow sulfur diesel (ULSD) fuel. Exhaust aftertreatment devices included a diesel oxidation catalyst (DOC) and a diesel particle filter (DPF). For the 1.7 L engine under load without a DOC, B20 reduced brake-specific emissions of particulate matter (PM), elemental carbon (EC), nonmethane hydrocarbons (NMHCs), and most volatile organic compounds (VOCs) compared to ULSD; however, formaldehyde brake-specific emissions increased. With a DOC and high load, B20 increased brake-specific emissions of NMHC, nitrogen oxides (NOx), formaldehyde, naphthalene, and several other VOCs. For the 6.4 L engine under load, B20 reduced brake-specific emissions of PM2.5, EC, formaldehyde, and most VOCs; however, NOx brake-specific emissions increased. When idling, the effects of fuel type were different: B20 increased NMHC, PM2.5, EC, formaldehyde, benzene, and other VOC emission rates from both engines, and changes were sometimes large, e.g., PM2.5 increased by 60% for the 6.4 L/2004 calibration engine, and benzene by 40% for the 1.7 L engine with the DOC, possibly reflecting incomplete combustion and unburned fuel. Diesel exhaust emissions depended on the fuel type and engine load (idle versus loaded). The higher emissions found when using B20 are especially important given the recent attention to exposures from idling vehicles and the health significance of PM2.5. The emission profiles demonstrate the effects of fuel type, engine calibration, and emission control system, and they can be used as source profiles for apportionment, inventory, and exposure purposes.