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The steam reforming of CH4 plays a crucial role in the high-temperature activity of natural gas three-way catalysts. Despite existing reports on sulfur inhibition in CH4 steam reforming, there is a limited understanding of sulfur storage and removal dynamics under various lambda conditions. In this study, we utilize a 4-Mode sulfur testing approach to elucidate the dynamics of sulfur storage and removal and their impact on three-way catalyst performance. We also investigate the influence of sulfur on CH4 steam reforming by analyzing CH4 conversions under dithering, rich, and lean reactor conditions. In the 4-Mode sulfur test, saturating the TWC with sulfur at low temperatures emerges as the primary cause of significant three-way catalyst performance degradation. After undergoing a deSOx treatment at 600 °C, NOx conversions were fully restored, while CH4 conversions did not fully recover.

Diesel oxidation catalyst (DOC) is one of the critical catalyst components in modern diesel aftertreatment systems. It mainly converts unburned hydrocarbon (HC) and CO to CO2 and H2O before they are released to the environment. In addition, it also oxidizes a portion of NO to NO2, which improves the NOx conversion efficiency via fast SCR over the downstream selective catalytic reduction (SCR) catalyst. HC light-off tests, with or without the presence of NOx, has been typically used for DOC evaluation in laboratory. In this work, we aim to understand the influences of DOC light-off experimental conditions, such as initial temperature, initial holding time, HC species, with or without the presence of NOx, on the DOC HC light-off behavior. The results indicate that light-off test with lower initial temperature and longer initial holding time (at its initial temperature) leads to higher DOC light-off temperature.

The prediction accuracy of a three-way catalyst (TWC) model is highly associated with the ability of the model to incorporate the reaction kinetics of the emission process as a lambda function. In this study, we investigated the O2 and H2 concentration profiles of TWC reactions and used them as critical inputs for the development of a global TWC model. We presented the experimental data and global kinetic model showing the impact of thermal degradation on the performance of the TWC. The performance metrics investigated in this study included CH4, NOx, and CO conversions under lean, rich, and dithering light-off conditions to determine the kinetics of oxidation reactions and reduction/reforming/water-gas shift reactions as a function of thermal aging. The O2 and H2 concentrations were measured using mass spectrometry to track the change in the oxidation state of the catalyst and to determine the mechanism of the reactions under these light-off conditions.

Upcoming, stricter diesel exhaust emissions standards will likely require aftertreatment architectures with multiple diesel exhaust fluid (DEF) introduction locations. Managing NH3 slip with technologies such as an ammonia slip catalyst (ASC) will continue to be critical in these future aftertreatment systems. In this study, we evaluate the impact of SO2 exposure on a state-of-the-art commercially available ASC. SO2 is co-fed at 0.5 or 3 ppmv to either approximate or accelerate a real-world exhaust SO2 impact. ASC performance during sulfur co-feeding is measured under a wide variety of simulated real-world conditions. Results indicate that the loss of NO conversion during SCR is dependent on the cumulative SO2 exposure, regardless of the inlet SO2 concentration. Meanwhile, N2O formation under SCR conditions is nonlinearly affected by SO2 exposure, with formation increasing during 0.5 ppmv SO2 exposure but decreasing in the presence of 3 ppmv SO2.

Stoichiometric natural gas engines with three-way catalysts emit less NOx and CH4 due to their higher efficiency compared to lean-burn natural gas engines. Although hydrothermal aging of three-way catalysts has been extensively studied, a deeper understanding beyond hydrothermal aging is needed to explain real-world performance, especially for natural gas engines with near-zero NOx emissions. In this investigation, field-aged three-way catalysts were characterized to identify the contribution of chemical aging to their overall performance. It was found that the sulfur species on the field-aged TWCs were entirely distributed along the catalyst length, showing a decreasing trend, whereas phosphorous contamination was mainly observed at the inlet section of the three-way catalysts, and the phosphorous concentration declined sharply along the axial length.

The primary goal of this project was to design and implement an oxidation catalyst specific to a high-performance spark ignited two stroke engines to reduce vehicle-out emissions. The primary challenges of two stroke catalysis at high loads include controlling the catalytic reaction temperature as well as minimizing the increase in exhaust back pressure due to the addition of a catalyst. Reaction temperature is difficult to control due to high HC and CO concentrations paired with an excess of oxygen in the exhaust stream. By limiting catalyst conversion efficiency, the reaction temperatures were controlled. Two stroke engines are also inherently sensitive to changes in exhaust back pressure and therefore location and sizing of the catalyst are key design considerations. Because of these challenges significant effort was directed toward developing the two-stroke specific catalyst design process.

The advancement in embedded systems and positional accuracy with base station GPS modules created opportunity to develop high performance autonomous ground vehicles. However, the development of vehicle model and making accurate state estimations play vital role in reducing the cross track error. The present research focus on developing Linear Quadratic Gaussian (LQG) with Kalman estimator for autonomous ground vehicle to track various routes, that are made with the series of waypoints. The model developed in the LQG controller is a kinematic bicycle model, which mimics 1/5th scale truck. Further, the cubic spline fit has been used to connect the waypoints and generate the continuous desired/target path. The testing and implementation has been done at APS labs, MTU on the mentioned vehicle to study the performance of controller. Python has been used for simulations, controller coding and interfacing the sensors with controller.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state.

Three-way catalysts have been used in a variety of stoichiometric natural gas engines for emission control. During real-world operation, these catalysts have experienced a large number of temporary and permanent deactivations including thermal aging and chemical contamination. Thermal aging is typically induced either by high engine-out exhaust temperatures or the reaction exotherm generated on the catalysts. Chemical contamination originates from various inorganic species such as Phosphorous (P) and Sulfur (S) that contain in engine fluids, which can poison and/or mask the catalyst active components. Such deactivations are quite difficult to simulate under laboratory conditions, due to the fact that multiple deactivation modes may occur at the same time in the real-world operations. In this work, a set of field-aged TWCs has been analyzed through detailed laboratory research in order to identify and quantify the real-world aging mechanisms.

Cummins has recently launched next-generation aftertreatment technology, the Single ModuleTM aftertreatment system, for medium-duty and heavy-duty engines used in on-highway and off-highway applications. Besides meeting EPA 2010+ and Euro VI regulations, the Single ModuleTM aftertreatment system offers 60% volume and 40% weight reductions compared to current aftertreatment systems. In this work, we present model-based approaches that were systematically adopted in the design and development of the Cummins Single ModuleTM aftertreatment system. Particularly, a variety of analytical and experimental component-level and system-level validation tools have been used to optimize DOC, DPF, SCR/ASC, as well as the DEF decomposition device.

Plug flow reactors, simulating engine exhaust gas, are widely used in emissions control research to gain insight into the reaction mechanisms and engineering aspects that controls activity, selectivity, and durability of catalyst components. The choice of relevant hydrocarbon (HC) species is one of the most challenging factor in such laboratory studies, given the variety of compositions that can be encountered in different application scenarios. Furthermore, this challenge is amplified by the experimental difficulties related to introducing heavier and multi-component HCs and analyzing the reaction products.

The aging impact on oxygen storage capacity (OSC) and catalyst performance was investigated on one degreened and one aged (hydrothermally aged at 955 °C for 50 h) commercial three-way catalyst (TWC) by experiments and modeling. The difference of OSC between the degreened and aged TWCs was dependent on catalyst temperature. The largest difference was found at 600 °C, at which the amount of OSC decreased by 45.5%. Catalyst performance was evaluated through lightoff tests at two simulated engine exhaust conditions (lean and rich) on a micro-reactor. The aging impact on the catalyst performance was different under lean and rich environments and investigated separately. At the lean condition, oxidation of CO and C3H6 was significantly suppressed while oxidation of C3H8 was relatively less degraded. At the rich condition, the inhibition effect was more pronounced on the aged TWC and inhibiting hydrocarbon species from C3H6 partial oxidation can survive at temperatures up to 450 °C.

Sustained NOx reduction at low temperatures, especially in the 150-200 °C range, shares some similarities with the more commonly discussed cold-start challenge, however, poses a number of additional and distinct technical problems. In this project, we set a bold target of achieving and maintaining 90% NOx conversion at the SCR catalyst inlet temperature of 150 °C. This project is intended to push the boundaries of the existing technologies, while staying within the realm of realistic future practical implementation. In order to meet the resulting challenges at the levels of catalyst fundamentals, system components, and system integration, Cummins has partnered with the DOE, Johnson Matthey, and Pacific Northwest National Lab and initiated the Sustained Low-Temperature NOx Reduction program at the beginning of 2015 and completed in 2017.

This paper describes a multi-sensor data set, suitable for testing algorithms to detect and track pedestrians and cyclists, with an autonomous vehicle’s sensor suite. The data set can be used to evaluate the benefit of fused sensing algorithms, and provides ground truth trajectories of pedestrians, cyclists, and other vehicles for objective evaluation of track accuracy. One of the principal bottlenecks for sensing and perception algorithm development is the ability to evaluate tracking algorithms against ground truth data. By ground truth we mean independent knowledge of the position, size, speed, heading, and class of objects of interest in complex operational environments. Our goal was to execute a data collection campaign at an urban test track in which trajectories of moving objects of interest are measured with auxiliary instrumentation, in conjunction with several autonomous vehicles (AV) with a full sensor suite of radar, lidar, and cameras.

Future light duty vehicles in the United States are required to be certified on the FTP-75 cycle to meet Tier 3 or LEV III emission standards [1, 2]. The cold phase of this cycle is heavily weighted and mitigation of emissions during this phase is crucial to meet the low tail pipe emission targets [3, 4]. In this work, a novel aftertreatment architecture and controls to improve Nitrogen Oxides (NOx) and Hydrocarbon (HC) or Non Methane Organic gases (NMOG) conversion efficiencies at low temperatures is proposed. This includes a passive NOx & HC adsorber, termed the diesel Cold Start Concept (dCSC™) catalyst, followed by a Selective Catalytic Reduction catalyst on Filter (SCRF®) and an under-floor Selective Catalytic Reduction catalyst (SCR). The system utilizes a gaseous ammonia delivery system capable of dosing at two locations to maximize NOx conversion and minimize parasitic ammonia oxidation and ammonia slip.

Copper- and Iron- based metal-zeolite SCR catalysts are widely used in US and European diesel aftertreatment systems to achieve drastic reduction in NOx emission. These catalysts are highly selective to N2 under wide range of operating conditions. Nevertheless, the type of transition metal has a significant impact on the key performance and durability parameters such as NOx conversion, selectivity towards N2O, hydrothermal stability, and sensitivity to fuel sulfur content. In this study, we explained the differences in the performance characteristics of these catalysts based on their relative acidic-basic nature of transition metal present in these catalysts using practically relevant gas species present in diesel exhaust such as NO2, SOx, and NH3. These experiments show that Fe-zeolite has relatively acidic nature as compared to Cu-zeolite that causes NH3 inhibition and hence explains low NOx conversion on Fe-zeolite at low temperature under standard SCR conditions.

Cu/CHA catalysts have been widely used in the industry, due to their desirable performance characteristics including the unmatched hydrothermal stability. While broadly recognized for their outstanding activity at or above 200°C, these catalysts may not show desired levels of NOx conversion at lower temperatures. To achieve high NOx conversions it is desirable to have NO2/NOx close to 0.5 for fast SCR. However even under such optimal gas feed conditions, sustained use of Cu/CHA below 200°C leads to ammonium nitrate formation and accumulation, resulting in the inhibition of NOx conversion. In this contribution, the formation and decomposition of NH4NO3 on a commercial Cu/CHA catalyst have been investigated systematically. First, the impact of NH4NO3 self-inhibition on SCR activity as a function of temperature and NO2/NOx ratios was investigated through reactor testing.

An accurate estimation of cycle-by-cycle in-cylinder mass and the composition of the cylinder charge is required for spark-ignition engine transient control strategies to obtain required torque, Air-Fuel-Ratio (AFR) and meet engine pollution regulations. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) sensors have been utilized in different control strategies to achieve these targets; however, these sensors have response delay in transients. As an alternative to air flow metering, in-cylinder pressure sensors can be utilized to directly measure cylinder pressure, based on which, the amount of air charge can be estimated without the requirement to model the dynamics of the manifold.

Measuring axial exhaust species concentration distributions within a wall-flow aftertreatment device provides unique and significant insights regarding the performance of complex devices like the SCR-on-filter. In this particular study, a less complex aftertreatment configuration which includes a DOC followed by two uncoated partial flow filters (PFF) was used to demonstrate the potential and challenges. The PFF design in this study was a particulate filter with alternating open and plugged channels. A SpaciMS [1] instrument was used to measure the axial NO2 profiles within adjacent open and plugged channels of each filter element during an extended passive regeneration event using a full-scale engine and catalyst system. By estimating the mass flow through the open and plugged channels, the axial soot load profile history could be assessed.