Browse Topic: Selective catalytic reduction (SCR)

Items (1,116)
Biodiesel blends (B7, B20, B100) were evaluated in a Stage V-compliant SCR on Filter (SCRoF) system for heavy-duty applications to quantify soot reactivity and filter regeneration capability. Compared to conventional diesel (B7), B20 showed slightly faster regeneration performance under real-driving conditions, while B100 resulted in reduced particulate formation and higher soot reactivity, with more intense exothermic events requiring careful management. These differences are attributed to the distinct physical-chemical properties of the fuels (oxygen content, lower heating value) and their interaction with Diesel Oxidation Catalyst (DOC)/SCRoF. All tests were conducted on an engine dynamometer with a Cursor 9 FPT (Fiat Powertrain). Findings are discussed in the context of EU Stage V limits and practical control strategies for heavy-duty applications.
Costa, Simone
Mitigation of harmful emissions from oil-based engines is essential to avoid environmental pollution and comply with various NOx regulations across the globe. This can be partially achieved by injecting urea to produce ammonia (NH3), which reacts with NOx in a catalyst to produce harmless nitrogen (N2) and water vapor (H2O). However, urea deposition in a selective catalytic reduction (SCR) system poses a significant threat to the NOx removal process by not only reducing the urea conversion rate but also blocking the incoming flow and causing an additional pressure drop. Numerical modeling of this urea deposit formation involves multiphase flow physics coupled with accurate heat transfer calculations. Additionally, since urea decomposes into various by-products like biuret, cyanuric acid (CYA), and ammelide, detailed chemical kinetics modeling is equally important. Accurate and fast computational fluid dynamics (CFD) simulations can help accelerate SCR system design cycles, leading to a reduction in experimental cost. In this study, we employ CONVERGE CFD to model the whole process from urea–water solution (UWS) injection to droplet evaporation and decomposition (using 12-step detailed-chemistry), film formation, and final deposition as a solid. A new spray-wall interaction model is introduced based on published experimental observations. The efficacy of the numerical model is demonstrated using an S-bend tube, where the UWS is injected just at the end of the S-bend. The predicted deposit mass and patterns are compared with the experiments, and good agreement is observed for three different operating conditions. A novel boundary morphing feature is activated to model the deformation of the tube walls because of urea deposition. Finally, to accelerate the simulations, a spray database approach is introduced. Coupled with the fixed-flow feature, this results in around 58% reduction in computational time without compromising accuracy. The present work thus provides a numerical framework to accurately capture urea deposition with a fast turnaround time.
Morab, Sumant R.Khalate, SurajAnsari, ShoaibYang, Pengze
To address the challenge of balancing voltage support and current limitation in grid-forming converters (GFCs)—a challenge induced by the uncontrollability of active power during transient faults in microgrids and weak grids—a low voltage ride through (LVRT) strategy utilizing adaptive virtual impedance with a variable resistance-to-inductance ratio is proposed. This strategy is designed to maximize the satisfaction of reactive power support and current limiting characteristics. By adaptively generating virtual impedance based on changing line parameters, the method enables adaptation to large disturbance conditions involving variations in line impedance and Short Circuit Ratio (SCR). First, a transient model of the virtual impedance for GFCs is established to clarify the transient instability mechanism. During the transient period, the power loop is controlled to prevent power angle divergence. Second, the influence mechanism of virtual impedance on reactive current and output current during transients is analyzed. By integrating inrush current limitation and LVRT requirements, an adaptive virtual impedance control strategy is formulated to achieve collaborative optimization of transient LVRT and current limiting. Finally, the effectiveness of the proposed control strategy is verified through MATLAB/Simulink simulation experiments.
Pang, BoYang, XiangzhenLiu, Fang
Simultaneously reducing criteria pollutants and fuel consumption is important for clean air and improving vehicle total cost of ownership. The goal of this effort was focused on a 90% NOx reduction and 10% fuel savings for an off-road 407 kW diesel engine. The baseline was a production Fiat Powertrain 13L engine and aftertreatment system meeting 0.4 g/kW-hr NOx. The baseline system was quantified over the NRTC, RMC, new low load cycle and five field cycles. A next generation engine was built incorporating several fuel-efficient design features, including a higher compression ratio, increased fuel-rail pressure, low-friction piston rings, and a high-efficiency variable-geometry turbocharger. Cylinder deactivation and EGR pump technologies were added to this engine as well. The combination was optimized prior to adding advanced aftertreatment systems, showing the trade-off of engine out NOx and exhaust temperature. Two next-generation catalyst technologies were employed into a LO-SCR plus main SCR system, both with and without an electric heater upstream of the LO-SCR. These catalysts were hydrothermally aged to simulate significant field use. Dual SCR dosing with newly developed controls played a critical role in achieving the proper split between the upstream LO-SCR and the downstream main SCR. Adding a next generation mixer for the downstream SCR proved essential in obtaining the final results. The optimal configuration required adding an electric heater to elevate the exhaust temperature at the LO-SCR for early cycle NOx reduction. The final results showed a 94.8% NOx reduction and 15.7% fuel savings on the composite NRTC.
McCarthy, Jr.,, JamesWine, JonathanBradley, RyanHasseman, AndyPrikhodko, VitalyHowell, Thomas
In the near to mid-term, hydrogen internal combustion engines (H2-ICE) can be a bridge technology for reducing carbon emissions. A few challenges anticipated under lean-burn H2-ICE operation are the significant drop in turbo-out temperatures, combined with higher water content, and the possible presence of unburned hydrogen in the exhaust, which could have a potential impact on performance and durability of the downstream exhaust aftertreatment system, particularly oxidation and SCR catalysts, as these conditions can suppress low-temperature oxidation activity, perturb Cu-site speciation and redox cycling in SCR catalysts, and exacerbate hydrothermal aging under sustained wet operation. This study examines the impact of excess water and residual hydrogen on Cu-SCR durability, active site chemistry, and stability for the case with and without an upstream oxidation catalyst, through aging tests at 450 °C and 550 °C. Changes in Cu redox cycles were assessed through site quantification using multiple titration techniques to determine the influence of excess H2O and H2 on catalyst performance and aging.
Kim, Mi-YoungDaya, RohilKamasamudram, Krishna
Achieving ultra-low NOx emissions remains a major challenge in diesel emission control industry worldwide, especially as increasingly stringent regulations are introduced globally. Selective Catalytic Reduction (SCR), the leading NOx reduction technology in diesel systems, performs best when “sufficient” heat and ammonia are made available to it. At the same time, any proposed solution must be both low-cost and functionally robust in an industry seeking near 100% NOx removal at the lowest feasible cost. This work presents a low-cost architecture, utilizing a small, highly compact, single heater-mixer unit along with a light-off (close-coupled) SCR for meeting most stringent NOx emission regulations worldwide. It also hinders deposit formation lowering warranty costs and mitigating failure modes. Engine studies using a fully-aged aftertreatment system demonstrate that the proposed solution enables compliance with newer heavy-duty regulations including 2027 US, Euro-VII, China-VII, and likely the upcoming Bharat-VII while also rendering a large ‘compliance margin’, providing significant margin for meeting in-use compliance.
Masoudi, MansourPoliakov, Nick
Fe/zeolite selective catalytic reduction (SCR) catalysts are commercially used for NOx emissions reduction from diesel engines. In comparison to Cu/zeolite, these catalysts are widely reported to form less N2O as a byproduct of the SCR reactions. However, Fe/zeolite SCR is less active than Cu/zeolite for low temperature NOx conversion under standard SCR conditions. In this study, a state-of-the-art Fe/zeolite SCR catalyst is probed with a combination of N2 physisorption, SEM/EDX, reactor-based performance and active site quantification. Measurements investigate the impact of degreening, mild and extreme hydrothermal aging. In a degreened condition, the impact of water vapor on standard and fast SCR and isothermal desorption of NH3 is assessed. The Fe/zeolite catalyst’s hydrothermal durability is studied following hydrothermal aging at temperatures from 550°C up to 950°C. NH3 adsorption and temperature programmed desorption (TPD) and NO2 adsorption and TPD experiments are used to quantify the surface acidity and active Fe sites of the catalysts, respectively. Kinetic analysis of the standard SCR data is conducted to elucidate the mechanisms responsible for SCR activity loss upon hydrothermal aging. The authors believe the results presented herein can support the industry wide efforts to continue to improve diesel emissions control.
Ottinger, NathanXi, YuanzhouLiu, Z. Gerald
Diesel aftertreatment systems continue to play a critical role in compliance of tailpipe criteria pollutant compliance for commercial transportation applications. Quantification of performance of the aftertreatment system in particular Selective Catalytic Reduction component as a function of aging is critical in ensuring real world tailpipe NOx standard for aged systems. As part of A2CAT-II consortium at Southwest research Institute this aspect of the production AT system was studied for different aging conditions using a set of DAAAC aged components. The performance of these aged components was quantified through a set of steady state reactor tests and transient ECTO burner lab tests that simulate on engine performance. The data was collected at 0, 33 and 100% equivalent aging conditions and this data was used to develop a GT suite-based model with a set of inhibition factors to simulate the loss of Ammonia Storage Capacity and reduced SCR reaction rates caused by thermal load and chemical poisons. A quantitative and qualitative discussion of the degradation mechanism is presented based on the inhibition factors determined as part of the simulation study. Primary mechanism of performance degradation for fully aged component consisted of a 12% drop in ammonia storage capacity and a 10% and 12% drop in standard and fast SCR reaction rates leading to reduced NOx conversion rate. Due to catalyst degradation up to 11% reduced NH3 oxidation rate was observed which led to increased NOx conversion for temperatures above 350C. These trends can have a significant impact of systems designed for ultra low NOx standards by EPA and CARB which require precise control over NOx conversion of the system.
Chundru, Venkata RajeshSharp, ChristopherGankov, StanislavEakle, Scott
As hydrogen internal combustion engines (H2-ICE) gain traction, optimizing exhaust aftertreatment technologies for nitrogen oxide (NOx) control has become increasingly critical. While selective catalytic reduction (SCR) systems remain the primary approach for NOx mitigation, oxidation catalysts are also being explored to facilitate hydrogen oxidation and improve overall exhaust treatment efficiency. This work presents a multifunctional catalyst (MFC) concept that combines supported Pd and Cu-zeolite to enable simultaneous NOx reduction and hydrogen oxidation within a single catalytic unit. Preliminary results show that hydrogen oxidation on supported Pd occurs above 300 °C, while Cu-zeolite achieves nearly complete NOx conversion. Experiments on individual components indicate that supported Pd initiates ammonia oxidation only after hydrogen is depleted. In the presence of hydrogen, ammonia conversion remains below 20%, indicating that hydrogen availability suppresses ammonia oxidation, which is favorable for SCR operation. The MFC can be configured either on a substrate or as an on-filter catalyst (MFCoF), providing simultaneous chemical conversion and urea-derived particulate filtration. In addition to hydrogen engines, the MFCoF concept can be applied to diesel and biodiesel engines, enabling effective filtration of soot particles while maintaining NOx reduction performance along with hydrocarbon oxidation capability. By combining NOx reduction, hydrogen/hydrocarbon oxidation, and particulate filtration in one unit, the MFCoF approach provides a promising pathway for next-generation exhaust systems across diverse engine platforms.
Danghyan, VardanBecker, Jan MartinHünnekes, EdgarPatchett, Joseph
In the pursuit of achieving stringent BS VI emission standards, maintaining the efficiency of Selective Catalytic Reduction (SCR) systems is paramount, especially in vehicles operating under low duty cycles. A significant concern in such scenarios is the accumulation of urea deposits within the SCR, which can lead to detrimental push-out effects and compromised catalyst performance. This issue is particularly prevalent during low-temperature operations, where the conditions are less favorable for the effective conversion of nitrogen oxides (NOx). To address this challenge, an innovative software control system has been developed to monitor operating conditions and detect potential urea deposit faults. The software continuously evaluates parameters such as temperature and vehicle duty cycle, identifying conditions that may lead to urea crystallization within the SCR system. When unfavorable conditions are detected, the software triggers a fault alert that activates a regeneration process aimed at dissolving the accumulated urea deposits. This proactive approach not only prevents the adverse effects of urea buildup but also ensures the continued efficiency of the SCR system in reducing NOx emissions. By facilitating timely regeneration, the software enhances the operational reliability of the SCR catalyst, thereby supporting compliance with regulatory standards.
K, SabareeswaranK K, Uthira Ramya BalaRaju, ManikandanK J, RamkumarYS, Ananthkumar
This study presents a comprehensive methodology for benchmarking hydrogen and diesel internal combustion Engines, with emphasis on virtual Real-Drive Emission (RDE) test procedures for diesel and hydrogen application. Emission profiles for legal cycles and RDE scenarios are accurately predicted through integration and development of Artificial Neural Networks (ANN) based on Long Short-Term Memory (LSTM) models. Virtual evaluations of Selective Catalytic Reduction (SCR) system performance, Diesel Exhaust Fluid (DEF) dosing accuracy, and exhaust temperature dynamics enabled by integrated data pipelines and physics-based modeling are also explored for holistic prediction of output. Across models, validation demonstrates good prediction accuracy including temperature (R2 > 0.94, RMS error < 25°C), air flow (92% accuracy, RMSE = 28 kg/h), upstream NOx (93% accuracy, RMSE < 10 mg/s), and SCR (TP NOx accuracy = 91.82%, dosing accuracy = 87.73%). This approach has the potential to offer significant reduction in the need of extensive on-road driving tests, as the model provides capability to emulate the same, thereby lowering development costs and supporting OEMs in meeting stringent emission standards through efficient benchmarking of Aftertreatment systems (ATS).
Shah, Jash VipinS, Manoj KumarRatnaparkhi, AdityaH, Shivaprakash
The study emphasizes on development of Diesel Exhaust Fluid (DEF) dosing system specifically used in Selective Catalytic Reduction (SCR) of diesel engine for emission control, where a low pressure pumpless DEF dosing system is developed, utilizing compressed air for pressurizing the DEF tank and discharging DEF through air assisted DEF injection nozzle. SCR systems utilize Diesel Exhaust Fluid (DEF) to convert harmful NOx emissions from diesel engines into harmless nitrogen and water vapor. Factors such as improper storage, handling, or refilling practices can lead to DEF contamination which pose significant operational challenges for SCR systems. Traditional piston-type, diaphragm-type, or gear-type pumps in DEF dosing systems are prone to mechanical failures leading to frequent maintenance, repairs, and costly downtimes for vehicles. To overcome the existing challenges and to create a more reliable and simple DEF delivery mechanism the pumpless DEF Dosing system is developed. The system includes a completely sealed DEF tank, pressurized to a calibrated system pressure, by connecting the tank entry line to compressed air. Signal from the Engine Control Unit is provided to the metering valve positioned in the delivery line which controls the quantity to be dosed. Pressure reducing valve, quick relief valve and pressure sensor for feedback are integrated, with the tank and the metering valve to develop a completely reliable DEF dosing system. The system has been modelled in MATLAB and tested for different operating pressure, height and volume of the tank and by varying the signals provided to the metering unit. Overall, we can conclude that the pumpless DEF dosing system is a simplified version among the existing DEF dosing practices. When implemented it provides significant reduction in cost, complexity, repair and maintenance of the system eliminating the challenges and failures posed by the existing pump-based dosing systems.
M, HareniGiridharan, JyothivelA.l, SureshV, YuvarajRajan, Bharath
Air pollution from vehicle exhaust emissions is a growing issue in major cities around the world. Hydrogen is a clean and carbon-free fuel that presents a promising alternative to the fossil fuels. However, despite its environmental advantages, hydrogen internal combustion engines still produce some nitrogen oxides as a by-product due to high combustion temperatures. This study investigates the effectiveness of current exhaust after-treatment technologies designed to reduce NOx emissions in hydrogen-powered engines. A comparative analysis is conducted between the conventional urea-based selective catalytic reduction used in diesel engines and emerging hydrogen-based selective catalytic reduction technologies for hydrogen engines. The analysis is performed using CFD simulation in ANSYS Fluent, focusing on NOx reduction efficiency and other operational parameters. The results provide valuable insights into the feasibility and effectiveness of hydrogen SCR in achieving reduced NOx emissions, and this technology also eliminates the current urea storage and dosing arrangement, as vehicle-on-board available hydrogen can be used for NOx reduction in hydrogen-based SCR technology.
Kashyap, KeshavKhandagale, AnupPetale, Mahendra
This paper is to introduce a new catalyst family in gasoline aftertreatment. The very well-known three-way catalysts effectively reduce the main emission components resulting from the combustion process in the engine, namely THC, CO, and NOx. The reduction of these harmful emissions is the main goal of emission legislation such as Bharat VI to increase air quality significantly, especially in urban areas. Indeed, it has been shown that under certain operating conditions, three-way catalysts may produce toxic NH3 and the greenhouse gas N2O, which are both very unwanted emissions. In a self-committed approach, OEMs could want to minimize these noxious pollutants, especially if this can be done with no architecture change, namely without additional underfloor catalyst. In most Bharat VI gasoline aftertreatment system architectures, significant amounts of NH3 occur in two phases of vehicle driving: situations with the catalyst temperature below light-off, which appear after cold start or at low-speed urban driving and hot, high mass flow phases. In this paper, we will compare several approaches to reduce NH3 starting with an existing gasoline technology, diesel technologies modified to gasoline conditions and the especially developed novel gasoline Secondary Emission Treatment (SET) catalyst, providing both ammonia abatement and underfloor three-way functionality. SET is the combination addressing both the cold start phase and hot driving conditions. In addition, it fulfills the role of an underfloor three-way catalyst, responsible for CO and NOx hot phase treatment.
Kuhn, SebastianMagar, AvinashKogel, JuliusLahousse, Christophe
This study develops deep learning (DL) long–short-term memory (LSTM) models to predict tailpipe nitrogen oxides (NOx) emissions using real-driving on-road data from a heavy-duty Class 8 truck. The dataset comprises over 4 million data points collected across 11,000 km of driving under diverse road, weather, and load conditions. The effects of dataset size, model complexity, and input feature set on model performance are investigated, with the largest training dataset containing around 3.5 million data points and the most complex model consisting of over 0.5 million parameters. Results show that a large and diverse training dataset is essential for achieving accurate prediction of both instantaneous and cumulative NOx emissions. Increasing model complexity only enhances model performance to a certain extent, depending on the size of the training dataset. The best-performing model developed in this study achieves an R2 higher than 0.9 for instantaneous NOx emissions and less than a 2% error for cumulative NOx emissions on the test data. Furthermore, the model achieves an F1 score above 0.9 in determining whether NOx emissions comply with emission standards. The developed DL tailpipe emission models in this study have diverse applications based on the amount and type of available input data, including engine and aftertreatment system control, diagnostics, and vehicle system-level simulations. These applications collectively contribute to minimizing NOx emissions of vehicles to meet stringent transportation emission standards.
Shahpouri, SaeidJiang, LuoKoch, Charles RobertShahbakhti, Mahdi
The Dosing Control Unit (DCU) is a vital component of modern emission control systems, particularly in diesel engines employing Selective Catalytic Reduction technology (SCR). Its primary function is to accurately control the injection of urea or Diesel Exhaust Fluid (DEF) into the exhaust stream to reduce nitrogen oxide (NOₓ) emissions. This paper presents the architecture, operation, diagnostic features, and innovation of a newly developed DCU system. The Engine Control Unit, using real-time data from sensors monitoring parameters such as exhaust temperature, NOₓ levels, and engine load, calculates the required DEF dosage. Based on DEF dosing request, the DCU activates the AdBlue pump and air valve to deliver the precise quantity of diesel exhaust fluid needed under varying engine conditions. The proposed system adopts a master-slave configuration, with the ECU as the master and the DCU as the slave. The controller design emphasizes cost-effectiveness and simplified hardware, and software architecture compared to commercial counterparts. Additionally, it integrates diagnostic functions compliant with On-Board Diagnostics (OBD) and Unified Diagnostic Services (UDS) standards to detect system anomalies such as blockages, leaks, and electrical faults (e.g., short to ground or battery). By combining accurate dosing with advanced diagnostics, the DCU enhances SCR system efficiency, fuel economy, and compliance with strict emission norms. Test bench and simulation results confirm that the developed controller meets international emission and diagnostic standards. This positions the DCU as a significant contributor to cleaner, more efficient, and sustainable automotive technologies.
Raju, ManikandanK, SabareeswaranK K, Uthira Ramya BalaKrishnakumar, PalanichamyArumugam, ArunkumarYS, Ananthkumar
In order to improve engine emission and limit combustion instabilities, in particular for low load and idle conditions, reducing the injected fuel mass shot-to-shot dispersion is mandatory. Unfortunately, the most diffused approach for the hydraulic analysis of low-pressure injectors such as PFIs or SCR dozers is restrained to the mean injected mass measurement in given operating conditions, since the use of conventional injection analyzers is unfeasible. In the present paper, an innovative injection analyzer is used to measure both the injection rate and the injected mass of each single injection event, enabling a proper dispersion investigation of the analysed low pressure injection system. The proposed instrument is an inverse application of the Zeuch’s method, which in this case is applied to a closed volume upstream the injector, with the injector being operated with the prescribed upstream-to-downstream pressure differential. Further, the injector can inject freely against air, thus enabling simultaneous analyses of the resulting spray such as imaging or momentum flux measurement. In the present paper, the proposed injection analyzer is used to characterize the tested PFI injector in terms of injection rate and injected mass dispersion in different operating conditions with atmospheric downstream pressure conditions. The simultaneous spray imaging is also used to complement the analysis of the investigated low pressure injection system in throttled-like operating conditions.
Postrioti, LucioMaka, CristianMartino, Manuel
Heavy duty diesel engines provide a robust power plant for transportation applications for both on highway and off road applications. Control of criteria pollutants such as particulate matter and NOx at tailpipe for these applications based on standards set by regulatory bodies such CARB and EPA is critical. SwRI has demonstrated capability to achieve 0.02 g/bhp-hr. tailpipe NOx standard through the application of a model based controls in EPA and CARB funded projects. This control mechanism enables precise urea dosing for both steady state and transient conditions by leveraging estimated ammonia storage state in a dual dosing system using a set of chemical kinetics-based SCR observer models. This controller is highly nonlinear, with a significant amount of controller tuning with up to 55 calibratable parameters. In order to improve the accuracy and reduce the time required for calibration of this controller, this work proposes the deployment of a Deep Learning-based SCR plant model in conjunction with a Genetic Algorithm based optimization script in a closed loop with the low NOx controller that can enable identification of near-optimal controller calibration in a simulation environment. This work describes the optimization framework and its validation with real-world experimental data. The calibration determined in this framework was able to achieve 0.02 g/bhp-hr for regulatory cycles consisting of CFTP, HFTP, RMC, and LLC. A quantitative and qualitative analysis on the results from this proposed framework is performed and is compared against existing expert driven manual calibration process.
Chundru, Venkata RajeshRajakumar Deshpande, ShreshtaSharp, ChristopherGankov, Stanislav
On-Board Diagnostic (OBD) strategies utilize a predictive model to estimate engine out NOx levels for a given set of operating conditions to ensure the accuracy of the Nitrogen Oxides (NOx) sensor. Furthermore, this model is also used to determine urea dosing quantities in situations where the NOx sensor is unavailable such as cold starts or as a reaction to a NOx sensor plausibility failure. Physics-based NOx prediction models guarantee high levels of accuracy in real-time but are computationally expensive and require measurements generally not available on commercial powertrains making them difficult to implement on controllers. Consequently, manufacturers tend to adopt a mathematical approach by estimating NOx under standard operating conditions and use a variety of correction factors to account for any changes that can influence NOx production. Such correction factors tend to be outcomes of base engine calibration settings or outputs of models of other related sub systems and may not accurately capture the effect of component level drifts that directly influence NOx production such as mass air flow (MAF) sensor drifts, humidity variations, exhaust gas recirculation (EGR) rate variations, etc. Since mathematical approaches approximate physical phenomena, errors in any of the inputs tend to be compounded, thereby diminishing the accuracy of the final output. The method presented in this material focuses on using lambda values derived from tailpipe O2 measurements as the sole input to adjust the NOx model since it is a direct representation of the quality of combustion and accounts for variations in operation that can influence NOx production. This produces an easy-to-implement “self-adjusting” NOx model strategy that is consistent with the physics of NOx formation without requiring any additional hardware and ensures high levels of accuracy required to guarantee OBD robustness.
Sunder, AbinavSuresh, RahulPolisetty, Srinivas
Achieving zero emissions across transportation is a tremendous challenge. The upcoming Euro 7/VII standards, set to be enforced in 2025, will mandate further reduction in ICEs exhaust emissions. Thus, additional improvements and potential new technologies and fuels are needed to design ultra-low emissions vehicles. Hydrogen seems to be a very attractive fuel, thanks to its high lower heating value, clean combustion, and extremely low pollutant emissions, due to the zero-carbon content. Nevertheless, NOx emissions are still an issue in hydrogen fueled engines and optimized lean-burn combustion and suitable after-treatment NOx reduction are mandatory to reach high specific power and efficiency and near zero NOx emissions, thus enabling H2-ICE powered vehicles to be zero-impact emitting technology solution. Selective Catalytic Reduction by using NH3 as the reducing agent is the most effective control technology for NOx abatement. Nevertheless, ongoing research and innovation are critical in developing new strategies for reducing NOx emissions, to overcome the NH3-SCR system main critical issues (extra equipment for urea storage and dosing, ammonia-slip, deactivation and fouling, low efficiency at low temperature). The SCR of NOx by hydrogen is considered a promising alternative to traditional ammonia-based deNOx technology. The H2-SCR catalysts are suitable for engine exhaust after-treatment during cold-start and urban-driving operations, exhibiting higher catalytic activity for low-temperature NOx emissions conversion (180 – 200 °C). Furthermore, in H2-ICE powered vehicles, the additional tank to store the reducing agent is not needed with a significant simplification of the engine exhaust lay-out. Experimental investigations on different H2-SCR catalysts have demonstrated that the conversion activity is greatly affected by the catalytic system configuration, the adsorption properties of the support material, the H2 spillover, that in turn are affected by H2/NO ratio and exhaust gas composition, temperature and flow rate. In the present paper, a feed-forward neural network model of H2-SCR is presented, with the aim of performing real-time estimation of reduction efficiency and supporting the design of suitable H2 management to achieve maximum NOx reduction and minimum hydrogen consumption. Model training and identification are carried out against a large set of experimental data measured on a H2-SCR small scale prototype at the Synthetic Gas Bench. The experimental tests were designed to reproduce the real conditions expected at the exhaust of a H2-fueled engine.
Crispi, Maria RosariaConde Cortabitarte, CarlaOcchicone, AlessioPiqueras, PedroArsie, IvanPianese, Cesare
Heavy-duty vehicles powered by hydrogen internal combustion engines (H2-ICEs) present a compelling solution for sustainable transportation. When optimized for ultra-lean operation, H2-ICEs are capable of meeting the most stringent contemporary legislative emission standards. However, achieving optimal drivability necessitates occasionally an enriched operating mode, thereby presenting significant challenges in maintaining ultra-low emissions. In this context, the implementation of advanced exhaust after-treatment technologies becomes essential to ensure near-zero tailpipe emissions with minimal impact on fuel efficiency and drivability. This paper investigates the potential of a passive Selective Catalytic Reduction (SCR) exhaust configuration for a heavy-duty hydrogen (HD H₂) engine, employing testing and modeling of a Lean NOx Trap, utilized as an ammonia (NH3) generator, in conjunction with a downstream Selective Catalytic Reduction system. We underscore the complexities associated with defining inlet boundary conditions—including exhaust flow rate, temperature, and composition—during transient engine operation. To address this challenge, an advanced engine model is used, providing the feed gas conditions for targeted steady-state and transient testing protocols on a synthetic gas bench (SGB). Based on the test results, we isolated the underlying phenomena, calibrating the Lean NOx Trap (LNT) and Selective Catalytic Reduction (SCR) kinetic models with a focus on NOx/NH3 storage, deNOx efficiency, and NH3 generation during LNT regeneration events. Utilizing a fully transient SGB test, the catalysts are subjected to transient conditions resembling real world driving cycles and to validate the fidelity of the catalyst models. The combined engine and aftertreatment model allows a comprehensive evaluation of the passive SCR technology potential for a heavy-duty hydrogen engine.
Zafeiridis, MenelaosAlexiadou, PanagiotaKoltsakis, Grigorios
Selective Catalytic Reduction (SCR) is a key technology for reducing nitrogen oxides (NOx) emissions in diesel engines. In this process, a urea-water solution (UWS) is injected upstream of the catalyst to generate ammonia, which reacts with NOx to form nitrogen. However, liquid urea can adhere to system walls, undergoing secondary reactions that lead to the formation of solid deposits. These deposits must be minimized to ensure the long-term durability and efficiency of the system. Computer-Aided Engineering (CAE) simulations play a crucial role in optimizing SCR performance during the design phase. However, accurately predicting deposit formation requires detailed chemical modelling, which is computationally expensive and introduces uncertainties related to reaction mechanisms definition. To address this challenge, simplified CAE approaches are needed to assess deposit formation risks while maintaining computational efficiency. This study presents an improved Deposit Risk Index (DRI) integrated into a 3D-CFD model of an off-road vehicle equipped with an SCR exhaust system. The enhanced DRI leverages film and near-wall gas properties to estimate deposit formation risks up to 350°C, eliminating the need for detailed chemical reactions and minimizing computational effort. Additionally, an updated Bai-Gosman droplet impingement model is used to improve liquid film formation prediction across a wider temperature range. To further enhance efficiency, a thermal transient acceleration technique was implemented, enabling the prediction of realistic solid temperatures within a few seconds of simulation. The proposed methodology was validated through experimental testing at challenging part-load operating conditions. Optical imaging of deposits was used to calibrate the DRI function and validate the 3D-CFD model. Simulation results demonstrated good agreement with experimental data, accurately capturing deposit locations and trends across various engine operating conditions. The proposed approach provides valuable insights for optimizing SCR system design and mitigating deposit-related issues while significantly reducing simulation time.
Bianco, AndreaPrestifilippo, MattiaRobino, CristinaPetrafesa, GiovanniPostrioti, LucioBuitoni, Giacomo
This article presents a novel approach to enhance the accuracy and efficiency of three-dimensional (3D) selective catalytic reduction (SCR) simulations in monolith reactors by leveraging high-fidelity urea–water solution computational fluid dynamics (UWS-CFD) data. The focus is on estimating the nonuniformity of NH₃ at the SCR inlet, crucial for achieving optimal performance in aftertreatment systems. Due to its high computational cost, a CFD-only approach is not feasible for transient drive cycle simulations aiming to accurately predict SCR NOx conversion and NH₃ slip by accounting for the nonuniform NH₃ distribution at the SCR inlet. Therefore, the development of reduced order or fast models is of prime importance. By employing artificial neural networks (ANNs), we establish a framework that eliminates the need for computationally expensive CFD calculations, allowing for swift and precise 3D SCR simulations under various injection, mixing region, and exhaust conditions. The methodology involves conducting extensive CFD simulations across a range of operating parameters to create a comprehensive dataset. This dataset is then utilized to train an ANN, enabling the accurate prediction of inlet NH₃ distribution for 3D SCR simulations within the GT-SUITE environment. Validation assessments demonstrate the trained ANN’s capability to predict inlet distributions even for conditions not explicitly included in the training dataset, attesting to its robust generalization. The trained ANN model serves as a powerful tool for optimizing aftertreatment system parameters, paving the way for enhanced design efficiency. Through systematic parameter optimization, the proposed methodology aims to minimize urea deposition and maximize NOx conversion efficiency while simultaneously minimizing NH₃ slip. The integration of UWS-CFD and ANN modeling not only expedites simulation processes but also contributes to the advancement of aftertreatment system design by providing a reliable and accurate predictive tool for engineers and researchers in the field.
Mishra, RohitGundlapally, SanthoshWahiduzzaman, Syed
Urea–water solution (UWS) is sprayed during selective catalytic reduction (SCR) in the aftertreatment system of a diesel engine. UWS decomposes to ammonia and reacts with harmful nitrogen oxides present in exhaust gas to convert it to harmless nitrogen and water vapor. The interaction of UWS spray droplets with the hot wall of the aftertreatment system plays a crucial role in the performance and life of the aftertreatment system used in modern diesel engines for emission control. We report here a comprehensive experimental investigation on the normal impact of UWS droplets on the heated wall of stainless steel (SS410), mimicking the droplet–wall interaction in an SCR aftertreatment system. We have built a regime map underlying the possible outcomes under operating conditions encountered in an SCR system. The transition zones are identified, and the complex transition dynamics from one regime to another are discussed. Finally, we investigate and discuss the universality of the non-dimensional parameters used to characterize drop impingement on a heated wall. Present study will help to develop strategies to avoid the urea deposits on the walls of an SCR system.
Singh, Kartikeya K.Deka, HiranyaPandey, VinodKhot, AmbarishBasak, NarendranathShastry D. M., Channaveera
Urea-based selective catalytic reduction (SCR) systems are widely used to meet stringent NOx emission standards in industrial diesel engines. However, suboptimal design of the urea-water solution (UWS) mixing pipes in SCR systems can lead to the formation of urea-derived solid deposits, which may adversely affect the system performance and reliability. Although recent advancements in deposit simulation technology using three-dimensional Computational Fluid Dynamics (3D CFD) have significantly improved the performance and compactness of mixing pipes, assessing deposit formation across all operating and environmental conditions remains challenging due to high simulation costs. This study introduces a novel computational method for predicting the formation and temperature of permanent liquid films from UWS injection which are closely related to deposit formation, along with new deposit evaluation criteria based on them. This proposed method integrates a one-dimensional heat transfer model with empirical thermal dissipation and film formation data derived from 3D CFD simulations, allowing for rapid prediction of film formation and temperature. By simplifying calculations to algebraic equations, this method enables rapid assessment of deposit formation across various operating conditions and provides a comprehensive evaluation of deposit formation in the SCR systems. The effectiveness of the proposed approach is validated through good correlations between simulation predictions and experimental results of deposit formation. In industrial machinery, versatile aftertreatment systems (ATS) are used across different applications and layouts. The proposed method enables speedy assessment of deposit formation by accounting for variations in ATS layouts, operating patterns, and environmental conditions during the design phase. It also supports the development of optimized insulation designs, balancing reliability, and cost-efficiency in product development.
Sugimoto, KazumaKawabe, Ken
Hydrogen internal combustion engines (H2-ICE) do not emit any fuel-borne carbon emission species. Nitrogen oxides are the remaining raw emission species at significant levels. However, the exhaust aftertreatment system is exposed to a different exhaust matrix, including unburned hydrogen. This raises the question of the role of hydrogen emissions for the aftertreatment system. Extensive synthetic gas bench (SGB) test campaigns address the role of hydrogen in several production catalyst components. Starting with selective catalytic reduction (SCR) systems, a systematic variation of the hydrogen concentration shows rather small effects on the NOX reduction performance. A change in selectivity results in increased secondary N2O emissions for a copper-zeolite system, whereas a vanadium-based SCR catalyst is unaffected. However, both SCR types are highly sensitive to the NO2/NOX ratio in the raw emission. Therefore, an upstream oxidation catalyst remains important for low temperature performance. Investigations of oxidation catalysts with varying platinum loadings show increased oxidation performance with higher hydrogen content. This effect is attributed to the accelerated heating of the catalytic centers due to the exothermic hydrogen reaction. In parallel however, secondary N2O emissions increase during light-off, speaking against a post-oxidation-based catalyst heating strategy. The strongest sensitivity to hydrogen is found in lambda sensors. Fast hydrogen diffusion through the zirconia distorts the signal towards rich mixtures. Overall, the results emphasize the important role of hydrogen, especially with respect to secondary N2O emissions, requesting H2-ICE-specific operating strategies to achieve zero-impact tailpipe emissions.
Sterlepper, StefanLampkowski, AlexanderHimmelseher, KatrinÖzyalcin, CanClaßen, JohannesPischinger, Stefan
Ammonia (NH3) is emerging as a promising fuel for longer range decarbonised heavy transport, predominantly due to relative favourable characteristics as an effective hydrogen carrier. This is despite generally unfavourable combustion and toxicity attributes, restricting ammonia’s end use to applications where robust health and safety protocols can always be assured. In the currently reported work, a spark ignited thermodynamic single cylinder research engine was equipped with separate gaseous ammonia and hydrogen port injection fuelling, with the aim of understanding the impact of varied co-fuelling upon combustion, fuel economy and engine-out emissions (and the arising implications upon future emissions after-treatment). Under stoichiometric conditions, the engine could be operated in a stable manner on pure NH3 at low-to-medium speeds and medium-to-high engine loads, with up to ~20% hydrogen (by energy) required at the lowest engine loads. Engine-out NH3 emissions remained relatively high across the stoichiometric operating map (ranging between 7000-8000ppm), with engine out NOx remaining comparatively low (between 1000-2000ppm). An alternative lean burn operating strategy was then investigated, with the intent of balancing ammonia slip versus NOx to a degree facilitating minimised tailpipe emissions by future use of Selective Catalytic Reduction (SCR) emissions after-treatment technology, where the NH3 slip can be directly utilised as NOx reductant (i.e. eliminating the need for a urea storage and injection system found in conventional SCR systems). Ideally such SCR systems operate with a fixed “alpha ratio” equal to ~1 (where this ratio is the ratio of engine-out NH3 to NOx on a ppm basis, with a value of unity indicating the ideal amount of reductant to simultaneously consume NH3 slip and decompose NOx). This was achieved by conducting a series of parametric sweeps, varying the air-to-fuel ratio and hydrogen content in the fuel mix to evaluate the ideal combinations of hydrogen substitution ratio and relative air-to-fuel ratio (λ) to achieve an alpha ratio of 1. It was concluded that operating the engine with ~20% hydrogen and slightly lean (λ~1.2) would result in an ideal alpha ratio of ~1 across most of the operating map, with little variation in alpha ratio or lambda noted with changing engine load. The results indicate, apparently for the first time, the high promise of a lean burn spark ignition ammonia/hydrogen co-fuelling strategy for balancing engine-out NOx and NH3 emissions via SCR after-treatment. The supplementary hydrogen along with the lean operation was noted to also result in small improvements in indicated thermal efficiency of 1-2% compared to baseline stoichiometric operation with minimum hydrogen.
Ambalakatte, AjithGeng, SikaiMurugan, ReeseVaraei, AmirataCairns, AlasdairHarrington, AnthonyHall, JonathanBassett, Michael
This paper investigates heated and cold Diesel Exhaust Fluid (DEF) sprays with the aim of establishing the effect of temperature on the resulting spray characteristics. The work is motivated by the need to optimize active Selective Catalytic Reduction (SCR) systems to meet more stringent nitrogen oxide (NOx) emission regulations for internal combustion engines. Pre-heating DEF has the potential to improve evaporation of the injected fluid, increasing the NOx conversion efficiency of the SCR at low exhaust temperatures. Experiments are carried out using the MAHLE SmartHeat fluid heater and mounted atop a DEF injector, with an incorporated thermocouple for fluid temperature. The fluid temperature established by the heater in this configuration was about 130 °C. The fluid is injected into an atmospheric environment and Schlieren imaging is used to visualize the spray evolution. CFD simulations are also carried out to validate the experimental observations and further shed light on the associated velocity field. With respect to the spray characteristics, the results show that the most significant difference between cold and heated DEF sprays occurs when the heated fluid experiences flash boiling prior to injection. This flash boiling is thought to arise from occasional overheating near the heating surfaces. Under conditions of normal hot liquid DEF injection, only a slight improvement in the atomization pattern is observed. The merit of the heating is expected to be more pronounced in the subsequent evaporation of the droplets. With respect to the simulations, it was found that the predicted penetration depths agree with the experimental observations. The observed pronounced differences between the characteristics of the cold and hot spray with flash boiling as well as the limited improvements of the hot liquid spray characteristics are explainable by considering their Reynolds and Weber numbers.
Liu, ZeyangPeters, NathanBunce, MikePothuraju Subramanyam, SaiAkih Kumgeh, Benjamin
The heavy-duty low NOx program funded by EMA at Southwest Research Institute (SwRI) evaluates a combination of engine and advanced aftertreatment systems to achieve a 0.035 g/bhp-hr tailpipe NOx standard. This work emphasizes improvements to the light-off SCR (LO SCR) model used for low NOx controls. Two key mechanisms drive these improvements: the first is a real-time feedback system that utilizes the LO SCR outlet NOx sensor for short-term corrections to the model state, and the second involves adjustments to the dosing mechanism based on long-term trends in dosing signals compared to predicted NH3 consumption, derived from LO SCR inlet and outlet NOx sensors, referred to as long-term trim. An algorithm is incorporated to differentiate the LO SCR outlet NOx sensor readings into NOx and NH3 components based on cross-correlation between inlet and out NOx sensors termed as speciation. The integration of this speciation algorithm with both short-term and long-term trim mechanisms significantly enhances the accuracy of the model estimated NH3 storage state, as well as the prediction of outlet NOx, and NH3 levels under various transient conditions, including CFTP, HFTP, RMC, and LLC cycles. This improved accuracy in the LO SCR observer model enables more precise control of transient tailpipe NOx in the system.
Chundru, Venkata RajeshAdsule, KartikSharp, Christopher
Cu/zeolite selective catalytic reduction (SCR) catalysts are used globally to reduce NOx emissions from diesel engines. These catalysts can achieve high NOx conversion efficiency, and they are hydrothermally durable under real world diesel exhaust environments. However, Cu/zeolite catalysts are susceptible to sulfur poisoning and require some type of sulfur management even when used with ultra-low sulfur diesel (ULSD). In the present study, the authors seek to better illuminate the chemical processes responsible for ammonium sulfate formation and decomposition occurring in Cu/zeolite SCR catalysts. Reactor-based experiments are first conducted with a real-world concentration of SO2 (0.5 ppmv) and a typical diesel exhaust water vapor concentration (7 vol.%) to quantify progressive effects of ammonium sulfate formation. A second group of experiments probe the chemical decomposition of ammonium sulfate via NO titration. The “movement” of sulfate species during this process is monitored with temperature programmed desorption experiments. Finally, the effect of NO2 on ammonium sulfate is investigated via either co-feeding during ammonium sulfate formation or post-feeding following ammonium sulfate formation, since it is expected that NH3, SO2, and NO2 will all be present at the catalyst surface during real-world operation. The authors believe the results presented herein can support the broad research effort to continue to improve low temperature NOx conversion which is notably degraded by the formation of ammonium sulfate species.
Ottinger, NathanXi, YuanzhouLiu, Z. Gerald
With the continuous upgrading of emission regulations for internal combustion engines, the nitrogen oxide treatment capacity of selective catalytic reduction (SCR) aftertreatment needs to be continuously improved. In this study, based on a prototype of SCR aftertreatment, the impact of the arrangement of key components in the SCR system (urea injector, mixer, and catalyst unit) on ammonia uniformity was investigated. First, parameterized designs of the urea injector, mixer, and SCR unit were conducted. Then, using computational fluid dynamics (CFD), numerical simulations of the established aftertreatment system models with different parameter factors were performed under a high-exhaust temperature and a low-exhaust temperature conditions to study the impact of each individual parameter on ammonia uniformity. Finally, an optimized solution was designed based on the observed patterns, and the optimized samples were tested on an engine performance and emission test bench to compare their ammonia uniformity. The test results showed that the ammonia uniformity of the optimized solution was improved by 2%–3% compared to the original design, reaching 0.952 and 0.967, respectively.
Jie, WangJin, JianjiaoWu, Yifan
Widely used as power equipment, diesel engines emit NO x , which significantly threatens the well-being of both the ecosystem and individuals. The SCR system, which is employed to reduce NO x emissions from diesel engines, relies on precise control of the NO x emission levels. Addressing the challenge that traditional NO x emission prediction methods struggle to accurately forecast the emissions under transient operating conditions, this article introduces a deep learning model that integrates CNN, ECA, and BIGRU. The model’s necessary experimental data were collected during the hot phase of the WHTC, and input parameters were screened through correlation analysis. The model employs a CNN for feature extraction, integrates an ECA module to refine key feature processing, and utilizes BIGRU to capture temporal dynamics and dependencies, yielding predictive outcomes. Additionally, the model employs the Adam optimizer and combines it with BWO to adjust hyperparameters, thereby elevating the model’s accuracy for predicting transient NO x emission. Comparative analysis with existing CNN, LSTM, and CNN–LSTM models revealed that CNN–ECA–BIGRU model had a notable reduction in MAE, RMSE, and MAPE, along with an enhanced R 2 value. These improvements highlight the model’s superior predictive accuracy and its robust nonlinear fitting ability.
Peng, YunlongWang, GuiyongWang, YuhuaWang, FeiyangWang, ZhiyuanHe, Shuchao
NOx after-treatment has greatly limited the development of lean-burn technology for gasoline engines. NH3-Selective Catalytic Reduction (SCR) technology has been successfully applied to NOx conversion in diesel engines. For gasoline engines, SCR catalyst is required to maintain high activity over a higher temperature window. In this study, we utilized a turbocharged and intercooled 2.0 L petrol engine to investigate the NOx conversion of two zeolite-based SCR catalysts, Cu-SSZ-13 and Fe/Cu-SSZ-13, at exhaust flows ranging from 80 to 300 kg/h and exhaust temperatures between 550 to 600°C. The catalysts were characterized using SEM, ICP, XRD, H2-TPR, NH3-TPD, and other methods. The selected Fe/Cu-SSZ-13 catalyst showed higher NOx conversion (>80%) in the temperature range of 550~600oC and 80~300 kg/h exhaust gas flow. NOx output could be controlled below 10ppm. The characterization results showed that although the specific surface area and acidic sites decreased after the aging treatment for Fe/Cu-SSZ-13, they still retained active sites, showing higher activity and stability.
Pan, ShiyiWang, RuwenZhang, NanXu, ZhiqinHu, JiangtaoLiao, XiukeDuan, PingpingChen, Ruilian
The present study aims to meet the Euro-VII compliance applicable for internal combustion engines (diesel and hydrogen) by improving the performance of selective catalytic reduction (SCR) system using a novel urea water solution (UWS) mist injection technique. In SCR system, the interaction of exhaust gas and UWS resulted into ammonia (NH3) species, which is mixed with harmful NOx emission and converted into harmless by-products. Despite the proven technology, there are several challenges presented in the existing system which restricts the ideal performance of SCR system especially during cold starting condition: (i) incomplete droplet evaporation (ii) solid deposit formation (iii) non uniformity of NH3 distribution at the catalyst entrance. The past studies shows that the droplet size plays a major role in this context. Further, it is noted that the smaller size droplets are desirable to overcome the impediments and enhance the efficiency of SCR application. Therefore, it is decided to investigate the effect of mist (contains very fine size droplets) injection on the important factors of SCR system such as formation and spatial uniformity of NH3 species, and urea solid deposition on the mixing chamber wall. For this purpose, the study is carried out using the numerical simulation where the Reynolds Average Navier Stoke (RANS) and discrete phase model (DPM) is used to simulate the exhaust gas and mist, respectively. The results highlight that using the mist injection is a promising solution as it not only promotes the droplet evaporation rate but also enhances the NH3 distribution which leads to a homogeneous mixture of NH3/NOx. Further, it is noted that the amount of urea solid deposition is significantly smaller on the mixing chamber wall.
Venkatachalam, PalaniappanShiva, ShashidharGovindarajan, VaishaliSoni, PrernaPatidar, Sachin
As vehicle emission standards are becoming stringent worldwide because of the looming climate crisis, it is important to control the pollutants that vehicles emit. To achieve the stringent emission target, it has become a priority to enhance the capability of Emission Control System (ECS) which consist of Diesel Oxidation Catalyst (DOC), Diesel Particulate Filter (DPF) and Selective Catalytic Reduction (SCR) sub-systems. One of the bottlenecks is the limited operating temperature range of the after-treatment system. In modern emission control systems, the temperature characteristics should always be optimized to have the best efficiency involving chemical conversions. To achieve this optimal operating temperature, different thermal control strategies are followed in the Engine and emission control unit. Temperature sensor values are one of the primary inputs for thermal management strategies. In the event of temperature sensor malfunction, the ECS performance is affected due to incorrect temperature input, resulting in higher emissions leading to performance limitations. To mitigate this issue, it is important to predict the exhaust gas temperature precisely. In this paper, studies are carried out to show Machine Learning (ML) based digital sensors can be instrumental in maintaining ECS functionality and performance. This paper focuses on developing Machine Learning (ML) Model to replicate the sensor prediction based on dependent parameters. A Multi-Layer Perceptron (MLP) neural network is explored and implemented to predict the SCR inlet temperature. The predicted temperature is used to control various thermal strategies to improve the SCR performance. The selected model is trained and tested with actual vehicle data for real time correlation. The model’s performance is improved through evaluation metrices such as R2-Score, Mean Squared Error, and Mean Absolute Error. These metrices provide a thorough evaluation of the algorithm’s performance compared to the actual observed values. The high R2 Score indicates strong predictive capability, while the low errors demonstrate the model’s reliability.
Kumar, AmitV H, YashwanthKumar, RamanHegde, KarthikManojdharan, Arjungopal
Selective catalytic reduction (SCR) technology is currently one of the most effective methods to reduce NOx emissions for engine. NH3-SCR technology is also considered to be the most promising hydrogen engine after-treatment device. This paper used Cu-SSZ-13, which is widely commercially available, as the research object, and explored the relationship between micron and nanoscale grain sizes through experimental methods such as BET, XRD, NH3-TPD, UV-vis-DRS and activity testing, the influence mechanism of micron-scale and nano-scale grain size on the morphology and properties of Cu/SSZ-13 catalyst was explored. The results show that the fresh nanoscale 900F sample has higher low-temperature NOx conversion efficiency, while the micron-scale 1800F sample has poor low-temperature activity and better high-temperature activity. This is closely related to its morphological characteristics, adsorption and desorption characteristics and dual-site properties. The specific surface area and total pore volume of the 900F sample are larger, but according to the diffraction peaks in XRD, its crystallinity is low, resulting in the high temperature activity of the 1800F sample being higher than that of the 900F sample. After SO2 poisoning, the proportions of strong Lewis acid sites and Brønsted acid sites increased, resulting in an increase in both low-temperature and high-temperature activities of the 900S sample. And the activity of micron-scale samples decreases sharply, and the high-activity temperature window shrinks.
Chen, YajuanLou, DimingZhang, YunhuaTan, PiqiangFang, LiangHu, Zhiyuan
A major challenge for auto industries is reducing NOx and other exhaust gas emissions to meet stringent Euro 7 emission regulations. A urea Selective Catalyst Reduction (SCR) after-treatment system (ATS) commonly uses upstream urea water injection to reduce NOx from the engine exhaust gas. The NOx emission conversion rate in ATSs is high for high exhaust gas temperatures but substantially low for temperatures below 200°C. This study aims to improve the NOx conversion rate using urea pulse injection in a mass-production 2.2 L diesel engine equipped with an SCR ATS operated under low exhaust gas temperature. The engine experimental results show that, under 200°C exhaust temperature and 3.73x104 h-1 gross hourly space velocity (SV), the NOx conversion rate can be improved by 5% using 5-sec ON and 12-sec OFF (denoted as 5/12 s) urea pulse supply compared to the constant supply under time-averaged 1.0 urea equivalence ratio. It is experimentally observed that the urea pulse supply’s efficacy decreases under higher exhaust gas temperatures. The SCR model is developed with surface reactions, and the CFD results indicate that the urea pulse supply oscillates the surface reaction rates for NO and NO2, suggesting improved conversion rates. Further results on the urea pulse and constant supplies at high exhaust temperatures are reported. The NOx conversion improvement rates under various ON-OFF urea pulses are also discussed. The predicted dynamic fluctuation of the pulse supply and dithering SCR reaction is investigated.
Yoshida, FukaTakahashi, HideakiKotani, YuyaZu, QiuyueSok, RatnakKusaka, Jin
Engine and aftertreatment solutions have been identified to meet the upcoming ultra-low NOx regulations on heavy duty vehicles in the United States. These standards will require changes to current conventional aftertreatment systems for dealing with low exhaust temperature scenarios while increasing the useful life of the engine and aftertreatment system. Previous studies have shown feasibility of meeting the US EPA and California Air Resource Board (CARB) requirements. This work includes a 15L diesel engine equipped with cylinder deactivation (CDA) and an aftertreatment system that was fully DAAAC aged to 800,000 miles. The aftertreatment system includes an e-heater (electric heater), light-off Selective Catalytic Reduction (LO-SCR) followed by a primary aftertreatment system containing a DPF and SCR. The e-heater was capable of providing up to 10 kW, however for the purpose of this project, lower power settings of 2.5 kW and 5 kW were studied in combination with CDA for lowest possible CO2 emissions. Test cycles included the heavy duty FPT (hot and cold), a low load cycle, a beverage cycle, and a stay hot operation. The data found in this study show how the application of a low power e-heater enables an engine with CDA and an aftertreatment system after 800,000 miles aging to meet ultra-low NOx emissions with minimum CO2 penalty.
Kramer, JanRice, MichaelZavala, BryanSharp, ChristopherMcCarthy, JamesKarrer, Ben
Electricity, e-fuel and H2 are considered important recent and future sources of energy for heavy-duty vehicles. Heavy-duty battery electric vehicles (BEV) have many technical challenges. Therefore, internal combustion engines (ICE) powered by e-fuel and hydrogen can be used as an alternative to batteries in heavy-duty trucks. Selective catalytic reduction (SCR) systems are necessary for achieving the goals of zero-emission internal combustion engines that use e-fuel or H2 as a fuel. The Japanese automotive industry mainly utilizes Cu-Zeolite-based SCR catalysts since vanadium-based catalysts have been difficult to be used to prevent the release of vanadium into the atmosphere due to the relatively low evaporation temperature. This study investigated whether improving the conversion rate by pulsing the NH3 supply was possible. Experiments were conducted in a mini-reactor with an inflow of simulated exhaust gas to examine the effect of the pulse amplitude, frequency, and duty ratio on the conversion rate when an NH3 pulse supply was applied to a test piece Cu-chabazite catalyst. The results of the reactor experiment were compared with numerical simulations that considered the detailed surface reaction processes on the catalyst. The experimental results showed that purification of NOx at low temperatures (200°C) improved from 45% to 62% by providing a pulsed supply of reducing agent (NH3) rather than a continuous supply. During the time when the pulse supply was off, the decomposition of ammonium nitrate (NH4NO3) was promoted, enhancing the conversion rate of NOx. The results of the simulations demonstrated that the gas concentrations and conversion rate in the catalyst and unique phenomena at low temperatures, such as the formation and decomposition of NH4NO3 and the ammonia-blocking effect, could be accurately reproduced and simulated.
Morita, DaikiKotani, YuyaZu, QiuyueYoshida, FukaSok, RatnakKusaka, Jin
Hydrogen (H2) is commonly considered as one of the most promising carbon-free energy carriers allowing for a decarbonization of combustion applications, for instance by retrofitting of conventional diesel internal combustion engines (ICEs). Although modern H2-ICEs emit only comparably low levels of nitrogen oxides (NOx), efficient catalytic converters are mandatory for exhaust gas after-treatment in order to establish near-zero emission applications. In this context, the present study evaluates the performance of a commercial state-of-the-art oxidation catalyst (OC) and of a catalyst for selective catalytic reduction (SCR) that are typically used for emission reduction from diesel exhausts under conditions representative for H2-fueled ICEs, namely oxygen-rich exhausts with high water vapor levels, comparably low temperatures, and potentially considerable levels of unburnt H2. Herein, the OC is supposed to convert H2 slippage, which can occur due to incomplete combustion, and to oxidize NO to NO2, which enables an efficient NOx removal over the SCR catalyst. While the vanadia-based SCR catalyst was barely affected by high water vapor levels, the presence of H2, or hydrothermal aging, H2O inhibited NO to NO2 oxidation over the OC and hydrothermal aging with 20 vol.-% H2O resulted in significant deactivation of the OC. At the cost of producing the inhibitor H2O and the greenhouse gas N2O, the presence of H2 facilitates a fast light-off due to temperature generation. These results underscore the importance of developing suitable catalyst operation strategies that account for efficient pollutant conversion and avoid secondary emissions formation.
Lott, PatrickSchäfer, KathrinDeutschmann, OlafWerner, ManuelWeinmann, PhilippZimmermann, LisaToebben, Heike
In this study, an integrated emission prediction model was used to predict whether EURO7-compliant commercial internal combustion engine vehicles would be able to meet upcoming regulations. In particular, the optimal value of Adblue injection and EHC (Electrically Heated Catalyst) control strategy for each combination of the specifications of the close-coupled SCR system (volume, substrate spec., EHC, etc.) was derived. Through this, it was intended to derive the best specification combination in terms of control and emission performance, and to use the results as a basis for decision-making in the early stages of product concept selection.
Cho, JihoChoi, SungmuLee, Sang MinHwang, Dong Min
The proposed Euro 7 regulation aims to substantially reduce the NOx emissions to 0.03 g/km, a trend also seen in upcoming China 6b and US EPA regulations. Meeting these stringent requirements necessitates advancements in Urea/Selective Catalytic Reduction (SCR) aftertreatment systems, with the urea deposit formation being a key challenge to its design. It’s proven that Computational Fluid Dynamics (CFD) can be an effective tool to predict Urea deposits. Transient wall temperature prediction is crucial in Urea deposit modeling. Additionally, fully understanding the kinetics of urea decomposition and by-products solidification are also critical in predicting the deposit amount and its location. In this study, we introduce (i) a novel film boiling model (IFPEN-BRT model) and (ii) a new urea by-product solidification model in the CONVERGE CFD commercial solver, and validate the results against the recent experiments. The IFPEN-BRT model handles the spray-wall heat transfer in various boiling regimes, and the urea by-product solidification model separates solid deposits from liquid film parcels and renders them inert on the walls. We couple the by-product solidification model with the detailed decomposition model for urea. We use surface morphing feature developed in CONVERGE to enable realistic representation of solid surface topology once the solid deposits are formed on the testing plate. Multiple acceleration schemes have been employed to achieve a faster turnaround time while maintaining high fidelity. Additionally, the fixed flow approach has been used to accelerate the simulation and reach the time scale required for appreciable deposit formation. The simulations, incorporating both the IFPEN-BRT model and the urea by-product solidification model, matches the experiments very well on several fronts: the wall temperature contours, the temporal evolution of wall temperature profiles, and film/deposit patterns. The simulations also correctly predict cyanuric acid (CYA) as the primary solid deposit, aligning with experimental findings after 20 minutes real time simulation.
Bhatt, Mrugank P.Yang, PengzeHabchi, Chaouki
Hydrogen Internal Combustion Engines (H2 ICE) are gaining recognition as a nearly emission-free alternative to traditional ICE engines. However, H2 ICE systems face challenges related to thermal management, N2O emissions, and reduced SCR efficiency in high humidity conditions (15% H2O). This study assesses how hydrogen in the exhaust affects after-treatment system components for H2 ICE engines, such as Selective Catalytic Reduction (SCR), Hydrogen Oxidation Catalyst (HOC), and Ammonia Slip Catalyst (ASC). Steady-state experiments with inlet H2 inlet concentrations of 0.25% to 1% and gas stream moisture levels of up to 15% H2O were conducted to characterize the catalyst response to H2 ICE exhaust. The data was used to calibrate and validate system component models, forming the basis for a system simulation. System model validation involved comparing the model against real-world data from production diesel engine after-treatment systems for transient cycles, including Federal Test Procedure (FTP) and Ramp model cycle (RMC) data. Subsequent simulations replicated H2 ICE exhaust conditions for steady-state and transient scenarios, yielding insights for optimizing H2 ICE applications. The paper’s final section presents results from an improved system comprising of HOC, SCR, ASC, and Hydrogen Particulate Filter (HPF), offering a potential pathway to achieving ultra-low NOx emissions in H2 ICE engines while addressing challenges like thermal management, N2O formation, and reduced SCR activity in high humidity conditions (15% H2O).
Chundru, Venkata RajeshSharp, ChristopherRahman, Mohammed MustafizurBalakrishnan, Arun
When used with injecting urea-water solution forming ammonia, Selective Catalytic Reduction (SCR) catalyst is a proven technology for greatly reducing tailpipe emission of nitrogen oxides (NOx) from Diesel engines. However, one major shortcoming of an SCR-based system is forming damaging urea deposits (crystals) in low temperature exhaust operations, especially exacerbated during higher injection rates. Deposits reduce SCR efficiency, damage exhaust components, and induce high concentration ammonia slips. We describe here an Electrically Heated Mixer (EHM™) demonstrated on a Diesel engine markedly inhibiting deposit formation in urea SCR systems, both in low (near 200 °C) and higher exhaust temperature operations and for both low and high urea injection rates in various, realistic engine operations. Engine test runs were conducted in long durations, 10 to 20 hours each, for a total of nearly 100 hours. In nearly all operation modes, EHM maintained deposits below 1% of the total injected DEF mass; most were below 0.5%, practically non-existent, including when in higher injection rates. To further gain confidence in and validate the deposit-free outcome due to the EHM impact, CFD simulations of the same exhaust conditions were performed, which further confirmed EHM’s capability in substantially inhibiting urea deposits observed on the engine. Along with prior publications, this work forms a trilogy demonstrating EHM enabling rapid heat-up making available several-fold lower tailpipe NOx, meeting ultra-stringent NOx regulations (e.g., Californian/EPA 2027 meeting 0.02 gr/bhp.hr), reducing tailpipe NOx in various regulatory and non-regulatory cycles [Frontier, 2022] while enabling highly efficient NOx conversion in low-load cycles and in fast transients [Topics in Catalysis, 2022, COMVEC, 2022].
Vernham, BruceKadam, VaibhavMasoudi, MansourNoorfeshan, SahmPoliakov, Nick
Selective Catalytic Reduction (SCR) is an optimized technology developed to encounter current BS6 Emission Regulations. AdBlue is the reductant used in the SCR Dosing system to eliminate NOx in the Exhaust gas. In order to ensure engine emissions compliance, insufficient or improper reductant in tank required to be detected. The right AdBlue concentration of 32.5% is highly necessary to attain the higher NOX conversion efficiency. Low concentration of the reductant will drastically reduce the NOx conversion in the system. Hence monitoring the AdBlue concentration in the tank itself is more important as per the OBD legislation. This implies on a physical quality sensor in the tank for detecting the reductant concentration. The functionalities of the quality sensor can also be instituted via a virtual software modelling called Improper Reductant Detection (IRD). IRD logic is highly robust and work competently to meet the BS6 stage 2 legislation’s NOx target. The reductant is suspected after each tank refill event, automatically IRD logic runs in the software in general, but the routine is started only if the NOx conversion efficiency is getting worse as well. The approach is to increase the AdBlue dosing rate if there is a suspicion of an improper reductant. The comparison of the NOx conversion efficiency before and after increasing dosing determines whether the reductant is good or not. Henceforth, the component failure of high-cost Quality sensor can be prevented and improvised through a software model that promises a low-cost solution to the product which in turn benefits the customer.
M, JayashreeK, SabareeswaranYS, Ananth Kumar
In the Journey towards Zero Emission and decarbonization, with emerging advancement in technology form current BS6 to near future EURO7 standards of emission, these emission norms are achievable when we amalgamate with an assistive technology of Electrically Heated System for thermal management in Diesel emission control i.e., called CatVap®. With the increasingly stringent limits on vehicle pollutants- including NOx emission levels are fulfilled with Twin Urea Dosing mechanism. These comprehensive lists of advanced technology to converge lowest NOx emissions without increasing CO2 emissions. The Major effort in the existing structure is to accelerate the SCR temperature and enhance the conversion efficiency of NOx in Real Drive Emission during cold start and low load duty cycle. CatVap®system provides sufficient thermal energy to facilitate rapid heating in the course of low load cycles and cold city rides for efficient gas conversion. As they are used to accelerate the light-off temperature for Diesel Oxidation Catalyst (DOC) and Selective Catalytic Reduction (SCR), this system is also highly adaptable for effective regeneration in Diesel Particulate Filter (DPF) and overall, it is an important promoter to accomplish Zero emission Internal Combustion Engines. Albonair is targeting towards optimization of well adapted and cost-effective CatVap technology and dual dosing system to improve BS6 emission standards and to meet BS7/Euro7 regulations. The Development cost and the estimated timeline to encounter BS7 System would not be much challengeable when compared to the implementation of BS6 system.
YS, AnanthkumarK, SabareeswaranM, Jayashree
The major objective of this paper is to develop thermal management strategy targeting optimum performance of Selective Catalytic Reduction (SCR) catalyst in a Medium Duty Diesel Engine performing in BS6 emission cycles. In the current scenario, the Emissions Norms are becoming more stringent and with the introduction of Real Drive Emission Test (RDE) and WHTC test comprising of both cold and hot phase, there is a need to develop techniques and strategies which are quick to respond in real time to cope with emission limit especially NOx. SCR seems to be suitable solution in reducing NOx in real time. However, there are limitations to SCR operating conditions, the major being the dosing release conditions which defines the gas temperature at which DEF (Diesel Exhaust Fluid) can be injected as DEF injection at lower gas temperatures than dosing release will lead to Urea deposit formation and will significantly hamper the SCR performance. The second factor for optimum SCR operation is to maintain the catalyst temperature where high NOx conversion efficiency is obtained. Dosing release temperature plays an important role to achieve high NOx conversion efficiency, specifically when the aftertreatment system is at ambient temperature. Therefore, thermal management strategy is employed to ensure quick heating of ATS to achieve the Dosing release temperature in the shortest possible time duration. Thermal management involves air path control where actuators are used to alter the exhaust temperature, and also the injection strategies that favors higher exhaust enthalpy at the cost of BSFC. Thermal Management is active until the ATS will reach the certain temperature threshold beyond which the thermal management will be deactivated as prolong activation of thermal management may result in fuel penalty. From the airpath point of view the focus of this paper is towards the utilization of intake throttling, engine brake and variable exhaust flap. Along with the airpath, the impact of combustion retardation is also covered.
Sharma, Ajeet KumarKreuzig, GerhardGupta, AyushGoyal, DineshGarg, Varun
Urea-NH3 dosed Selective Catalytic Reduction is a powerful reaction system to ensure NOx reduction in the exhaust gases by minimizing ammonia slip. When the dosed ammonia exceeds the actual request than the required, NH3 to NOx ratio is potentially high, the unused ammonia is limited to 10ppm corresponding to experimental result of every World Harmonic Transient Cycle. The dosage estimation depends on the NOx sensors which has this drawback of high cross-sensitivity to ammonia that can affect the measurement of NOx and compromise the SCR-ASC closed loop strategies. This paper aims to resolve the complexity in prediction of ammonia slip to resolve the cross-sensitivity of tailpipe NOx sensor in the SCR system by a closed loop estimation of NOx and ammonia slip to ensure high NOx conversion efficiency. The focus is to develop a simplified model-based solution for estimating ammonia slip, because of the limitations in the real drive conditions in SCR system. This model approach is designed in such a way that it predicts the NOx and NH3 emissions after the SCR catalyst and calculates even in the failure conditions of closed loop feedback of urea dosing. A Filtering solution that combines the signals from inlet NOx sensor, tailpipe NOX sensor and the total system efficiency to provide a reliable estimation of NH3 slip.
K, SabareeswaranM, JayashreeYS, Ananthkumar
BS6.1 emission standards were implemented in India in 2020 followed by BS6.2 which added more controls on emission limits. For BS6.2 OBD (On Board Diagnostics) and RDE (Real Driving Emission) were added on to the existing BS6.1 emissions. Emission control changes usually need addition of new parts, calibration changes and durability requirements. For the current 1.5L, 3-cylinder diesel engine an pSCR (Passive Selective Catalytic Reduction) brick was added for control of NOx for meeting RDE. For meeting OBD requirements PM (Particulate Matter) and NOx sensors were added in the cold end pipe along with calibration changes to meet the BS6.2 norms. In this paper we will discuss on the design aspects of sensors and pSCR only. The sensor and pSCR positioning plays vital role in meeting the legislative requirements and to ensure the ease of assembly and durability of the parts. We discuss on the various options explored for positioning, the constraints of sensor application and the importance of positioning on the emission compliance. Post the sensor positioning, parts were made, and successful testing and validation was completed demonstrating the emission compliance and sensor durability.
Vinaya Murthy, VijayendraRengaraj, ChandrasekaranDharan R, BharaniSasikumar, M
This paper describes the after-treatment technology that could be used to meet a future BS-VII standard, considering close-coupled SCR (cc-SCR) to help start NOx conversion earlier. Both active (Cu/Fe-SCR based) and passive (V-SCR based) systems have the potential to meet emission limits. V-SCR may be considered in the rear position because V-SCR shows a fast response with very low N2O formation. Next-gen V-SCR technology shows significantly improved performance and durability closer to Cu-SCR. The steady-state NOx conversions over Next-Gen V-SCR were better than BS-VI V-SCR in both fresh and aged-580°C/100h conditions. High durability was also observed after engine aging of 1000h (WHTC + high load). Another big challenge in BS VII could be the PN10 requirement. With enhanced filtration coating (EFC) technology, PN emissions drop drastically in comparison to Euro VI reference without EFC to meet a future BS VII.
Singhania, AmitWallin, MikaelaEdvardsson, JonasChatterjee, SougatoVediappan, SudhagarKomori, MitsuruPhillips, Paul
Items per page:
1 – 50 of 1116