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Diesel exhaust aftertreatment solutions using injection, such as urea-based SCR and lean NOx trap systems, effectively reduce the emission NOx level in various light vehicles, commercial vehicles, and industrial applications. The performance of the injector plays an important role in successfully utilizing this type of technology, and the CFD tool provides not only a time and cost-saving, but also a reliable solution for extensively design iterations for optimizing the injector internal nozzle flow design. Inspired by this fact, a virtual test methodology on injector dosing rate utilizing CFD was proposed for the design process of injector internal nozzle flows.

As emissions regulations around the world become more stringent, emerging markets are seeking alternative strategies that align with local infrastructures and conditions. A Lean NOx Catalyst (LNC) is developed that achieves up to 60% NOx reduction with ULSD as its reductant and ≻95% with ethanol-based fuel reductants. Opportunities exist in countries that already have an ethanol-based fuel infrastructure, such as Brazil, improving emissions reduction penetration rates without costs and complexities of establishing urea infrastructures. The LNC performance competes with urea SCR NOx reduction, catalyst volume, reductant consumption, and cost, plus it is proven to be durable, passing stationary test cycles and adequately recovering from sulfur poisoning. Controls are developed and applied on a 7.2L engine, an inline 6-cylinder non-EGR turbo diesel.

Catalysts and filters continue to be applied widely to meet particulate matter regulations across new and retrofit diesel engines. Soot management of the filter continues to be enhanced, including regeneration methodologies. Concerns regarding in-cylinder post-injection of fuel for active regeneration increases interests in directly injecting this fuel into the exhaust. Performance of secondary fuel injection layouts is discussed, and sensitivities on thermal uniformity are measured and analyzed, providing insight to packaging challenges and methods to characterize and improve application designs. Influences of end cone geometries, mixers, and injector mounting positions are quantified via thermal distribution at each substrate's outlet. A flow laboratory is applied for steady state characterization, repeated on an engine dynamometer, which also provides transient results across the NRTC.

This study presents a probabilistic life (failure) and damage assessment approach for components under general fatigue loadings, including constant amplitude loading, step-stress loading, and variable amplitude loading. The approach consists of two parts: (1) an empirical probabilistic distribution obtained by fitting the fatigue failure data at various stress range levels, and (2) an inverse technique, which transforms the probabilistic life distribution to the probabilistic damage distribution at any applied cycle. With this approach, closed-form solutions of damage as function of the applied cycle can be obtained for constant amplitude loading. Under step-stress and variable amplitude loadings, the damage distribution at any cycle can be calculated based on the accumulative damage model in a cycle-by-cycle manner. For Gaussian-type random loading, a cycle-by-cycle equivalent, but a much simpler closed-form solution can be derived.

The low-NOx standard for heavy-duty trucks proposed by the California Air Resources Board will require rapid warm-up of the aftertreatment system (ATS). Several different aftertreatment architectures and technologies, all based on selective catalytic reduction (SCR), are being considered to meet this need. One of these architectures, the close-coupled SCR (ccSCR), was evaluated in this study using two different physics-based, 1D models; the simulations focused on the first 300 seconds of the cold-start Federal Test Procedure (FTP). The first model, describing a real, EuroVI-compliant engine equipped with series turbochargers, was used to evaluate a ccSCR located either i) immediately downstream of the low-pressure turbine, ii) in between the two turbines, or iii) in a by-pass around the high pressure turbine.

Durability/reliability design of products, such as auto exhaust systems, is essentially based on the observation of test data and the accurate interpretation of these data. Therefore, test planning and related data analysis are critical to successful engineering designs. To facilitate engineering applications, testing and data analysis methods have been standardized over the last decades by several standard bodies such as the American Society for Testing and Materials (ASTM). However, over the last few years, several effective testing and data analysis methods have been developed, and the existing standard procedures need to be updated to incorporate the new observations, knowledge, and consensus. In this paper, the common practices and the standard test planning and data analysis procedures are reviewed first. Subsequently, the recent development in accelerated testing, equilibrium based data fitting, design curve construction, and Bayesian statistical data analysis is presented.

The Diesel Particulate Filter (DPF) is used on today's diesel vehicles to reduce the amount of soot being released into the atmosphere from diesel exhaust. The DPFs are typically wall-flow filtration devices of various extruded porous ceramic materials with more than 95% efficiency. Once the filter has loaded with soot, the DPF undergoes regeneration where the exhaust temperature is raised to burn off the soot. With the DPF being relatively new aftertreatment technology, the exhaust industry must investigate the acoustic and performance effects of the DPF when added to an exhaust system. In many applications the DPF replaces the exhaust muffler because of limited packaging space. The acoustic performance of the DPF changes with increasing soot density and exhaust backpressure. The acoustic response is measured with physical testing at multiple soot load densities. This study is part of a graduation thesis project for Kettering University[1].

Road vibrations cause fatigue failures in vehicle components and systems. Therefore, reliable and accurate damage and life assessment is crucial to the durability and reliability performances of vehicles, especially at early design stages. However, durability and reliability assessment is difficult not only because of the unknown underlying damage mechanisms, such as crack initiation and crack growth, but also due to the large uncertainties introduced by many factors during operation. How to effectively and accurately assess the damage status and quantitatively measure the uncertainties in a damage evolution process is an important but still unsolved task in engineering probabilistic analysis. In this paper, a new procedure is developed to assess the durability and reliability performance, and characterize the uncertainties of damage evolution of components under constant amplitude loadings.

Great efforts have been made to develop the ability to accurately and quickly predict the durability and reliability of vehicles in the early development stage, especially for welded joints, which are usually the weakest locations in a vehicle system. A reliable and validated life assessment method is needed to accurately predict how and where a welded part fails, while iterative testing is expensive and time consuming. Recently, structural stress methods based on nodal force/moment are becoming widely accepted in fatigue life assessment of welded structures. There are several variants of structural stress approaches available and two of the most popular methods being used in automotive industry are the Volvo method and the Verity method. Both methods are available in commercial software and some concepts and procedures related the nodal force/moment have already been included in several engineering codes.

The Diesel engine combustion process results in harmful exhaust emissions, mainly composed of Particulate Matter (PM), Hydro Carbon (HC), Carbon monoxide (CO) and Nitrogen Oxides (NOx). Several technologies have been developed in the past decades to control these diesel emissions. One of the promising and well matured technology of reducing NOx is to implement Selective Catalytic Reduction (SCR) using ammonia (NH3) as the reducing agent. For an effective SCR system, the aqueous urea solutions should be fully decomposed into ammonia and it should be well distributed across the SCR. In the catalyst, all the ammonia is utilized for NOx reduction process. In the design stage, it is more viable to implement Computational Fluid Dynamics (CFD) for design iterations to determine an optimized SCR system based on SCR flow distribution. And in later stage, experimental test is required to predict the after-treatment system performance based on NOx reduction.

To meet EPA Tier IV large diesel engine emission targets, intensive development efforts are necessary to achieve NOx reduction and Particulate Matter (PM) reduction targets [1]. With respect to NOx reduction, liquid urea is typically used as the reagent to react with NOx via SCR catalyst [2]. Regarding to PM reduction, additional heat is required to raise exhaust temperature to reach DPF active / passive regeneration performance window [3]. Typically the heat can be generated by external diesel burners which allow diesel liquid droplets to react directly with oxygen in the exhaust gas [4]. Alternatively the heat can be generated by catalytic burners which enable diesel vapor to react with oxygen via DOC catalyst mostly through surface reactions [5].

In product design and development stage, validation assessment methods that can provide very high reliability and confidence levels are becoming highly demanded. High reliability and confidence can generally be achieved and demonstrated by conducting a large number of tests with the traditional approaches. However, budget constraints, test timing, and many other factors significantly limit test sample sizes. How to achieve high reliability and confidence levels with limited sample sizes is of significant importance in engineering applications. In this paper, such approaches are developed for two fundamental and widely used methods, i.e. the test-to-failure method and the Binomial test method. The concept of RxxCyy (e.g. R90C90 indicates 90% in reliability and 90% in confidence) is used as a criterion to measure the reliability and confidence in both the test-to-failure and the Binomial test methods.