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This paper describes the joint development by Tenneco and Pi Shurlok of a complete diesel engine aftertreatment system for controlling particulate matter emissions. The system consists of a DOC, DPF, sensors, controller and an exhaust fuel injection system to allow active DPF regeneration. The mechanical components were designed for flow uniformity, low backpressure and component durability. The overall package is intended as a complete PM control system solution for OEMs, which does not require any significant additions to the OEM's engine control strategies and minimizes integration complexity. Thus, to make it easier to adapt to different engine platforms, ranging from small off-road vehicle engines to large locomotive engines, model-based control algorithms were developed in preference to map-based controls.

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.

Numerous test data have been generated in many testing institutions over the years and the historical information from previous similar designs and operating conditions can shed light on the current and future designs since they would share some common features when the changes are not drastic. To effectively utilize the historical information for current and future designs, two steps are necessary: (1) finding an approach to consistently correlate the test data; (2) utilizing Bayesian statistics, which can provide a rigorous mathematical tool for extracting useful information from the historical data. In this paper, a procedure for test sample size reduction is proposed based on historical fatigue S-N test data and Bayesian statistics. First, the statistical information is extracted from a large amount of fatigue test data collected over the years.

This paper reviews the correlation concepts and tools available, with the emphasis on their historical origins, mathematical properties and applications. Two of the most commonly used statistical correlation indicators, i.e., modal assurance criterion (MAC) for structural deformation pattern identification/correlation and the coefficient of determination (R2) for data correlation are investigated. The mathematical structure of R2 is critically examined, and the physical meanings and their implications are discussed. Based on the insights gained from these analyses, a data scatter measure and a dependency measure are proposed. The applications of the measures for both linear and nonlinear data are also discussed. Finally, several worked examples in vehicle dynamics analysis and statistical data analyses are provided to demonstrate the effectiveness of these concepts.

Vehicle exhaust components and systems under fatigue loading often show multiple failure modes, which should be treated, at least theoretically, with rigorous advanced bi-modal and multi-modal statistical theories and approaches. These advanced methods are usually applied to mission-critical engineering applications such as nuclear and aerospace, in which large amounts of test data are often available. In the automotive industry, however, the sample size adopted in the product validation is usually small, thus the bi-modal and multi-modal phenomena cannot be distinguished with certainty.

In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.

Structural stress methods are now widely used in fatigue life assessment of welded structures and structures with stress concentrations. The structural stress concept is based on the assumption of a global stress distribution at critical locations such as weld toes or weld throats, and there are several variants of structural stress approaches available. In this paper, the linear traction stress approach, a nodal force based structural stress approach, is reviewed first. The linear traction stress approach offers a robust procedure for extracting linear traction stress components by post-processing the finite element analysis results at any given hypothetical crack location of interest. Pertinent concepts such as mesh-insensitivity, master S-N curve, fatigue crack initiation and growth mechanisms are also discussed.

Durability and reliability performance is one of the most important concerns of a recently developed Thermal Regeneration Unit for Exhaust (T.R.U.E-Clean®) for exhaust emission control. Like other ground vehicle systems, the T.R.U.E-Clean® system experiences cyclic loadings due to road vibrations leading to fatigue failure over time. Creep and oxidation cause damage at high temperature conditions which further shortens the life of the system and makes fatigue life assessment even more complex. Great efforts have been made to develop the ability to accurately and quickly assess the durability/reliability of the system in the early development stage. However, reliable and validated simplified engineering methods with rigorous mathematical and physical bases are still urgently needed to accurately manage the margin of safety and decrease the cost, whereas iterative testing is expensive and time consuming.

Fatigue, creep, oxidation, or their combinations have long been recognized as the principal failure mechanisms in many high-temperature applications such as exhaust manifolds and thermal regeneration units used in commercial vehicle aftertreatment systems. Depending on the specific materials, loading, and temperature levels, the role of each damage mechanism may change significantly, ranging from independent development to competing and combined creep-fatigue, fatigue-oxidation, creep-fatigue-oxidation. Several multiple failure mechanisms based material damage models have been developed, and products to resist these failure mechanisms have been designed and produced. However, one of the key challenges posed to design engineers is to find a way to accelerate the durability and reliability tests of auto exhaust in component and system levels and to validate the product design within development cycle to satisfy customer and market's requirements.

Diesel burners introduce combustion of diesel fuel to raise exhaust gas temperature to Diesel Oxidization Catalyst (DOC) light-off or Diesel Particulate Filter (DPF) regeneration conditions, thereby eliminating the need of engine measures such as post-injections. Such diesel combustion requirement nevertheless poses challenges to burner development especially in combustion control and risk mitigation of DPF material failure. In particular, burner design must satisfy good soot distribution and heat distribution at DPF front face after meeting minimum requirements of ignition, heat release, and backpressure. In burner development, Computational Fluid Dynamics (CFD) models have been developed based on commercial codes for burner thermal and flow management with capability of predicting comprehensive physical and chemical phenomena including turbulence induced mixing, fuel injection, fuel droplet transport, diesel combustion, radiation, conjugate heat transfer and etc.

In order to satisfy tightening global emissions regulations, diesel truck manufacturers are striving to meet increasingly stringent Oxides of Nitrogen (NOx) reduction standards. The majority of heavy duty diesel trucks have integrated urea SCR NOx abatement strategies. To this end, aftertreatment systems need to be properly engineered to achieve high conversion efficiencies. A EuroV intent urea SCR system is evaluated and failed to meet NOx conversion targets with severe urea deposit formation. Systematic enhancements of the design have been performed to enable it to meet targets, including emission reduction efficiency via improved reagent mixing, evaporation, distribution, back pressure, and removing of urea deposits. Multiple urea mixers, injector mounting positions and various system layouts are developed and evaluated, including both CFD analysis and full scale laboratory tests.

With increasing applications of urea SCR for NOx emission reduction, improving the system performance and durability has become a high priority. A typical urea SCR system includes a urea injector, injector housing, mixer, and appropriate pipe configurations to allow continuous urea injection into the exhaust stream and evaporation of urea solution into gaseous products. Continuous operation at various conditions with high NOx reduction is possible, but one problem that threatens the life and performance of these systems is urea deposit. When urea or its byproducts become deposited on the inner surfaces of the system including walls, mixers, injector housings and substrates it can create concerns of backpressure and material deteriorations. In addition, deposits as a waste of reagents can negatively affect engine operation, emissions performance and DEF economy. Urea deposit behavior is explored in terms of heat transfer, pipe geometry, injector layout and mixing mechanisms.

A probabilistic distribution function roughly consists of two parts: the middle part and the tails. The fatigue life distribution at a stress/load level is often described with two-parameter lognormal or Weibull distribution functions, which are more suitable for modeling the mean (middle) behaviors. The domains of the conventional probabilistic distribution functions are often unbounded, either infinite small (0 for the two-parameter Weibull) or infinite large or both. For most materials in low- and medium-cycle fatigue regimes, the domains of fatigue lives are usually bounded, and the inclusion of the bounds in a probabilistic model is often critical in some applications, such as product validation and life management. In this paper, four- and five-parameter Weibull distribution functions for the probabilistic distributions with bounds are developed. Finally, the applications of these new models in fatigue data analysis and damage assessment are provided and discussed.

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].

EPA 2015 Tier IV emission requirements pose significant challenges to large diesel engine after treatment system development with respect to reducing exhaust emissions including HC, CO, NOx and Particulate Matter (PM). For a typical locomotive, marine or stationary generator engine with 8 to 20 cylinders and 2500 to 4500 BHP, the PM reduction target could be over 90% and NOx reduction target over 75% for a wide range of running conditions. Generally, HC, CO and PM reductions can be achieved by combining DOC, cDPF and active regeneration systems. NOx reduction can be achieved by injecting urea as an active reagent into the exhaust stream to allow NOx to react with ammonia per SCR catalysts, as the mainstream approach for on-highway truck applications.

Recent stringent government regulations on emission control and fuel economy drive the vehicles and their associated components and systems to the direction of lighter weight. However, the achieved lightweight must not be obtained by sacrificing other important performance requirements such as manufacturability, strength, durability, reliability, safety, noise, vibration and harshness (NVH). Additionally, cost is always a dominating factor in the lightweight design of automotive products. Therefore, a successful lightweight design can only be accomplished by better understanding the performance requirements, the potentials and limitations of the designed products, and by balancing many conflicting design parameters. The combined knowledge-based design optimization procedures and, inevitably, some trial-and-error design iterations are the practical approaches that should be adopted in the lightweight design for the automotive applications.

A statistic fatigue life assessment procedure is presented in this paper for estimating fatigue damage under stationary Gaussian multi-axial loadings with narrow-band frequency. The fatigue damage is determined by using the Miner-Palmgren rule in connection with a recently developed path-length based multi-axial cycle counting and fatigue life assessment method. In this procedure, the path length is determined by averaging sinusoidal waves with uniformly distributed phase angles while the cycles are estimated from the observation of peak counting results of stress components. Numerically simulated random loading paths with different degrees of non-proportionality are used here to compare the proposed statistical method with its time domain counterpart. Possible further improvement in this research direction is also indicated.

It is important to quantitatively characterize the automotive events in order to not only accurately interpret their past but also to reliably predict and forecast their short-term, medium-term, and even long-term future. In this paper, several automotive industry related events, i.e. vehicle safety, vehicle weight/HP ratio, the emissions of CO2, HC, CO, and NOx, are analyzed to find their general trends. Exponential and power law functions are used to empirically fit and quantitatively characterize these data with an emphasis on the two functions’ effectiveness in predictability. Finally, three empirical emission laws based on the historical HC, CO, and NOx data are proposed and the impact of these laws on emission control is discussed.

The approaches of obtaining both fatigue strength distribution and fatigue life distribution for a given set of fatigue S-N data are reviewed in this paper. A new fatigue S-N curve transformation technique, which is based on the fundamental statistics definition and some reasonable assumptions, is specifically developed in this paper to transform a fatigue life distribution to a fatigue strength distribution. The procedures of applying the technique to multiple-stress level, two-stress level, and one-stress level fatigue S-N data are presented.

A design curve, such as a fatigue design S-N curve, is required in engineering design processes. The design curve is usually constructed by analyzing test data, which often exhibit relatively large scatter. For assumed linear test data, two-stress level test plan is commonly used for accelerated life testing (ALT) and subsequent design curve construction. In this paper, based on the two-stress level test plan, a tolerance limit approach is adopted to develop a simple design curve construction procedure. The predicted results from the new method are compared with that of other methods. The advantage of the new method is demonstrated by analyzing the fatigue S-N test data of exhaust components. The determination of minimum sample size is also discussed with a worked table and a graph.