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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.

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.

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.

Strength and fatigue life prediction is very difficult for stamped structural steel parts because the manufacturing process alters the localized material properties. Traditional tensile tests cannot be used to obtain material properties due to size limitations. Because of this, FEA predictions are most often “directional” at best. In this paper an improved prediction methodology is suggested. With a material library developed from standard homogenous test specimens, or even textbook material property tables, localized strength and plastic strain numbers can be inferred from localized hardness tests(1). The new method, using standard ABAQUS static analysis (not commercial fatigue analysis software with many unknowns), is shown to be very accurate. This paper compares the new process FEA strength and fatigue life predictions to laboratory test results using statistical confidence intervals.

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.

A new passive muffler valve has been developed that offers the advantages of both the current passive and active valves without their major drawbacks. Like current passive valves this new valve provides high restriction at low to medium engine speeds for improved noise control. But with a near over-center spring action and unique flap shape, this high performance valve has minimal pressure drop at high engine speeds, closer to the active valve pressure drop performance. The in-line design of the valve makes it ideal for low restriction OE mufflers, resonators, and aftermarket performance mufflers. The new valve design is uncomplicated, with few components and has been tested extensively for durability utilizing both bench and vehicle level testing.

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.

Study and design of the lifetime durability of mechanical components in an automotive exhaust system becomes a challenging task today for engineers. During the investigation, both experimental tests and finite element simulations are used for the investigation under dynamic engine excitations. For the dynamic finite element analysis, the experimental system must be simplified as a linear mathematic model and real boundary conditions are idealized. Due to this simplification, the dynamic behavior of the finite element model may strongly deviate from that in operational conditions. To gain insight into the dynamic behavior of exhaust systems from simulations, the finite model must be modified based on experimental results. As known the harmonic response is related to modal shapes and engine loads. Therefore, modifications of the finite element model can be done from these two aspects.

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.

Durability life is one of the major concerns in the automotive industry. Road Load Data Acquisition (RLDA) is one of the most important steps to verify exhaust system durability performance. RLDA will not only provide data for system level rig testing drive file development but also for exhaust components validation (computing safety factors). Modal transient FEA can be utilized to simulate either vehicle durability testing or sub-system level rig testing. How to simulate correctly is critical in the simulation. One of the most challenging portions in the full exhaust system simulation is isolator modeling due to its non-linear characteristics. However, we have to use linear modeling to simulate isolator in modal transient analysis, which induces errors.

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.

Durability and reliability assessment of stress raisers is difficult in testing because the true deformation at a stress raiser often cannot be directly measured. Many approximate engineering approaches have been developed over the last decades, but further fundamental understanding of the problems and the development of more effective engineering methods are still strongly demanded. In this paper, several new concepts and engineering testing approaches are developed and introduced with the emphasis on thermal-fatigue assessment of welded structures.

Life testing or test-to-failure method and binomial testing method are the two most commonly used methods in product validation and reliability demonstration. The two-parameter Weibull distribution function is often used in the life testing and almost exclusively used in the extended time testing, which can be considered as an accelerated testing method by appropriately extending the testing time but with significantly reduced testing samples. However, the fatigue data from a wide variety of sources indicate that the three-parameter Weibull distribution function with a threshold parameter at the left tail is more appropriate for fatigue life data with large sample sizes. The uncertainties introduced from the assumptions about the underlying probabilistic distribution would significantly affect the interpretation of the test data and the assessment of the performance of the accelerated binomial testing methods, therefore, the selection of a probabilistic model is critically important.

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].

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.

Fatigue life prediction of elastomer NVH suspension products has become an operating norm for OEMs and suppliers during the product quoting process and subsequent technical reviews. This paper reviews a critical plane analysis based fatigue simulation methodology for a front lower control arm. Filled natural rubber behaviors were measured and defined for the analysis, including: stress-strain, fatigue crack growth, strain crystallization, fatigue threshold and initial crack precursor size. A series of four distinct single and dual axis bench durability tests were derived from OEM block cycle specifications, and run to end-of-life as determined via a stiffness loss criterion. The tested parts were then sectioned in order to compare developed failure modes with predicted locations of crack initiation. In all cases, failure mode was accurately predicted by the simulation, and predicted fatigue life preceded actual end-of-life by not more than a factor of 1.4 in life.

Automotive exhaust system experiences vibratory and thermal loads. Bogey test had been the major validation method until recent years when the strain-life approach was adopted to evaluate component's fatigue life. In practice, when using the strain-life model to evaluate a component subjected to elevated temperature, temperature effect on component fatigue life is considered by introducing a temperature scale factor KC that is used to scale up the measured nominal strain, hence the mechanical load. This paper intends to propose a method to estimate KC by designing component bench tests at room temperature and at elevated temperature, respectively. Two major failure modes in the exhaust system are investigated and different temperature effects on the base metal fatigue and on the weld or heat-affected zone are analyzed.

This paper presents a hybrid method that predicts the whistle occurrence of an automotive exhaust tuning device. The method utilizes inputs from a limited amount of test work or numerical simulation to predict the whistle occurrence in a wider range of flow conditions (temperature and velocity). It has the advantages of being quick and low cost compared with extensive tests or the computational fluid dynamics approach.

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.