Search Results

As greenhouse gas regulations continue to tighten, more opportunities to improve engine efficiency emerge, including exhaust gas heat recovery. Upon cold starts, engine exhaust gases downstream of the catalysts are redirected with a bypass valve into a heat exchanger, transferring its heat to the coolant to accelerate engine warm-up. This has several advantages, including reduced fuel consumption, as the engine’s efficiency improves with temperature. Furthermore, this accelerates readiness to defrost the windshield, improving both safety as well as comfort, with greater benefits in colder climates, particularly when combined with hybridization’s need for engine on-time solely for cabin heating. Such products have been in the market now for several years; however they are bulky, heavy and expensive, yielding opportunities for competitive alternatives.

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.

Component bench testing is a basic method to validate the component fatigue life. However, the component bench testing takes long time and is costly. With the development of more powerful computer and CAE simulation techniques, virtual CAE simulation method becomes more important in the component design, optimization, and validation due to its efficiency and low cost. Fatigue life of components of exhaust system is a critical characteristic and it is not deterministic but statistical phenomenon. Thus, a probabilistic approach is necessary. Variations and reliability of fatigue life can be considered in physical testing by testing more samples. However, how to account variations from manufacturing and testing in virtual CAE simulation is a big challenge. In this paper, a virtual CAE fatigue life prediction of components of exhaust system by probabilistic approach is studied and proposed.

Engineering components and systems are usually subjected to mixed-mode and multiaxial fatigue loadings, and these conditions should be considered in product durability and reliability design and the maintenance of aging equipment, especially mission-critical components and systems. However, modeling the damage and degradation processes under these complex loading conditions is difficult and challenging task because not only the concepts, such as range, mean, peak, valley etc., developed for uniaxial loading usually cannot be directly transferred to mixed-mode and multiaxial loadings, but also some very unique phenomena related to these complex loading conditions. One such a phenomenon is the loading path effect that can be simply described as: out-of-phase loading is more damaging than in-phase loading for some ductile materials.

Durability and reliability performance is one of the most important concerns for vehicle components and systems, which experience cyclic fatigue loadings and may eventually fail over time. Durability and reliability assessment and associated product validation require effective and robust testing methods. Several testing methods are available and among them, three basic testing methods are widely used: life testing, binomial testing (bogey testing), and degradation testing. In fact, their commonalities, differences, and relationships have not been clearly defined and fully understood. Therefore, the maximum potential of these testing methods to generate efficient, optimized, and cost-effective testing plans, consistent results, and meaningful results interpretation have been significantly limited. In this paper, a unified framework for representing these testing methods and conducting reliability analysis in a single damage-cycle (D-N) diagram is provided.

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.

With introductions of stringent diesel engine emission regulations, the DOC and DPF systems have become the mainstream technology to eliminate soot particles through diesel combustion under various operation conditions. Urea-based SCR has been the mainstream technical direction to reduce NOx emissions. For both technologies, low-temperature conditions or cold start conditions pose challenges to activate DOC or SCR emission-reduction performance. To address this issue, mini or full flow burner systems may be used to increase exhaust temperature to reach DOC light-off or SCR initiation temperature by combustion of diesel fuel. In essence, the burner systems incorporate a fuel injector, spray atomization, proper fuel / air mixing mechanisms, and combustion control as independent heat sources.

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].

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.

External Exhaust Gas Recirculation (EGR) has been used on diesel engines for decades and has also been used on gasoline engines in the past. It is recently reintroduced on gasoline engines to improve fuel economy at mid and high engine load conditions, where EGR can reduce throttling losses and fuel enrichment. Fuel enrichment causes fuel penalty and high soot particulates, as well as hydrocarbon (HC) emissions, all of which are limited by emissions regulations. Under stoichiometric conditions, gasoline engines can be operated at high EGR rates (> 20%), but more than diesel engines, its intake gas including external EGR needs extreme cooling (down to ~50°C) to gain the maximum fuel economy improvement. However, external EGR and its problems at low temperatures (fouling, corrosion & condensation) are well known.

The purpose of this work was to initiate a comparative evaluation of the aqueous corrosion resistance of ferritic stainless steels currently used to fabricate automotive exhaust systems. Both acid condensate and double loop electrochemical potentiokinetic reactivation (DL-EPR) testing using both as-received and heat treated test coupons prepared from Types 409, 409Al, 436 and 439 stainless steel was conducted for this purpose. A truncated version of an in-house acid condensate testing protocol revealed that Type 409Al stainless steel was the most resistant to corrosion of the four ferritic stainless steels examined, whereas Type 409 stainless steel was the least resistance to corrosion.

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.

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.

Corrosion-fatigue (CF) and stress corrosion cracking (SCC) have long been recognized as the major degradation and failure mechanisms of engineering materials under combined mechanical loading and corrosive environments. How to model and characterize these failure phenomena and how to screen, rank, and select materials in corrosion-fatigue and stress corrosion cracking resistance is a significant challenge in the automotive industry and many engineering applications. In this paper, the mathematical structure of a superposition-theory based corrosion-fatigue model is investigated and possible closed-form and approximate solutions are sought. Based on the model and the associated solutions and test results, screening and ranking of the materials in fatigue, corrosion-fatigue are discussed.

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].

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.

To meet the 2010 diesel engine emission regulations, an aftertreatment system was developed to reduce HC, CO, NOx and soot. In NOx reduction, a baseline SCR module was designed to include urea injector, mixing decomposition tube and SCR catalysts. However, it was found that the baseline decomposition tube had unacceptable urea mixing performance and severe deposit issues largely because of poor hardware design. The purpose of this article is to describe necessary development work to improve the baseline system to achieve desired mixing targets. To this end, an emissions Flow Lab and computational fluid dynamics were used as the main tools to evaluate urea mixing solutions. Given the complicated urea spray transport and limited packaging space, intensive efforts were taken to develop pre-injector pipe geometry, post-injector cone geometry, single mixer design modifications, and dual mixer design options.

The Cu-zeolite (CuZ) SCR catalyst enables higher NOx conversion efficiency in part because it can store a significant amount of NH3. “NH3 storage control”, where diesel exhaust fluid (DEF) is dosed in accord with a target NH3 loading, is widely used with CuZ catalysts to achieve very high efficiency. The NH3 loading actually achieved on the catalyst is currently estimated through a stoichiometric calculation. With future high-capacity CuZ catalyst designs, it is likely that the accuracy of this NH3 loading estimate will become limiting for NOx conversion efficiency. Therefore, a direct measurement of NH3 loading is needed; RF sensing enables this. Relative to RF sensing of soot in a DPF (which is in commercial production), RF sensing of NH3 adsorbed on CuZ is more challenging. Therefore, more attention must be paid to the “microwave resonance cavity” created within the SCR assembly. The objective of this study was to develop design guidelines to enable and enhance RF sensing.

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 series of novel metal-oxide (TiO2, TiO2-SiO2)-supported Mn, Fe, Co, V, Cu and Ce catalysts were prepared by incipient wetness technique and investigated for the low-temperature selective catalytic reduction (SCR) of NOx with ammonia at industrial relevantly conditions. Among all the prepared catalysts, Cu/TiO2 showed superior de-NOx performance in the temperature range of 150-200 °C followed by Mn/TiO2 in the temperature range of 200-250 °C. The Ce/TiO2 catalyst exhibited a broad temperature window with notable de-NOx performance in the temperature regime of 250-350 °C. The phyico-chemical characterization results revealed that the activity enhancement was correlated with the properties of the support material. All the anatasetitania-supported catalysts (M/TiO2 (Hombikat)) demonstrated significantly high de-NOx performance above 150 °C.