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Induction machines (IM) are considered work horse for industrial applications due to their rugged, reliable and inexpensive nature; however, their low power density restricts their use in volume and weight limited environments such as an aerospace, traction and propulsion applications. Given recent advancements in additive manufacturing technologies, this paper presents opportunity to improve power density of induction machines by taking advantage of higher slot fill factor (SFF) (defined as ratio of bare copper area to slot area) is explored. Increase in SFF is achieved by deposition of copper in much more compact way than conventional manufacturing methods of winding in electrical machines. Thus a design tradeoff study for an induction motor with improved SFF is essential to identify and highlight the potentials of IM for high power density applications and is elaborated in this paper.

If Design of Experiments (DOE) is so good why isn't it used more? Despite its power DOE has some demanding conditions. You don't have to be a statistician to conduct a successful DOE, however. In Aerospace we are very often faced with the design, improvement or correction of a product, process or service. The most serious task is determination of the most relevant variables or factors that affect the final result or performance of the process or product in question. Once these factors have been established, we then need to determine an optimal combination of settings or levels for each factor. There is also the complicating possibility of interaction among the factors also. Design of Experiments (DOE) is an established statistical technique used on its own or in conjunction with a Six Sigma project to determine the strongest individual factors and if there is interaction among the factors.

The Systems Engineering Relationship between Qualification, Environmental Stress Screening (ESS), and Reliability is often poorly understood: as a consequence resources are expended on efforts that degrade inherent hardware reliability and vitiate reliability predictions. This article expatiates on the Systems Engineering relationship between Qualification and ESS, and how their proper application enhances inherent reliability and supports credible reliability predictions. Examples of how their uninformed application degrades inherent hardware reliability and vitiates reliability predictions, and how program/equipment managers can avoid this, are presented.

The embedded software has played an increasing role in safety-critical systems. At the same time the current development process of “build, then integrate” has proven unaffordable for the Aerospace industry. This paper outlines challenges in safety-critical embedded systems in addressing system-level faults that are currently discovered late in the development life cycle. We then discuss an architecture-centric approach to model-based engineering, i.e., to complement the validation of systems with analysis of different operational quality aspects from an architecture model. A key technology in this approach is the Architecture Analysis & Design Language (AADL), an SAE International standard for embedded software system. It supports analysis of operational qualities such as responsiveness, safety-criticality, security, and reliability through model annotations.

Experimental decklids for the Cadillac STS sedan were made with Al AA5083 sheet outer panels and Mg AZ31B sheet inner panels using regular-production forming processes and hardware. Joining and coating processes were developed to accommodate the unique properties of Mg. Assembled decklids were evaluated for dimensional accuracy, slam durability, and impact response. The assemblies performed very well in these tests. Explicit and implicit finite element simulations of decklids were conducted, and showed that the Al/Mg decklids have good stiffness and strength characteristics. These results suggest the feasibility of using Mg sheet closure panels from a structural perspective.

The capability of theoretical durability studies to offer an efficient alternative methodology for predicting the potential performance of catalysts has improved in recent years. In this regard, multi-scale theoretical methods for predicting sintering behavior of Pt on various catalyst supports are being developed. Various types of Pt diffusions depending on support were confirmed by the micro-scale ultra accelerated quantum chemical molecular dynamics (UA-QCMD) method. Moreover, macro-scale sintering behavior of Pt/ɣ-Al2O3, Pt/ZrO2 and Pt/CeO2 catalyst were studied using a developed 3D sintering simulator. Experimental results were well reproduced. While Pt on ɣ-Al2O3 sintered significantly, Pt on ZrO2 sintered slightly and Pt on CeO2 demonstrated the highest stability against sintering.

In the present work, an experimental and numerical analysis of high pressure Diesel spray evolution is carried out in terms of spray momentum flux time history and instantaneous injection rate. The final goal of spray momentum and of injection rate analyses is the evaluation of the nozzle outlet flow characteristics and of the nozzle internal geometry possible influences on cavitation phenomena, which are of primary importance for the spray evolution. Further, the evaluation of the flow characteristics at the nozzle exit is fundamental in order to obtain reliable boundary conditions for injection process 3D simulation. In this paper, spray momentum data obtained in ambient temperature, high counter-pressure conditions at the Perugia University Spray Laboratory are presented and compared with the results of 3D simulations of the momentum rig itself.

Accelerated life testing (ALT) is widely used to determine the failure time distribution of a product and the associated life-stress relationship in order to predict the product's reliability under normal operating conditions. Many types of stress loadings such as constant-stress, step-stress and cyclic-stress can be utilized when conducting ALT. Extensive research has been conducted on the analysis of ALT data obtained under a specified stress loading. However, the equivalency of ALT experiments involving different stress loadings has not been investigated. In this paper, a definition is provided for the equivalency of various ALT plans involving different stress loadings. Based on this definition, general equivalent ALT plans and some special types of equivalent ALT plans are explored. For demonstration, a constant-stress ALT and a ramp-stress ALT for miniature lamps are presented and their equivalency is investigated.

As the number of electrical devices in modern vehicles increases, the battery becomes more critical component for the operation of vehicles. To ensure the startability of the vehicle, battery conditions such as state of charge and state of health should be properly monitored and maintained. To reduce walk-home incidents due to no-start situation, appropriate warning should be issued to the driver to advise necessary actions such as replacing or re-charging the battery. For the last couple of years, General Motors has studied and developed several battery health monitoring methods based on different battery health signatures. Yet, it is found that relying on a single method may lead to false alarm or misdetection due to lack of information or uncertainty. This paper develops the algorithm for more robust and reliable battery health monitoring and prognosis, by applying Evidence Theory to fuse different battery health signatures.

A simulation-based, system reliability-based design optimization (RBDO) method is presented that can handle problems with multiple failure regions and correlated random variables. Copulas are used to represent the correlation. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with a trust-region optimization approach and local metamodels covering each trust region. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation per trust region. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. The PRRA method is based on importance sampling. It provides accurate results, if the support of the sampling PDF contains the support of the joint PDF of the input random variables. The sequential, trust-region optimization approach satisfies this requirement.

A new liquid surface conditioner has been developed to improve phosphate coating quality and enable a low-temperature phosphating system designed to reduce CO₂ emissions during the pretreatment processes of automobile production. Phosphate film is formed by a phosphating treatment that provides corrosion resistance for the steel plates that make up auto bodies. In the vehicle body, pocket-shaped structures such as side sills and wheel arches are likely to collect muddy water and form rust. Regarding anticorrosion quality assurance, particular attention must be paid to these pocket structures, in which phosphating solution flows slowly, and a lower solution-volume-to-surface-area ratio contributes less to the phosphating reaction. For this reason, with the conventional liquid surface conditioner, a low-temperature phosphating system cannot coat substrate surfaces sufficiently, which would result in lower corrosion resistance.

Structural adhesive joints are expected to retain integrity in their entire service-life that normally involves cyclic loading concurrent with environmental exposure. Under such a severe working condition, effective determination of fatigue life at different temperatures is crucial for reliable joint design. The main goal of this work was thus defined as evaluation of fatigue performance of adhesive joints at their extreme working temperatures in order to be compared with their fracture properties under static loading. A series of standard double-cantilever-beam (DCB) specimens have been bonded by three structural 3M epoxy adhesives selected from different applications. The specimens were tested under monotonic and cyclic opening loads (mode-I) in order to evaluate the quasi-static and fatigue performances of selected adhesives at room temperature, 80°C and -40°C.

Incremental Sheet Forming (ISF) is an emerging sheet metal prototyping technology where a part is formed as one or more stylus tools are moving in a pre-determined path and deforming the sheet metal locally while the sheet blank is clamped along its periphery. A deformation analysis of incremental forming process is presented in this paper. The analysis includes the development of an analytical model for strain distributions based on part geometry and tool paths; and numerical simulations of the forming process with LS-DYNA. A skew cone is constructed and used as an example for the study. Analytical and numerical results are compared, and excellent correlations are found. It is demonstrated that the analytical model developed in this paper is reliable and efficient in the prediction of strain distributions for incremental forming process.

In this study, a full vehicle with advanced LMS comfort and durability tire (CDT) model was established with ADAMS software to predict the spindle loads of the vehicle under a severe proving ground rough road event. From a series of simulations with various design changes, the spindle loads sensitivities to those design changes were identified. The simulated results were also compared with the measured data and a good correlation was achieved.

This paper reports on the comprehensive applications testing of the first commercial volumes of Gas-to-Liquids (GTL) diesel produced via the Sasol Slurry Phase Distillate™ (Sasol SPD™) process, a Low Temperature Fischer-Tropsch (LTFT) process, at the Oryx GTL plant in Qatar. The technical literature is well populated with results of emissions and applications studies of GTL diesel; however, these results have been limited to product produced at pilot plant and relatively small commercial scale. To ensure that diesel produced commercially not only matches the performance of material previously produced at pilot plant scale using the same technology, but is also fit-for-purpose in the broader sense, a series of chemical assessments and applications testing was performed using both neat and blended diesel fuels. These included emissions tests in passenger cars and heavy-duty applications, engine durability, injector fouling performance and a passenger car fleet trial.

In this research, the interior noise of a passenger car was measured, and the sound quality metrics including sound pressure level, loudness, sharpness, and roughness were calculated. An artificial neural network was designed to successfully apply on automotive interior noise as well as numerous different fields of technology which aim to overcome difficulties of experimentations and save cost, time and workforce. Sound pressure level, loudness, sharpness, and roughness were estimated by using the artificial neural network designed by using the experiment values. The predicted values and experiment results are compared. The comparison results show that the realized artificial intelligence model is an appropriate model to estimate the sound quality of the automotive interior noise. The reliability value is calculated as 0.9995 by using statistical analysis.

In the automobile industries, weight reduction has been investigated to improve fuel efficiency together with reduction of CO2 emission. In such circumstance, it becomes necessity to make an electric power steering (EPS) more compact and lightweight. In this study, we aimed to have a smaller and lighter EPS gear size by focusing on an impact load caused at steering end. In order to increase the shock absorption energy without increase of stopper bush size, we propose new theory of impact energy absorption by not only spring function but also friction, and a new stopper bush was designed on the basis of the theory. The profile of the new stopper bush is cylinder form with wedge-shaped grooves, and when the new stopper bush is compressed by the end of rack and the gear housing at steering end, it enables to expand the external diameter and produce friction. In this study, we considered the durability in the proposed profile.

The paper presents a model-based approach to testing embedded automotive software systems in a real-time. Model-based testing approach relates to a process of creating test artifacts using various kinds of models. Real-time testing involves the use of a real-time environment to implement test application. Engineers shall use real-time testing techniques to achieve greater reliability and/or determinism in a test system. The paper contains an instruction how to achieve these objectives by proper definition, implementation, execution, and evaluation of test cases. The test cases are defined and implemented in a modeling environment. The execution and evaluation of test results is made in a real-time machine. The paper is concluded with results obtained from the initial deployment of the approach on a large scale in production stream projects.

Quality, Reliability, Durability (QRD) and Safety of vehicular Electrical/Electronics (E/E) systems traditionally have resulted from arduous rounds of Design-Built-Test-Fix (DBTF) Reliability and Durability Growth Testing. Such tests have historically required 12-16 or more weeks of Accelerated Life Testing (ALT), for each round of validation in a new product development program. Challenges have arisen from: The increasing number of E/E modules in today's vehicle places a high burden on supplier's test labs and budgets. The large size and mass of electric vehicle power modules results in a lower test acceleration factors which can extend each round of ALT to 5-6 months. Durability failures tend to occur late in life testing, resulting in the need to: perform a root cause investigation, fix the problem, build new prototype parts and then repeat the test to verify problem resolutions, which severely stress program budgets and schedules.

Failure analysis (FA) management is insufficiently described by current standards and literature. Previously proposed three-step systemic FA methodology provides effective and efficient alternative to sporadic FA. Organization, methods and results of the first step of the systemic FA, failure mode analysis (FMA), during product/project life cycle, is described. FMA promptly address ∼80% of all problems and justify/supports further actions using conventional ready techniques and resources. Original subject matter tools (three FMA levels, joint FMA-FMECA-F5 technique, and P5 failure classification) substantiate, facilitate and illustrate FMA. Multiple examples demonstrate FMA strengths and limitations with uniquely broad range of products and applications. Particular attention is paid to rare combination of high quality, reliability and profitability.