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Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

A variety of structures resonate when they are excited by external forces at, or near, their natural frequencies. This can lead to high deformation which may cause damage to the integrity of the structure. There have been many applications of external devices to dampen the effects of this excitation, such as tuned mass dampers or both semi-active and active dampers, which have been implemented in buildings, bridges, and other large structures. One of the active cancellation methods uses centrifugal forces generated by the rotation of an unbalanced mass. These forces help to counter the external excitation force coming into the structure. This research focuses on active force cancellation using centrifugal forces (CFG) due to mass imbalance and provides a virtual solution to simulate and predict the forces required to cancel external excitation to an automotive structure. This research tries to address the challenges to miniaturize the CFG model for a body-on-frame truck.

For the designing of world class vehicles, ride comfort is one of the criteria that vehicle manufacturers are constantly trying to improve. The automotive seating system is an important sub-system in a vehicle that contributes to the ride comfort of the vehicle occupants. Seat vibrations are perceived by the occupants and make them feel uncomfortable during driving conditions. These vibrations are majorly transferred from engine and road excitation loads. For road excitation loads, the road testing may not be accurately repeatable, and measurements based on four post shakers are used to assess the discomfort. The major challenges for the vehicle manufactures is the availability of physical prototypes at an early stage of vehicle development and any changes in the design due to test validation leads to huge cost and time.

Vibration shaker testing is a great tool of validating the vibration fatigue performance of automotive components & systems. However, the representative vibration schedule requires a pre-knowledge of the acceleration history for the test object, which usually is not available until the later development phase of a vehicle program when physical properties are available. Sometimes, a generic vibration schedule developed from the worst-case loading profiles are used with risk of lacking correlation with later full vehicle durability test such as Road Test Simulator (RTS) or Proving Ground (PG) road test due to the higher loading amplitude. This paper proposes a virtual accelerometer approach to collect acceleration responses of a component from a virtual vehicle model. First, a multiple body dynamic model will be produced for virtual load calculation over a series of digitalized virtual proving ground road profiles.

A vehicle driving down the road naturally pitches, rolls and heaves due to road inputs (for example, bumps, potholes, driving dynamics, etc.) and also due to the influence of aerodynamic forces. The vehicle attitude changes directly as a result of aerodynamic forces that can be seen during wind tunnel testing of production level vehicles, with some measurements possible in order to evaluate the aerodynamics effects. This naturally occurring phenomenon is not always represented in aerodynamics simulations, either for reduced scale models or computational fluid dynamics (CFD) simulations or even rigid body full scale testing. It can be shown through visual techniques how much deflection is typically occurring, including both vehicle attitude changes as well as vehicle body distortions. From the analysis, an adjustment to the CFD models can be made to compensate for the aerodynamics effects.

As the move to decrease physical prototyping increases the need to virtually prototype vehicles become more critical. Assessing NVH vehicle targets and making critical component level decisions is becoming a larger part of the NVH engineer’s job. To make decisions earlier in the process when prototypes are not available companies need to leverage more both their historical and simulation results. Today this is possible by utilizing a hybrid modelling approach in an NVH Simulator using measured on road, CAE, and test bench data. By starting with measured on road data from a previous generation or comparable vehicle, engineers can build virtual prototypes by using a hybrid modeling approach incorporating CAE and/or test bench data to create the desired NVH characteristics. This enables the creation of a virtual drivable model to assess subjectively the vehicles acoustic targets virtually before a prototype vehicle is available.

Cost benefit and teraflop restrictions imposed by racing sanctioning bodies make steady-state RANS CFD simulation a widely accepted first approximation tool for aerodynamics evaluations in motorsports, in spite of its limitations. Research involving generic and simplified vehicle bodies has shown that the veracity of aerodynamic CFD predictions strongly depends on the turbulence model being used. Also, the ability of a turbulence model to accurately predict aerodynamic characteristics can be vehicle shape dependent as well. Modifications to the turbulence model coefficients in some of the models have the potential to improve the predictive capability for a particular vehicle shape. This paper presents a systematic study of turbulence modeling effects on the prediction of aerodynamic characteristics of a NASCAR Gen-6 Cup racecar. Steady-state RANS simulations are completed using a commercial CFD package, STAR-CCM+, from CD-Adapco.

In response to demands for higher fuel economy and stringent emission regulations, OEMs always strive hard to improve component/system efficiency and minimize losses. In the driveline system, improving the efficiency of an automotive rear-axle is critical because it is one of the major power-loss contributor. Optimum oil-fill inside an axle is one of the feasible solutions to minimize spin losses, while ensuring lubrication performance and heat-dissipation requirements. Thus, prior to conducting vehicle development tests, several dyno-level tests are conducted to study the thermal behavior of axle-oil (optimum level) under severe operating conditions. These test conditions represent the axle operation in hot weather conditions, steep grade, maximum tow capacity, etc. It is important to ensure that oil does not exceed its thermal limits (disintegration of oil leading to degradation).

In this paper, the development of a transient thermal analysis model for the exhaust system is presented. Given the exhaust gas temperature out of the engine, a software tool has been developed to predict changes in exhaust gas temperature and exhaust surface temperature under various operating conditions. The software is a thermal solver that will predict exhaust gas and wall surface temperatures by modeling all heat transfer paths in the exhaust system which includes multi-dimensional conduction, internal forced/natural convection, external forced/natural convection, and radiation. The analysis approach involves the breaking down of the thermal system into multiple components, which include the exhaust system (manifold, takedown pipe, tailpipe, etc.), catalytic converter, DPF (diesel particulate filter), if they exist, thermal shields, etc. All components are modeled as 1D porous and 1D non-porous flow streams with 3D wall layers (solid and air gaps).

As more electric vehicles (BEV, HEV, PHEV, etc.) are adopted in the upcoming decades, it is becoming increasingly important to conduct vehicle-level thermal simulations under different drive-cycle conditions while incorporating the various subsystem thermal losses. Thermal management of the various heat sources in the vehicle is essential both in terms of ensuring passenger safety as well as maintaining all the subsystems within their corresponding safe temperature limits. It is also imperative that these thermal simulations include energy consumption prediction, while considering the effect of battery degradation both in terms of increased thermal losses as well as reduction in the vehicle’s range. For this purpose, a three-dimensional transient thermal analysis framework was coupled with an electrochemical P2D-based battery model and a vehicle dynamics model to test different scenarios and their effect on a hybrid vehicle’s range and the lithium-ion battery life.

This research studies the transformation kinetics of austempered ductile iron (ADI) with and without nickel as the main alloying element. ADI has improved mechanical properties compared to ductile iron due to its ausferrite microstructure. Not only can austempered ductile iron be produced with high strength, high toughness and high wear resistance, the ductility of ADI can also be increased due to high carbon content austenite. Many factors influence the transformation of phases in ADI. In the present work, the addition of nickel was investigated based on transformation kinetics and metallography observation. The transformation fractions were determined by Rockwell hardness variations of ADI specimens. The calculation of transformation kinetics and activation energy using the “Avrami Equation” and “Arrhenius Equation” is done to describe effects of nickel alloy for phase reactions.

In current scenario, there is an increasing need to have faster product development and achieve the optimum design quickly. In an automobile air conditioning system, the main function of HVAC third row floor duct is to get the sufficient airflow from the rear heating ventilating and air-conditioning (HVAC) system and to provide the sufficient airflow within the leg locations of passenger. Apart from airflow and temperature, fatigue strength of the duct is one of the important factors that need to be considered while designing and optimizing the duct. The challenging task is to package the duct below the carpet within the constrained space and the duct should withstand the load applied by the passenger leg and the luggage. Finite element analysis (FEA) has been used extensively to validate the stress and deformation of the duct under different loading conditions applied over the duct system.

Cooling airflow is an essential factor when it comes to vehicle performance and operating safety. In recent years, significant efforts have been made to maximize the flow efficiency through the heat exchangers in the under-hood compartment. Grille shutters, new fan shapes, better sealings are only some examples of innovations in this field of work. Underhood cooling airflow simulations are an integral part of the vehicle development process. Especially in the early development phase, where no test data is available to verify the cooling performance of the vehicle, computational fluid dynamics simulations (CFD) can be a valuable tool to identify the lack of fan performance and to develop the appropriate strategy to achieve airflow goals through the heat exchangers. For vehicles with heat exchangers in the underhood section the airflow through those components is of particular interest.

Determining coolant flow distribution in a topologically complex flow path for efficient heat rejection from the critical regions of the engine is a challenge. However, with the established computational methodology, thermal response of an engine (via conjugate heat transfer) can be accurately predicted [1, 2] and improved upon via Design of Experiment (DOE) study in a relatively short timeframe. This paper describes a method to effectively distribute the coolant flow in the engine coolant cavities and evenly remove the heat from various components using a novel technique of optimization based on an approximation model. The current methodology involves the usage of a sampling technique to screen the design space and generate the simulation matrix. Isight, a process automation and design exploration software, is used to set the framework of this study with the engine thermal simulation setup done in the CFD solver, STAR-CCM+.

This paper will explore the effect that non-constant function CD (as observed during wind tunnel testing) would have on the coastdown derived drag coefficient and other regulatory drive cycles. It is common in wind tunnel testing to observe road vehicle drag coefficients that vary with speed. These varying CD values as a function of velocity will be expressed as CD(V) in this paper. Wind tunnel testing for product development is generally conducted at 110 km/h (68.3 mph) which are similar speeds and typical of the United States (US), European, and Asian highway speeds. Reported values of CD are generally gathered at these speeds. However, coastdown testing by definition takes place over a large range of speeds mostly lower than the wind tunnel test speeds. This paper will explore the effect that six typical functions of CD(V) have on the coastdown derived CD. One of the six functions is a constant, to represent a wind tunnel reported CD.

The test cycle average drag coefficient is examined for the variation of allowable EPA coastdown ambient conditions. Coastdown tests are ideally performed with zero wind and at SAE standard conditions. However, often there is some variability in actual ambient weather conditions during testing, and the range of acceptable conditions is further examined in detail as it pertains to the effect on aerodynamic drag derived from the coastdown data. In order to “box” the conditions acceptable during a coastdown test, a sensitivity analysis was performed for wind averaged drag (CD¯) as well as test cycle averaged drag coefficients (CDWC) for the fuel economy test cycles. Test cycle average drag for average wind speeds up to 16 km/h and temperatures ranging from 5C to 35C, along with variation of barometric pressure and relative humidity are calculated. The significant effect of ambient cross winds on coastdown determined drag coefficient is demonstrated.

Significant reduction in Nitrogen Oxide (NOx) emissions will be required to meet LEV III Emissions Standards for Light Duty Diesel passenger vehicles (LDD). As such, Original Equipment Manufacturers (OEMs) are exploring all possible aftertreatment options to find the best balance between performance, robustness and cost. The primary technology adopted by OEMs in North America to achieve low NOx levels is Selective Catalytic Reduction (SCR) catalyst. The critical parameters needed for SCR to work properly are: an appropriate reductant such as ammonia (NH3) typically provided as urea, adequate operating temperatures, and optimum Nitrogen Dioxide (NO2) to NOx ratios (NO2/NOx). The NO2/NOx ratio is mostly influenced by Precious Group Metals (PGM) containing catalysts located upstream of the SCR catalyst. Different versions of zeolite based SCR technologies are available on the market today and these vary in their active metal type (iron, copper, vanadium), and/or zeolite type.

The purpose of this paper is to provide a comparison of multiaxial fatigue limit models and their correlation to experimental data. This paper investigates equivalent stress, critical plane and invariant-based multiaxial fatigue models. Several methods are investigated and compared based on ability to predict multiaxial fatigue limits from data published in literature. The equivalent stress based model developed by Lee, Tjhung and Jordan (LTJ), provides very accurate predictions of the fatigue limit under multiaxial loading due to its ability to account for non-proportional loading. This accuracy comes from the model constant which is calculated based on multiaxial fatigue data. This is the only model investigated that requires multiaxial fatigue testing to generate the model parameters. All other models rely on uniaxial test results.

Several popular frequency-based fatigue damage models (Wirsching and Light, Ortiz and Chen, Larsen and Lutes, Benascuitti and Tovo, Benascuitti and Tovo with α.75, Dirlik, Zhao and Baker, and Lalanne) are reviewed and assessed. Seventy power spectrum densities with varied amplitude, shape, and irregularity factors from Dirlik’s dissertation are used to study the accuracies of these methods. Recommendations on how to set up the inverse fast Fourier transform to synthesize load data and obtain accurate rainflow cycle counts are given. Since Dirlik’s method is the most commonly used one in industry, a comprehensive investigation of parameter setups for Dirlik’s method is presented. The mean error and standard deviation of the error between the frequency-based model and the rainflow cycle counting method was computed for fatigue slope exponent m ranging from 3 to 12.

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).