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Vibration and sound radiation characteristics of bead-stiffened panels are investigated. Rectangular panels with different bead configurations are considered. The attention is focused on various design parameters, such as orientation, depth, and periodicity, and their effects on equivalent bending stiffness, modal density, radiation efficiency and sound transmission. A combined FEA-SEA approach is used to determine the response characteristics of panels across a broad frequency range. The details of the beads are represented in fine-meshed FEA models. Based on predicted surface velocities, Rayleigh integral is evaluated numerically to calculate the sound pressure, sound power and then the radiation efficiency of beaded panels. Analytical results are confirmed by comparing them with experimental measurements. In the experiments, the modal densities of the panels are inferred from averaged mechanical conductance.

Regulations implemented by safety commissions throughout the world have resulted in extensive physical testing to protect the occupants during frontal impact events. Significant prototype and test costs aimed at optimizing structure and restraint systems are associated with meeting these regulations. To help reduce development costs, Computer Aided Engineering (CAE) is often applied. LS-DYNA [1] coupled with MADYMO [2] is widely used in crash and occupant safety simulation. An analysis technique which utilized a single model to design and optimize interiors (instrument panel, seats, visor, steering wheel, steering column) and restraints (airbag, seatbelts, retractor, pre-tensioner) was developed. The single model concept captures the global structural kinematics through minimal vehicle representation. Global vehicle modes such as pitch and roll can be represented by applying prescribed motion boundary conditions extracted from full vehicle models.

A predictive automatic gear shift system is currently under development. The system optimizes the gear shift process, taking the conditions of the road ahead into account, such that the fuel consumption is minimized. An essential part of the system is a module that predicts the vehicle speed dynamics: This calculates a speed trajectory, i.e. the most probable vehicle speed the driver will desire for the upcoming section of the route. In the paper the theoretical background for predicting the vehicle speed, and simulation results of the predictive shift algorithm are presented.

This paper presents a new approach to improve occupant response in a front impact event. Instead of designing a vehicle structure for maximum structural efficiency and safety and then engineer a restraint system for the vehicle, this paper proposes to use a systems approach. In this approach, the vehicle structural response during impact (i.e., pulse) and the restraint system are considered together in the optimization process. In this paper, the 35 mph front impact into a rigid barrier with belted occupants, which is the NHTSA NCAP test, will be used to demonstrate the proposed new approach.

In this paper, cradle design functional objectives are briefly reviewed and a durability development process is proposed focusing on the cradle loads, stress, strain, and fatigue life analysis. Based upon the proposed design process, sample isolated and non-isolated cradle finite element (FE) models for a uni-body sport utility vehicle (SUV) under different design phases are solved and correlated with laboratory bench and proving ground tests. The correlation results show that the applied cradle models can be used to accurately predict the critical stress spots and fatigue life under various loading conditions.

Adhesive joining is a common autobody subassembly technique especially for outer panels, where visible spot welding is objectionable. To accommodate mass production with the use of certain adhesives very high thermal gradient usually exists, which may result in panel dimensional distortion and variation. The temperature distribution over location and over time are monitored, and its impact to panel dimension is investigated. Experimental results on the effect of the distance between panel and induction coil on the panel temperature is obtained. The thermal induced shape distortion is simulated with a simplified FEA model. The approach to improvement of the induction curing process is discussed.

The hybrid Finite Element Analysis (hybrid FEA) has been developed for performing structure-borne computations in automotive vehicle structures [1, 2 and 3]. The hybrid FEA method combines conventional FEA with Energy FEA (EFEA). Conventional FEA models are employed for modeling the behavior of the stiff members in a system. Appropriate damping and spring or mass elements are introduced in the connections between stiff and flexible members in order to capture the presence of the flexible members during the analyses of the stiff ones. The component mode synthesis method is combined with analytical solutions for determining the driving point conductance at joints between stiff and flexible members and for defining the properties of the concentrated elements which represent the flexible members when analyzing the stiff components.

Some of the best teaching methods are laboratory courses in which students experience application of the principles being presented. Preparing young engineering students for a career in the automotive industry challenges us to provide comparable opportunities to explore the dynamic performance of motor vehicles in a controlled environment. Today we are fortunate to have accurate and easy-to-use software programs making it practical for students to simulate the performance of motor vehicles on “virtual” proving grounds. At the University of Michigan the CarSim® vehicle dynamics simulation program has been introduced as such a tool to augment the learning experience. The software is used in the Automotive Engineering course to supplement homework exercises analyzing acceleration, braking, aerodynamics, and cornering performance. This paper provides an overview of the use of simulation in this setting.

Diesel fuel is a blend of various middle distillate components separated at the refinery. The composition and characteristics of the diesel fuel blend changes daily if not hourly because of normal process variation, changing refinery processing conditions, changing crude oil diet or changing diesel fuel and kerosene market conditions. Regardless of the situation going on at the refinery or the market, the resultant diesel fuel must consistently meet established cloud point specifications. To consistently meet the cloud point specifications, refiners are forced to blend their diesel fuels in such a way that the resultant blend is always on the low side of the cloud point specification even when the refining process adversely changes the fuel characteristics. This practice has the effect of producing several degrees of cloud point “giveaway” when the refinery is not experiencing adverse swings in product quality.

The emerging Variable Valve Timing (VVT) technology complicates the estimation of air flow rate because both intake and exhaust valve timings significantly affect engine's gas exchange and air flow rate. In this paper, we propose to use Artificial Neural Networks (ANN) to model the air flow rate through a 2.4 liter VVT engine with independent intake and exhaust camshaft phasers. The procedure for selecting the network architecture and size is combined with the appropriate training methodology to maximize accuracy and prevent overfitting. After completing the ANN training based on a large set of dynamometer test data, the multi-layer feedforward network demonstrates the ability to represent air flow rate accurately over a wide range of operating conditions. The ANN model is implemented in a vehicle with the same 2.4 L engine using a Rapid Prototype Controller.

The Engine Oil Industry Base Oil Interchange (BOI) and Viscosity Grade Read Across (VGRA) guidelines developed by the American Petroleum Institute (API) provide a means to significantly reduce the time to market for current technology oils. The guidelines also allow conversion of a fraction of the millions of dollars spent each year on engine testing in pursuit of API engine oil licensing into research testing and the development of fundamental knowledge. In the past, guidelines have been developed based upon a general assessment of minimal engine test data. Recently, however, regression models have been used to assess Base Oil and Viscosity Grade effects. The use of statistical regression models and Virtual Tests in determining effects to establish BOI and VGRA has several advantages. These advantages, demonstrated through an example and a case study, include volume of data and breadth of data.

One of the key functions of lubricating oil additives in diesel engines is to control oil thickening caused by soot accumulation. Over the last several years, it has become apparent that the composition of the base oil used within the lubricant plays an extremely important role in the oil thickening phenomenon. In particular, oil thickening observed in the Mack T-8 test is significantly affected by the aromatic content of the base oil. We have found that the Mack T-8 thickening phenomenon is associated with high electrical activity, i.e., engine drain oils which exhibit high levels of viscosity increase show significantly higher conductivities. These findings suggest that electrical interactions are involved in soot-induced oil thickening.

A traction test machine, developed for evaluation of traction-CVT fluids for the automotive consortium, USCAR, provides precision traction measurements to stresses up to 4 GPa. The high stress machine, WAMhs, provides an elliptical contact between AISI 52100 steel roller and disc specimens. Machine stiffness and positioning technology offer precision control of linear slip, sideslip and spin. A USCAR traction test methodology includes entrainment velocities from 2 to 10 m/sec and temperatures from -20°C to 140°C. The purpose of the USCAR machine and test methodology is to encourage traction fluid development and to establish a common testing approach for fluid qualification. The machine utilizes custom software, which provides flexibility to conduct comprehensive traction fluid evaluations.

Accurate motion prediction can be used to evaluate vibrations at seat track and steering wheel. This paper presents the prediction and correlation of truck frame motion from wheel force transducer (WFT) measurements. It is assumed that the method can be used to predict vibrations at seat track and steering wheel for unibody vehicles. Two durability events were used for calculation. WFT measurements were used as inputs applied on frame from suspension. Frame loads were then used as inputs to calculate frame motions using a FEA approach. The predicted frame motions are represented by four exhaust hangers and they are compared with measured motions of the same locations. The correlations include displacement, velocity, and acceleration. It is shown that good correlations are obtained in velocity and displacement. Acceleration shows bigger differences than velocity and displacement.

This paper introduces a reliable method to calculate body mount loads from wheel-force-transducer (WFT) measurements on framed vehicles. The method would significantly reduce time and cost in vehicle development process. The prediction method includes two parts: Hybrid Load Analysis (HLA) that has been used by DaimlerChrysler Corporation and Body Mount Load Analysis (BMLA) that is introduced by this paper for the first time. The method is validated on a body-on-frame SUV and a pickup truck through one proving ground events. The example shown in this paper is for a SUV and one of the most severe events. In HLA, the loads at suspension-to-frame attachments are calculated from spindle loads measured by WFT. In BMLA, body mount loads were calculated using outputs of HLA with detailed finite-element-modeled frame and body. The loads are compared with measured body mount loads. The comparisons are conducted in range, standard deviation (S.D.), and fatigue pseudo-damage.

Transmission mounts are usually tested as an assembly and typically only translational stiffnesses are provided. The torsional stiffness of the assembly is traditionally estimated based on experience in load simulation and analysis. This paper presents a procedure to estimate the torsional stiffness of the transmission mount assembly by using the test data. The effects of the torsional stiffness on the simulation results are also discussed.

The transient cone angle of pressure swirl sprays from injectors intended for use in gasoline direct injection engines was measured from 2D Mie scattering images. A variety of injectors with varying nominal cone angle and flow rate were investigated. The general cone angle behavior was found to correlate well qualitatively with the measured fuel line pressure and was affected by the different injector specifications. Experimentally measured modulations in cone angle and injection pressure were forced on a comprehensive spray simulation to understand the sensitivity of pulsating injector boundary conditions on general spray structure. Ignoring the nozzle fluctuations led to a computed spray shape that inadequately replicated the experimental images; hence, demonstrating the importance of quantifying the injector boundary conditions when characterizing a spray using high-fidelity simulation tools.

It is often necessary to measure three-axis displacement of a deforming or moving part in static or dynamic impact tests. A point moving in the three-dimensional space can be monitored and measured using three string-pots or other distance measuring devices with a methodology developed here. A numerical algorithm along with required equations are shown and discussed. The algorithm was applied as an example to static seat pull test and compared to results from film analysis. The application with string pots is useful especially when the point of concern gets hidden or blocked by other parts disabling the photogrammetry technology.

In API engine oil licensing, a candidate oil must meet the performance requirements of category defined engine tests. The reason for the engine tests is to assess the capability of the candidate oil in field performance. Unfortunately, due to the time consuming and expensive nature of most engine tests, a candidate oil is typically run only once or twice in an attempt to meet the performance requirements. Given that the results from most engine tests have large amounts of variability, the assessment of the candidate oil in several tests, although adequate, is obviously not perfect or inexpensive. The Virtual Engine Test is a process in which the time and expense of category defined engine tests may be reduced while maintaining, or even improving, the assessment of the candidate oil capability.

Over the past five years, the US Automotive Materials Partnership (USAMP) has brought together representatives from DaimlerChrysler, General Motors, Ford Motor Company and over 40 other participant companies from the Mg casting industry to create and test a low-cost, Mg-alloy engine that would achieve a 15 - 20 % Mg component weight savings with no compromise in performance or durability. The block, oil pan, and front cover were redesigned to take advantage of the properties of both high-pressure die cast (HPDC) and sand cast Mg creep- resistant alloys. This paper describes the alloy selection process and the casting and testing of these new Mg-variant components. This paper will also examine the lessons learned and implications of this pre-competitive technology for future applications.