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Misfire diagnostics are required to detect missed combustion events which may cause an increase in emissions and a reduction in performance and fuel economy. If the misfire detection system is based on crankshaft speed measurement, driveline torque variations due to rough road can hinder the diagnosis of misfire. A common method of rough road detection uses the ABS (Anti-Lock Braking System) module to process wheel speed sensor data. This leads to multiple integration issues including complexities in interacting with multiple suppliers, inapplicability in certain markets and lower reliability of wheel speed sensors. This paper describes novel rough road detection concepts based on signal processing and statistical analysis without using wheel speed sensors. These include engine crankshaft and Transmission Output Speed (TOS) sensing information. Algorithms that combine adaptive signal processing and specific statistical analysis of this information are presented.

We propose a composite thermal model of the vehicle passenger compartment that can be used to predict and analyze thermal comfort of the occupants of a vehicle. Physical model is developed using heat flow in and out of the passenger compartment space, comprised of glasses, roof, seats, dashboard, etc. Use of a model under a wide variety of test conditions have shown high sensitivity of compartment air temperature to changes in the outside air temperature, solar heat load, temperature and mass flow of duct outlet air from the climate control system of a vehicle. Use of this model has subsequently reduced empiricism and extensive experimental tests for design and tuning of the automatic climate control system. Simulation of the model allowed several changes to the designs well before the prototype hardware is available.

There is an increasing interest in transient thermal simulations of automotive brake systems. This paper presents a high-fidelity CFD tool for modeling complete braking cycles including both the deceleration and acceleration phases. During braking, this model applies the frictional heat at the interface on the contacting rotor and pad surfaces. Based on the conductive heat fluxes within the surrounding parts, the solver divides the frictional heat into energy fluxes entering the solid volumes of the rotor and the pad. The convective heat transfer between the surfaces of solid parts and the cooling airflow is simulated through conjugate heat transfer, and the discrete ordinates model captures the radiative heat exchange between solid surfaces. It is found that modeling the rotor rotation using the sliding mesh approach provides more realistic results than those obtained with the Multiple Reference Frames method.

This paper discusses an analytical technique for computing the failure rate of steel springs used in automotive part applications. Preliminary computations may be performed and used to predict spring failure rates quickly at a very early stage of a product development cycle and to establish program reliability impact before commitment. The analytical method is essentially a combination of various existing procedures that are logically sequenced to compute a spring probability of failure under various operational conditions. Fatigue life of a mechanical component can be computed from its S-N curve. For steels, the S-N curve can be approximated by formulae which describe the fatigue life as a function of its endurance limit and its alternating stress. Most springs in service are preloaded and the actual stress fluctuates about a mean level. In order to compute an equivalent alternating stress with zero mean, an analytical method based on the Goodman Diagram is used.

This paper describes the application of Statistical Energy Analysis (SEA) and Experimental SEA (ESEA) to calculating the transmission of air-borne and structure-borne noise in a mid-sized sedan. SEA can be applied rapidly in the early stages of vehicle design where the degree of geometric detail is relatively low. It is well suited to the analysis of multiple paths of vibrational energy flow from multiple sources into the passenger compartment at mid to high frequencies. However, the application of SEA is made difficult by the geometry of the vehicle's subsystems and joints. Experience with current unibody vehicles leads to distinct modeling strategies for the various frequency ranges in which airborne or structure-borne noise predominates. The theory and application of ESEA to structure-borne noise is discussed. ESEA yields loss factors and input powers which are combined with an analytical SEA model to yield a single hybrid model.

A methodology involving Design for Six Sigma (DFSS) and Multi-body dynamic simulation is employed to tune a body-on-frame vehicle, for improved ride (shake) performance. The design space is limited to four sets of symmetric body mounts for a vehicle. The stiffness and damping characteristics of the mounts are the control factors in the virtual experiment. Variation of these design parameters from the nominal settings, as well as axle size, tire and wheel combinations, tire pressure, shock damping, and vehicle speed constitute the noise factors. This approach proves to be an excellent predictor of the vehicle behavior, by which much insight as to influence of each parameter on vehicle performance is gained. Ultimately, specific recommendations for the control factor settings are provided. Subsequent hardware builds show excellent agreement with the analytical model and suggested tuning.

Since 1997, General Motors Body Manufacturing Engineering - Die Engineering Services (BME-DES) has been working jointly with our software vendor to develop and implement a parallel version of stamping simulation software for mass production analysis applications. The evolution of this technology and the insight gained through the implementation of DMP/MPP technology as well as performance benchmarks are discussed in this publication.

The use of regrind acrylonitrile-butadiene-styrene (ABS) for automotive parts and components results in two types of financial savings. The first is the shared monetary savings between General Motors and the molder for the difference in the virgin resin price versus price of the ABS regrind. The second is a societal energy savings seen in the life cycle of virgin ABS versus reground ABS. An added benefit is the preservation of natural resources used to produce virgin ABS.

Finite element analysis (FEA) predictions of magnesium beams are compared to load versus displacement test measurements. The beams are made from AM60B die castings, AM30 extrusions and AZ31 sheet. The sheet and die cast beams are built up from two top hat sections joined with toughened epoxy adhesive and structural rivets. LS-DYNA material model MAT_124 predicts the magnesium behavior over a range of strain rates and accommodates different responses in tension and compression. Material test results and FEA experience set the strain to failure limits in the FEA predictions. The boundary conditions in the FEA models closely mimic the loading and constraint conditions in the component testing. Results from quasi-static four-point bend, quasi-static axial compression and high-speed axial compression tests of magnesium beams show the beam's behavior over a range of loadings and test rates. The magnesium beams exhibit significant material cracking and splitting in all the tests.

Fully Flexible Valve Actuation (FFVA) systems provide maximum flexibility to adjust lift profiles of engine intake and exhaust valves. A research grade electro-hydraulic servo valve based FFVA system was designed to be used with an engine in a test cell to precisely follow desired lift profiles. Repetitive control was chosen as the control strategy. Crank angle instead of time is used to trigger execution to ensure repeatability. A single control is used for different engine speeds even though the period for one revolution changes with engine speeds. The paper also discusses lift profile extension, instantaneous lift profile switching capability and built-in safety features.

Casting, machining and structural simulations were completed on a V8 engine block made in Compacted Graphite Iron (CGI) for use in a racing application. The casting and machining simulations generated maps of predicted tensile strength and residual stress in the block. These strength and stress maps were exported to a finite element structural model of the machined part. Assembly and operating loads were applied, and stresses due to these loads were determined. High cycle fatigue analysis was completed, and three sets of safety factors were calculated using the following conditions: uniform properties and no residual stress, predicted properties and no residual stress, and predicted properties plus residual stress.

The Auto/Steel Partnership established the Light Truck Frame Project Group in 1996 with two objectives: (a) to develop materials, design and fabrication knowledge that would enable the frames on North American OEM (original equipment manufacturer) light trucks to be reduced in weight, and (b) to improve corrosion resistance of frames on these vehicles, thereby allowing a reduction in the thickness of the components and a reduction in frame weight. To address the issues relating to corrosion, a subgroup of the Light Truck Frame Project Group was formed. The group comprised representatives from the North American automotive companies, test laboratories, frame manufacturers, and steel producers. As part of a comprehensive test program, the Corrosion Subgroup has completed tests on frame coatings. Using coated panels of a low carbon hot rolled and pickled steel sheet and two types of accelerated cyclic corrosion tests, seven frame coatings were tested for corrosion performance.

This paper describes the recent efforts on developing an automotive climate control system throughout integrating an electrically-controlled variable capacity scroll compressor with a fuzzy logic control-based refrigerant flow management. Applying electrically-controlled variable capacity compressor technology to climate control systems has a significant impact on improving vehicle fuel economy, achieving higher passenger comfort level, and extending air and refrigerant temperature controllability as well. In this regard, it is very important for automotive climate control engineers to layout a system-level temperature control strategy so that the operation of variable capacity compressor can be optimized through integrating the component control schemes into the system-level temperature control. Electronically controlled expansion devices have become widely available in automotive air conditioning (A/C) systems for the future vehicle applications(1, 2, 3 and 4).

The overall vision of this project was to develop a new technology that will be an enabler to reduce design and development time of HVAC systems by an order of magnitude. The objective initially was to develop a parametric model of an automotive HVAC Windshield Defrost Duct coupled to a passenger compartment. It can be used early on in the design cycle for conducting coarse packaging studies by quickly exploring “what-if” design alternatives. In addition to the packaging studies, performance of these design scenarios can be quickly studied by undertaking CFD simulation and analyzing flow distribution and windshield melting patterns. The validated geometry and CFD models can also be used as knowledge building tools to create knowledge data warehouses or repositories for precious lessons learned.

The bulge test in hydroforming is a simple fundamental experiment used to obtain basic knowledge in tube expansion. The results can be used to assist design and manufacturing of hydroformed automotive parts. It also can be used to develop a failure criterion for tubes in hydroforming. For these purposes, a section of a long unsupported tube with fixed ends was simulated numerically to obtain the mechanical states of the tube subjected to internal pressure. Steel and aluminum tubes are used. For the bulge tests, the internal pressure reaches a maximum and then decreases in value without failure while the stress, strain and volume of the tube keep increasing. A failure criterion for the bursting of a tube is proposed based on the stress-strain curve of the material.

Brake squeal has been analyzed by finite elements for some time. Among several methods, complex eigenvalue analysis is proving useful in the design process. It requires hardware verification and it falls into a simulation process. However, it is fast and it can provide guidance for resolving engineering problems. There are successes as well as frustrations in implementing this analysis tool. Its capability, robustness and reliability are closely examined in many companies. Generally, the low frequency squealing mechanism is a rotor axial direction mode that couples the pads, rotor, and other components; while higher frequency squeal mainly exhibits a rotor tangential mode. Design modifications such as selection of rotor design, insulator, chamfer, and lining materials are aimed specifically to cure these noise-generating mechanisms. In GM, complex eigenvalue analysis is used for brake noise analysis and noise reduction. Finite element models are validated with component modal testing.

This paper documents a joint development process between General Motors and Dow Automotive to improve primary body structure frequencies on the GM family of midsize vans by utilizing cavity-filling structural foam. Optimum foam locations, foam quantity, and foam density within the body structure were determined by employing both math-based modeling and vehicle hardware testing techniques. Finite element analysis (FEA) simulations of the Body-In-White (BIW) and “trimmed body” were used to predict the global body structure modes and associated resonant frequencies with and without structural foam. The objective of the FEA activity was to quantify frequency improvements to the primary body structure modes of matchboxing, bending, and torsion when using structural foam. Comprehensive hardware testing on the vehicle was also executed to validate the frequency improvements observed in the FEA results.

A gasoline direct injection fuel spray was observed using a fired, optical access, square cross-section single cylinder research engine and high-speed video imaging. Spray interaction with the piston is described qualitatively, and the results are compared with Computational Fluid Dynamics (CFD) simulation results using KIVA-3V version 2. CFD simulations predicted that within the operating window for stratified charge operation, between 1% and 4% of the injected fuel would remain on the piston as a liquid film, dependent primarily on piston temperature. The experimental results support the CFD simulations qualitatively, but the amount of fuel film remaining on the piston appears to be under-predicted. High-speed video footage shows a vigorous spray impingement on the piston crown, resulting in vapor production.

In performing stochastic simulations using computer models, the method of sampling is important. It affects the quality and the convergence speed of the results. This paper discusses one special case: sampling of spot-weld locations from potentially thousands of spot welds on a vehicle body. This study is prompted by the need of evaluating the effect of missed spot welds on the structural integrity, identifying critical welds, and optimizing weld locations. A balanced random sampling algorithm based on the concept of Latin-Hypercube sampling is developed for this application. We also present a case study in which the efficiency of three different sampling methods is compared using a car joint stiffness example. The new method, called the Balanced Latin-Hypercube Sampling (BLHS), has shown significantly faster convergence over the other two.

Robust optimization usually requires numerous functional evaluations, which is not feasible when the functional evaluation is time-consuming. Examples in automobile industry include crash worthiness/safety and fatigue life simulations. In practice, a response surface model (RSM) is often used as a surrogate to the CAE model, so that robust optimization can be carried out. However, if the error in the RSM is significant, the solution based on the RSM can be invalid. This paper proposes a method of finding multiple candidate solutions, all of which have similar predicted performances. This approach is effective in finding the close-to-optimum solutions when the model has error, and providing design alternatives. Examples are provided to illustrate the method.