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The demand for improved fuel economy in both cars and trucks has emphasized the need for lighter weight components. The application of high strength steel to wheels, both rim and disc, represents a significant opportunity for the automotive industry. This paper discusses the Ranger HSLA wheel program that achieved a 9.7 lbs. per vehicle weight savings relative to a plain carbon steel wheel of the same design. It describes the Ranger wheel specifications, the material selection, the metallurgical considerations of applying HSLA to wheels, and HSLA arc and flash butt welding. The Ranger wheel design and the development of the manufacturing process is discussed, including design modifications to accommodate the lighter gage. The results demonstrate that wheels can be successfully manufactured from low sulfur 60XK HSLA steel in a conventional high volume process (stamped disc and rolled rim) to meet all wheel performance requirements and achieve a significant weight reduction.

Vehicle restraint system design is a difficult optimization problem to solve because (1) the nature of the problem is highly nonlinear, non-convex, noisy, and discontinuous; (2) there are large numbers of discrete and continuous design variables; (3) a design has to meet safety performance requirements for multiple crash modes simultaneously, hence there are a large number of design constraints. Based on the above knowledge of the problem, it is understandable why design of experiment (DOE) does not produce a high-percentage of feasible solutions, and it is difficult for response surface methods (RSM) to capture the true landscape of the problem. Furthermore, in order to keep the restraint system more robust, the complexity of restraint system content needs to be minimized in addition to minimizing the relative risk score to achieve New Car Assessment Program (NCAP) 5-star rating.

Four vehicle fleets, consisting of 3 to 4 vehicles each, were emission tested on a 48″ roll chassis dynamometer using both the FTP urban dynamometer driving cycle and the REP05 driving cycle. The REP05 cycle was developed to test vehicles under high speed and high load conditions not included in the FTP. The vehicle fleets consisted of 1989 light-duty gasoline vehicles, 1992-93 limited production FFV/VFV methanol vehicles, 1992-93 compressed natural gas (CNG) vehicles and their gasoline counterparts, and a 1992 production and two prototype ethanol FFV/VFV vehicles. All vehicles (except the dedicated CNG vehicles) were tested using Auto/Oil AQIRP fuels A and C2. Other fuels used were M85 blended from A and C2, E85 blended from C1, which is similar to C2 but without MTBE, and four CNG fuels representing the range of in-use CNG fuels. In addition to bag measurements, tailpipe exhaust concentration and A/F data were collected once per second throughout every test.

A model is presented which incorporates the key mechanisms in the formation and reduction of unburned HC emissions from spark ignited engines. The model includes the effects of piston crevice volume, oil layer absorption / desorption, partial burns, and in-cylinder and exhaust port oxidation. The mechanism for the filling and emptying of the piston crevice takes into account the location of the flame front so that the flow of both burned gas and unburned gas is recognized. Oxidation of unburned fuel is calculated with a global, Arrhenius-type equation. A newly developed submodel is included which calculates the amount of unburned fuel to be added to the cylinder as a result of partial burns. At each crankangle, the submodel compares the rate of change of the burned gas volume to the rate of change of the cylinder volume.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

Combustion flame geometry calculation is a critical task in the design and analysis of combustion engine chamber. Combustion flame directly influences the fuel economy, engine performance and efficiency. Currently, many of the flame geometry calculation methods assume certain specific chamber and piston top shapes and make some approximations to them. Even further, most methods can not handle multiple spark plug set-ups. Consequently, most of the current flame geometry calculation methods do not give accurate results and have some built-in limitations. They are particularly poor for adapting to any kind of new chamber geometry and spark plug set-up design. This report presents a novel methodology which allows the accurate calculation of flame geometry regardless of the chamber geometry and the number of spark plugs. In this methodology, solid models are used to represent the components within the chamber and unique attributes (colors) are attached respectively to these components.

An analytical model based on “vortex sound” theory was investigated for predicting the frequency, the relative magnitude, the onset, and the offset of self-sustained interior pressure fluctuations inside a vehicle with an open sunroof. The “buffeting” phenomenon was found to be caused by the flow-excited resonance of the cavity. The model was applied to investigate the optimal sunroof length and width for a mid-size sedan. The input parameters are the cavity volume, the orifice dimensions, the flow velocity, and one coefficient characterizing vortex diffusion. The analytical predictions were compared with experimental results obtained for a system which geometry approximated the one-fifth scale model of a typical vehicle passenger compartment with a rectangular, open sunroof. Predicted and observed frequencies and relative interior pressure levels were in good agreement around the “critical” velocity, at which the cavity response is near resonance.

The present work focused on modeling turbulent flame propagation combustion process using a direct chemical kinetics model. Firstly, the theory of turbulent flame propagation combustion modeling directly using chemical kinetics is given in detail. Secondly, two important techniques in this approach are described. One technique is the selection of chemical kinetics mechanism, and the other one is the selection of AMR (adaptive mesh refinement) level. A reduced chemical kinetics mechanism with minor modification by the authors of this paper which is suitable for simulating gasoline engine under warm up operating conditions was selected in this work. This mechanism was validated over some operating conditions close to some engine cases. The effect of AMR level on combustion simulation is given, and an optimum AMR level of both velocity and temperature is recommended.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

The optimized design of an exhaust emission system in terms of performance, cost, packaging, and engine control strategy will be a key part of competitively meeting future more stringent emission standards. Extensive use of vehicle experiments to evaluate design system tradeoffs is far too time consuming and expensive. Imperative to successfully meeting the challenges of future emission regulations and cost constraints is the development of an exhaust system simulation model which offers the ability to sort through major design alternatives quickly while assisting in the interpretation of experimental data. Previously, detailed catalyst models have been developed which require the specification of intricate kinetic mechanisms to determine overall catalyst performance. While yielding extremely valuable results, these models use complex numerical algorithms to solve multiple partial differential equations which are time consuming and occasionally numerically unstable.

The small-displacement direct-injection (DI) diesel engine is a prime candidate for future transportation needs because of its high thermal efficiency combined with near term production feasibility. Ford Motor Company and FEV Engine Technology, Inc. are working together with the US Department of Energy to develop a small displacement DI diesel engine that meets the key challenges of emissions, NVH, and power density. The targets for the engine are to meet ULEV emission standards while maintaining a best fuel consumption of 200g/kW-hr. The NVH performance goal is transparency with state-of-the-art, four-cylinder gasoline vehicles. Advanced features are required to meet the ambitious targets for this engine. Small-bore combustion systems enable the downsizing of the engine required for high fuel economy with the NVH advantages a four- cylinder has over a three-cylinder engine.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

Manual Materials Handling has been historically recognized as one of the more prevalent causes for work related lost time injuries. Many manufacturing facilities use Material Handling Systems (lift/ tilt tables, hoists, articulated arms), often to alleviate ‘ergonomic’ stressors as well as to optimize production. If not used appropriately, Material Handling Systems can create new ergonomic concerns, or in some cases increase the physical demands of a job. A strategy designed to optimize the fit between the operator, the appropriate equipment and the operation is addressed in this paper.

A structural ceramic diesel engine has the potential to provide low heat rejection and significant improvements in fuel economy. Analytical and experimental evaluations were conducted on the critical elements of this engine. The structural ceramic components, which included the cylinder, piston and pin, operated successfully in a single cylinder engine for over 100 hours. The potential for up to 8-11% improvement in indicated specific fuel consumption was projected when corrections for blow-by were applied. The ringless piston with gas squeeze film lubrication avoided the difficulty with liquid lubricants in the high temperature piston/cylinder area. The resulting reduction in friction was projected to provide an additional 15% improvement in brake specific fuel consumption for a multi-cylinder engine at light loads.

The characteristics of multiple spark ignition systems with respect to engine performance, emissions, lean misfire, and tolerance to exhaust gas recirculation (EGR) have been investigated using a carbureted single-cylinder engine. The results, which were compared to those obtained with a standard single spark ignition system, show that both lean misfire limit and EGR tolerance are extended with the multiple spark system. The amount of extension varies with engine load, being largest at the lighter loads studied. Engine power and emissions at non-misfiring conditions are the same with both ignition systems.

Ribbed floor panels have been widely applied in vehicle body structures to reduce interior noise. The conventional approach to evaluate ribbed floor panel designs is to compare natural frequencies and local stiffness. However, this approach may not result in the desired outcome of the reduction in radiated noise. Designing a “quiet” floor panel requires minimizing the total radiated noise resulting from vibration of the floor panel. In this study, the objective of ribbed floor panel design is to reduce the total radiated sound power by optimizing the rib patterns. A parametric study was conducted first to understand the effects of rib design parameters such as rib height, width, orientation, and density. Next, a finite element model of a simplified body structure with ribbed floor panel was built and analyzed. The structural vibration profile was generated using MSCINastran, and integrated with the acoustic boundary element model.

In this paper we describe the application of optimization techniques to the design of valvetrains in high revving internal combustion engines. The methods presented are based on parameter optimization [1] and the minimum principle by Pontrjagin [2] and will be applied to cam lobe and valve spring optimization, aiming at reducing oscillation amplitudes and improving control of the valvetrain over a broad speed range. To put the task of optimization into context the engineering requirements for valvetrains and methods to allow their computer based analysis are described. Furthermore principle considerations for valve event curve generation and parametrization, and on optimization techniques are discussed. Based on these fundamentals, optimization aims and constraints are formulated. Furthermore different examples of the application of automated optimization are presented in the area of cam profile optimization and valve spring optimization.

Designing a high-quality door sealing system at low cost is an economic and technological engineering challenge. Robust design is a systematic and efficient technique to meet this challenge of design optimization for performance, quality, and cost. This technique, also called parameter design, focuses on making product and process designs insensitive (i.e. robust) to hard-to-control variations called noise factors. In this paper, we illustrate and apply the principles of robust design using a response model approach to a door sealing system design problem where vehicle interior sound is the primary response being studied. The Appendix contains a glossary of all italicized words for reference.

Multidisciplinary design optimization (MDO) methods are commonly used for weight reduction in automotive industry. The design variables for MDO are often selected based on critical parts, which usually are close to optimal after many design iterations. As a result, the real weight reduction benefit may not be fully realized due to poor selection of design parameters. In addition, most applications require running design of experiments (DOE) to explore the full design space and to build response surfaces for optimization. This approach is often too costly if too many design variables are simultaneously considered. In this research, an alternative approach to address these issues is presented. It includes two optimization phases. The first phase uses critical parts for design iterations and the second phase use non-critical for weight reduction. A vehicle body structure is used to demonstrate the proposed strategy to show its effectiveness.