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A 1.8L turbocharged diesel engine valvetrain friction was investigated, and the effectiveness of using a solid film lubricant (SFL) coating in reducing friction was determined throughout the operable speed range. This valvetrain design features direct acting mechanical bucket valve lifters. Camshaft journal bearing surfaces and all camshaft rubbing surfaces except lobe tips were coated. The direct acting bucket shims were etched with a cross hatch pattern to a depth sufficient to sustain a SFL film coating on the shim rubbing surfaces subjected to high surface loads. The SFL coated valvetrain torque was evaluated and compared with uncoated baseline torque. Coating the cam bearing journal surfaces alone with II-25D SFL reduced valvetrain friction losses 8 to 17% for 250 to 2000 rpm cam speed range (i.e. 500 - 4000 rpm engine speed). When bucket tappet and shims were also coated with the SFL, further significant reductions in coated valvetrain friction were observed.

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.

A single cylinder indirect injection diesel engine was used to evaluate the emissions, fuel consumption, and ignition delay of non-petroleum liquid fuels derived from coal, shale, and tar sands. Correlations were made relating fuel properties with exhaust emissions, fuel consumption, and ignition delay. The results of the correlation study showed that the indicated fuel consumption, ignition delay, and CO emissions significantly correlated with the H/C ratio, specific gravity, heat of combustion, aromatics and saturates content, and cetane number, Multiple fuel properties were necessary to correlate the hydrocarbon emissions. The NOx emissions did not correlate well with any fuel property. Because these fuels from various resources were able to correlate succesfully with many of the fuel properties suggests that the degree of refinement or the chemical composition of the fuel is a better predictor of its performance than its resource.

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).

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 effects of engine operating conditions on the octane requirement and the resulting knock-limited output were studied on a single cylinder engine using production cylinder heads. A 4-valve cylinder head with port deactivation was used to study the effect of fuel octane, inlet air temperature, coolant temperature, air/fuel ratio, compression ratio and exhaust back pressure. The effect of the thermal environment was studied in more detail using separate cooling systems for the cylinder head and engine block on a 2-valve cylinder head. The results of this study compared closely with results found in the literature even though the engine and/or operating conditions were quite different in many cases.

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.

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.

In this paper, we present the results of a series of experiments to determine the exhaust particulate size distributions from a number of diesel, gasoline and compressed natural gas (CNG) fuelled vehicles. The results show that all three types of vehicle produce significant populations of particulates under certain operating conditions. Particulates produced by gasoline and CNG engines tend to be smaller than for diesel engines. At low loads, there is a significant particulate distribution for diesel engines but much lower particulate numbers for both gasoline and CNG vehicles. Under these conditions, the gasoline particulate distribution has little structure but the CNG distribution is clearly bimodal. At higher loads, the number of particulates produced by diesel vehicles increases by an order of magnitude from idle and both the CNG and gasoline distributions are comparable in peak height. The diesel vehicle produces a much larger particulate volume than gasoline or CNG.

In the current design process, the designer generates the detailed geometry of the component based on experience. Prototypes of this design are built and tested to verify the performance. This design - build - test iterative process is continued until performance targets/criteria are met. Computer Aided Engineering is often used to verify the design. This paper presents a new product development process to substantially reduce the number of design - analysis - build - test iterations. This Upfront Analysis Driven Design process incorporates several state of the art technologies in finite element structural analysis, optimization, and Computer Aided Design. This process ensures a near optimum design in the first design level itself.

The study presented in this paper is concerned with the application of a finite element based technique to deal with crankshaft-crankcase interaction. A finite element model of the crankshaft and the crankcase was developed and appropriately reduced. This model was used for a crankshaft optimization, strategy to analyse related effects on the NVH performance with focus on main bearing acceleration. The crankshaft and the cylinder block were modelled using beam and shell elements with structural and dynamic properties correlated up to 1600 Hz. The interaction between crankshaft and the cylinder block was represented by using non-linear properties. Applying this model, the dynamic crankshaft and engine block behaviour and repercussion on NVH performance was analysed by investigating main bearing acceleration.

With the adoption of large-scale vehicle system models for NVH analysis, it has become possible to optimize the properties of chassis components to minimize the perception of vibration and/or sound in a vehicle. It has been found that these analytical optimization procedures are useful both in the early concept stage of the vehicle design/development process and in the subsequent component detailed design stage. While the process is rather complex and costly, it can be less costly than the alternative — the building and testing of multiple prototype parts or vehicles. From this standpoint, it may be that analytical optimization is the only practical way of evaluating the many combinations of design parameters that could lead to improved vehicles. To reduce the complexity of the analytical procedure, the vehicle modeling process has been automated and software pre and post-processors have been produced to supplement the primary analysis and optimization codes.

Naturally aspirated Homogeneous Charge Compression Ignition (HCCI) operational window is very limited due to inherent issues with combustion harshness. Load range can be extended for HCCI operation using a combination of intake boosting and cooled EGR. Significant range extension, up to 8bar NMEP at 1000RPM, was shown to be possible using these approaches in a single cylinder engine running residual trapping HCCI with 91RON fuel with a 12:1 compression ratio. Experimental results over the feasible speed / load range are presented in this paper for a negative valve overlap HCCI engine. Fuel efficiency advantage of HCCI was found to be around 15% at 2.62bar / 1500RPM over a comparable SI engine operating at the same compression ratio, and the benefit was reduced to about 5% (best scenario) as the load increased to 5bar at the same speed.