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Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

This paper describes the development of an analytical method to assess and optimize halfshaft joint angles to avoid excessive 3rd halfshaft order vibrations during wide-open-throttle (WOT) and light drive-away events. The objective was to develop a test-correlated analytical model to assess and optimize driveline working angles during the virtual design phase of a vehicle program when packaging tradeoffs are decided. A twelve degree-of-freedom (12DOF) system model was constructed that comprehends halfshaft dynamic angle change, axle torque, powertrain (P/T) mount rate progression and axial forces generated by tripot type constant velocity (CV) joints. Note: “tripot” and “tripod” are alternate nomenclatures for the same type of joint. Simple lumped parameter models have historically been used for P/T mount optimization; however, this paper describes a method for using a lumped parameter model to also optimize driveline working angles.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

A task group within the SAE Automotive Corrosion and Protection (ACAP) Committee continues to pursue the goal of establishing a standard test method for in-laboratory cosmetic corrosion evaluations of finished aluminum auto body panels. The program is a cooperative effort with OEM, supplier, and consultant participation and is supported in part by USAMP (AMD 309) and the U.S. Department of Energy. Numerous laboratory corrosion test environments have been used to evaluate the performance of painted aluminum closure panels, but correlations between laboratory test results and in-service performance have not been established. The primary objective of this project is to identify an accelerated laboratory test method that correlates with in-service performance. In this paper the type, extent, and chemical nature of cosmetic corrosion observed in the on-vehicle exposures are compared with those from some of the commonly used laboratory tests

The two-dimensional, frictional tyre-road contact interaction is investigated. A transient contact algorithm is developed, consisting of an analytical belt model, a non linear sidewall structure and a discretized viscoelastic tread foundation. The relationship between the magnitude/shape of the predicted two-dimensional pressure distribution and the corresponding belt deformation is identified. The effect of vertical load and the role of sidewall non linearity are highlighted. The modal expansion/reduction method is proposed for the increase of the computational efficiency and the effect of the degree of reduction on the simulation accuracy is presented. The qualitative results are physically explained through the participation of certain modes in the equilibrium solution, offering directions for the application of the modal reduction method in shear force oriented tyre models.

In order to increase the efficiency of automotive turbochargers at low speed without compromising the performance at maximum boost conditions, variable geometry compressor (VGC) systems, based on either variable inlet guide vanes or variable geometry diffusers, have been recently considered as a future design option for automotive turbochargers. This work presents a modeling, analysis and optimization study for a Diesel engine equipped with a variable geometry compressor that help understand the potentials of such technology and develop control algorithms for the VGC systems,. A cycle-averaged engine system model, validated on experimental data, is used to predict the most important variables characterizing the intake and exhaust systems (i.e., mass flow rates, pressures, temperatures) and engine performance (i.e., torque, BMEP, volumetric efficiency), in steady-state and transient conditions.

A large contribution to the aerodynamic drag of a vehicle (30%(1) or more depending on vehicle shape) arises from the low base pressure in the wake region, especially on square-back configurations. A degree of base pressure recovery can be achieved through careful shape optimization, but the flow structures and mechanisms within the wake that cause these base pressure changes are not well understood. A more complete understanding of these mechanisms may provide opportunities for further drag reductions from both passive shape changes and in the future through the use of active flow control technologies. In this work surprisingly large changes in drag and lift coefficients of a square-back style vehicle have been measured as a result of physically small passive modifications. Tests were performed at quarter scale using a simplified vehicle model (Windsor Model) and at full scale using an MPV. The full scale vehicle was tested with and without a flat floor.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

General Motors (GM) recently purchased an acoustic holography system based on the Helmholtz Equation Least Squares (HELS) methodology. Typically acoustic holography has utilized planar transformation of the Fourier acoustic equations. General Motors conducted a variety of experiments on a simple well understood structure. This enabled us to understand the setup parameters and confirm the manufacturer's claims for accuracy. Measurements on the structure were taken using the HELS based equipment and a laser vibrometer. Conclusions are drawn on how to set up the equipment for future testing on vehicles.

The Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

Technical groups worldwide have been actively developing specifications and requirements for biodegradable hydraulic fluids for mobile applications. These groups have recognized that an industry-wide specification is necessary due to the increase in environmental awareness in the agriculture, construction, forestry, and mining industries, and to the increasing number of local regulations primarily throughout Europe. Caterpillar has responded to this need by publishing a requirement, Caterpillar BF-1, that may be used by Caterpillar dealers, customers, and industry to help select high-performance biodegradable hydraulic fluids. This requirement was written with the input of several organizations that are known to be involved with the development of similar types of specifications and requirements.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

This paper presents a control system design strategy for a novel fuel cell - internal combustion engine hybrid power system. Dynamic control oriented models of the system components are developed. The transient behavior of the system components is investigated in order to determine control parameters and set-points. The analysis presented here is the first step towards development of a controller for this complex system. The results indicate various possibilities for control design and development. A control strategy is discussed to achieve system performance optimization.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

As noise concerns for snowmobiles become of greater interest for governing bodies, standards such as SAE J192 are implemented for regulation. Specific to this pass-by noise standard, and unlike many other pass-by tests, multiple non-standardized test surfaces are allowed to be used. Manufacturers must understand how the machines behave during these tests to know how to best improve the measured noise levels. Data is presented that identifies the contributions of different sources for different snowmobiles on various test surface conditions. Adaptive resampling for Doppler removal, frequency response functions and order tracking methods are implemented in order to best understand what components affect the overall measurement during the pass-by noise test.