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When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

The performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

The road profile has been shown to have significant effects on various vehicle conditions including ride, handling, fatigue or even energy efficiency; as a result it has become a variable of interest in the design and control of numerous vehicle parts. In this study, an integrated state estimation algorithm is proposed that can provide continuous information on road elevation and profile variations, primarily to be used in active suspension controls. A novel tire instrumentation technology (smart tire) is adopted together with a sensor couple of wheel attached accelerometer and suspension deflection sensor as observer inputs. The algorithm utilizes an adaptive Kalman filter (AKF) structure that provides the sprung and unsprung mass displacements to a sliding-mode differentiator, which then yields to the estimation of road elevations and the corresponding road profile along with the quarter car states.

Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

A graphical user interface (GUI) toolbox called Vehicle System Simulator (VSS) is developed in MATLAB to ease the use of this vehicle model and hopefully encourage its widespread application in the future. This toolbox uses the inherent MATLAB discrete-time solvers and is mainly based on Level-2 s-function design. This paper describes its built-in vehicle dynamics model based on multibody dynamics approach and nonlinear tire models, and traction/braking control systems including Cruise Control and Differential Braking systems. The built-in dynamics model is validated against CarSim 8 and the simulation results prove its accuracy. This paper illustrates the application of this new MATLAB toolbox called Vehicle System Simulator and discusses its development process, limitations, and future improvements.

Internal combustion (IC) engines fueled by hydrogen are among the most efficient means of converting chemical energy to mechanical work. The exhaust has near-zero carbon-based emissions, and the engines can be operated in a manner in which pollutants are minimal. In addition, in automotive applications, hydrogen engines have the potential for efficiencies higher than fuel cells.[1] In addition, hydrogen engines are likely to have a small increase in engine costs compared to conventionally fueled engines. However, there are challenges to using hydrogen in IC engines. In particular, efficient combustion of hydrogen in engines produces nitrogen oxides (NOx) that generally cannot be treated with conventional three-way catalysts. This work presents the results of experiments which consider changes in direct injection hydrogen engine design to improve engine performance, consisting primarily of engine efficiency and NOx emissions.

Tappet/bore friction and torque at the camshaft were measured for a direct acting bucket tappet using a cam/tappet friction apparatus. Tappet/bore and cam/tappet friction torque and friction coefficient as a function of cam angle were derived from those measurements. The results showed that, for the particular geometry tested, tappet/bore friction torque accounted for about 13% of the total cam/tappet/bore friction torque at 250 cam rpm. This fraction decreased with increasing speed. Tappet bore friction was greatest at about ± 40 degrees of cam angle, where side loads on the tappet bore were highest. In contrast, earlier results for a center pivot rocker arm design showed tappet bore friction to be negligible.

This paper presents engine dynamometer testing and modeling analysis of ethanol compared to gasoline at part load conditions where the engine was not knock-limited with either fuel. The purpose of this work was to confirm the efficiency improvement for ethanol reported in published papers, and to quantify the components of the improvement. Testing comparing E85 to E0 gasoline was conducted in an alternating back-to-back manner with multiple data points for each fuel to establish high confidence in the measured results. Approximately 4% relative improvement in brake thermal efficiency (BTE) was measured at three speed-load points. Effects on BTE due to pumping work and emissions were quantified based on the measured engine data, and accounted for only a small portion of the difference.

Oscillating heat transfer is a fundamental phenomenon occurring in Stirling machines and IC engines. A group of relevant dimensionless numbers which characterize this problem is identified by dimensional analysis. The convective heat transfer coefficient, or Nusselt number, is a function of the Reynolds number, the Prandtl number, plus the dynamic Reynolds number and the dimensionless amplitude, when compressibility is not considered. The case for compressible fluid is more complicated. An experiential study confirms above analysis and results in a nonlinear longitudinal fluid temperature distribution in the pipe. The history effect is found to affect the heat transfer rate remarkably. A correlation equation for Nusselt number is obtained by multivariate analysis.

Fuel-air mixing in a direct-injection SI engine was studied to further improve full-load torque output. The fuel-injection location of DI vs. PFI results in different heat sources for fuel evaporation, hence a DI engine has been found to exhibit higher volumetric efficiency and lower knocking tendency, resulting in higher full-load torque output [1]. The ability to change injection timing of the DI engine affects heat transfer and mixture temperature, hence later injection results in lower knocking tendency. Both the higher volumetric efficiency and the lower knocking tendency can improve engine torque output. Improving volumetric efficiency requires that the fuel is injected during the intake stroke. Reducing knocking tendency, in contrast, requires that the fuel is injected late during the compression stroke. Thus, a strategy of split injection was proposed to compromise the two competing requirements and further increase direct-injection SI engine torque output.

In recent years, rapid and significant advances in fuel cell technology, together with advances in power electronics and control methodology, has enabled the development of high performance fuel cell powered electric vehicles. A key advance is that the low temperature (80°C) proton-exchange-membrane (PEM) fuel cell has become mature and robust enough to be used for automotive applications. Apart from the apparent advantage of lower vehicle emission, the overall fuel cell vehicle static and dynamic performance and power and energy efficiency are critically dependent on the intelligent design of the control systems and control methodologies. These include the control of: fuel cell heat and water management, fuel (hydrogen) and air (oxygen) supply and distribution, electric drive, main and auxiliary power management, and overall powertrain and vehicle systems.

Rapid Prototyping, Fabrication and Tooling is a process that blends a series of technologies (machines, tools, and methods) capable of generating physical objects directly from a CAD database. The process dramatically reduces the time spent during product development by allowing for fast visualization, verification, iteration, optimization, and fabrication of parts and tools. Many new techniques of tooling have been and are being developed by using rapid fabricated parts. These are having a dramatic impact on both timing and costs throughout the automotive industry. One area that these methods can be utilized to their full potential is motorsports. Of particular interest is the growing use of bridge tooling to provide first article through production intent parts that promote cost effective changes.

There are a number of benefits from Ford Motor Company's participation in motorsports. This paper will describe how an engineering team developed a CAE process to assist in the design of a race car to meet impact requirements, with the technology transfer benefit of improved impact performance of composite structures in passenger cars. In 1997/98, a CAE process was developed and applied in the design and test of Formula One race car composite impact structures. For this particular engineering effort, a Ford proprietary software program, COMP-COLLAPSE, was the primary analysis tool that was utilized to successfully predict impact performance. As a result, COMP-COLLAPSE was used extensively in the design of race car composite impact structures. There were two beneficiaries from this effort: Race Vehicles: Improved vehicle impact performance as well as design improvement in crush efficiency, packaging, weight, and manufacturing.

FMVSS 201U, interior head impact performance is required for each new vehicle program. In the laboratory, testing to this requirement includes laying out the target locations, defining additional robustness target points based on targeting variation, positioning the Free Motion Headform (FMH), impacting each location with the headform and measuring HIC values. The tests may involve some conservative strategies and robustness studies to protect for the worst-case scenarios, where an impact might produce the highest HIC(d) within variations of impact conditions. In order to automate the best practices and procedures for both laboratory and CAE, a process automation environment was used to develop the Interior Head Impact Toolkit (IHIT, pronounced as i-hit). The IHIT software addresses several key testing processes and is grouped into four modules.

This paper presents an enhanced Bayesian based model validation method together with probabilistic principal component analysis (PPCA). The PPCA is employed to address multivariate correlation and to reduce the dimensionality of the multivariate functional responses. The Bayesian hypothesis testing is used to quantitatively assess the quality of a multivariate dynamic system. Unlike the previous approach, the differences between test and CAE results are used for dimension reduction though PPCA and then to assess the model validity. In addition, physics-based thresholds are defined and transformed to the PPCA space for Bayesian hypothesis testing. This new approach resolves some critical drawbacks of the previous method and provides desirable properties of a validation method, e.g., symmetry. A dynamic system with multiple functional responses is used to demonstrate this new approach.

This work presents a statistical approach for simulation based on Monte Carlo method. As an exercise of the method a CAE vehicle dynamics model was specifically created to evaluate the likelihood to meet a given target driving a maneuver for given inputs variations. In the exercise, three different inputs were chosen as stochastic inputs (also called noise factors) and all relevant information about their statistics has been raised, based in components information. The chosen inputs are: front/rear dampers curves, front/rear ride heights and tire surface temperature. A brief description of the Monte Carlo technique is presented. The choice of this method is due to the reduced number of simulations required to have a given accuracy in comparison with other approaches, especially for multivariable system. As output variable for the exercise, the tire patch height was chosen and the resulting probability density function of it is presented.

The behavior knowledge of the vehicle on uphill maneuvers - startability on grade, is an important metric for sizing powertrain components, such as the engine torque, clutch, first and reverse gear ratios, final drive and tire sizes. During the uphill maneuver, all components of the powertrain are subject to efforts that determine the vehicle performance in this condition. The analysis of this maneuver, for a front-wheel-drive vehicle, is evaluated in this article, through a correlation of a computer program developed in Matlab-Simulink, with experimental measurements performed on the vehicle at the track, becoming an important tool for analysis of passenger vehicles subject to these conditions present on Brazilian streets.

As automotive manufacturers continue to increase their use of thermoplastics for interior and exterior components, there is a likelihood of squeaks due to material contacts. To address this issue, Ford's Body Chassis NVH Squeak and Rattle Prevention Engineering Department has developed a tester that can measure friction, and any accompanying audible sound, as a function of sliding velocity, normal load, surface roughness, and environmental factors. The Ford team has been using the tester to address manufacturing plant issues and to develop a database of polymeric material pairings that will be used as a guide for current and future designs to eliminate potential noise concerns. Based upon the database, along with a physical property analysis of the various plastic (viscoelastic) materials used in the interior, we are in the process of developing an analytical model which will be a tool to predict frictional behavior.

Vehicle body with aluminum riveted construction instead of steel welded one will be a big challenge to NVH. In this paper, aluminum and steel rails with the dimensions similar to the rear rail portion of a typical mid-size sedan were fabricated. Rivets were used to assemble the aluminum rails while welds were used to assemble the steel rails. Adhesive, rivet/weld spacing, and rivet/weld location were the three major factors to be studied and their impact on NVH were investigated. The DOE matrix was developed using these three major factors. Modal tests were performed on those rails according to the DOE matrix. The FEA models corresponding to the hardware were built. CAE modal analysis were performed and compared with test data. The current in-house CAE modeling techniques for spot weld and adhesive were evaluated and validated with test data.

While a Ni-MH battery has good performance properties, such as a high power density and no memory effect, it needs a powerful thermal management system to maintain within the required narrow thermal operating range for the 42V HEV applications. Inappropriate battery temperatures result in degradation of the battery performance and life. For the battery cooling system, air is blown into the battery pack. The exhaust is then vented outside due to potential safety issues with battery emissions. This cooling strategy can significantly impact fuel economy and cabin climate control. This is particularly true when the battery is experiencing frequent charge and discharge of high-depths in extreme hot or cold weather conditions. To optimize performance and life of HEV traction batteries, the battery cooling design must keep the battery operation temperature below a maximum value and uniform across the battery cells.