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Positive displacement pumps are key components in automotive and hydraulic fluid systems, often serving as the primary power source and a major source of noise in both on-highway and off-highway vehicles. Specifically, gerotor pumps are widely utilized in vehicle coolant, lubricating, and other fluid systems for both conventional and electric powertrains. This study introduces a novel method for predicting noise in gerotor pumps by combining a Computational Acoustics (CA) approach with a 3D Computational Fluid Dynamics (CFD) approach, both implemented in the Simerics–MP+ code. The CFD simulation includes the detailed transient motion of the rotors (including related mesh motion) and models the intricate cavitation/air release phenomena at varying pump speeds. The acoustic simulation employs a Ffowcs–Williams Hawkings (FW–H) integral formulation to predict sound generation and propagation based on the detailed flow field predictions from the CFD model.

Springback is a serious problem in sheet metal stamping. It measures the difference between the final shape of the part and the shape of the forming die. Sheet metal forming simulation has made significant progress in predicting springback and several computer simulation codes are commercially available to predict and compensate for it in tool design. The accurate prediction of springback is important and there is a need to validate and verify those predictions with experimental results. Current validation techniques lack standardized procedures, require measurement fixtures that may impose unrealistic restraint on the part, require profiling equipment such as CMM or laser scanning and for the most part produce small springback which reduces measurement accuracy and increases experimental error. A benchmark test has been developed which addresses all these concerns and compares springback predictions by various numerical simulation codes with each other and with experimental results.

This paper presents a mechanical energy control volume analysis for incompressible flow around road vehicles using results from Detached Eddy Simulation Computational Fluid Dynamics calculations. The control volume approach equates the rate of work done by surface forces of the vehicle to (i) the rate of work and kinetic energy flux at the control volume boundaries (particularly in the vehicle wake) and (ii) the rate of energy loss in the domain. At the downstream control volume boundary, the wake terms can be divided into lift-induced and profile drag terms. The rate of energy loss in the domain can be used as a volumetric analog for drag (drag counts/m3, when normalized). This allows for a quantitative break down of the contributions of different flow features/regions to the overall drag force.

A model has been developed for estimating the oil vaporization rate from the cylinder liner of a reciprocating engine. The model uses input from an external cycle simulator and an external liner oil film thickness model. It allows for the change in oil composition and the change in oil film thickness due to vaporization. It also estimates how the passage of the compression and scraper rings combine with the vaporization to influence the steady-state composition of the oil layer in the upper ring pack. Computer model results are presented for a compression-ignition engine using a range of liner temperatures, several engine speeds, and two different oils. Vaporization is found to be highly dependent on liner temperature and steady-state oil composition. The steady-state oil composition near the top of the cylinder is found to be significantly different than the composition of the oil near the bottom of the cylinder.

Due to complexities of interaction among gears and crescent-shaped island, a crescent oil pump is one of the most difficult auto components to model using three dimensional Computational Fluid Dynamics(CFD) method. This paper will present a novel approach to address the challenges inherent in crescent oil pump modeling. The new approach is incorporated into the commercial pump design tool PumpLinx from Simerics, Inc.. The new method is applied to simulate a production crescent oil pump with inlet/outlet ports, inner/outer gears, irregular shaped crescent island and tip leakages. The pump performance curve, cavitation effects and pressure ripples are studied using this tool and will be presented in this paper. The results from the simulations are compared to the experiment data with excellent agreement. The present study shows that the proposed computational model is very accurate and robust and can be used as a reliable crescent pump design tool.

One of the issues in stamping of advanced high strength steels (AHSS) is the stretch bending fracture on a sharp radius (commonly referred to as shear fracture). Shear fracture typically occurs at a strain level below the conventional forming limit curve (FLC). Therefore it is difficult to predict in computer simulations using the FLC as the failure criterion. A modified Mohr-Coulomb (M-C) fracture criterion has been developed to predict shear fracture. The model parameters for several AHSS have been calibrated using various tests including the butter-fly shaped shear test. In this paper, validation simulations are conducted using the modified (M-C) fracture criterion for a dual phase (DP) 780 steel to predict fracture in the stretch forming simulator (SFS) test and the bending under tension (BUT) test. Various deformation fracture modes are analyzed, and the range of usability of the criterion is identified.

This paper investigates the use of an adaptive proportional-integral-derivative (APID) controller to reduce a combustion engine crankshaft speed pulsation. Both computer simulations and engine test rig experiments are used to validate the proposed control scheme. The starter/alternator (S/A) is used as the actuator for engine speed control. The S/A is an induction machine. It produces a supplemental torque source to cancel out the fast engine torque variation. This machine is placed on the engine crankshaft. The impact of the slowly varying changes in engine operating conditions is accounted for by adjusting the APID controller parameters on-line. The APID control scheme tunes the PID controller parameters by using the theory of adaptive interaction. The tuning algorithm determines a set of PID parameters by minimizing an error function. The error function is a weighted combination of the plant states and the required control effort.

Fuel power consumption for light duty vehicles has previously been shown to be proportional to vehicle traction power, with an offset for overhead and accessory losses. This allows the fuel consumption for an individual powertrain to be projected across different vehicles, missions, and drive cycles. This work applies the power-based model to commercial vehicles and demonstrates its usefulness for projecting fuel consumption on both regulatory and customer use cycles. The ability to project fuel consumption to different missions is particularly useful for commercial vehicles, as they are used in a wide range of applications and with customized designs. Specific cases are investigated for Light and Medium Heavy- Duty work trucks. The average power required by a vehicle to drive the regulatory cycles varies by nearly a factor 10 between the Class 4 vehicle on the ARB Transient cycle and the loaded Class 7 vehicle at 65 mph on grade.

Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Various computer models for occupant restraint systems are developed. The models simulate the vehicle interior, restraint system, and occupants in different crash scenarios. In order to improve the efficiency during the product development process, the model quality and its predictive capabilities must be ensured. In this research, an objective model validation metric is developed to evaluate the model validity and its predictive capabilities when multiple occupant injury responses are simultaneously compared with test curves. This validation metric is based on the probabilistic principal component analysis method and Bayesian statistics approach for multivariate model assessment. It first quantifies the uncertainties in both test and simulation results, extracts key features, and then evaluates the model quality.

In the automobile industry, the reliability and predictive capabilities of computer models for a dynamic system need to be assessed quantitatively. Quantitative validation allows engineers to assess and improve model reliability and quality objectively and ultimately lead to potential reduction in the number of prototypes built and tests. A good metric, which is essential in model validation, requires considering uncertainties in both testing and computer modeling. In addition, it needs to be able to compare multiple responses simultaneously, as multiple quantities are often encountered at different spatial and temporal points of a dynamic system. In this paper, a state-of-the-art validation technology is developed for multivariate complex dynamic systems by exploiting a probabilistic principal component analysis method and Bayesian statistics approach.

The abdomen is the second most commonly injured region in children using adult seat belts, but engineers are limited in their efforts to design systems that mitigate these injuries since no current pediatric dummy has the capability to quantify injury risk from loading to the abdomen. This paper develops a porcine (sus scrofa domestica) model of the 6-year-old human's abdomen, and then defines the biomechanical response of this abdominal model. First, a detailed abdominal necropsy study was undertaken, which involved collecting a series of anthropometric measurements and organ masses on 25 swine, ranging in age from 14 to 429 days (4-101 kg mass). These were then compared to the corresponding human quantities to identify the best porcine representation of a 6-year-old human's abdomen. This was determined to be a pig of age 77 days, and whole-body mass of 21.4 kg.

This paper focuses on the development of a framework of nonlinear finite element model validation for vehicle crash simulation. Integrated computational and test-based methods were discussed for validating computational models under physical, informational and model uncertaintes. Several methods were investigated to quantify transient time-domain data (functional data). The concept of correlation index was proposed to determine the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. The methodologies developed in this paper can also be used for CAE model updating, parameter tuning, and model calibration.

The present work deals with the development of a CFD method to simulate water fording/water wading for a passenger car. Water wading of automobiles in different water depths can lead to water ingestion into the air induction snorkel. This is unfavourable as this ingested water can cause the malfunction of the engine. This takes on an added importance when designing multi-terrain vehicles, where the interest could be in wading water effectively in many scenarios. The design of the snorkel, its position and height can be important in preventing water from entering the Air Induction System (AIS) and hence the engine. So, a water fording test of a vehicle is conducted to ensure the efficacy of the AIS snorkel in preventing water entering the AIS system. The ability of numerical simulations to effectively replicate testing performed in a long water tank is put to test in this paper. The CFD method development has been done using the commercial code, Simerics-MP+®.

The following paper highlights the results of a vehicle emission improvement program with emphasis on two main points: In the initial phase, various combinations of Pd and Pt-based three-way catalyst technologies were evaluated on a TLEV and a LEV calibrated vehicle in order to generate ULEV exhaust gas levels. One goal in this portion of the study was to achieve technical equivalence between a viable Pd-based technology and a newly developed Pt-based technology. A combination of the Pd- and Pt-based technologies was able to meet the ULEV and part of the ULEV II regulations in the test vehicle after a catalyst aging cycle that resembles 50,000 miles of vehicle driving. In the later phase, a mathematical algorithm based on the original TLEV and LEV vehicle data was developed in order to conduct computer modeling of the exhaust gas aftertreatment system. This algorithm described the kinetic behavior of the individual catalysts over a broad range of reaction conditions.

This paper reviews the structural assessment of a compact vehicle under frontal impact according to Federal Motor Vehicle Safety Standard (FMVSS) 204 Requirement – Steering Control Reward Displacement. The steering column intrusion analysis is made adding a collapsible joint under axial load. Injury analysis is assessed for the driver according to Federal Motor Vehicle Safety Standard 208 Requirement – Occupant Crash Protection – considering HIC (Head Injury Criterion), Chest Deceleration, Chest Deflection and Femur Load. Computational models have been built based on Ford Motor Company experience using MECALOG RADIOSS (FEA Code) and TNO - MADYMO (Occupant Code).

Powertrain Engineering Tool (PET) [1, 2, 3], developed at Ford Powertrain and Vehicle Research Laboratory, is a powertrain computer model that allows rapid development of preliminary powertrain component geometry, and evaluation of engine performance and friction. Based on specified design objectives such as engine torque, power and geometric constraints, PET calculates the powertrain component geometry by employing its integrated design rules and a non-linear SQP-based (Sequential Quadratic Programming) geometry optimizer. PET also generates parametric solid models of powertrain systems based on its integrated dynamic component assembly schemes and solid modeling database. The cranktrain system consists of high-speed moving and rotating components. Complex dynamic analysis is typically required to achieve optimum cranktrain component design. This paper discusses development of a systematic approach in the calculation of optimal cranktrain component geometry.

Battery packs for Hybrids, Plug-in Hybrids, and Electric Vehicles are assembled from a system of modules (sheets) with a tight sheet metal casing around them. Each module consists of an array of individual cells which vary in the composition of electrodes and separator from one manufacturer to another. In this paper a general procedure is outlined on the development of a constitutive and computational model of a cylindrical cell. Particular emphasis is placed on correct prediction of initiation and propagation of a tearing fracture of the steel can. The computational model correctly predicts rupture of the steel can which could release aggressive chemicals, fumes, or spread the ignited fire to the neighboring cells. The initiation site of skin fracture depends on many factors such as the ductility of the casing material, constitutive behavior of the system of electrodes, and type of loading.

This paper presents a design for reliability methodology based on the DfSS DCOV process, applied to the development of a cost effective timing chain drive for a four cylinder diesel engine. A CAE model for the timing chain drive was used to study the distribution of the chain loads, which provided an essential input both for the concept selection stage and for the development of a reliability model for the timing chain. A DoE study on the CAE model aimed at investigating the significant factors for chain load variability lead to a reliability improvement achieved by reducing the variability in the chain load through revising the tolerances for the sprocket tooth profile. The paper demonstrates the efficiency of the process and the usefulness of computer simulation in achieving reliability and robustness enhancement while reducing design and development time and costs.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Within the automotive industry, more and more of this validation testing is being performed using Hardware-in-the-Loop (HIL) simulators to automate the extensive test sequences. A HIL simulation typically mates the physical PCS to a closed-loop real time computer simulation of a powertrain. Interfacing the physical PCS hardware to a powertrain simulation requires the HIL simulator to have extensive signal input/output (I/O) electronics and simulated actuator electrical loading.

The primary coating layer that inhibits salt spray induced corrosion on vehicle bodies is electrocoat. The application of electrocoat involves the electrodeposition of a polymer film on all metallic components of the vehicle body after body construction. Particularly challenging in the electrocoat process is the deposition of the coating in recessed areas of the vehicle due to material and electrical current access constraints to those regions. Currently the verification of correct electrocoat coverage requires the use of costly tear-down prototypes. A simulation tool, called EPD, has been developed that predicts the electrocoat coverage on the full vehicle body. The tool allows engineers to identify areas where there may be issues with electrocoat coverage and to see the effect of vehicle design or process modifications on coverage. A challenge in the development of any simulation tool is computational speed.