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Simulation has become an integral part in the design and development of an automotive air-conditioning (AC) system. Simulation is widely used for both system level and component level analyses and are carried out with one-dimensional (1D) and Computational Fluid Dynamics (CFD) tools. This paper describes a 1D approach to model refrigerant loop and vehicle cabin to simulate the soak and cool down analysis. Soak and cool down is one of the important tests that is carried out to test the performance of a heating, ventilation and air-conditioning (HVAC) system of a vehicle. Ability to simulate this cool down cycle is thus very useful. 1D modeling is done for the two-phase flow through the refrigerant loop and air flow across the heat exchangers and cabin with the commercial software AMESim. The model is able to predict refrigerant pressure and temperature inside the loop at different points in the cycle.

A body mount joint is a typical clamped joint that is under severe loading conditions, due to its structural function services as a gateway of load path between body and frame of an automotive vehicle. Stresses/strains on durability concerned components at the joint cannot be captured accurately by using the pseudo stress analysis approach because of the complexity of stress state generated by the pre-stress from clamp load, contacts between the components and nonlinear material properties. In this paper, development of a technique for fatigue life estimation of the joint is described in detail.

Edge cracking is one of the major formability concerns in advanced high strength steel (AHSS) stamping. Although finite element analysis (FEA) together with the Forming Limit Diagram has been widely used, it has not effectively predicted edge cracking. Primary problems in developing a methodology to insure that parts are safe from edge cracking are the lack of an effective failure criterion and a simple and accurate measurement method that is not only usable in both die tryout and production but also can be verified by finite element analysis. The intent of this study is to develop a methodology to ensure that parts with internal cutouts, such as a body side panel can be produced without edge cracking. During tryout and production, edge cracking has traditionally been detected by visual examination, but this approach is not adequate for ensuring freedom from edge cracking.

The air induction system (AIS), which provides clean air to the engine for combustion, is very important for engine acoustics. A practical CAE procedure to predict AIS inlet noise is presented in this paper. GT-Power, a commercially available software program can be used to simulate the engine performance and predict air induction noise. The accuracy of GT-Power is dependent on many variables, such as: proper duct discretization size, proper number of flow splits to model the air box and the capturing of the correct resonator geometry for tuning frequency. Since GT-Power is based on a 1D assumption, several iterations need be performed to model the complex AIS components, such as, irregular shaped air box, resonator volume, porous ducts and perforated pipes. Because of this, the GT-Power AIS model needs to be correlated to test data using transmission loss data.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

With the increased market share of electric vehicles, the demand for energy-efficient routing algorithms specifically optimized for electric vehicles has increased. Traditional routing algorithms are focused on optimizing the shortest distance or the shortest time in finding a path from point A to point B. These traditional methods have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power limits, battery capacity limits, and vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present an ant colony based, energy-efficient routing algorithm that is optimized and designed for electric vehicles. Simulation results show improvements in the energy consumption of electric vehicles when applied to a start-to-destination routing problem.

Improvements to 1D engine modeling accuracy and computational speed have led to greater reliance on this simulation technology during the engine development process. The benefits of modeling show up in many ways: increased simulation iterations for better optimization, reduction in prototype hardware iterations, reduction in program timing and overall cost. In this study a 1D GT-Power model of a turbocharged engine system was used to assist in the initial design phase and throughout the program. The model was developed using Chrysler Group LLC proprietary modeling features for predictive combustion and knock event prediction. In all stages of this project the model's accuracy was improved through regular correlation with dynamometer data. This paper mainly focuses on engine compression ratio selection, turbocharger selection, and cycle-to-cycle variation/cylinder-to-cylinder variation reduction through the combination of 1D GT-Power model optimization and dynamometer tests.

Fatigue analysis in the time domain using the rainflow cycle counting algorithm is considered the most accurate method for estimating damage. Dirlik's method has been found to be very accurate for damage estimation in the frequency domain. Previous studies have demonstrated the usefulness of Dirlik's method for ocean engineering and wind turbines but few have shown how well Dirlik performs in automotive applications. This study compares Dirlik's method with the rainflow cycle counting and with other frequency domain methods. The study analyzes measured data for an automotive component subjected to five test track load conditions. In addition, fourteen of Dirlik's original spectra and seven additional spectra which combine sine and random spectra are studied. It was found that Dirlik's method predicts more damage than the rainflow cycle counting method when applied to the original data used in creating the method.

There is a continual need to apply heat treatment processes in innovative ways to optimize material performance. One such application studied in this research is carburizing followed by austempering of low carbon alloy steels, AISI 8620, AISI 8822 and AISI 4320, to produce components with high strength and toughness. This heat treatment process was applied in two steps; first, carburization of the surface of the parts, second, the samples were quenched from austenitic temperature at a rate fast enough to avoid the formation of ferrite or pearlite and then held at a temperature just above the martensite starting temperature to partially or fully form bainite. Any austenite which was not transformed during austempering, upon further cooling formed martensite or was present as retained austenite.

The performance of door assembly is very significant for the vehicle design and door sag/set is one of the important attribute for design of door assembly. This paper provides an overview of conventional approach for door sag/set study based on door-hinge-BIW assembly (system level approach) and its limitation over new approach based on subassembly (subsystem level approach). The door sag/set simulation at system level is the most common approach adopted across auto industry. This approach evaluates only structural adequacy of door assembly system for sag load. To find key contributor for door sagging is always been time consuming task with conventional approach thus there is a delay in providing design enablers to meet the design target. New approach of door sag/set at “subsystem level” evaluates the structural stiffness contribution of individual subsystem. It support for setting up the target at subsystem level, which integrate and regulate the system level performance.

Recently, the Two-Measurement correction method that yields a wake distortion adjustment for open jet wind tunnels has shown promise of being able to adjust for many of the effects of non-ideal static pressure gradients on bluff automotive bodies. Utilization of this adjustment has shown that a consistent drag results when the vehicle is subjected to the various gradients generated in open jet wind tunnels. What has been lacking is whether this consistent result is independent of the other tunnel interference effects. The studies presented here are intended to fill that gap and add more realistic model and wind tunnel conditions to the evaluations of the performance of the two-measurement technique. The subject CFD studies are designed to greatly reduce all wind tunnel interference effects except for the variation of the non-linear static pressure gradients. A zero gradient condition is generated by simulating a solid wall test section with a blockage ratio of 0.1%.

Establishing data adjustments that will give an interference free result for bluff bodies in automotive wind tunnels has been pursued for at least the last 45 years. Recently, the Two-Measurement correction method that yields a wake distortion adjustment for open jet wind tunnels has shown promise of being able to adjust for many of the effects of non-ideal static pressure gradients on bluff automotive bodies. Utilization of this adjustment has shown that a consistent drag results when the vehicle is subjected to the various gradients generated in open jet wind tunnels. What has been lacking is whether this consistent result is independent of the other tunnel interference effects. The studies presented here are intended to fill that gap on the performance of the two-measurement technique. The subject CFD studies are designed to eliminate all wind tunnel interference effects except for the variation of the (linear) static pressure gradient.

During the vehicle development process, dimensional variation simulation modeling has been applied extensively to estimate the effects of build variation on the final product. Traditional variation simulation methods analyze the tolerance inputs of structural components, but do not account for any compliance effects due to stiffness variation in tuning components, such as bushings, springs, isolators, etc., since both product and process variation are simulated based on rigid-body assumptions. Vehicle performance objectives such as ride and handling (R&H) often involve these compliance metrics. The objective of this paper is to present a method to concurrently simulate the tolerance from the structural parts as well as the variability of compliance from the tuning components through an integration package. The combination of these two highly influential effects will allow for a more accurate prediction and assessment of vehicle performance.

Springback is a major phenomenon in sheet metal forming process that has to be tackled to achieve the desired product with greater dimensional accuracy. Springback occurs due to elastic recovery of sheet metal after the stamping process. The automobile industry is gradually moving from use of conventional steels to advanced high strength steels (AHSS) for their light weight and greater strength properties; however AHSS possesses greater springback effect due to higher elastic limit which proves to be difficult to deal with the springback effect. Hence it is imperative that the counter measures are taken to minimize the springback effect. The purpose of the study is to showcase various factors that influence the prediction of springback phenomenon. In this study the simulation results are compared with scanned data of actual stamped panels and their deviation is studied.

To meet the 2010 diesel engine emission regulations, an aftertreatment system was developed to reduce HC, CO, NOx and soot. In NOx reduction, a baseline SCR module was designed to include urea injector, mixing decomposition tube and SCR catalysts. However, it was found that the baseline decomposition tube had unacceptable urea mixing performance and severe deposit issues largely because of poor hardware design. The purpose of this article is to describe necessary development work to improve the baseline system to achieve desired mixing targets. To this end, an emissions Flow Lab and computational fluid dynamics were used as the main tools to evaluate urea mixing solutions. Given the complicated urea spray transport and limited packaging space, intensive efforts were taken to develop pre-injector pipe geometry, post-injector cone geometry, single mixer design modifications, and dual mixer design options.

Physical modeling has been used by the industry to improve development time and produce a quality product. In this paper, we will describe two methods used in system control to take advantage of the physical model. One method describes a complete transmission physical model with a full system control utilizing co-simulation techniques. Data will be presented, and comparison to vehicle data will be conducted and verified. The second method will illustrate how to utilize the physical model to improve system design and modification. In this method, vehicle data will be used as inputs to the model, the model output will be verified against vehicle output data. The two methods are excellent tools for the Design For Six Sigma process (DFSS design).

A process to create a vehicle resistance curve based on airflow predictions using Computational Fluid Dynamics (CFD) simulation technique is presented. 1-dimensional engine cooling system simulation tool KULI is used to compute the coefficients of vehicle resistance curve. A full factorial Design of Experiment (DOE) established the relationship between the coefficients and the sum of absolute difference between KULI and CFD predictions. The NLPQL optimization routine is used to accurately predict the coefficients so that sum of absolute difference between KULI and CFD predictions is minimized.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

Corrosion tendency is one of the major inhibitors for increased use of magnesium alloys in automotive structural applications. Moreover, systematic or standardized methods for evaluation of both general and galvanic corrosion of magnesium alloys, either as individual components or eventually as entire subassemblies, remains elusive, and receives little attention from professional and standardization bodies. This work reports outcomes from an effort underway within the U.S. Automotive Materials Partnership - ‘USAMP’ (Chrysler, Ford and GM) directed toward enabling technologies and knowledge base for the design and fabrication of magnesium-intensive subassemblies intended for automotive “front end” applications. In particular, subassemblies consisting of three different grades of magnesium (die cast, sheet and extrusion) and receiving a typical corrosion protective coating were subjected to cyclic corrosion tests as employed by each OEM in the consortium.

In this paper, thermal models are developed based on experimental test data, and the physics of thermal systems. If experimental data is available, the data can be fitted to mathematical models that represent the system response to changes in its input parameters. Therefore, empirical models which are based on test data are developed. The concept of time constant is presented and applied to development of transient models. Mathematical models for component temperature changes during transient vehicle driving conditions are also presented. Mathematical models for climate control system warm up and cool-down are also discussed. The results show the significance of adopting this concept in analysis of vehicle test data, and in development of analytical models. The developed models can be applied to simulate the system or component response to variety of changes in input parameters. As a result, significant testing and simulation time can be saved during the vehicle development process.