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Laser lap welding quality is a non-linear response based on a host of categorical and numeric material and process variables. This paper describes a Grammatical Evolution approach to the structure identification of the laser lap welding process and compares its performance with linear regression and a neuro-fuzzy inference system.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

A Computational Fluid Dynamics (CFD) method, combined with a dynamic modeling technique is introduced to study the flow and performance of automotive hydraulic dampers / shock absorbers. The flow characteristics of components obtained by CFD are lied to a dynamic modeling package to predict the damping force. The component CFD analysis showed unique features of flow pattern, discharge coefficients, and pressure distribution for various shock absorber components. A dynamic damper model is constructed by integrating the hydraulic system with component flow information provided by CFD. The modeling results agree with test data well. It is shown that automotive shock absorber performance can be simulated accurately without physical testing.

The ever-growing number of interacting electronic vehicle control systems requires new control algorithms to manage the increasing system complexity. The paper describes a torque-based engine control architecture which uses a central torque demand variable to control the regulating qualities. This torque demand variable is the result of the coordination of all torque requests throughout the vehicle. Therefore, the system manages the whole process of prioritizing the torque demands of the different subsystems such as electronic stability or transmission control. If further vehicle subsystems have to be integrated, the structure can be easily extended as the torque demand variable is the only interface between the engine control algorithms and other vehicle control systems.

Vehicle thermal protection is an important aspect of the overall vehicle development process. It involves optimizing the exhaust system routing and designing heat shields to protect various components that are in near proximity to the exhaust system. Reduced time to market necessitates an efficient process for thermal protection development. A robust procedure that utilizes state of the art CFD simulation techniques proactively during the design phase is described. Simulation allows for early detection of thermal issues and development of countermeasures several months before prototype vehicles are built. Physical testing is only used to verify the thermal protection package rather than to develop heat shields. The new procedure reduces the number of physical tests and results in a robust, efficient methodology.

This paper summarizes the major activities of CFD study on rear window buffeting of production vehicles during the past two years at DaimlerChrysler. The focus of the paper is the attempt to find suitable solutions for buffeting suppression using a developed procedure of CFD simulation with commercial software plus FFT acoustic post-processing. The analysis procedure has been validated using three representative production vehicles and good correlation with wind tunnel tests has been attained which has gained the confidence in solving the buffeting problem. Several attempts have been proposed and tried to find solution for buffeting reduction. Some of them are promising, but feasibility and manufacturability still need discussion. In order to find suitable solution for buffeting reduction, more basic research is necessary, more ideas should be collected, and more joint efforts of CFD and testing are imperative.

Fluid flow, temperature prediction, thermal response and light-off behavior of the catalytic converter were investigated using Computational Fluid Dynamics (CFD), combined with a conjugate heat transfer and a chemical reaction model. There are two objectives in this study: one to predict the maximum operation temperature for appropriate materials selection; and the other, to develop a numerical model which can be adjusted to reflect changes in the catalyst/washcoat formulation to accurately predict effects on the flow, temperature and light-off behavior. Temperature distributions were calculated for exhaust gas, catalyzed substrate, mounting mat and converter skin. Converter shell skin temperature was obtained for different mat materials. By changing reactant mass concentrations and noble metal loading, the converter light-off behavior, thermal response and temperature distributions were changed.

The flow within the disengaged wet clutch packs of an automatic transmission has been simulated as a three-dimensional, steady-state, two-phase flow using the commercial computational fluid dynamics (CFD) code FLUENT. The flow within a clutch with ungrooved friction plates was first solved for validating the CFD model, followed by a simulation of the flow within a clutch with grooved friction plates. A group of dimensionless variables have been established for mathematically modeling the drag torque and power loss in clutch packs. The effects of rotating speed of friction plate, pack clearance, and flow rate on drag torque and power loss have been studied.

Variable Valve Actuation (VVA) technology provides high potential in achieving high performance, low fuel consumption and pollutant reduction. However, more degrees of freedom impose a big challenge for engine characterization and calibration. In this study, a simulation based approach and optimization framework is proposed to optimize the setpoints of multiple independent control variables. Since solving an optimization problem typically requires hundreds of function evaluations, a direct use of the high-fidelity simulation tool leads to the unbearably long computational time. Hence, the Artificial Neural Networks (ANN) are trained with high-fidelity simulation results and used as surrogate models, representing engine's response to different control variable combinations with greatly reduced computational time. To demonstrate the proposed methodology, the cam-phasing strategy at Wide Open Throttle (WOT) is optimized for a dual-independent Variable Valve Timing (VVT) engine.

Cam-phasing is increasingly considered as a feasible Variable Valve Timing (VVT) technology for production engines. Additional independent control variables in a dual-independent VVT engine increase the complexity of the system, and achieving its full benefit depends critically on devising an optimum control strategy. A traditional approach relying on hardware experiments to generate set-point maps for all independent control variables leads to an exponential increase in the number of required tests and prohibitive cost. Instead, this work formulates the task of defining actuator set-points as an optimization problem. In our previous study, an optimization framework was developed and demonstrated with the objective of maximizing torque at full load. This study extends the technique and uses the optimization framework to minimize fuel consumption of a VVT engine at part load.

A stochastic simulation based on the Monte-Carlo method was developed to re-target gap bulk density (GBD) in ceramic catalytic converters. The combined effect of manufacturing tolerances, shell spring back and thermal expansion was analyzed by this model. Shell spring back during the canning process was calculated using Finite Element Analysis (FEA). Thermal shell expansion was obtained using can deformation data from the Key-Life Test (KLT). An example of optimized GBD that provides a robust and manufacturable design is also presented.

A stochastic simulation based on the Monte-Carlo method was developed to study the effect of substrate, mounting mat and converter shell dimensional tolerances on the converter manufacturing process. Results for a stuffed converter with nominal gap bulk density (GBD) 1.00 g/cm3 show an asymmetric probability density function ranging from 0.90 to 1.13 g/cm3. Destructive and non-destructive GBD measurements on oval and round production converters show close correlation with the Monte-Carlo model. Several manufacturing options offering tighter GBD control based on component sorting and matching are described. Improvements ranging from 28% and 64% in GBD control are possible.

Combustion feedback using cylinder pressure sensors, ion current sensors or alternative sensing techniques is actively under investigation by the automotive industry to meet future legislative emissions requirements. One of the drawbacks of many rapid prototyping engine management systems is their available analog interfaces, often limited to 10-12 bits with limited bandwidth, sampling rate and very simple anti-aliasing filters. Processing cylinder pressure or other combustion feedback sensors requires higher precision, wider bandwidths and more processing power than is typically available. For these reasons, Ricardo in collaboration with GM Research has developed a custom, high precision analog input subsystem for the rCube rapid prototyping control system that is specifically targeted at development of combustion feedback control systems.

In internal combustion engines, liquid fuel injection is one of the most prevalent means of fuel delivery and air-fuel mixture preparation. The behavior of the fuel spray and wall film is a key factor in determining air-fuel mixing and hence combustion and emissions. A comprehensive model for the liquid fuel spray has been developed in conjunction with the one-dimensional gas flow code WAVE. The model includes droplet dynamics and evaporation, spray-wall impingement, wall film dynamics and evaporation. The fuel injector can be placed in the manifold, inlet port or cylinder. Liquid fuel droplets are injected with a prescribed size distribution, and their subsequent movement and vaporization are modeled via the discrete particle approach, frequently used in multi-dimensional CFD codes. This approach ensures conservation of mass, momentum and energy between the gas and liquid phases.

The use of composite materials in the automotive industry has become increasingly widespread. With this increase in use, techniques for non-destructive testing (NDT) have become more and more important. Various optical NDT inspective methods such as holography, moiré techniques, and shearography have been used for material testing. Among these methods, shearography appears to be most practical. Shearography has a simple optical setup due to its “self-referencing” system, and it is relatively insensitive against rigid-body motions. Measurements of displacement derivatives, and thus strain directly, rather than the displacement itself is achieved through this method. Therefore shearography detects defects in objects by correlating anomalies of strain which are usually easier than correlating the anomalies of the displacement itself, as in holography. To date shearography has shown potential as a NDT tool for identifying defects in small structures.

In this report, the DCX Stress Lab and the Tool Development & Test Support groups investigated automating a resonant bending crankshaft fatigue test. Fatigue testing, in general, is a laborious process since many samples are needed for analysis. This makes development cost and speed dependant on the component test efficiency. In the case of crankshaft resonant bending testing, both cost and speed are influenced by the manual feedback operation needed to run the current procedure. In order to increase the efficiency of this process, this project sought to automate the following tasks: maintaining the load on the part, reacting to resonance changes in the part, mapping resonance changes, logging the number of cycles, and discerning resonance frequency shift failure modes objectively.

A project was undertaken to demonstrate an engine stop/start at idle system utilizing a 12 volt Belt driven Starter Generator (BSG). The system was developed on a production four cylinder vehicle to determine emissions, driveability, and fuel economy impact.

Current engine development processes typically involve extensive steady-state and simple transient testing in order to characterize the engine's fuel consumption, emissions, and performance based on several controllable inputs such as throttle, spark advance, and EGR. Steady-state and simple transient testing using idealistic load conditions alone, however, is no longer sufficient to meet powertrain development schedule requirements. Mapping and calibration of an engine under transient operation has become critically important. And, independent engine development utilizing accelerated techniques is becoming more attractive. In order to thoroughly calibrate new engines in accelerated fashion and under realistic transient conditions, more advanced testing is necessary.

Tire stiffness can have a significant effect on the spindle and component loads. While its’ effect on the component loads may show a different trend. This paper deals with data acquisition loads using Wheel Force Transducer (WFT) with 17 inch, 18 inch and 20 inch tires and shows how the spindle loads changed for different tire. These loads are applied on the analytical suspension model to generate both component and the body attachment loads. Some of the measured channels are correlated for all the wheel sizes for multiple events to ensure the confidence in the model. It is found that even if spindle loads are increased with tire stiffness, the component loads do not necessarily show a similar trend. This paper studies why higher spindle forces do not always give higher component loads and what are the possible alternatives one may look into to shortlist or select one set of loads over the other.

Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) networks within the Intelligent Transportation System (ITS) lead to safety and mobility improvements in vehicle road traffic. This paper presents case studies that support the realization of the ITS architecture as an evolutionary process, beginning with driver information systems for enhancing feedback to the users, semi-autonomous control systems for improved vehicle system management, and fully autonomous control for improving vehicle cooperation and management. The paper will also demonstrate how the automotive, telecom, and data and service providers are working together to develop new ITS technologies.