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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.

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.

Lithium-ion batteries (LIBs) have been widely used as the energy storage system in plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) due to their high power and energy density and long cycle life compared to other chemistries. However, LIBs are sensitive to operating conditions, including temperature, current demand and surface pressure of the cell. One very well understood phenomenon of lithium-ion battery is the reduction in charge capacity over time due to cycling and storage commonly known as capacity fade. Considering the need for predicting the behavior of an aged cell and the need for estimating battery useful life for warranty purpose, it is crucial to predict the capacity fade with reasonable accuracy. To accommodate this need, a novel cell level empirical aging model is built based on storage tests and cycle tests. The storage test captures the calendar aging of the lithium-ion cell while the cycle test estimates the cycle aging of the cell.

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.

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.

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.

The Fischer-Tropsch (FT) process can be used to synthesize diesel fuels from a variety of energy sources, including coal, natural gas and biomass. Diesel fuels produced from the FT process are essentially sulfur-free, have very low aromatic content, and have excellent ignition characteristics. Because of these favorable attributes, FT diesel fuels may offer environmental benefits over transportation fuels derived from crude oil. Previous tests have shown that FT diesel fuel can be used in unmodified engines and have been shown to lower regulated emissions. Whereas exhaust emissions reductions from these previous studies have been impressive, this paper demonstrates that far greater exhaust emissions reductions are possible if the diesel engine is optimized to exploit the properties of the FT fuels. A Power Stroke 7.3 liter turbocharged diesel engine has been modified for use with FT diesel.

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.

The damping loss factor of a structural panel plays a significant role in its vibro-acoustic performance. The objective of this paper is to present a new procedure for evaluating the damping loss factors of these panels. Traditionally, the damping loss factors are determined by using the decay rate of the decay curves which are experimentally obtained from the structure. However, this is time consuming and the accuracy is limited by fluctuations in the decay curve. In this paper, the envelope signal of each decay curve is determined through its Hilbert transform, and the remaining small fluctuations in the envelope signal are further smoothed out by the exponential average method. Finally, the damping loss factor is estimated based on the smoothed envelope signal of each decay curve. A computer program has been developed to implement this procedure. It is shown that this procedure improves both accuracy and efficiency of the decay rate method for estimating damping loss factor.

This investigation evaluated different pressure transducers in one cylinder to examine the combustion measurement differences between them simultaneously. There were a total of eleven transducers ranging in both diameter and type of transducer (piezo-electric, piezoresistive, and optical). Furthermore, the sensors differed in the methodology for minimizing signal distortion due to temperature. This methodology could take the form of various size mounting passages, heat shields, watercooling or heat transfer paths. To evaluate the sensors, different engine operating conditions were conducted, focusing at full load and low speeds. Other hardware configurations of the same engine family were used to exaggerate the combustion environment, specifically a tumble-motion plate and turbocharging.

Component bench fatigue testing is a cost-effective way to evaluate the durability of exhaust catalytic converters. A successful bench fatigue test depends on the development of a test specification. The test specification should represent the actual customer duty cycle that the component is exposed to. Based on the concept of equivalent fatigue damage, a systematic approach is presented to obtain the test specification from the acquired road load data. A method based on damage analysis is proposed to determine the effective notch factor, and an empirical relationship is presented to account for the thermal effect on the test specification. The principles and procedures of multiple block testing and constant amplitude testing are also presented.

Vehicle evaluations and model calculations were conducted on a vacuum-insulated catalytic converter (VICC). This converter uses vacuum and a eutectic PCM (phase-change material) to prolong the temperature cool-down time and hence, may keep the converter above catalyst light-off between starts. Tailpipe emissions from a 1992 Tier 0 5.2L van were evaluated after 3hr, 12hr, and 24hr soak periods. After a 12hr soak the HC emissions were reduced by about 55% over the baseline HC emissions; after a 24hr soak the device did not exhibit any benefit in light-off compared to a conventional converter. Cool-down characteristics of this VICC indicated that the catalyst mid-bed temperature was about 180°C after 24hrs. Model calculations of the temperature warm-up were conducted on a VICC converter. Different warm-up profiles within the converter were predicted depending on the initial temperature of the device.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.