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This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

General Motors recently demonstrated two driveable test vehicles powered by a Homogeneous Charge Compression Ignition (HCCI) engine. HCCI combustion has the potential of a significant fuel economy benefit with reduced after-treatment cost. However, the biggest challenge of realizing HCCI in vehicle applications is controlling the combustion process. Without a direct trigger mechanism for HCCI's flameless combustion, the in-cylinder mixture composition and temperature must be tightly controlled in order to achieve robust HCCI combustion. The control architecture and strategy that was implemented in the demo vehicles is presented in this paper. Both demo vehicles, one with automatic transmission and the other one with manual transmission, are powered by a 2.2-liter HCCI engine that features a central direct-injection system, variable valve lift on both intake and exhaust valves, dual electric camshaft phasers and individual cylinder pressure transducers.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

The Advanced Engineering (AE) group within General Motors Powertrain (GMPT) develops next generation engines and transmissions for automotive and marine products. As a research organization, AE needs to prototype design ideas quickly and inexpensively. To this end, AE has embraced model-based development techniques and is currently investigating the benefits of software in-the-loop (SIL) testing. The underlying obstacle faced in developing a practical SIL system lays in the ability to integrate a plant model with sufficient fidelity together with target application software. ChiasTek worked with AE utilizing their CosiMate tool chain to eliminate these barriers and delivered a flexible SIL system simulation solution.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

In this article, the authors illustrate the benefits of axiomatic design (AD) for robust optimization and how to integrate axiomatic design into a total robust design process. Similar to traditional robust design, the purpose of axiomatic design is to improve the probability of a design in meeting its functional targets at early concept generation stage. However, axiomatic design is not a standalone method or tool and it needs to be integrated with other tools to be effective in a total robust development process. A total robust development process includes: system design, parameter design, tolerance design, and tolerance specifications [1]. The authors developed a step-by-step procedure for axiomatic design practices in industrial applications for consistent and efficient deliverables. The authors also integrated axiomatic design with the CAD/CAE/statistical/visualization tools and methods to enhance the efficiency of a total robust development process.

A DFSS study identified a new mechanism for clamp load loss in aluminum threads due to thermal cycling. In bolted joints tightened to yield, the difference in thermal expansion between the aluminum and steel threads can result in a loss of clamp load with each thermal cycle. This clamp load loss is significantly greater than the loss that can be explained by creep alone. A math model was created and used to conduct a robust analysis. This analysis led to an understanding of the design factors necessary to reduce the cyclic clamp load loss in the aluminum threads. This understanding was then used to create optimized design solutions that satisfy constraints common to powertrain applications. Estimations of clamp load loss due to thermal cycling from the math model will be presented. The estimates of the model will be compared to observed physical test data. A robust analysis, including S/N and mean effect summary will be presented.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Under the initiative of the United States Council for Automotive Research LLC (USCAR§) Transmission Working Group, a collaborative effort was made with LuK USA LLC to study the influence of the friction interface parameters on the shudder durability of a wet launch clutch. A test bench was designed. Clutch configurations with different combinations of four friction materials (A, B, C and D), three groove patterns (waffle, radial and waffle–parallel) and two separator plate conditions (nitrided and non–nitrided) were considered. Considerable improvement in performance was seen by changing from CVT fluid* to DCT fluid*. A thermal analysis based on thermal model predictions and measurement correlations was conducted. Comparisons of clutch configurations with four and five friction plates were done. The waffle and radial groove pattern showed better heat transfer than the waffle–parallel groove pattern.

Under the initiative of the United States Council for Automotive Research LLC (USCAR§) Transmission Working Group, a collaborative effort was made with LuK USA LLC to study the influence of the friction interface parameters on the shudder durability of a wet launch clutch. Clutch configurations with different combinations of four friction materials (A, B, C and D), three groove patterns (waffle, radial and waffle-parallel) and two separator plate conditions (nitrided and non-nitrided) were considered. Durability testing consisted of a test profile, with 110 kJ energy per test cycle, developed earlier in this project. Materials A, B and C with nitrided separator plates reached the end of test criteria for the torque gradient and showed shudder. Materials B and C were more wear resistant as compared to materials A and D. The loss of friction coefficient (μ) was lower for materials B, C and D as compared to material A.

A compatibility study was conducted on fluorinated elastomers (FKM and FEPM) in various Automatic Transmission Fluids (ATF). Representative compounds from various FKM families were tested by three major FKM raw material producers - DuPont Performance Elastomers (DPE), Dyneon and Solvay. All involved FKM compounds were tested in a newly released fluid (ATF-A) side-by-side with conventional transmission fluids, at 150°C for various time intervals per ASTM D471. In order to evaluate the fluid compatibility limits, some FKM's were tested as long as 3024 hrs, which is beyond the normal service life of seals. Tensile strength and elongation were monitored as a function of ATF exposure time. The traditional dipolymers and terpolymers showed poor resistance to the new fluid (ATF-A). Both types demonstrated significant decreases in strength and elongation after extended fluid exposure at 150°C.

This paper presents four methodologies for modeling gear mesh excitations in simple and compound planetary gear sets. The gear mesh excitations use simplified representations of the gear mesh contact phenomenon so that they can be implemented in a numerically efficient manner. This allows the gear mesh excitations to be included in transmission system-level, multibody dynamic models for the assessment of operating noise and vibration levels. After presenting the four approaches, a description is made regarding how they have been implemented in software. Finally, example models are used to do a comparison between the methods

The dash mat is one of the most important acoustic components in the vehicle for both powertrain noise and road noise attenuation. To optimize acoustic performance and mass requirements in the advanced development stage, analytical modeling is essential. The development of a detailed Statistical Energy Analysis (SEA) model of a dash mat is discussed in this paper. Modeling techniques and correlation with test are presented for two different production dash mat designs, a barrier-decoupler conventional system and a dual layer dissipative system without a mass barrier. The material properties and thickness distribution are used in the SEA model together with the geometry information of the dash panel. With the SEA model suitably correlated, trade-off studies are conducted to investigate the relationship between mass reduction of the barrier and change in decoupler thickness. The effects of air gaps are also considered in both modeling and testing.

Development and integration of the cooling system for an automotive vehicle requires a balancing act between several performance and styling objectives. The cooling system needs to provide sufficient air for heat rejection with minimal impact on the aerodynamic drag, styling requirements and other criteria. An optimization of various design parameters is needed to develop a design to meet these objectives in a short amount of time. Increase in the accuracy of the numerical predictions and reduction in the turn-around time has made it possible for Computational Fluid Dynamics (CFD) to be used early in the design phase of the vehicle development. This study shows application of the CFD for robust design of the engine cooling system.

This paper presents the hybrid technique application in identifying the noise transfer paths and the force transmissibility between the interfaces of the different components in the vehicle. It is the stiffness based formulation and is being applied for the low to mid frequency range for the vibration and structure borne noise. The frequency response functions such as dynamic compliance, mobility, inertance, and acoustic sensitivity, employed in the hybrid method, can either be from the test data or finite element solution or both. The Source-Path-Receiver concept is used. The sources can be from the road surface, engine, transmission, transfer case, prop-shaft, differential, rotating components, chain drives, pumps, etc., and the receiver can be driver/passenger ears, steering column, seats, etc.

In an endeavor to improve upon historically subjective and hardware-based steering tuning development, a team was formed to find an optimal and objective solution using Design For Six Sigma (DFSS). The goal was to determine the best valve assembly design within a hydraulic power-steering assist system to yield improved steering effort and feel robustness for all vehicle models in a future truck program. The methodology utilized was not only multifaceted with several Design of Experiments (DOEs), but also took advantage of a CAE-based approach leveraging modeling capabilities in ADAMS for simulating full-vehicle, On-Center Handling behavior. The team investigated thirteen control factors to determine which minimized a realistic, compounded noise strategy while also considering the ideal steering effort function (SEF) desired by the customer. In the end, it was found that response-dependent variability dominated the physics of our valve assembly design concept.

Simultaneously obtaining a linear temperature control curve along with the correct temperature stratification at module outlets is one of the most difficult tasks in developing an automotive HVAC module. Traditionally, Computational Fluid Dynamics (CFD) development of temperature control linearity has been accomplished by iteratively adjusting the location, size and orientation of baffles which redirect warm and cold airstreams. This approach demands considerable interaction from the engineer in building the computational mesh, defining boundary and operating conditions and post processing the simulation results. The present study was conducted to investigate the optimization of HVAC temperature regulation curves using the multi-objective optimization code modeFrontier (1, 3) in conjunction with CFD code, Fluent (2). An auxiliary HVAC module was selected for the present study.

Managing (minimizing and optimizing) the total mass of a vehicle is recognized as a critical task during the development of a new vehicle, as well as throughout its production lifecycle. This paper summarizes a literature review of, and investigation into, the strategies, methods and best practices for achieving low total mass in new vehicle programs, and/or mass reductions in existing production vehicle programs. Empirical and quantitative data and examples from the automotive manufacturers and suppliers are also provided in support of the material presented.

The hybrid system for the 2007 Model Year Saturn VUE Green Line Hybrid SUV was designed to provide the fuel economy of a compact sedan, while delivering improved acceleration performance over the base vehicle, and maintaining full vehicle utility. Key elements of the hybrid powertrain are a 2.4L DOHC engine with dual cam-phasers, a modified 4-speed automatic transmission, an electric motor-generator connected to the crankshaft through a bi-directional belt-drive system, power electronics to control the motor-generator, and a NiMH battery pack. The VUE's hybrid functionality includes: engine stop-start, regenerative braking, intelligent charge control of the hybrid battery, electric power assist, and electrically motored creep. Methods of improving urban and highway fuel economy via optimal use of the hybrid motor and battery, engine and transmission hardware and controls modifications, and vehicle enhancements, are discussed.

The optimal selection of vehicle body and powertrain mounts from “mount libraries” is one of the major undertakings to achieve optimal vehicle dynamics and N&V performance through the reuse of existing mount designs. The great challenges of the process are due to the facts that conventional optimization procedures, either through simulation or DOE, can not be used directly because the stiffness rates of the mounts are scattered and bundled. Sorting out the best through hardware tests is generally unrealistic simply due to the huge number of mount combinations. This paper presents a new approach to the optimal mount selection, and demonstrates through applications that it is efficient and reliable. This approach characterizes a mount by its effective stiffness rate and evaluates its deviation from an associated target. Continuous dummy variables are used to determine the selection targets through conventional processes for performance optimization.