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Adopting robust design principles is a proven methodology for increasing design reliability. General Motors Powertrain (GMPT) has incorporated robust design principles into their Signal Delivery Subsystem (SDSS) development process by moving traditional prototype manufacturing and test functions from hardware to software. This virtual manufacturing technique, where subsystems are built and tested using simulation software, increases the number of possible prototype iterations while simultaneously decreasing the time required to gather statistically meaningful test results. This paper describes how virtual manufacturing was developed using distributed computing.

This paper illustrates a methodology in which complete material-manufacturing process cases for closure panels, reinforcements, and assembly are modeled and compared in order to identify the preferred option for a lightweight closure design. First, process-based cost models are used to predict the cost of lightweighting the closure set of a sample midsized sports utility vehicle (SUV) via material and process substitution. Weight savings are then analyzed using a powertrain simulation to understand the impact of lightweighting on fuel economy. The results are evaluated in the context of production volume and total mass change.

Robust assessment using standardized signal-to-noise (SS/N) is a Design For Six Sigma (DFSS) methodology used to assess the mating quality of USCAR electrical connectors. When the insertion force vs. distance relationship is compared to a standard under varying environmental and system-related noise conditions, the ideal function is transformed into a linear relationship between actual and ideal force at the sample points acquired during the mating displacement. Since the ideal function used in the robust assessment of competing designs has a linear slope of 1 through the origin, the SS/N function used is of the form 10 log (1/σ2), also known as nominal-the-best type 2. Using this assessment methodology, designs are compared, with a higher SS/N indicating lower variation from the standard.

This paper presents the implementation and performance of an electric all-wheel drive system on a series-parallel, through-the-road hybrid electric vehicle. Conventional methods of all-wheel drive do not provide a suitable solution for this type of vehicle as the powertrain lacks a mechanical link between the front and rear axles. Moreover, this unique architecture allows the vehicle to be propelled solely by the front, or the rear, wheels during typical operation. Thus, the algorithm presented here manages wheel slip by either the front, or rear wheels when engaging to provide all-wheel drive capability. necessary testing validates the robustness of this Extensive system.

While the industry has recognized the value of modeling and code generation, the role of verification has taken a limited second tier role. Model Based Testing (MBT) is typically discussed in the context of automation of testing activities to eliminate the burden of generation and execution of tests. Unfortunately, this objective of effort minimization has skewed solutions away from using quality as a guiding metric. Alternatively, we have identified the simple objective of increasing the quality of testing practices and productivity of developers. In the following paper we introduce the integration of traditional software quality practices of functional, unit, and regression testing with the automated, model-driven world. This approach enables a quantitative approach to model driven software quality. The result is a robust technique that enables confident use of model-based development for production applications.

The drum brake pulsation is an issue that may cause a major customer complaint. One of the root causes of the drum pulsation is the deformation of the drum to an out of roundness (OOR) shape during the wheel-drum-axle assembly process under the presence of the uneven wheel flatness. This paper summarizes the newly developed OOR simulation method using ABAQUS and the counter-measures to reduce the OOR, and subsequently pulsation, by identifying the drum design parameter effects on OOR.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Reducing Carbon Dioxide (CO2) emissions is one of the major challenges for automobile manufacturers. This is driven by environmental, consumer, and regulatory demands in all major regions worldwide. For conventional vehicles, a host of technologies have been applied that improve the overall efficiency of the vehicle. This reduces CO2 contributions by directly reducing the amount of energy consumed to power a vehicle. The hybrid electric vehicle (HEV) continues this trend. However, there are limits to CO2 reduction due to improvements in efficiency alone. Other major improvements are realized when the CO2 content of the energy used to motivate vehicles is reduced. With the introduction of Extended Range Electric Vehicles (E-REVs) and Plug-in HEVs (PHEVs), electric grid energy displaces petroleum. This enables the potential for significant CO2 reductions as the CO2 per unit of electrical energy is reduced over time with the improving mix of energy sources for the electrical grid.

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.

We start our study with a survey of existing variable valve actuation (VVA) devices. We then describe our work, taken place over a time period from 2001 to 2007, on several VVA concepts. All of our projects described include pre-design modeling and simulation. Also, for each one of the proposed designs, a bench-top motorized test fixture was built and ran for proof of concept. Our projects represent a mixture of exploratory research and production-related development work. They can be classified in four broad categories: discrete-step systems; mechanical continuously-variable systems; active stationary-hydraulic lash adjusters; cam-driven hydraulic-lost-motion mechanism. These devices differ in their complexity and versatility but offer a spectrum of design solutions applicable to a range of products. Specific attributes of these different approaches are analyzed and discussed, and some test results are presented.

Shock absorbers and damper systems are important parts of automobiles and motorcycles because they have effects on safety, ride comfort, and handling. In particular, for vehicle safety, shock absorber system plays a fundamental role in maintaining the contact between tire and road. Generally, to assure the best trade-off between safety and ride comfort, a fine experimental tuning on all shock absorber components is necessary. Inside a common damper system the presence of several conjugated actions made by springs, oil and pressurized air requires a significant experimental support and a great number of prototypes and test. Aimed to reduce the design and tuning phases of a damper system, it is necessary to join these phases together with a numerical modelling phase. The aim of this paper is to present the development of a mono-dimensional (1D) model for simulating dynamic behaviour of damper system.

Modern passenger cars are being equipped with advanced driver assistance systems such as lane departure warning, collision avoidance systems, adaptive cruise control, etc. Testing for operation and effectiveness of these warning systems involves interaction between vehicles. While dealing with multiple moving vehicles, obtaining discriminatory results is difficult due to the difficulty in minimizing variations in vehicle separation and other parameters. This paper describes test strategies involving an automated test driver interacting with another moving vehicle. The autonomous vehicle controls its state (including position and speed) with respect to the target vehicle. Choreographed maneuvers such as chasing and overtaking can be performed with high accuracy and repeatability that even professional drivers have difficulty achieving. The system is also demonstrated to be usable in crash testing.

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.

In automotive body manufacturing, there are two processes are often applied, Nominal Build and Functional Build. The Nominal Build process requires all individual stamping components meet their nominal dimensions with specified tolerances. While, the Functional Build process emphasizes more on the tolerances of the entire assembly as opposed to those of the individual stamped parts. The common goal of both processes is to build the body assemblies that meet the specified tolerances. Although there is strict tolerance specified for individual stamping parts the finished stampings frequently are released to assembly process with certain levels of dimensioning deviations, or they are within the specified tolerances but require heavy clamping during assembly. It is of high interest to predict the dimensional deviations in the stamping sub-assembly or body-in-white assembly process.

In racetrack conditions, brake systems are subjected to extreme energy loads and energy load distributions. This can lead to very high friction surface temperatures, especially on the brake corner that operates, for a given track, with the most available traction and the highest energy loading. Individual brake corners can be stressed to the point of extreme fade and lining wear, and the resultant degradation in brake corner performance can affect the performance of the entire brake system, causing significant changes in pedal feel, brake balance, and brake lining life. It is therefore important in high performance brake system design to ensure favorable operating conditions for the selected brake corner components under the full range of conditions that the intended vehicle application will place them under. To address this task in an early design stage, it is helpful to use brake system modeling tools to analyze system performance.

The market growth for electric-hybrid passenger vehicles has been very significant and is expected to reach nearly 25% of all vehicles sold in the US by 2015. Hybrid commercial vehicles are also being developed by several OEM's. This paper discusses the progress of Delphi Thermal Systems in developing an integrated electric compressor drive with high cooling capacity (9 kW+), sufficient for large hybrid SUV's and commercial vehicles such as Class 8 tractors with sleeper. An important driver for use of the electric compressor in the hybrid truck application is the reduction of engine idling time while maintaining comfort in the cab or sleeper. Design details of a compact 5 kW SPM motor, its inverter drive, and issues related to its integration into the compressor housing are described. Test results are given confirming excellent performance.

This paper shows how Rapid Control Prototyping (RCP) and Computational Fluid Dynamics (CFD) techniques have been applied to design and implement an engine control system for a common rail diesel engine. The project aim is to setup a high performance engine in order to participate to the Italian Tractor Pulling Championship (Prostock category). The original engine is a John Deere 6081 Tier2 model, already equipped with a common rail system. Engine performance is substantially determined by the control system, which is in charge of limiting engine speed, boost pressure and Air to Fuel Ratio (AFR). Given that typically the information and equipment needed to change control parameters are not accessible to customers, the first step of the project has been to replace the original control system, while maintaining injectors and pumps. This solution can guarantee the best performance, but it requires time to design the new control system, both in terms of hardware and software.

Plug-In Hybrid Vehicles (PHEVs) represent the middle point between Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs), thus combining benefits of the two architectures. PHEVs can achieve very high fuel economy while preserving full functionality of hybrids - long driving range, easy refueling, lower emissions etc. These advantages come at an expense of added complexity in terms of available fuel. The PHEV battery is recharged both though regenerative braking and directly by the grid thus adding extra dimension to the control problem. Along with the minimization of the fuel consumption, the amount of electricity taken from the power grid should be also considered, therefore the electricity generation mix and price become additional parameters that should be included in the cost function.