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The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

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.

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.

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.

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

A numerical investigation of automobile sunroof buffeting on a prototype sport utility vehicle (SUV) is presented, including experimental validation. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using the PowerFLOW code, a CFD/CAA software package from Exa Corporation based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution.

This paper examines the aerodynamic forces on the open hood of a stationary vehicle when another large vehicle, such as an 18-wheel semi-truck, passes by at high speed. The problem of semi-truck passing a parked car with hood open is solved as a transient two-vehicle aerodynamics problem with a Dynamic Moving Mesh (DMM) capability in commercial CFD software package FLUENT. To assess the computational feasibility, a simplified compact car / semi-truck geometry and CFD meshes are used in the first trial example. At 70 mph semi-truck speed, the CFD results indicate a peak aerodynamic force level of 20N to 30N on the hood of the car, and the direction of the net forces and moments on the hood change multiple times during the passing event.

Model-based design and development is emerging in the automotive industry, largely revealing its popularity in chassis control systems [1]. Although it is an efficient and accepted design tool for chassis systems, proper processes and strategies need to be in place to ensure the integrity and correctness of the production software. This paper describes software testing strategies for complex chassis control systems in a model-based environment. In detail, it highlights various testing methods for different phases, such as unit testing and integration testing. It will also address issues and challenges that were faced with each method and propose possible solutions.

The value of model-based design has been attempted to be communicated for more than a decade. As methods and tools have appeared and disappeared from a series of different vendors it has become apparent that no single vendor has a solution that meets all users’ needs. Recently standards (UML, MDA, MOF, EMF, etc.) have become a dominant force and an alternative to vendor-specific languages and processes. Where these standards have succeeded and vendors have failed is in the realization that they do not provide the answer, but instead provide the foundation to develop the answer. It is in the utilization of these standards and their capability to be customized that companies have achieved success. Customization has occurred to fit organizations, processes, and architectures that leverage the value of model-driven design.

This paper presents a pioneer work and first time application of Multi Objective Robust Optimization to analytically improve Idle Shake Performance. The method is developed to obtain a robust design with multiple objectives under consideration along with managing material property variation. It was a Robust Optimization on top of Multi Objective Genetic Algorithm, Robu-MOGA. The design variables in the study included the nominal values and tolerances of Sound Transmission Loss property, and interior material Absorption property. The analytical objective was not only to minimize the peak airborne noise at each specified frequency, but also to reduce the total cost and the total mass of the materials. In the study, AutoSEA (statistical energy analysis) from ESI Software, Inc. was used as the solver. AutoSEA was integrated with iSIGHT from Engineous Software, Inc.

The goal was to automate the entire analytical process of structural fatigue life variation assessment with respect to the variations associated with the geometry such as thickness, material properties and loading conditions. Consequently, the structural reliability is evaluated systematically. This process automation has been realized by using an internally developed software package called Structural Fatigue/Reliability Sensitivity II (i.e. FRS II). The package is a bundle of MSC/Nastran, nCode, iSIGHT, and internally developed program scripts.

The past 10 years have created such buzzwords as “model-based development” and “auto-code generation”. Conveniently absent from the tool literature on model-based development are the equally, or more important concepts of Software Architecture and Process. When developing product line software, the process and architecture form a critical foundation to base reusable products and components. The development process can no longer be viewed as “model-based”, but rather as “model-driven”, due to the reliance on the models as the source artifact as opposed to the creators of the source artifacts. A model-driven product line software development process allows capturing of behavior, for commonality across different products, and having a different implementation for a specific product release.

FlexRay is a new communication subsystem for future in-vehicle controls. There is a lack of mature model-based development methodologies to build complex FlexRay-based systems. In this paper we describe an end-to-end model-based development process for building a complex FlexRay-based distributed control system. We describe this in the context of safety critical x-by-wire systems for a realistic automotive application. This involves: control system modeling, functional simulation, and distributed software development. We first describe the process of functional and physical architecture design. Next we discuss the software development process dealing with software to hardware allocation, as well as scheduling of software and communication tasks on a time-triggered communication bus under stringent practical restrictions. We conclude by considering the integration issues relating to joint OEM/supplier development of distributed control systems.

Control System testing determines whether the embedded controller (software and its HWIO / hardware system) are operating according to specification. General Motors Powertrain (GMPT) has increased its span of test coverage through the use of automated testing. Further use of this type of testing is advised to enhance quality in a field that is rapidly growing more complex.

The global market pressure of requiring high quality vehicles at lower prices has forced automotive manufacturers to change the way they engineer their products. In the electrical/electronic part of the automobile business, a strategy of reusing common hardware and software components was needed to support these market pressures. The General Motors strategy was to develop a standard electrical architecture. This paper will identify what a standard electrical architecture is, how a standard electrical architecture helps General Motors meet market demands, and issues that General Motors encountered in trying to implement this standard electrical architecture.

Signal delivery is the means of translating a physical parameter from a sensor measurement to the application software in the electronic controller. Signal delivery is also translating a digital word from the application software to an actuator response. In both cases, there are many transform functions along the path that will introduce noise, error, and non-linearity. This paper will discuss the importance of understanding the error and sensitivity to variation that signal delivery analysis provides. The analysis will direct design change to improve control system robustness as well as decisions for failure events.

This paper outlines a method for computing the transfer functions of structures using their mass loaded responses. According to the method, scaled transfer functions are computed from the response of a structure and without any knowledge of the input forces. The paper outlines the analytical approach, develops the necessary equations for the computation of transfer functions between a mass loading point and other points on a linear dynamic system. A numerical example to show the validity, advantages and limitations of the method is also provided. Currently, the method can be applied to the responses obtained from analytical simulations where it may be necessary to compute coupled response of a simulated dynamic system with other dynamic systems that are not (or cannot be) included in a simulation. It is not uncommon that many dynamic simulations exclude certain coupling effects between the main and the auxiliary systems.

This paper describes the development of a generic test cell software designed to overcome many vehicle-component testing difficulties by introducing modern, real-time control and simulation capabilities directly to laboratory test environments. Successfully demonstrated in a transmission test cell system, this software eliminated the need for internal combustion engines (ICE) and test-track vehicles. It incorporated the control of an advanced AC induction motor that electrically simulated the ICE and a DC dynamometer that electrically replicated vehicle loads. Engine behaviors controlled by the software included not only the average crankshaft torque production but also engine inertia and firing pulses, particularly during shifts. Vehicle loads included rolling resistance, aerodynamic drag, grade, and more importantly, vehicle inertia corresponding to sport utility, light truck, or passenger cars.

This paper presents a project that was done to solve an integration problem between a brake system and a cruise control system on a GM vehicle program, each of which was supplied by a different supplier. This paper presents how the problem was resolved using a CAE tool which was a combination of formulated MS/Excel spreadsheet, Overdrive (GM internal code), and iSIGHT of Engineous Software Inc, which is a process integrator and process automator. A sensitivity study of system reliability was conducted using iSIGHT. The most sensitive factor was found through the sensitivity study. Thereafter, a Robust design was obtained. The recommended Robust Design was implemented in the vehicle program, which led to a substantial cost saving. The CAE software tool (the combination) developed through the problem solving process will be used to ensure quality of brake and cruise system performance for future vehicle programs.