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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.

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 common occurrence in computer aided design is the need to make changes to an existing CAD model to compensate for shape changes which occur during a manufacturing process. For instance, finite element analysis of die forming or die tryout results may indicate that a stamped panel springs back after the press line operation so that the final shape is different from nominal shape. Springback may be corrected by redesigning the die face so that the stamped panel springs back to the nominal shape. When done manually, this redesign process is often time consuming and expensive. This article presents a computer program, FESHAPE, that reshapes the CAD or finite element mesh models automatically. The method is based on the technique of volume morphing pioneered by Sederberg and Parry [Sederberg 1986] and refined in [Sarraga 2004]. Volume morphing reshapes regions of surfaces or meshes by reshaping volumes containing those regions.

This paper describes the methodology used to design and perform a CFD analysis of a Chevrolet Impala SS Funny Car body. This body was designed for the purpose of making it available for teams to race it in the National Hot Rod Association (NHRA) drag racing series beginning with the 2007 race season. Several challenges were presented in this project: (1) This was the first time a General Motors drag racing body for use in professional classes (Funny Car or otherwise) was ever designed in CAD. (2) The body was originally designed as a 2007 Chevrolet Monte Carlo. After the tooling was completed, changes in Chevrolet’s product lineup required that the body be changed to a 2007 Impala SS. (3) Budget constraints precluded CFD analysis until after the bodies were already being manufactured. There were several teams that raced the new body during the 2007 race season. One of these teams won the Funny Car Driver’s Championship.

Due to competitive pressures and the need to rapidly develop new products for the automotive marketplace, the automotive industry has to rapidly develop and validate automotive subsystems and components. While many CAE tools are employed to decrease the time needed for a number of brake engineering tasks such as stress analysis, brake system sizing, thermo-fluid analysis, and structural dynamics, brake lining wear and the associated concept of “lining life” are still predominantly developed and validated through resource intensive public road vehicle testing. The goal of this paper is to introduce and detail an energy-based, lumped-parameter CAE approach to predict brake lining life in passenger cars and light trucks.

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.

As a virtual manufacturing press line, line die forming simulation provides a full range math-based engineering tool for stamping die developments of automotive structure and closure panels. Much beyond draw-die-only formability analysis that has been widely used in stamping simulation community during the last decade, the line die formability analysis allows incorporating more manufacturing requirements and resolving more potential failures before die construction and press tryout. Representing the most difficult level in formability analysis, conducting line die formability analysis of automotive body side outers exemplifies the greatest technological challenge to stamping CAE community. This paper discusses some critical issues in line die analysis of the body side outers, describes technical challenges in applications, and finally demonstrates the impact of line die forming simulation on the die development.

In GM R&D Powertrain/Engine Control Group, rapid prototyping controller (RPC) systems with Matlab/Simulink are used extensively to design, simulate and implement advanced engine control algorithms and models. However, those RPC systems use powerful microprocessors with large amounts of RAM contrary to engine control modules (ECM) in production vehicles. Therefore, a thorough analysis on the comparatively much more complicated algorithms and models cannot be performed during the research stage, since there are not enough tools to enable the smooth transition from Matlab/Simulink to the production type processor. The Real-Time Interface (RTI) Blockset for a production like microprocessor would close the transition gap between rapid prototyping controller systems and production type microprocessors by leveraging the power and popularity of Matlab/Simulink in control engineering world and automatic code generation tools.

In the automotive industry, vehicle durability analysis is based on test schedule encompassing multiple road surfaces (events) including rough roads, potholes, etc. Traditionally, in the Computer Aided Engineering (CAE) world, road load data for various road surfaces are measured/predicted and fatigue life is predicted for each individual road surface. Fatigue life for the complete test schedule is then calculated with Miner’s rule by summing fatigue damage for each road surface with an appropriate number of repetitions. A major pitfall of this approach is that it does not consider the effect of the largest rainflow range across the entire test schedule. The method described in this paper was developed to perform fatigue analysis of structures subjected to diverse road surfaces and also consider the case in which the maximum overall peak and minimum overall valley do not occur over the same road surface.

Today automotive thermal systems development is a joint effort between an OEM and its suppliers. This paper presents a pilot program showing how OEMs and suppliers can jointly develop a reliable and robust thermal system using CAE tools over the internet. Federated Intelligent Product Environment (FIPER) has been used to establish B2B communication between OEMs and suppliers. Suppliers remotely run thermal systems computer models at the OEM site using the FIPER B2B feature.

Exhaust durability is an important measure of quality, which can be predicted using CAE with accurate mount loads. This paper proposes an innovative method to calculate these loads from measured mount accelerations. A Chrysler vehicle was instrumented with accelerometers at both ends of its four exhaust mounts. The vehicle was tested at various durability routes or events at DaimlerChrysler Proving Grounds. These measured accelerations were integrated to obtain their velocities and displacements. The differences in velocities and displacements at each mount were multiplied by its damping and stiffness rates to obtain the mount load. The calculation was conducted for all three translational directions and for all events. The calculated mount loads are shown within reasonable range. Along with CAE, it is suggested to explore this method for exhaust durability development.

In developing the 2007 Model Year Saturn VUE Green Line hybrid vehicle, a vehicle model for prediction of fuel economy and performance was developed. This model was developed in Matlab / Simulink / Stateflow by augmenting an existing conventional vehicle model to include hybrid components and controls. The generic structure and the functionalities of the model are presented. This simulation model was used for rapid concept selection and requirements balancing early in the vehicle development process. Engine usage and energy distributions are shown based on simulation results. Fuel economy breakdown was also discussed.

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.

This paper describes a lightweight magnesium intensive automobile body structure concept developed at DaimlerChrysler to support a high fuel-efficiency vehicle project. This body structure resulted in more than 40% weight reduction over a conventional steel structure while achieving significantly improved structural performance as evaluated through CAE simulations. A business case analysis was conducted and showed promising results. One concept vehicle was built for the purpose of demonstrating concept feasibility. The paper also identifies areas for further development to enable such a vehicle to become a production reality at a later time.

Regulations implemented by safety commissions throughout the world have resulted in extensive physical testing to protect the occupants during frontal impact events. Significant prototype and test costs aimed at optimizing structure and restraint systems are associated with meeting these regulations. To help reduce development costs, Computer Aided Engineering (CAE) is often applied. LS-DYNA [1] coupled with MADYMO [2] is widely used in crash and occupant safety simulation. An analysis technique which utilized a single model to design and optimize interiors (instrument panel, seats, visor, steering wheel, steering column) and restraints (airbag, seatbelts, retractor, pre-tensioner) was developed. The single model concept captures the global structural kinematics through minimal vehicle representation. Global vehicle modes such as pitch and roll can be represented by applying prescribed motion boundary conditions extracted from full vehicle models.

4-Post durability test simulations using a nonlinear FEA model have been executed by engineers responsible for structural durability performance and validation. An integrated Body and Chassis, full FEA model has been used. All components of the test load input were screened and only the most damaging events were incorporated in the simulation. These events included the Potholes, Belgian Block Tracks, Chatter Bump Stops, Twist Ditches, and Driveway Ramps. The CAE technology Virtual Proving Ground (eta/VPG®*) was used to model the full system and the 4-Post test fixtures. The nonlinear dynamic FE solver LS-DYNA** was used in this analysis. The fatigue damage of each selected event was calculated separately and then added together according to the test schedule. Due to the lack of stress/strain information from hardware test, only the analyzed fatigue damage results of the baseline model were scaled to correlate with physical test data.

The durability of fuel tank straps is essential for vehicle safety. Extensive physical tests are conducted to verify designs for durability. Due to the complexity of the loads and the fuel-to-tank interaction, computer-aided-engineering (CAE) simulation has had limited application in this area. This paper presents a CAE method for fuel tank strap durability prediction. It discusses the analytical loads, modeling of fuel-to-tank interaction, dynamic analysis methods, and fatigue analysis methods. Analysis results are compared to physical test results. This method can be used in either a fuel-tank-system model or a full vehicle model. It can give directional design guidance for fuel tank strap durability in the early stages of product development to reduce vehicle development costs.

Computer applications have been widely used to assist product design. The successes and sophistication of computer aided engineering (CAE) techniques are respectfully recognized in this field. CAE applications in the manufacturing area however are still developing, although the manufacturing community is increasingly starting to pay attentions to computer simulations in its daily workings. This paper will briefly introduce some of these applications and promote awareness of computer simulations in manufacturing area. It contains four main sections: finite element analysis (FEA) in machining fixture design, FEA applications in component assembly, machining process simulations and machining vibrations in the milling operation. Each section comes with a practical case study, potential benefits are identified and conclusions are presented by using an integrated design and analysis approach.

One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability