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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

Computer-aided engineering (CAE) is an important tool routinely used to simulate complex engineering systems. Virtual simulations enhance engineering insight into prospective designs and potential design issues and can limit the need for expensive engineering prototypes. For complex engineering systems, however, the effectiveness of virtual simulations is often hindered by excessive computational cost. To minimize the cost of running expensive computer simulations, approximate models of the original model (often called surrogate models or metamodels) can provide sufficient accuracy at a lower computing overhead compared to repeated runs of a full simulation. Metamodel accuracy improves if constructed using space-filling designs of experiments (DOEs). The latter provide a collection of sample points in the design space preferably covering the entire space.

This research proposes an automatic computer-aided design, analysis, and optimization process of a twist beam rear suspension system. The process combines CAD (Computer-Aided Design), CAE (Computer-Aided Engineering), and optimization technologies into an automation procedure, which includes: structural design, dynamic analysis, vibration analysis, durability analysis, and multidisciplinary optimization. The automation results shown the twist beam rear suspension weight reduced, the durability fatigue life increased, and the K&C (kinematics & compliance) characteristics are improved significantly.

The Press-in-Place (PIP) gasket is a static face seal with self-retaining feature, which is used for the mating surfaces of engine components to maintain the reliability of the closed system under various operating conditions. Its design allows it to provide enough contact pressure to seal the internal fluid as well as prevent mechanical failures. Insufficient sealing pressure will lead to fluid leakage, consequently resulting in engine failures. A test fixture was designed to simulate the clamp load and internal pressure condition on a gasket bolted joint. A sensor pad in combination with TEKSCAN equipment was used to capture the overall and local pressure distribution of the PIP gasket under various engine loading conditions. Then, the test results were compared with simulated results from computer models. Through the comparisons, it was found that gasket sealing pressure of test data and CAE data shows good correlations in all internal pressure cases when the bolt load was 500 N.

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.

Vehicle design and packaging is a repetitive and tedious process that involves frequent engineering and design changes. To improve design efficiency, a standard naming vehicle design methodology is proposed in this paper. For the geometric or the functional object used in the vehicle context, a standard name is assigned and also used as a unique object feature through its life cycle. With the proposed standard naming design methodology, the engineering knowledge can be efficiently embedded into the CAD design, and hence, vehicle design can be executed in a more automated fashion. Work case of the standard naming design methodology is illustrated by a vehicle design and packaging application using CATIA V5.

Billboards are an effective instrument of advertisement at areas with high traffic flow such as alongside highways. They provide information to drivers for food, fuel, lodging, attractions, etc. A novel mechanical billboard has been conceived recently which contains rolling tubes to alternate as many as twelve printed signs. It has the advantages of both flexibility and cost-effectiveness. A container is built to protect the mechanism from the weather elements. To allow the displayed messages to be visible, a transparent acrylic front is installed. Due to its mechanical properties, it is a challenging task in designing a functional acrylic front. A reinforcement is selected to counter the weak flexural rigidity of the front during winds. On the other hand, the reinforced acrylic front must maintain sufficient visibility.

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.

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.

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.

In the early stages of a vehicle program, it is a common practice to set target ranges for the global body, suspension and powertrain modes. This modal management process allows engineers to avoid potential noise and vibration problems stemming from strong overlap of major global modes. Before the first prototype hardware is built, finite element models of the body, suspension and powertrain are usually exercised to compare predicted versus targeted ranges of the major system modes in the form of a modal management chart. However, uncertainty associated with the design parameters, manufacturing process and other sources can lead to a major departure from the design intent when the first hardware prototype is built. In this study, a first order reliability method is used to predict variance of the eigen values due to parameter uncertainties. This allows the CAE engineers to add a “three sigma” bound on the eigen values reported in the modal management chart.

A vehicle drivetrain is designed to meet specific vehicle performance criteria which usually involve trade-offs among conflicting performance measures. This paper describes a methodology to optimize the drivetrain design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A complete vehicle dynamic model is developed using the bond graph method. The model includes the vehicle, engine, transmission, torque converter, driveline, and transmission controller. An equivalent MATLAB Simulink model is also developed in order to carry out the nonlinear dynamic analysis efficiently. A deterministic optimization is first performed to determine the optimum design in terms of fuel economy, without considering variations or uncertainties. Subsequently, a Reliability-Based Design Optimization is carried out to find the optimum design in the presence of uncertainty.

Although the performance of CNC machines is accurate, unavoidable human errors at the part loading position have serious repercussions on engine performance. In the present paper the authors would like to develop an algorithm for error compensation when the tool movement is unrestricted in space. The new solution algorithm will be in terms of the known initial system variables such as the part loading errors, drill tool inclinations, location of spindle etc. This modified paper employs the same principles of inverse kinematics as done in the earlier paper wherein a faulty compound-hole angle axis in space caused by the translational and rotational errors at the part loading position is identified with an imaginary true axis in space by enforcing identity through a modified machine axes taking into effect inclination of the drill tool in space. In the absence of any specific application, this algorithm is verified on Solid Works a commercial CAD tool and found to be correct.

In automotive industry, all passenger vehicles are treated with damping materials to reduce structure borne noise. The effectiveness of damping treatments depends upon design parameters such as choice of damping materials, locations and size of the treatment. This paper proposes a CAE (Computer Aided Engineering) methodology based on finite element analysis to optimize damping treatments. The developed method uses modal strain-energy information of bare structural panels to identify flexible regions, which in turn facilitates optimization of damping treatments with respect to location and size. The efficacy of the method is demonstrated by optimizing damping treatment for a full-size pick-up truck. Moreover, simulated road noise performances of the truck with and without damping treatments are compared, which show the benefits of applying damping treatment.

A process to achieve vehicle system level NVH objectives using CAE simulation tools is discussed. Issues of modeling methodology, already covered adequately in the literature, are less emphasized so that the paper can focus on the application of a process that encompasses objective setting, design synthesis, and performance achievement using simulation predictions. A reference simulation model establishes correlation levels and modeling methods that are applied to future predictions. The new model, called a “Digital Mule”, is an early new product “design intent” simulation used to arrive at subsystem goals to meet the vehicle level NVH objectives. Subsystem goals are established at discrete noise paths where structure borne noise enters the body subsystem. The process also includes setting limits on the excitation sources, such as suspension and powertrain.

Optimizing the trade-off between reliability and cost of operating a microgrid, including vehicles as both loads and sources, can be a challenge. Optimal energy management is crucial to develop strategies to improve the efficiency and reliability of microgrids, as well as new communication networks to support optimal and reliable operation. Prior approaches modeled the grid using MATLAB, but did not include the detailed physics of loads and sources, and therefore missed the transient effects that are present in real-time operation of a microgrid. This article discusses the implementation of a physics-based detailed microgrid model including a diesel generator, wind turbine, photovoltaic array, and utility. All elements are modeled as sources in Simulink. Various loads are also implemented including an asynchronous motor. We show how a central control algorithm optimizes the microgrid by trying to maximize reliability while reducing operational cost.

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.

Springback study on a Dodge Ram fender outer panel is detailed in this paper. A simple measurement fixture is designed for the panel, wherein non-contact laser scan technology is applied The measurement data are compared with the original CAD design surface and deviation contour maps are obtained. Consistency of measurement is studied at different sections among three samples. Details of FEA simulations are outlined. The comparison between measurement and simulation prediction is summarized. A method to describe the consistency of measurement and the accuracy of simulation prediction is proposed. The targets for measurement consistency and simulation accuracy are verified. A sensitivity analysis is also performed to investigate various simulation input parameters.

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.