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This paper describes the design, synthesis-analysis and development of the unique vehicle structure architecture for the fifth generation Chevrolet Corvette, ‘C5’, which starts in the 1997 model year. The innovative structural layout of the ‘C5’ enables torsional rigidity in an open roof vehicle which exceeds that of all current production open roof vehicles by a wide margin. The first structural mode of the ‘C5’ in open roof configuration approaches typical values measured in similar size fixed roof vehicles. Extensive use of CAE and a systems methodology of benchmarking and requirements rolldown were employed to develop the ‘C5’ vehicle architecture. Simple computer models coupled with numerical optimization were used early in the design process to evaluate every design concept and alternative iteration for mass and structural efficiency.

In an automotive air-conditioning (AC) system, the amount of work done by the compressor is also influenced by the suction line which meters the refrigerant flow. Optimizing the AC suction line routing has thus become an important challenge and the plumbing designers are required to come up with innovative packaging solutions. These solutions are required in the early design stages when prototypes are not yet appropriate. In such scenarios, one-dimensional (1D) simulations shall be employed to compute the pressure drop for faster and economical solution. In this paper, an approach of creating a modeling tool for suction line pressure drop prediction is discussed. Using DFSS approach L12 design iterations are created and simulations are carried out using 1D AMESim software. Prototypes are manufactured and tested on HVAC bench calorimeter. AC suction line pressure drop predicted using the 1D modeling co-related well with the test data and the error is less than 5%.

Determining the fundamental role of gravity in vital biological systems in space is one of six science and research areas that provides the philosophical underpinning for why NASA exists. The study of cells, tissues, and microorganisms in a spaceflight environment holds the promise of answering multiple intriguing questions about how gravity affects living systems. To enable these studies, specimens must be maintained in an environment similar to that used in a laboratory. Cell culture studies under normal laboratory conditions involve maintaining a highly specialized environment with the necessary temperature, humidity control, nutrient, and gas exchange conditions. These same cell life support conditions must be provided by the International Space Station (ISS) Cell Culture Unit (CCU) in the unique environment of space. The CCU is a perfusion-based system that must function in microgravity, at unit gravity (1g) on earth, and from 0.1g up to 2g aboard the ISS centrifuge rotor.

The benefits of utilizing virtual engineering include not only shortened product development time and reduced reliance on expensive physical testing, but also the opportunities for greater standardization to support higher product quality. This paper describes a project for building a smart meshing template with a CAD/CAE link. The objective of the project is to optimize the utilization of CAD software and CAE preprocessing software capabilities. The deliverable of the project is a cylinder head mesh template which meets all the cylinder head durability simulation meshing requirements, and which links to CAD/CAE software. Special surface areas identified are built into the cylinder head CAD model design. By using one of the features in CAD software, all the special surfaces can be automatically updated throughout the design process.

In recent trend, there is a huge demand for lightweight chassis frame, which improves fuel efficiency and reduces cost of the vehicle. Stiffness based optimization process is simple and straightforward while durability (life) based optimizations are relatively complex, time consuming due to a two-step (Stress then life) virtual engineering process and complicated loading history. However, durability performances are critical in chassis design, so a process of optimization with simplified approach has been developed. This study talks about the process of chassis frame weight optimization without affecting current durability performance where complex durability load cases are converted to equivalent static loadcases and life targets are cascaded down to simple stress target. Sheet metal gauges and lightening holes are the parameters for optimization studies. The optimization design space is constrained to chassis unique parts.

Two finite element optimization techniques are presented for minimizing automotive engine air induction structural radiated noise and mass. Air induction systems are generally made of thin wall plastic which is exposed to high levels of pulsating engine noise. Weak air induction system walls vibrate excessively creating noise that can be heard by the driver. The conventional approach is to add ribs (many times through trial and error) which increase part weight or by adding “kiss-offs,” which restrict air flow. The finite element optimization methods considered here are shape optimization and topometry optimization. Genesis, a fully integrated finite element analysis and optimization package by Vanderplaats Research & Development, was used to perform finite element optimization. Choice of optimization method is primarily dependent on several factors which are appearance, part interference and flow restriction requirements.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

Internal combustion (IC) engines still power most of the vehicles on road and will likely to remain so in the near future, especially for heavy duty applications in which electrification is typically more challenging. Therefore, continued improvements on IC engines in terms of efficiency and longevity are necessary for a more sustainable transportation sector. Two important design objectives for heavy duty engines with wet liners are to reduce friction loss and to lower the risks of cavitation damages, both of which can be greatly influenced by the piston-liner clearance and the design of the piston skirt. However, engine design optimization is difficult due to the nonlinear interactions between the key design variables and the design objectives, as well as the multi-physics and multi-scale nature of the mechanisms that are relevant to the design objectives.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

In an Automotive air conditioning system, the air flow distribution in the cabin from the HVAC (Heating, ventilation and air conditioning), ducts and outlets is evaluated by the velocity achieved at driver and passenger mannequin aim points. Multiple simulation iterations are being carried out before finalizing the design of HVAC panel duct and outlets until the target velocity is achieved. In this paper, a parametric modeling of the HVAC outlet is done which includes primary and secondary vane creation using CATIA. Java macro files are created for simulation runs in STAR CCM+. ISIGHT is used as an interface tool between CATIA and STARCCM+. The vane limits of outlet and the target velocity to be achieved at mannequin aim points are defined as the boundary conditions for the analysis. Based on the optimization technique and the number of iterations defined in ISIGHT, the vane angle model gets updated automatically in CATIA followed by the simulation runs in STARCCM+.

This paper presents an optimization technique for clamping forces determination in fixture design. First, the finite element analysis (FEA) is applied to determine the coefficients of compliant matrix of a fixture-workpiece system subjected to machining and clamping forces. Then, a nonlinear optimization model is constructed in terms of the FEA results and mechanical and geometrical constraints. The optimization model is derived to determine the feasible clamps under the corresponding force effects. The optimal magnitude and direction of clamping forces minimize the workpiece deformation at particular key points. Finally, a scaled engine block with the 3-2-1 fixturing principle is given as an example.

In a complex system, large numbers of design variables and responses are involved in performance analysis. Relationships between design variables and individual responses can be complex, and the outcomes are often competing. In addition, noise from manufacturing processes, environment, and customer misusage causes variation in performance. The proposed method utilizes the two-step optimization process from robust design and performs the optimization on multiple responses using Hotelling's T2 statistic. The application of the T2-statistic allows the use of univariate tools in multiple objective problems. Furthermore, the decomposition of T20 into a location component, T2M and a dispersion component, T2D substitutes a complex multivariate optimization process with the simpler two-step procedure. Finally, using information from the experiment, a multivariate process capability estimates for the design can be made prior to hardware fabrication.

Robust optimization usually requires numerous functional evaluations, which is not feasible when the functional evaluation is time-consuming. Examples in automobile industry include crash worthiness/safety and fatigue life simulations. In practice, a response surface model (RSM) is often used as a surrogate to the CAE model, so that robust optimization can be carried out. However, if the error in the RSM is significant, the solution based on the RSM can be invalid. This paper proposes a method of finding multiple candidate solutions, all of which have similar predicted performances. This approach is effective in finding the close-to-optimum solutions when the model has error, and providing design alternatives. Examples are provided to illustrate the method.

A Multi-Objective Optimization (MOO) problem concerning the thermal control problem of Multifunctional Structures (MFSs) is here addressed. In particular the use of Multi-Objective algorithms from an optimization tool and Self-Organizing Maps (SOM) is proposed for the identification of the optimal topological distribution of the heating components for a multifunctional test panel, the Advanced Bread Board (ABB). MFSs are components that conduct many functions within a single piece of hardware, shading the clearly defined boundaries that identify traditional subsystems. Generally speaking, MFSs have already proved to be a disrupting technology, especially in aeronautics and space application fields. The case study exploited in this paper refers to a demonstrator breadboard called ABB. ABB belongs to a particular subset of an extensive family of MFS, that is, of thermo-structural panels with distributed electronics and a health monitoring network.

Brake judder is a brake induced vibration that a vehicle driver experiences in the steering wheel or floor panel at highway speeds during vehicle deceleration. The primary cause of this disturbance phenomenon is the brake torque variation (BTV). Virtual CAE tools from both kinematics and compliance standpoints have been applied in analyzing sensitivities of the vehicle systems to BTV. This paper presents a recently developed analytical approach that identifies parameters of steering and suspension systems for achieving optimal settings that desensitize the vehicle response to BTV. The analytical steps of this integrated approach started with creating a lumped mass noise-vibration-harshness (NVH) control model and a separate multi-body dynamics (MBD) suspension model. Then, both models were linked to run in a sequence through optimization software so the results from the MBD model were used as quasi-static inputs to the lumped mass NVH model.

This paper presents a new computerized approach for designing the automobile window glass contour, the glass drop motion, and the regulator systems. The three-dimensional geometrical relationship of the glass contour, the drop path, and its guidance system have been studied. Methods for barrel and helical drops are presented for optimizing the glass profile and drop path trajectories. Criteria for perfecting the glass contour are developed for shaping the profile of the vehicle clay model. Methods for correcting the glass contour and shape are presented. Examples are provided to illustrate how to improve the design. This approach integrates the development works of glass contour, drop motion and regulator systems. Through this design approach the window glass can fit and move perfectly in the door assembly.

Advanced high strength steels (AHSS) offer a good balance of strength, durability, crash energy absorption and formability. Applications of AHSS for lightweight designs of automotive structures are accelerating in recent years to meet the tough new CAFE standard for vehicle fuel economy by 2025. At the same time, the new generation pickup cargo box is to be designed for a dramatic increase in payload. Upgrading the box material from conventional mild steels to AHSS is necessary to meet the conflicting requirements of vehicle light weighting and higher payload. In this paper, typical AHSS grades such as DP590 and DP780 were applied to selected components of the pickup cargo box for weight reduction while meeting the design targets for fatigue, strength and local stiffness.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

This paper summarizes the design, development, fabrication, validation, and application of a new device called the Skin Thermal Transducer (STT). The development of this instrument was driven by the demand for reliable information on human skin temperatures during contact with a warm surface on the interior of an automobile. The primary technology that enabled the development of the STT was the thermo-electric cooler (TEC) in combination with a heat sink that is used to simulate the core temperature of the human body. The STT was validated with human skin data and the agreement was within an acceptable range. The STT provides the automotive engineer with a measuring device to optimize and validate the underbody regions of the vehicle with respect to occupant thermal comfort. The STT can also be applied to optimize other automotive and non-automotive products in which the human skin touches a warm surface.

The Cu-zeolite (CuZ) SCR catalyst enables higher NOx conversion efficiency in part because it can store a significant amount of NH3. “NH3 storage control”, where diesel exhaust fluid (DEF) is dosed in accord with a target NH3 loading, is widely used with CuZ catalysts to achieve very high efficiency. The NH3 loading actually achieved on the catalyst is currently estimated through a stoichiometric calculation. With future high-capacity CuZ catalyst designs, it is likely that the accuracy of this NH3 loading estimate will become limiting for NOx conversion efficiency. Therefore, a direct measurement of NH3 loading is needed; RF sensing enables this. Relative to RF sensing of soot in a DPF (which is in commercial production), RF sensing of NH3 adsorbed on CuZ is more challenging. Therefore, more attention must be paid to the “microwave resonance cavity” created within the SCR assembly. The objective of this study was to develop design guidelines to enable and enhance RF sensing.