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Since interior noise has a strong effect on vehicle salability, it is particularly important to be able to estimate noise levels accurately by means of simulation at the design stage. The use of sensitivity analysis makes it easy to determine how the analytical model should be modified or the structure optimized for the purpose of reducting vibration and noise of the structural-acoustic systems. The present work focused on a structural-acoustic coupling problem. As the coefficient matrices of a coupled structural-acoustic system are not symmetrical, the conventional orthogonality conditions obtained in structural dynamics generally do not hold true for the coupled system. To overcome this problem, the orthogonality and normalization conditions of a coupled system were derived by us. In this paper, our sensitivity analysis methods are applied to an interior noise problem of a cabin model.

A multi-domain and multi-step topology optimization approach has been developed to address a wide range of structural design problems with manufacturability and other application concerns. The potential applications have been demonstrated in our previous work [1,2]. In this paper, we try to extend this method for vehicle crash design problem. The design process will be explained and examples will be provided to illustrate the potential application of this method for complicated crash design problems.

Computer Aided Engineering (CAE) has been successfully utilized in automotive industries. CAE numerically estimates the performance of automobiles and proposes alternative ideas that lead to the higher performance without building prototypes. Most automotive designers, however, cannot directly use CAE due to the sophisticated operations. In this paper, we propose a new breed of CAE, First Order Analysis (FOA), for automotive body designers. The basic ideas include (1) graphic interfaces using Microsoft/Excel to achieve a product oriented analysis (2) use of mechanics of materials to provide the useful information for designs, (3) the topology optimization method using function oriented elements. Further, some prototypes of software are presented to confirm the method for FOA presented here.

Computer Aided Engineering (CAE) has been successfully utilized in automotive industries. CAE numerically estimates the performance of automobiles and proposes alternative ideas that lead to the higher performance without building prototypes. Most automotive designers, however, cannot directly use CAE due to the sophisticated operations. In order to overcome this problem, we proposed a new concept of CAE, First Order Analysis (FOA). The basic ideas include (1) graphic interfaces using Microsoft/Excel to achieve a product oriented analysis (2) use the knowledge of the mechanics of materials to provide the useful information for designers, and (3) the topology optimization method using beam and panel elements. In this paper, outline of FOA and application are introduced

First Order Analysis (FOA) is useful for designing subunits in the mid-frequency range, as the layout and mounting positions can easily be decided at the conceptual design phase. In order to reduce vibration, we propose FOA for Noise and Vibration (NV) with the following characteristics. First, a dynamic beam element is formulated analytically using Euler's beam theory [1], so that a long uniform beam can express one element with high-order vibration. Second, power flow between potential energy and kinetic energy can be expressed as post-processing, so we can examine how to change or cut off the vibration energy path. In this paper, the above analysis is applied to a front subframe for the conceptual design of an automotive body structure.

In FOA (First Order Analysis) any vehicle body structure might be interpreted as a collective simple structure that can be decomposed into 3 fundamental structure types. The first structure is the “BEAM”, whose cross sectional properties as well as its material dominates the mechanical behavior, the second is the “PANEL (shear panel, plate, and shell)”, whose mechanical behavior can be varied by changing its geometrical properties in the thickness direction, i.e. adding beads or flanges. The third structure is the “JOINT”, which connects the proceeding structures, and transfer complex three-dimensional loads with three-dimensional deformation. In the present work, we shall propose a methodology to identify a portion of an arbitrary FE model of an automotive body structure, with a “BEAM” structure in the FOA approach. In the latter chapter of this paper, cross section loads will be related with cross sectional properties in the aspect of the element strain energy concept.

In this study, the genetic algorithm so called GA is newly applied for the optimization of many engine mounting parameters, calculations of stiffness matrix and inverse matrix to obtain 6 degrees of freedoms displacements at mounting points and a center of gravity. As a result, the optimized result could be shortly obtained in a minute, and an inexperienced engineer could easily make the optimum engine mounting layout, which can satisfy the vibration isolation and the non-interference in an engine compartment.

The design of automobile human safety is a very important design factor, which the car manufacturers have recently focused. Crash tests have provided information on dummy response measurements such as the maximum chest acceleration head injury criteria (HIC) value and femur loading. The subject of this research is an optimal design of the seat belt in consideration of the deformation behavior of a vehicle cabin with the aim of reducing the human injury. The research focuses on the optimization method of taking the comprehensive trade off between the global approximation and computational cost. The optimization approach called Most Probable Optimal Design (MPOD) proposed by the authors is modified to be applicable to the optimization of cabin crash deformation behavior and safety belt with the mixed discrete and continuous design variables. The application example of the Hybrid III dummy model shows that the MPOD technique is effective in saving the computational cost.

A multi-domain and multi-step topology optimization approach is presented in this paper, which can be used to simplify the architecture/topological structure of an “optimum” structure obtained from the topology optimization process, and thus significantly improves the manufacturability of the final design. Examples will be given to illustrate how this approach can be applied to a realistic engineering design problem for developing lightweight and high-performance structures in next-generation ground vehicles.

The objective of this research is to verify the optimum design obtained from a topology optimization process. The verification is through both numerical analysis and physical test. It will be shown that the optimum topology obtained from an example topology optimization process is independent of the material used and the dimension/size of the structure. This important feature is then proved for more general cases through theoretical analyses, numerical simulations, and physical experiments. The result extends the applicability of the optimum design and simplifies the prototyping and test process thus will result in significant cost saving in building full-size prototypes and performing expensive tests. This work is a combined effort with theoretical, numerical and experimental methods. A multi-domain multi-step topology optimization technique [1] will be utilized to find the optimum structural design.

In various practical structural design problems, decision of a layout of material or stiffeners in the given design space satisfying some design constraints is the most difficult task for design engineers. Also, they must consider many possible cases for safety, performance and some other requirements. But it is very difficult to solve this type of layout (topology) problem by any conventional structural optimization techniques because its mathematical modeling of topology is so complex. To solve this problem, we employed the new topology optimization technique using the homogenization method that was recently introduced by Bensøe and Kikuchi. The method gives the minimum compliance design under certain material constraint. This technique was also extended to three dimensional shells and three dimensional solids by Suzuki and Kikuchi. In this paper, shape and topology optimization problem under multi-loading conditions is discussed.

Previous research [1] using an advanced multi-domain topology optimization technique has shown a great promise for the crashworthiness design using the new technique. In this paper, we try to answer some fundamental questions regarding the crashworthiness design, which include: 1) what are the fundamental crash mechanisms of a general crash process; 2) how the uncertainties in the system will affect the crash behavior of a structure; and 3) what is the proper approach for the crashworthiness design optimization that will have needed effectiveness and efficiency. In this paper, three different kinds of uncertainties, uncertainties in the structural parameters, the modeling processes, and the loading and boundary conditions, will be considered to assess the effects of the uncertainties in the crash process. The possible crash mechanisms are then studied to provide an understanding for the design problem.

The shape and topology optimization method using a homogenization method is a powerful design tool because it can treat topological changes of a design domain. This method was originally developed in 1988 [1] and have been studied by many researchers. However, their scope of application in real vehicle design works has been limited where a design domain and boundary conditions are very complicated. The authors have developed a powerful optimization system by adopting a general purpose finite element analysis code. A method for treating vibration problems is also discussed. A new objective function corresponding to a multi-eigenvalue optimization problem is suggested. An improved optimization algorithm is then applied to solve the problem. Applications of the optimization system to design the body and the parts of a solar car are presented.

Most of the existing control techniques applied to automobiles are based on a linear model of the relevant dynamic system. However, in spite of the increasing demand for more sophisticated vehicles, very little research is being directed toward understanding and predicting the nonlinear response caused by non-predictable operating conditions such as the variation of suspension characteristics due to wear and tear or the frictional coefficient of the road. In this research, we used a neural network based identification technique to predict the structural response of dynamic systems and validated the technique through comparison with experimental data obtained with a cantilever beam. This identification technique is further extended to forecast the frictional coefficient μ of roads. Numerical results indicate promising future applications.

Vehicle structure crashworthiness design is one of the most challenging problems in product development and it has been studied for decades. Challenges still remain, which include developing a reliable and systematic approach for general crashworthiness design problems, which can be used to design an optimum vehicle structure in terms of topology, shape, and size, and for both structural layout and material layout. In this paper, an advanced and systematic approach is presented, which is called Magic Cube (MQ) approach for crashworthiness design. The proposed MQ approach consists of three major dimensions: Decomposition, Design Methodology, and General Considerations. The Decomposition dimension is related to the major approaches developed for the crashworthiness design problem, which has three layers: Time (Process) Decomposition, Space Decomposition, and Scale Decomposition.

In order to calculate efficiently the characteristics of car body vibration and the acoustic characteristic of the passenger compartment, a structural-acoustic analysis system, ‘CAD-B’, was developed. This system divides the body into three components - front body, main cabin and rear body. The characteristics of front and rear body vibration are expressed in modal parameters. The vibration characteristic throughout the car body is then calculated through the building block approach, while the main cabin remains in finite elements. A good agreement in eigen pairs was seen between this approach and the conventional finite element method. As for the passenger compartment, it is divided into finite elements and its eigen pairs are calculated. Then by linking body vibration with the acoustic characteristic of the passenger compartment, sound pressure in the passenger compartment is calculated.

The occurrence of various vibrations and noises in an automobile, such as idling vibration, boom noise and road noise, is greatly affected by the natural vibration modes and could be developed for controlling the body strength and weight these problems could be solved and a high-performance vehicle realised. This paper presents an analytical method developed by the authors to solve these problems and gives examples of its application. In developing this method, the problems of natural vibration mode and static stiffness control were addressed. Perturbation and sensitivity analysis methods have already been proposed for mode control. Four typical methods were examined and the best one was chosen in terms of accuracy and calculation time when handling large-scale problems. For static sensitivity analysis, we proposed a nevi method which is like natural mode sensitivity analysis.

Energy optimal control theory (EOC) is applied to the energy flow control of a hybrid electric vehicle. Since the differential equation is solved analytically, the control law can be easily implemented in real time. Because the objective function is described in power form that permits negative value, not only the energy consumption is minimized but also the energy regeneration by the motor is maximized. In the simulation for the 10-mode driving, it is shown that the fuel cost of EOC is 15% lower than the rule based control (RBC).

When structures may have dynamic instability complex eigenvalue analysis is a useful tool to predict it. Although the accurate prediction itself is significant, it is also crucial to obtain sensitivity of unstable eigensolutions in order to eliminate instability efficiently. Since the mathematical relationship between stiffness matrix and design variables may seldom be found in reality, finite difference method has been typically used to approximate the sensitivity. The novel way to accurately calculate the sensitivity is developed without implementing finite difference method. This paper shows the advantages of analytical sensitivity analysis compared to other methods for choosing the most important components' eigenvalues. It also provides necessary amount of frequency shift for each chosen components' eigenvalue to eliminate unstable eigenvalues.