Crash Safety Design Of Vehicles Research Articles

Grid-based collaborative simulation system for vehicle crashworthiness

Globalization and increasing market competition are forcing the automotive industry to develop technology that will enable more efficient collaboration between carmakers and their suppliers. One of the options that can meet this demand is to adopt grid technology in the collaboration process. For the system to be successfully applied, the trust relationship among Virtual Organization (VO) members becomes a very important factor. Systems lacking in secure mechanisms require all the collaborating members to fully trust each other, and thus make their application quite limited. Based on grid technology, this paper proposes a collaborative simulation system for vehicle crash safety design, and discusses the trust relationship among VO members. The grid middleware VEGA and web services working for the collaboration also contribute to the simulation system. Also, a test bed is set up on the basis of the Local Area Network (LAN). At the end of this paper, a real case involving a carmaker and a door supplier is presented to demonstrate how the grid-based collaborative simulation system works.

A grid-based collaborative system for vehicle crash safety design and its application based on LAN

Car manufacturers and their suppliers are usually geographically dispersed, heterogeneous characters of various resources. To solve the resource sharing and data security problems in vehicle collaborative design environment, grid technology and Computer Supported Collaborative Work (CSCW) technology are integrated. This paper proposes a collaborative design system for vehicle crash safety design based on grid technology that is conformed to the OGSA framework, and explains how the grid middleware VEGA contributes to make collaboration more efficiently. Web services about the functions in this collaborative system are realized based on VEGA. Design principles and methods based on the FE analysis tool LS-DYNA are also presented. Finally, a test bed is built based on LAN and a case of a carmaker collaborating with a seat supplier is presented.

Multiobjective optimization for crash safety design of vehicles using stepwise regression model

In automotive industry, structural optimization for crashworthiness criteria is of special importance. Due to the high nonlinearities, however, there exists substantial difficulty to obtain accurate continuum or discrete sensitivities. For this reason, metamodel or surrogate model methods have been extensively employed in vehicle design with industry interest. This paper presents a multiobjective optimization procedure for the vehicle design, where the weight, acceleration characteristics and toe-board intrusion are considered as the design objectives. The response surface method with linear and quadratic basis functions is employed to formulate these objectives, in which optimal Latin hypercube sampling and stepwise regression techniques are implemented. In this study, a nondominated sorting genetic algorithm is employed to search for Pareto solution to a full-scale vehicle design problem that undergoes both the full frontal and 40% offset-frontal crashes. The results demonstrate the capability and potential of this procedure in solving the crashworthiness design of vehicles.

Multi-objective optimization for crash safety design of vehicles using stepwise regression model

In the automotive industry,structural optimization related to erashworthiness and energy absorption capability is of great importance,which involves highly nonlinear computational analysis and design with many material and structural parameters.Unfortunately,conventional design, analysis techniques and the experiments can only improve the structural crashworthiness to a limited extent,and in most engineering design problems there are several conflicting objectives that have to be considered for optimization.In order to improve crashworthiness design,a method using a multi-objective optimization technique based on stepwise regression model is presented through the applications of design of experiments and response surface models and finite element simulation technique.The method is applied for the multi- objective optimization design of the reinforced members of a vehicle,where the mass,toe board intrusion,and the integrated value of collision acceleration are chosen as the objective functions.The results show the new computational design method is a practical tool for the crash safety design of vehicles.

On reliability-based optimisation methods for automotive structures

To reduce the cost of prototype and physical tests, CAE analysis has been widely used to evaluate vehicle performance during the product development process. Combining CAE analysis and optimisation approach, the vehicle design process can be implemented more efficiently at affordable cost. Reliability-based design optimisation (RBDO) formulation considers variations of input variables, such as component gauges and material properties. This paper is on the application of reliability-based design optimisation of automotive structures. Several fundamental approaches aimed at simulations, optimisation and robustness analysis are discussed. They include sampling techniques and non-linear response surface methodologies, optimisation and robustness assessment, reliability-based design optimisation and robust design formulation. The major focus is on the implementation of reliability-based design optimisation methodologies in vehicle crash safety design. Some recent applications are presented to demonstrate how these approaches were used for vehicle structure design.

Designing for head impact safety using a combination of lumped parameter and finite element modeling

The current paper describes an improved lumped parameter model with a mass and a nonlinear spring that can be useful in vehicle crash safety design. The area of vehicle upper interior headform impact is chosen here for the purpose of illustration. The improvement in lumped parameter modeling stems from the piecewise linear representation of unloading force vs. displacement curves of arbitrary shapes. Available test results and responses from a finite element model with a featureless Hybrid 3 headform that has been developed for the current study are used for ascertaining the efficacy of the lumped parameter model with modified unloading behavior. The comparisons indicate extremely good predictability of test and finite element-based headform responses and HIC (d) with the present improved lumped parameter model. Finally, a new hybrid approach is illustrated for obtaining an optimized head impact countermeasure design using a combination of finite element and lumped parameter modeling.

Novel Development and Applications in Finite Element Technologies. Optimum Design of Vehicle Frontal Structure and Occupant Restraint System for Crashworthiness. A Multilevel Approach Using SDSS.

CAE tools have been applied for the crash safety design of vehicles, though they haven’t satisfied the optimum design of vehicles. The authors have proposed a Statistical Design Support System (SDSS), and have found that the SDSS is one of available optimization approaches for the nonlinear and dynamic phenomena. This system is a synthetic design method which is based on the response surface methodology and the design of experiments. In this study, a multilevel optimization approach using the SDSS is presented. This approach is well-suited to large-scale multilevel and multidisciplinary optimization problems, and optimum design of vehicle frontal structure and occupant restraint system for crashworthiness is solved. It is shown that successfully and effectively collaborative optimization for frontal structure and occupant restraint system can be conducted by this new approach.

Optimisation and robustness for crashworthiness of side impact

This paper presents a nonlinear response surface-based safety optimisation and robustness process. The stepwise regression and optimal Latin hyper cube sampling methods are employed to construct the "efficient-to-compute" surrogate model. A sequential quadratic programming method with mixed type of variables is employed for the design optimisation. A reliability based design optimisation model for robust system parameter design of vehicle safety is proposed and a Monte Carlo based stochastic simulation is used to perform the robustness assessment and the reliability-driven robust design. The methodology has been applied to the vehicle crash safety design of side impact. It shows that the vehicle weight can be significantly reduced with an improved safety performance and with a higher level of confidence. CAE simulation is used to validate the optimal results.

Multi Objective Optimization of Reinforced Members for Crash Safety Design of Automobiles.

CAE technology has been widely applied for the crash safety design of vehicles.Nevertheless, the optimum design approach has not been completed for the crash behavior of the vehicles because of the non-linearity of the dynamic problem.The authors have proposed a Statistical Design Support System(SDSS), and brought forward that the SDSS is one of the available optimal approaches for the nonlinear and dynamic problems such as the vehicles crashing. In this study, the SDSS was applied for the multi-objective optimization design of the main reinforced members of a vehicle. The thickness of each member was chosen as the design variables, and the total weight and the deformation of the cabin as the multi-objection functions.It was shown that the SDSS could satisfactorily be used as a practical multi-objective optimization design fool for the crash safety design of vehicles, and the design cycle could be significantly cut down using SDSS.

Optimization of reinforced members for crash safety design of vehicles

CAE technology has been widely applied for the crash safety design of vehicles. Nevertheless, an optimum design approach has not been completed for the crash behavior of the vehicles because of the nonlinearity of the dynamic problem. The authors have proposed a Statistical Design Support System (SDSS), and suggested this is one of the available optimal approaches for nonlinear and dynamic problems such as the vehicles. In this study, the SDSS was applied for the multiobjective optimization design of the main reinforced members of a vehicle. The thicknesses of each member were chosen as the design variables, and the total weight and the deformation of the cabin as the multi-objective functions. It was shown that the SDSS could satisfactorily be used as a practical multi-objective optimization design tool for the crash safety design of vehicles, and the design cycle could be significantly reduced using SDSS. Transactions on the Built Environment vol 37 © 1999 WIT Press, www.witpress.com, ISSN 1743-3509