Vehicle Crashworthiness Simulation Based on Virtual Design of Auto-body

Vehicle crashworthiness simulation is the main component of the virtual auto-body design. One developing commercial vehicle was simulated on crashworthiness by the non-linear finite element method. The bumper crashworthiness at the speed of 8 km/h was analyzed and valuated. On the other hand, the deformation of the auto-body, the movement of the steering wheel and the dynamic responses of the occupant at the initial velocity of 50 km/h were studied. The results appear that the design of the vehicle could be improved on structure and material. Finally, the frontal longitudinal beam, the main energy-absorbing part of the auto-body, was optimized on structure. Simulation results also show that applying new material, such as high strength steel, and new manufacture techniques, such as tailor-welded blanks could improve the crashworthiness of the vehicle greatly.

Study on Dimension Chain Generation for Auto-body Tolerance Analysis

For auto-body product, assembly dimensional quality evaluation using tolerance analysis method is a challenging task because there are plenty of elements impacting on the variation stack-up and propagation during assembly process. Traditional method of dimension chain generation based on tolerance charting technique can not suit the case of auto-body assembly. This paper proposed a method to generate dimension chain based on developing a jot chain model of assembly, which can be integrated with important information needed for variation analysis, such as joints types and assembly sequences. The implementation of such a procedure will contribute to rapid evaluation of body dimensional quality in the design stage.

Study on optimal design to improve auto-body structural crashworthiness

In this paper the optimal model of the main energy absorbed structure in an auto-body “front rail”, based on structural crashworthiness is built. For an optimal design on structure crashworthiness, the new method is based on a response surface model and Pareto GA, which improves the efficiency and flexibility of an optimal design, that is brought forward. The traditional optimal method can not be applied in the design of an impact structure due to the high nonlinearity and large time cost of crashworthiness FE analysis. So the method of an optimal design based on crashworthiness is brought forward. After constructing the response surface model of auto-body crashworthiness, the Pareto GA can be applied to find the multi-objective globally. The optimal solution set can then be used to provide many scheme combinations for choice structural parameters.To acquire the optimized structure parameters on front rail crashworthiness, this simplified model of an original design is built. After studying various ways of reinforcing the cross-section to control the structural failure mode, a better method has been found. On the precondition of not increasing the mass of the structure, an optimal design of the front rail is performed further. Finally, the optimized scheme is implemented in the full-car impact analysis and crashworthiness is studied. With proper measures to control deformation of the front rail structure the crashworthiness can be improved with minor structural modifications.

Method of Measuring Fixture Automatic Design and Assembly for Auto-Body Part

A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose for the part model, fixture configuration and fixture elements in virtual auto-body assembly space are given. Transforming fixture element from itself coordinate system space to assembly space with homogeneous transformation matrix is realized. Based on the second development technique of unigraphics（UG）, the automated assembly is implemented with application program interface （API） function. Lastly the automated assembly of measuring fixture for rear longeron as a case is implemented.

Minimizing assembly variation in selective assembly for auto-body parts based on IGAOT

Purpose–Dimensional quality of sheet metal assemblies is an important factor for the final product.However,the part tolerance is not easily controlled because of the spring back deformation during the stamping process.Selective assembly is a means to decrease assembly tolerance of the assembly from low-precision components.Therefore,the purpose of this paper is to propose a fully efficient method of selective assembly optimization based on an improved genetic algorithm for optimization toolbox(IGAOT)in MATLAB.Design/methodology/approach–The method of influence coefficient is first applied to calculate the assembly variation of sheet metal components since the traditional rigid assembly variation model cannot be used due to welding deformation.Afterwards,the IGAOT is proposed to generate optimal selective groups,which consists of advantages of genetic algorithm for optimization toolbox(GAOT)and simulated annealing.Findings–The cases of two simple planes and the tail lamp bracket assembly are used to illustrate the flowchart of optimizing combinations of selective groups.These cases prove that the proposed IGAOT has better precision than that of GAOT with the same parameters for selective assembly.Originality/value–The research objective of this paper is to evaluate the changes from rigid bodies to sheet metal parts which are very complex for selective assembly.The method of IGAOT was proposed to the selected groups which has better precision than that of current optimization algorithms.

Application of Data Mining and Process Knowledge Discovery in Sheet Metal Assembly Dimensional Variation Diagnostic

Sheet metal is widely used on auto-bodies, plane-bodies and metal furniture, etc. For instance, a typical auto-body commonly consists of hundreds of sheet metal stamping parts. Because of its complexity of structure and manufacturing process, auto-bodies inevitably have geometrical variation results from a number of different sources, such as the geometrical variation of stamping parts, the transformation of assembly process parameters and even the improper design concept. As more than 30% quality defects of an auto-body are born from the dimensional deviation of Body-In-White originated during the manufacturing process, effective diagnosis and control of dimensional faults are essential to the continuous improvement of the quality of vehicles. Especially during the period of new car launching or model changing when the assembly process was changed and adjusted frequently. For continuously improving the quality of modern cars, rapid dimensional variation causes identification becomes a challenging but essential work. In this paper, main variation causes of auto-body was firstly been cataloged and analyzed, then, a dimensional variation diagnostic reasoning and decision approach was developed through the combination of data mining and knowledge discovery techniques. This approach is driven by variation pattern identification which can be discovered from the dispersive, isolated massive measured data: Correlation Analysis (CA) and Maximal Tree (MT) methods were applied to extract the large variation group from massive multidimensional measured data, while multivariate statistical analysis (MSA) approach was used to discovery the principle variation pattern. A Decision Tree (DT) approach based on the knowledge of product and assembly process was developed to fulfill the "Hypothesis and Validation" characterized variation causes reasoning procedure. An practical application case with sudden and severe dimension variation on rear end panel in up/down direction was analyzed and successfully solved aided by the devloped variation diagnostic method, which have proved that the approach is effective and efficient.

Research on friction law in deep drawing process of rectangular parts

Friction law is researched in rectangular parts deep drawing using simulation test ma-chine that is used to assess lubricants performance in deep drawing process. Friction coefficientsin different positions on die surface in deep drawing process are measured through probe sensors.Friction coefficients of flange corner, near straight border and far straight border are verified anddescribed quantitatively. It plays an important role in using appropriate lubricants in auto-bodypanel deep drawing process.