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Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

Corrosion tendency is one of the major inhibitors for increased use of magnesium alloys in automotive structural applications. Moreover, systematic or standardized methods for evaluation of both general and galvanic corrosion of magnesium alloys, either as individual components or eventually as entire subassemblies, remains elusive, and receives little attention from professional and standardization bodies. This work reports outcomes from an effort underway within the U.S. Automotive Materials Partnership - ‘USAMP’ (Chrysler, Ford and GM) directed toward enabling technologies and knowledge base for the design and fabrication of magnesium-intensive subassemblies intended for automotive “front end” applications. In particular, subassemblies consisting of three different grades of magnesium (die cast, sheet and extrusion) and receiving a typical corrosion protective coating were subjected to cyclic corrosion tests as employed by each OEM in the consortium.

The helical spring is one of fundamental mechanical elements used in various industrial applications such as valves, suspension mechanisms, shock and vibration absorbers, hand levers, etc. In high speed applications, for instance in the internal combustion engine or in reciprocating compressor valves, helical springs are subjected to dynamic and impact loading, which can result in a phenomenon called “surge”. Hence, proper design and selection of helical springs should consider modeling the dynamic and impact response. In order to correctly characterize the physics of a helical spring and its response to dynamic excitations, a comprehensive model of spring elasticity for various spring coil and wire geometries, spring inertial effects as well as contacts between the windings leading to a non-linear spring force behavior is required. In practical applications, such models are utilized in parametric design and optimization studies.

This presentation evaluates the contribution of multi-objective programming scheme for the conceptual design of the Hybrid Electric Vehicle frame's structure using topological optimization. The compromise programming method was applied to describe the statically loaded multicompliance topology optimization. Solid Isotropic Material with Penalization (SIMP) was used as the interpolation scheme to indicate the dependence of material modulus upon regularized element densities. The sequential convex programming approach was applied to solve the optimization problem. The application on the chassis frame was used to demonstrate the characteristics of the presented methodologies based on the commercial software package OptiStruct.

In this paper, the finite element model for static analysis of an electric tractor's frame is presented firstly, and the rigidity and strength of one electric tractor's frame is calculated. Based upon the analysis results, the topology and shape of this electric tractor's frame is optimized. As to the topology optimization, the optimization goal under multiple load cases is defined and the frame is optimized by two steps-one is to determine the position of the transverse rails using solid elements which can simulate the material-filling space, another is to obtain the shape of the frame in which shell elements are applied as to increase the calculation efficiency. After the topology optimization the frame's stiffness is improved significantly but there still is local stress concentration. So the shape of the stress concentration area is optimized using control points method, and the greatest stress is reduced below the strength limits.

Since statistics indicate that front impact is the major accident type, Ford has been studying energy-absorbing structures for some time. Early designs such as the “ball and tube” and “rail splitter” were discarded in favor of the “S” frame. Details of the design approach and testing are given in this paper. Design objectives were increased effective collapse distance, compatibility with production practices, and maintenance of satisfactory noise, vibration, and harshness levels. Safety objectives are improved passenger compartment integrity and reduction of seat belt loads. Barrier crash tests at 30 mph (equivalent to collision into standing vehicle at 50 mph) were used to evaluate the design of the “S” frame. Results of testing indicate that occupant restraint with seat belts, combined with front end structural improvements, offer the most promise for injury reduction during service front impact accidents.