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Growing demand for fuel-efficient or light weight vehicle has become a challenge for vehicle development. Upfront engineering process provides more opportunities for engineers to improve body weight efficiency. To accelerate the upfront body development process, the parametric concept modeling technology is commonly employed to generate parametric three-dimensional geometry, joints, modular components, concept welding, and finite element meshes. The topology optimization which determines the best structural layout without weight penalty has also been used during the conceptual design stage. The objective of this research is to explore the feasibility of integrating the advanced parametric concept modeling and both topology optimization and structural optimization technologies into upfront body architecture development process.

Automotive crashworthiness design requires considering multiple impact modes which are often coupled by common design variables, such as sheet metal gauges. Together with different types of disciplinary design constraints and design variables, it is difficult to achieve an optimal design that meets all the design criteria with affordable cost. The objective of this research is to employ the advanced optimization and trade-off technologies to help engineers systematically get insight into the design space and subsequently select an optimal design. A vehicle example which considers multiple impact modes including full frontal, frontal offset, side, and rear impact is presented to demonstrate the proposed optimization and trade-off procedure.

This paper focuses on the methodology development and application of reliability-based design optimization to a vehicle exhaust system under noise, vibration and harshness constraints with uncertainties. Reliability-based design optimization provides a systematic way for considering uncertainties in product development process. As traditional reliability analysis itself is a design optimization problem that requires many function evaluations, it often requires tremendous computational resources and efficient optimization methodologies. Multiple functional response constraints and large number of design variables add further complexity to the problem. This paper investigates an integrated approach by taking advantages of variable screening, design of experiments, response surface model, and reliability-based design optimization for problems with functional responses. A typical vehicle exhaust system is used as an example to demonstrate the methodology.

A new, systematic, sensitivity based design process for weight reduction is presented. Traditionally, a trial and error method is used when a design fails to meet the weight and the design criteria, which often conflict. This old approach not only is time and cost consuming but also does not provide insight into structural behavior. This proposed process uses state-of-the-art technologies such as design sensitivity analysis, numerical optimization, graphical user interface, etc. It handles multi-discipline design criteria simultaneously and provides design engineers insight into structural responses for frequency, durability, and stiffness concerns and a means for systematic weight reduction and quality improvement. The new design process has been applied for the weight reduction of advanced truck frame designs. Results show that a significant weight savings has been achieved while all design criteria are met.