Abstract
Multidisciplinary Design Optimization (MDO) of an automobile body structure is a challenging task as it involves multiple, often conflicting requirements of crash, durability & NVH. Conventionally MDO process requires running large number of design of experiments (DOE) to explore the full design space and to build response surface for optimization. As the crash simulations are highly nonlinear in nature, they typically require significant amount of computational time and resources when compared to the NVH and durability simulations. Hence, the conventional MDO approach is too expensive and time consuming. In this paper, strategies for quick MDO approaches are explored compared to conventional MDO. One such process identified is the Hybrid MDO process using the combination of RSM based optimization & Equivalent Static Load (ESL) method. In the suggested method, RSM based approach is used for NVH and Durability analyses and ESL method for crash analyses to achieve quick MDO results. The basic idea of the ESL is to divide the original nonlinear dynamic optimization problem into an iterative linear optimization and nonlinear analysis process. In the present work, MDO has been performed on the body structure of a SUV using Hybrid algorithm & Conventional MDO methodologies. Critical global load cases from safety, durability & NVH domains have been identified as constraints and problem is solved with an objective of minimizing the mass through gauge optimization method (Sizing). It is noted from the results that there is a substantial reduction of computation time in Hybrid MDO for reaching the same accuracy of results as that of conventional MDO