The design of a complex system such as an automobile consists of the design of many highly complex subsystems. To address this level of complexity, traditionally the designers use a sequential and spiral design process with the goal of achieving a final feasible design that meets all of the competing and, sometimes, conflicting subsystem requirements. This process is highly influenced by designer's subjectivity and may lead to a suboptimal system design. Furthermore, the influence of subsystems on the overall design is reduced as the design progresses sequentially along the design spiral.
This paper explores the development and applicability of an alternative Multidisciplinary Design Optimization (MDO) method, utilizing decomposition based optimization schemes. A simplified Synthesis Design Model (SDM) is developed that expresses the marketability of a standard midsize sedan on the U.S market based on fuel efficiency, curb weight and market price. The model decomposes the overall system into these coupled subsystems in a manner suitable for advanced optimization methods such as Collaborative Optimization (CO). Several preliminary Design Space Exploration (DSE) and multi-objective optimization studies are conducted and reported.
The results of this preliminary work show that early stage synthesis design of automobiles can be substantially enhanced by using advanced MDO and CO theories together with appropriate software. The fidelity of the optimized design produced by this method depends on the complexity and fidelity of the models used to define the overall system and subsystems. Development of more comprehensive decomposed SDM models are required for practical application of this approach to new and innovative designs. These models should preferably be developed in collaboration with manufacturers in order to include relevant new and often classified data.
