Analytical Target Cascading for Multi-Mode Design Optimization: An Engine Case Study

Abstract

Advances in design and information science have enabled the engineering community to look into changeable systems that work under multiple operating scenarios or modes. In this paper, a multidisciplinary design optimization approach for changeable systems is presented, with its focus on sharing a uniform part of system configuration across all the operating scenarios. Compared to the fully adaptive system approach, this approach enables reduction in the computational expense due to the repetitive mode-by-mode optimization, which becomes impractical as the number of modes increases. In the proposed approach, Analytical Target Cascading (ATC), a hierarchical optimization methodology, models the multi-mode design optimization in a two-level structure: the subsystem problems achieve the performance targets through optimizing local copies of the system configuration; and the system problem coordinates system configuration copies at multiple modes to obtain consistency. Local objectives are introduced to accommodate (unattainable) targets assigned locally for the individual systems, and a weight-updating scheme utilizing local objective information is proposed to balance among performance deviations at multiple modes. A case study on industrial engine simulation parameter identification demonstrates the effectiveness of the proposed approach.