Sharma, S., Sahu, A., and Bhosale, S., "Multidisciplinary Design Optimization of Automobile Tail Door," SAE Technical Paper 2017-01-0251, 2017.
Stringent emission norms by government and higher fuel economy targets have urged automotive companies to look beyond conventional methods of optimization to achieve an optimal design with minimum mass, which also meets the desired level of performance targets at the system as well as at vehicle level. In conventional optimization method, experts from each domain work independently to improve the performance based on their domain knowledge which may not lead to optimum design considering the performance parameters of all domain. It is time consuming and tedious process as it is an iterative method. Also, it fails to highlight the conflicting design solutions. With an increase in computational power, automotive companies are now adopting Multi-Disciplinary Optimization (MDO) approach which is capable of handling heterogeneous domains in parallel. It facilitates to understand the limitations of performances of all domains to achieve good balance between them. The paper presents the MDO of a Tail door of a sports utility vehicle (SUV) which is carried out at the stage where major structural design has been finalized, and the only gauge of the tail door panels can be taken for design variables. The objective of the exercise was to minimize the mass while meeting various performance parameters. Modal and frequency response function (FRF) load cases are considered for noise vibration and harshness (NVH) domain and stiffness load cases for durability domain. Crashworthiness domain load cases for the tail door were not considered here because crash norms are not applicable for rear impact. Response surface based optimization method has been selected for the optimization considering resource availability and dexterity of being applied in various domains. A sensitivity study was used to identify critical panels for each performance parameter. Broken constraint charts were studied to identify the load cases which limit the mass reduction opportunity. The study showed twelve percent of mass saving which is significant for automotive doors.