Tail-welded blanks (TWBs) are widely used in automotive bodies to improve the structural performance and reduce weight. The stiffness and modal lightweight design optimisation of TWBs for automotive doors was performed in this study. The finite element model was validated through physical experiments. An L27 (3¹²) Taguchi orthogonal array was used to collect the sample points. The multi-objective optimisation problem was transformed into a single-objective optimisation problem based on the grey relational degree. The optimal combination of structural design parameters was obtained for a tail-welded door using the proposed method, and the weight of the door structure was reduced by 2.83 kg. The proposed optimisation method has fewer iterations and a lower computational cost, enabling the design of lightweight TWBs.

The characteristics of a mechanical structure under operating conditions may differ from those in a static state. It is often more desirable to obtain the frequency response function (FRF) of the operating structure in engineering applications. While operational modal analysis (OMA) can estimate modal parameters during operation, it fails to provide mass-normalized mode shapes for FRF synthesis. This paper presents a new method using experimental modal analysis (EMA) to compensate for the absent information in OMA. It categorizes operational mode shapes into changed ones and those that remain the same compared to the static state, applying different scaling techniques accordingly. This method adapts to changes in dynamic characteristics without altering the operating conditions. Stability is emphasized throughout the process. Two examples are provided to verify the method, considering noise and incompleteness in measurement, and disturbances in dynamic properties. The proposed method is proven to be feasible and reliable to capture the changes in operational FRFs.