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Water fording events are one of the most challenging situations that vehicles undergo during their lifetime. During these events the underbody components (e.g. Front fascia, Bellypan, wheel liner etc.) are subject to very high loads. Typically, vehicle water fording tests are performed for various depths of water at prescribed vehicle speeds. Water fording tests are usually carried out during the proto phase of the vehicle development program to ensure acceptable performance. If issues are discovered, making changes to the fascia or body panels are typically very expensive. To avoid late changes, a fully virtual methodology was developed to facilitate vehicle water fording performance. The simulation is targeted to evaluate multiple aspects such as air induction system and estimation of hydrodynamic loads on body panel components.

The automotive door structure experience various static and dynamic loading conditions while going through an opening and closing operation. A typical swing door is attached to the body with two hinges and a check strap. These mechanisms carry the loads while the door is opened. Similarly, while closing the door, the latch/striker mechanism along with the seal around the periphery of the door react all loads. Typically, computer aided engineering (CAE) simulations are performed considering a nominal manufacturing (or build) tolerance condition, that results in one loading scenario. But while assembling the door with the body, the build variations in door mechanisms mentioned above can result in different loading scenarios and it should be accounted for design evaluation. This paper discusses various build tolerances and its effect on door durability performances to achieve a robust door design.

In side-closures’ design, mass reduction provides numerous benefits in addition to reduced cost. This paper presents a Meta model based non-linear durability optimization to develop a lightweight structure for vehicle swing door. A surrogate model developed is using Kriging methodology and the thickness of the door components are given as input design variables. Adaptive Multi-Objective Genetic Algorithm (AMGA), a nonlinear optimization technique, is used in this study, to formulate the mass minimization under durability constraints. The optimized swing door design shows the overall mass saving of ~10% over initial design in terms of frame and sag deflection. The present investigation shows better effectiveness and practical applicability to develop the lightweight structure for the vehicle swing door.

An automobile door is a complex module, which consists of various fixed and movable subassemblies and components. Parameters such as safety, vehicle dynamics, aesthetic and strength are critical while designing the door assembly. Apart from the above, the design of door trim should minimize BSR (buzz squeak and rattle) at vehicle running conditions. Stiffness is one of the key engineering requirements which if not optimized will result in higher BSR levels and failure of the door trim components. In this study, more importance is given to optimize the stiffness of door trim. As per DVP (design verification and planning) standards of the OEMs, the range of deflection for the plastic trim parts is defined considering the conditions, comfort level and location of use. If stiffness is higher than the requirement, the door trim plastic parts are harder and will violate the quality and safety norms. If it is lower, then trim parts will not meet the functional requirements and safety norms.