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Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

In order to remain competitive in the current challenging automotive industry, there is a great demand for a common design that can be used across different platforms. Such common design can not only lower the cost due to the high volume production, but also significantly reduces the design development time. However, how to meet different programs' unique requirements by the same design remains as a challenge. In the case of a seat design, it is important that the seat natural frequencies are separated from the full vehicle system's resonant frequencies to avoid the possible alignment causing the seat vibration issue. This paper describes a method of how to design a mass damper that not only separates the seat modes from the vehicle's specific resonant frequency range but also reduces the seat back vibration amplitude significantly. The response surface based optimization method is used to tune the elastic mass damper parameters to meet the program's specific requirements.

FMVSS 207/210 relates to seat system forward longitudinal strength and is one of the most important safety requirements for seats. Seat performance to satisfy FMVSS 207/210 can be simulated using LS-DYNA FEA code. When developing a seat design there is often a need to optimize the design to satisfy requirements/meet targets and to minimize weight. However LS-DYNA does not have optimization capabilities. This paper shows how the response surface based optimization can be used to meet FMVSS 207/210 requirements and reduce weight. A number of DOE runs are performed with different combinations of upper/lower/baseline gages. Data are collected for the maximum Von Misses stress and maximum effective plastic strain in each of the major seat parts along with the total weight of the seat. Based on the collected data the response surfaces are generated using Gaussian Stochastic Kriging method.