Multidisciplinary Design Optimization of Vehicle Weight Reduction

Author: 
Zhendan Xue (ESTECO North America)

CHALLENGE - There are many benefits to reducing vehicle weight. Among these are improving gas mileage and improving the handling and performance. Zhendan Xue from ESTECO North America presents a weight reduction case study in which two types of multidisciplinary optimization (MDO) processes are shown: All-at-Once (AAO) and Collaborative Optimization (CO). MDO is a viable approach but with many challenges, such as large number of design variables, track changes, multiple disciplines, and more.

SOLUTION - The weight reduction of a 2001 Ford Taurus vehicle is presented. 49 design variables and safety and NVH requirement constraints are considered. The MDO process is run in SOMO + modeFRONTIER. At the AAO and CO System level a genetic algorithm (GA) is picked due to its capability of handling nonlinear constraints and locating the global optimum.

BENEFITS - MOGA II in modeFRONTIER is chosen for the methodology. In the AAO optimization results, RSM based optimal design from AAO is 249.02kg, a 16.28% weight reduction from the baseline design (297.44kg). When comparing with CO, AAO in practice is clearly the first choice for this type of MDO problem.

 

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