Lightweight Design and Multi-Objective Optimization for a Lower Control Arm Considering Multi-Disciplinary Constraint Condition Jilin University

Format:

Book

Conference/Event

Author/Creator:

Chen, Chen, author.

Contributor:

Chen, Shuming

Liu, Zhen

Peng, Bo

Tang, Aotian

Conference Name:

WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2019

Summary:

AbstractThe requirement for low emissions and better vehicle performance has led to the demand for lightweight vehicle structures. Two new lightweight methods of design and optimization for the lower control arm were proposed in this research to improve the effectiveness of the traditional lightweight method. Prior to the two lightweight design and optimization methods, the static performance, including strength, stiffness and mode, and fatigue performance for the lower control arm were analyzed and they provided constraints for subsequent design and optimization. The first method of lightweight design and optimization was integrated application of topography optimization, size optimization, shape optimization and free shape optimization for the control arm. Topography optimization was first applied to find the optimal distribution form of reinforcement rib for the lower control arm. Size optimization was then applied in this study to optimize the plate thickness. Shape optimization was applied to determine the optimal radius of the control arm arc. Free shape optimization was also applied in this step to determine the best flange length. This method reduced weight by 32.1%. The second approach of lightweight design and optimization was multi-objective optimization for the lower control arm. The material of the lower control arm was replaced with the aluminum alloy. Topology optimization was also applied in this step to obtain an optimal distribution of the aluminum alloy. Multi-objective optimization of the lower control arm was applied through parametric modeling and the Non-Dominated Sorting Genetic Algorithm. This method reduced weight by 52%. These results indicated that the lightweight effectiveness was achieved successfully while keeping the main performance uncompromising

Notes:

Vendor supplied data

Publisher Number:

2019-01-0822

Access Restriction:

Restricted for use by site license