Multi-Objective Lightweight Optimization of Parameterized Suspension Components Based on NSGA-II Algorithm Coupling with Surrogate Model

被引:38
作者
Jiang, Rongchao [1 ]
Jin, Zhenchao [1 ]
Liu, Dawei [1 ]
Wang, Dengfeng [2 ]
机构
[1] Qingdao Univ, Coll Mech & Elect Engn, Qingdao 266071, Peoples R China
[2] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130022, Peoples R China
基金
中国国家自然科学基金;
关键词
suspension components; vehicle dynamics performance; surrogate model; lightweighting; multi-objective optimization; DESIGN; CRASHWORTHINESS;
D O I
10.3390/machines9060107
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to reduce the negative effect of lightweighting of suspension components on vehicle dynamic performance, the control arm and torsion beam widely used in front and rear suspensions were taken as research objects for studying the lightweight design method of suspension components. Mesh morphing technology was employed to define design variables. Meanwhile, the rigid-flexible coupling vehicle model with flexible control arm and torsion beam was built for vehicle dynamic simulations. The total weight of control arm and torsion beam was taken as optimization objective, as well as ride comfort and handling stability performance indexes. In addition, the fatigue life, stiffness, and modal frequency of control arm and torsion beam were taken as the constraints. Then, Kriging model and NSGA-II were adopted to perform the multi-objective optimization of control arm and torsion beam for determining the lightweight scheme. By comparing the optimized and original design, it indicates that the weight of the optimized control arm and torsion beam are reduced 0.505 kg and 1.189 kg, respectively, while structural performance and vehicle performance satisfy the design requirement. The proposed multi-objective optimization method achieves a remarkable mass reduction, and proves to be feasible and effective for lightweight design of suspension components.
引用
收藏
页数:15
相关论文
共 22 条
[1]   High performance automotive chassis design: a topology optimization based approach [J].
Cavazzuti, Marco ;
Baldini, Andrea ;
Bertocchi, Enrico ;
Costi, Dario ;
Torricelli, Enrico ;
Moruzzi, Patrizio .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2011, 44 (01) :45-56
[2]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[3]   Automotive Lightweight Design: Simulation Modeling of Mass-Related Consumption for Electric Vehicles [J].
Del Pero, Francesco ;
Berzi, Lorenzo ;
Antonacci, Andrea ;
Delogu, Massimo .
MACHINES, 2020, 8 (03)
[4]   Multi-objective system reliability-based optimization method for design of a fully parametric concept car body [J].
Duan, Libin ;
Li, Guangyao ;
Cheng, Aiguo ;
Sun, Guangyong ;
Song, Kai .
ENGINEERING OPTIMIZATION, 2017, 49 (07) :1247-1263
[5]   Multi-objective shape optimization of body-in-white based on mesh morphing technology [J].
Fang, Jianguang ;
Gao, Yunkai ;
Wang, Jingren ;
Wang, Yuan .
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2012, 48 (24) :119-126
[6]   A-type frame fatigue life estimation of a mining dump truck based on modal stress recovery method [J].
Gu, Zhengqi ;
Mi, Chengji ;
Wang, Yutao ;
Jiang, Jinxing .
ENGINEERING FAILURE ANALYSIS, 2012, 26 :89-99
[7]   Optimal Design and Control of a Two-Speed Planetary Gear Automatic Transmission for Electric Vehicle [J].
Huang, Wei ;
Huang, Jianfeng ;
Yin, Chengliang .
APPLIED SCIENCES-BASEL, 2020, 10 (18)
[8]  
[蒋荣超 Jiang Rongchao], 2021, [汽车工程, Automotive Engineering], V43, P421
[9]  
[蒋荣超 Jiang Rongchao], 2016, [吉林大学学报. 工学版, Journal of Jilin University. Engineering and Technology Edition], V46, P35
[10]  
[李兆凯 Li Zhaokai], 2016, [中国公路学报, China Journal of Highway and Transport], V29, P149