Please wait a minute...
浙江大学学报(工学版)  2020, Vol. 54 Issue (8): 1490-1496    DOI: 10.3785/j.issn.1008-973X.2020.08.006
机械工程     
基于克里金模型的微电热驱动器优化设计
陈浩(),王新杰,王炅*(),席占稳,曹云
南京理工大学 机械工程学院,江苏 南京 210094
Optimization and design of micro-electro-thermal actuator based on Kriging model
Hao CHEN(),Xin-jie WANG,Jiong WANG*(),Zhan-wen XI,Yun CAO
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
 全文: PDF(1128 KB)   HTML
摘要:

基于局部型四维参数的函数,采用克里金代理模型和遗传-粒子群(GA-PSO)优化算法,开展大位移U型电热驱动器优化设计研究. 建立U型电热驱动器的多物理场仿真模型并进行实验验证. 发现在不同电压下,电热驱动器仿真位移与实验位移曲线一致,从而保证克里金模型中样本数据来源的可靠性. 搭建ANSYS和MATLAB联合自动仿真平台以解决克里金模型中样本数据的批量采集问题. 基于该平台,采用简单随机抽样的方法,得到不同采样点下电热驱动器的位移,从而形成样本数据. 根据样本数据建立克里金模型并基于该模型采用遗传-粒子群算法进行参数优化. 研究结果表明,克里金模型能代替有限元模型准确预测驱动器的位移;控制驱动器形状的4个关键参数与位移成单调关系;经形状优化后,18 V电压下U型电热驱动器的位移提高35.2%.

关键词: 电热驱动器优化联合仿真克里金模型遗传-粒子群优化(GA-PSO)算法    
Abstract:

A combination of the Kriging surrogate model and the genetic and particle swarm optimization (GA-PSO) algorithm was applied to the design and optimization of the U-shaped electro-thermal actuator with large displacement, based on the local function with four parameters. The multi-physical coupling simulation model of the U-shaped electro-thermal actuator was established and validated by experiment. The displacement from simulation shows a good agreement with that from experiment with different voltages, which ensures the accuracy of the sample data for the Kriging model. A co-simulation using ANSYS and MATLAB was created, which can capture the sample data in batches. The simple random sampling was utilized to get sample points. The displacements of different sample points were obtained as sample data. The Kriging model was established with the sample data and the GA-PSO algorithm was used for optimization based on the established Kriging model. Results show that the Kriging model can replace the simulation model for predicting the displacement of the U-shaped actuator precisely. The monotonic relationship exists between the displacement and each of the four key parameters, which can decide the shape of the actuator. The displacement of the U-shaped actuator increases 35.2% under 18 V after the shape optimization.

Key words: electro-thermal actuator    optimization    co-simulation    Kriging model    genetic and particle swarm optimization (GA-PSO) algorithm
收稿日期: 2019-12-03 出版日期: 2020-08-28
CLC:  TH 122  
基金资助: 国家自然科学基金资助项目(51675282,51805268)
通讯作者: 王炅     E-mail: 17766106120@163.com;wjiongz@njust.edu.cn
作者简介: 陈浩(1993—),男,博士生,从事微光机电研究. orcid.org/0000-0002-6334-2345. E-mail: 17766106120@163.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  
陈浩
王新杰
王炅
席占稳
曹云

引用本文:

陈浩,王新杰,王炅,席占稳,曹云. 基于克里金模型的微电热驱动器优化设计[J]. 浙江大学学报(工学版), 2020, 54(8): 1490-1496.

Hao CHEN,Xin-jie WANG,Jiong WANG,Zhan-wen XI,Yun CAO. Optimization and design of micro-electro-thermal actuator based on Kriging model. Journal of ZheJiang University (Engineering Science), 2020, 54(8): 1490-1496.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2020.08.006        http://www.zjujournals.com/eng/CN/Y2020/V54/I8/1490

图 1  U型电热驱动器的结构
T/K λ/(W?(m?K)?1
单晶硅 空气
300 146.4 0.026 9
600 57.5 0.044 4
900 37.6 0.061 6
1 200 28.2 0.078 1
1 500 25.1 0.093 6
表 1  单晶硅和空气的热传导系数与温度的关系
材料 E/GPa μ ρ/(Ω?mm) α/K?1
169 0.28 0.22 2.6×10?6
空气 ? ? 3×1016 ?
表 2  单晶硅和空气的材料参数
图 2  ANSYS中的U型电热驱动器几何模型
图 3  ANSYS和MATLAB联合仿真流程图
参数 数值/μm 参数 数值/μm
Lh 3 200 Wc 340
Lc 2 700 Wf 50
Wh 50 tg 100
g 50 ? ?
表 3  加工后的U型电热驱动器测量尺寸
图 4  加工后的U型电热驱动器结构
图 5  U型电热驱动器位移测量实验装置
图 6  不同电压下U型电热驱动器的实验与仿真位移
图 7  克里金模型整体优化流程图
图 8  样本点处U型电热驱动器克里金模型预测位移和仿真计算位移
图 9  样本点处克里金模型与仿真模型的预测位移结果误差
图 10  U型电热驱动器中单一设计变量与位移间的关系
图 11  冷、热臂宽度同时作用下U型电热驱动器位移的变化
μm
阶段 Lf Wh g Wc D
克里金 有限元
初始0 500 50 50 340 ? 87.3
优化1 279 42 58 263 107.4 107.0
优化2 292 44 46 257 109.9 109.0
优化3 243 43 68 395 120.3 118.0
表 4  U型电热驱动器不同优化尺寸下的位移
图 12  遗传-粒子群组合算法中迭代次数与位移关系
1 THANGAVEL A, RENGASWAMY R, SUKUMAR P K, et al Modelling of Chevron electrothermal actuator and its performance analysis[J]. Microsystem Technologies, 2018, 24 (4): 1767- 1774
doi: 10.1007/s00542-018-3791-8
2 KOLAHDOOZAN M, ROUHANI E A, HASSANI M Experimental and numerical investigation of the arms displacement in a new electrothermal MEMS actuator[J]. Advanced Design and Manufacturing Technology, 2017, 10 (2): 71- 81
3 AFRANG S, NEMATKHAH N A new MEMS based variable capacitor using electrostatic vertical comb drive actuator and auxiliary cantilever beams[J]. Microsystem Technologies, 2019, (2): 1- 11
4 SHABESTARI N P, VAZIRI M R R, BAKHSHANDEH M, et al Fabrication of a simple and easy-to-make piezoelectric actuator and its use as phase shifter in digital speckle pattern interferometry[J]. Journal of Optics, 2019, 48 (2): 272- 282
5 TAKANAMI S, KITAGAWA W, TAKESHITA T. Design for improvement of torque-thrust characteristic in simultaneous drive in two-degree-of-freedom electromagnetic actuator [C]// International Conference on Electrical Machines and Systems. Chiba: IEEE, 2017.
6 KARBASI S M, SHAMSHIRSAZ M, NARAGHI M, et al Optimal design analysis of electrothermally driven microactuators[J]. Microsystem Technologies, 2010, 16 (7): 1065- 1071
doi: 10.1007/s00542-009-0959-2
7 CHEN R S, KUNG C, LEE G B Analysis of the optimal dimension on the electrothermalmicroactuator[J]. Journal of Micromechanics and Microengineering, 2002, 12 (3): 291- 296
doi: 10.1088/0960-1317/12/3/315
8 ATRE A. Design optimization of a surface micromachined electro-thermal beam flexure polysilicon actuator [C] // Proceedings of the Modeling and Simulation of Microsystems. Anaheim: [s.n.], 2005: 493-496.
9 HUANG Q A, KA N, LEE S Analysis and design of polysilicon thermal flexure actuator[J]. Journal of Micromechanics and Microengineering, 1999, 9 (1): 64- 70
doi: 10.1088/0960-1317/9/1/308
10 MAYYAS M, SHIAKOLAS P S, LEE W H, et al Thermal cycle modeling of electro thermal microactuators[J]. Sensors and Actuators: A Physical, 2009, 152 (2): 192- 202
doi: 10.1016/j.sna.2009.03.015
11 HUSSEIN H, TAHHAN A, LE MOAL P, et al Dynamic electro-thermo-mechanical modelling of a U-shaped electro-thermal actuator[J]. Journal of Micromechanics and Microengineering, 2016, 26 (2): 025010
doi: 10.1088/0960-1317/26/2/025010
12 ANTONOVA E E, LOOMAN D C. Finite elements for thermoelectric device analysis in ANSYS [C] // 24th InternationalConference on Thermoelectrics. Clemson: IEEE, 2005.
13 HICKEY R, SAMEOTO D, HUBBARD T, et al Time and frequency response of two-arm micromachined thermal actuators[J]. Journal of Micromechanics and Microengineering, 2003, 13 (1): 40- 46
doi: 10.1088/0960-1317/13/1/306
14 MUKHIYA R, AGARWAL P, BADJATYA S, et al Design, modelling and system level simulations of DRIE-based MEMS differential capacitive accelerometer[J]. Microsystem Technologies, 2019, (6): 3521- 3532
15 KLEIJNEN J P C Kriging metamodeling in simulation: a review[J]. European Journal of Operational Research, 2009, 192 (3): 707- 716
doi: 10.1016/j.ejor.2007.10.013
16 SIMPSON T W, MAUERY T M, KORTE J J, et al Kriging models for global approximation in simulation-based multidisciplinary design optimization[J]. AIAA Journal, 2001, 39 (12): 2233- 2241
doi: 10.2514/2.1234
17 RUI W, CHEN S, MA L, et al. Multi-indicator bacterial foraging algorithm with kriging model for many-objective optimization [C]// International Conference on Swarm Intelligence. Shanghai: Spring Cham, 2018: 530-539.
18 SAAD A, DONG Z, BUCKHAM B, et al A new Kriging–bat algorithm for solving computationally expensive black-box global optimization problems[J]. Engineering Optimization, 2018, 51: 1- 21
19 KIM H, HIRTA K Vector control for loss minimization of induction motor using GA–PSO[J]. Applied Soft Computing Journal, 2008, 8 (4): 1692- 1702
doi: 10.1016/j.asoc.2006.09.001
20 CHEN W C, NGUYEN M H, CHIU W H, et al Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO[J]. International Journal of Advanced Manufacturing Technology, 2016, 83 (9?12): 1873- 1886
doi: 10.1007/s00170-015-7683-0
[1] 李伟达,王柱,张虹淼,李娟,顾洪. 床式步态康复训练系统机构设计[J]. 浙江大学学报(工学版), 2021, 55(5): 823-830.
[2] 赵福林,张通,马光,陈哲,郭创新,张金江. 考虑源-荷波动的电力系统灵活性运行域研究[J]. 浙江大学学报(工学版), 2021, 55(5): 935-947.
[3] 高新智,刘作军,张燕,陈玲玲. 基于GWO-SVM的下肢假肢穿戴者骑行相位识别[J]. 浙江大学学报(工学版), 2021, 55(4): 648-657.
[4] 于勇,薛静远,戴晟,鲍强伟,赵罡. 机加零件质量预测与工艺参数优化方法[J]. 浙江大学学报(工学版), 2021, 55(3): 441-447.
[5] 李伟达,李娟,李想,张虹淼,顾洪,史逸鹏,张浩杰,孙立宁. 欠驱动异构式下肢康复机器人动力学分析及参数优化[J]. 浙江大学学报(工学版), 2021, 55(2): 222-228.
[6] 季琳琳,王清威,周豪,郑美妹. 考虑顾客满意度的冷链水果路径优化[J]. 浙江大学学报(工学版), 2021, 55(2): 307-317.
[7] 王忠宇,王玲,王艳丽,吴兵. 基于网络变结构优化的大型活动交通拥堵预防方法[J]. 浙江大学学报(工学版), 2021, 55(2): 358-366.
[8] 马一凡,赵凡宇,王鑫,金仲和. 基于改进指针网络的卫星对地观测任务规划方法[J]. 浙江大学学报(工学版), 2021, 55(2): 395-401.
[9] 王进,王向坤,扶建辉,陆国栋,金超超,陈燕智. 重载机器人横梁结构静动态特性分析与优化[J]. 浙江大学学报(工学版), 2021, 55(1): 124-134.
[10] 李笑竹,王维庆. 区域综合能源系统两阶段鲁棒博弈优化调度[J]. 浙江大学学报(工学版), 2021, 55(1): 177-188.
[11] 楼恺俊,俞峰,夏唐代,马健. 黏土中地下连续墙支护结构的稳定性分析[J]. 浙江大学学报(工学版), 2020, 54(9): 1697-1705.
[12] 毛晨涛,陈章位,张翔,祖洪飞. 基于相对精度指标的机器人运动学校准[J]. 浙江大学学报(工学版), 2020, 54(7): 1316-1324.
[13] 黄凯,孙志坚,钱文瑛,杨继虎,俞自涛,胡亚才. 中间介质型烟气换热器无量纲材料成本模型[J]. 浙江大学学报(工学版), 2020, 54(7): 1362-1368.
[14] 王跃,周振邦,彭赟. 三电平双模块并联协同特定谐波消除脉宽调制[J]. 浙江大学学报(工学版), 2020, 54(7): 1425-1432.
[15] 喻伯平,李高华,谢亮,王福新. 基于代理模型的旋翼翼型动态失速优化设计[J]. 浙江大学学报(工学版), 2020, 54(4): 833-842.