Please wait a minute...
浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2023, Vol. 57 Issue (3): 606-615    DOI: 10.3785/j.issn.1008-973X.2023.03.019
    
Parameters optimization design of dual-input dual-buck inverter system based on hyperplane NSGA-II
Huang LI1(),Hong-juan GE1,2,*(),Ying MA3,Yong-shuai WANG2
1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211016, China
3. COMAC Shanghai Aircraft Design and Research Institute, Shanghai 201210, China
Download: HTML     PDF(1205KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

Aiming at the problems of uneven population distribution and slow convergence in the calculation process of non-dominated sorting genetic algorithm II (NSGA-II), a hyperplane NSGA-II (HP-NSGA-II) was proposed. The algorithm constructed a hyperplane by connecting extreme points reflecting the edge distribution of the population, with its normal vector as the evolutionary trend, the critical layer individuals were projected on the hyperplane, which promoted the population to evolve towards the optimal solution with uniform distribution and good convergence. Dual-input dual-buck inverter (DIDBI) was a multi-objective optimization object, the switching loss, total harmonic distortion of output voltage, and volume of filter elements were regarded as optimization objectives. According to the requirements of resonant frequency, inductor current ripple, and the power factor, the constraint conditions of filter capacitance, filter inductance, and switching frequency were derived. The application situation and value of the HP-NSGA-II were compared with NSGA-II and γ-NSGA-II considering the importance of each target. An Inverter prototype was regarded as an example, the experimental research on parameters optimization design was carried out, and the results show the effectiveness and correctness of the design.

Key words： dual-input dual-buck inverter (DIDBI)      hyperplane-non-dominated sorting genetic algorithm II (HP-NSGA-II)      multi-objective      system parameter     
Received: 23 March 2022      Published: 31 March 2023
CLC:  TM 46  
Fund:  国家自然科学基金委员会-中国民用航空局民航联合研究基金项目资助（U2233205，U1933115，U2133203）
Corresponding Authors: Hong-juan GE     E-mail: 15834188137@163.com;allenge@nuaa.edu.cn
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Huang LI
Hong-juan GE
Ying MA
Yong-shuai WANG
Cite this article:

Huang LI,Hong-juan GE,Ying MA,Yong-shuai WANG. Parameters optimization design of dual-input dual-buck inverter system based on hyperplane NSGA-II. Journal of ZheJiang University (Engineering Science), 2023, 57(3): 606-615.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2023.03.019     OR     https://www.zjujournals.com/eng/Y2023/V57/I3/606


基于超平面NSGA-II的双输入双降压逆变器系统参数优化设计

针对第二代非支配排序遗传算法（NSGA-II）计算过程中存在种群分布不均匀、收敛性速度较慢的问题，提出超平面NSGA-II（HP-NSGA-II）. 该算法通过连接反映种群边缘分布的极值点构造超平面，以其法向量为进化趋势，对临界层个体在超平面进行投影，促使种群朝着分布均匀且收敛良好的最优解进化. 以双输入双降压型逆变器（DIDBI）为多目标优化对象，开关损耗、输出电压总谐波失真和滤波元件体积为优化目标，依据谐振频率、电感电流纹波和功率因数的要求，推导出滤波电容、滤波电感和开关频率的约束条件，比较分析HP-NSGA-II与NSGA-II、考虑各目标重要度的 ${\boldsymbol{\gamma}} $-NSGA-Ⅱ的应用场合和价值. 以某型逆变器样机为例，开展参数优化设计实验研究，结果表明了设计的有效性与正确性.


关键词： 双输入双降压型逆变器(DIDBI),  超平面第二代非支配排序遗传算法(HP-NSGA-II),  多目标,  系统参数 
Fig.1 Topology of dual-input dual-buck inverter
Fig.2 Switching processes of switches and diodes
Fig.3 Flow chart of hyperplane non-dominated sorting genetic algorithm II
Fig.4 Hyperplane construction of critical layer individual based on hyperplane non-dominated sorting genetic algorithm II
Fig.5 Performance test experiment of hyperplane non-dominated sorting genetic algorithm II
Fig.6 Evolution process of each objective function values before and after improvement of non-dominated sorting genetic algorithm II
编号 NSGA-Ⅱ HP-NSGA-II γ-NSGA-Ⅱ,γ1 = [THD, VL,Ploss] γ-NSGA-Ⅱ,γ2 = [Ploss, THD,VL]
THD V/dm3 Ploss/W THD V/dm3 Ploss/W THD V/dm3 Ploss/W THD V/dm3 Ploss/W
1 0.041 0.060 12.27 0.036 0.055 12.01 0.028 0.061 12.41 0.040 0.064 11.78
2 0.043 0.064 12.30 0.034 0.057 12.16 0.030 0.063 12.33 0.039 0.065 11.71
3 0.040 0.058 12.28 0.035 0.054 12.05 0.029 0.062 12.30 0.042 0.064 11.77
4 0.039 0.059 12.23 0.035 0.052 12.05 0.029 0.059 12.41 0.041 0.066 11.82
5 0.042 0.057 12.25 0.037 0.055 12.02 0.030 0.059 12.41 0.043 0.067 11.69
6 0.040 0.060 12.20 0.036 0.053 12.01 0.028 0.061 12.39 0.042 0.068 11.75
7 0.041 0.062 12.25 0.033 0.051 12.06 0.030 0.058 12.35 0.044 0.064 11.76
8 0.042 0.060 12.26 0.036 0.054 12.02 0.030 0.059 12.37 0.041 0.066 11.83
9 0.042 0.058 12.31 0.037 0.053 12.08 0.031 0.063 12.32 0.042 0.065 11.80
10 0.041 0.059 12.24 0.035 0.050 12.09 0.029 0.062 12.33 0.041 0.063 11.77
平均 0.041 0.060 12.26 0.035 0.053 12.05 0.029 0.061 12.36 0.042 0.065 11.77
Tab.1 Comparison of the fiftieth generation Pareto solution set before and after algorithm improvement
Fig.7 Prototype of dual-input dual-buck inverter
Fig.8 Output voltage waveforms of dual-input dual-buck inverter
[1]   卢其威, 邓欢, 陈婷, 等 LLCC谐振滤波器在高频正弦波逆变器中的优化设计[J]. 电工技术学报, 2017, 32 (20): 142- 152
LU Qi-wei, DENG Huan, CHEN Ting, et al Parameters optimization and design of LLCC resonant converter in high frequency sinusoidal inverter[J]. Transactions of China Electrotechnical Society, 2017, 32 (20): 142- 152
[2]   张俊红, 郭迁, 王健, 等 塑料机油冷却器盖加强筋参数的多目标优化[J]. 浙江大学学报: 工学版, 2016, 50 (7): 1360- 1366
ZHANG Jun-hong, GUO Qian, WANG Jian, et al Multi-objective optimization of ribs design parameters for plastic oil cooler cover[J]. Journal of Zhejiang University: Engineering Science, 2016, 50 (7): 1360- 1366
[3]   CHEW C K, KONDAPALLI S R R. Modelling, analysis, simulation and design optimization (genetic algorithm) of DC-DC converter for uninterruptible power supply applications [C]// 2005 International Conference on Power Electronics and Drive Systems. Kuala Lumpur: IEEE, 2006: 1530-1535.
[4]   WU Biao, ZHANG Lei, MENG Jin An optimization design method of low frequency resonant filter based on NSGA-II[J]. Electrical Measurement and Instrumentation, 2018, 55 (10): 62- 67
[5]   ELKHOLY M M, EL-HAMEED M A, EL-FERGANY A A Harmonic analysis of hybrid renewable microgrids comprising optimal design of passive filters and uncertainties[J]. Electric Power Systems Research, 2018, 163: 491- 501
doi: 10.1016/j.jpgr.2018.07.023
[6]   SRINIVAS N, DEB K Multiobjective function optimization using nondominated sorting genetic algorithms[J]. Evolutionary Computation, 1994, 2 (3): 221- 248
doi: 10.1162/evco.1994.2.3.221
[7]   DEB K, PRATAP A, AGARWAL S, et al A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6 (2): 182- 197
doi: 10.1109/4235.996017
[8]   程虹, 高元海, 王淳, 等 基于无重访NSGA-Ⅱ算法的配电网多目标重构[J]. 电力系统保护与控制, 2016, 44 (23): 10- 16
CHENG Hong, GAO Yuan-hai, WANG Chun, et al Multi-objective distribution network reconfiguration based on non-revisiting NSGA-II algorithm[J]. Power System Protection and Control, 2016, 44 (23): 10- 16
[9]   苏玉刚, 陈苓芷, 唐春森, 等 基于NSGA-Ⅱ算法的ECPT系统PID参数寻优及输出稳压控制[J]. 电工技术学报, 2016, 31 (19): 106- 114
SU Yu-gang, CHEN Ling-zhi, TANG Chun-sen, et al Evolutionary multi-objective optimization of PID parameters for output voltage regulation in ECPT system based on NSGA-Ⅱ[J]. Transactions of China Electrotechnical Society, 2016, 31 (19): 106- 114
[10]   何忠华, 袁一星 基于剩余能量熵的供水管网可靠性优化设计[J]. 浙江大学学报: 工学版, 2014, 48 (7): 1188- 1194
HE Zhong-hua, YUAN Yi-xing Reliability optimization design of water distribution system based on surplus energy entropy[J]. Journal of Zhejiang University: Engineering Science, 2014, 48 (7): 1188- 1194
[11]   刘思. 基于NSGA-Ⅱ算法的SWISS整流器多目标优化研究 [D]. 哈尔滨: 哈尔滨理工大学, 2020.
LIU Si. Multi-objective optimization of SWISS rectifier based on NSGA-Ⅱ algorithm [D]. Harbin: Harbin University of Science and Technology, 2020.
[12]   王康, 王久和, 王路 低压开关槽式变换器多目标优化[J]. 西安科技大学学报, 2021, 41 (5): 938- 947
WANG Kang, WANG Jiu-he, WANG Lu Multi-objective optimization of switched-tank converter for low-voltage applications[J]. Journal of Xi’an University of Science and Technology, 2021, 41 (5): 938- 947
[13]   MOHAMMADI M Bacterial foraging optimization and adaptive version for economically optimum sitting, sizing and harmonic tuning orders setting of LC harmonic passive power filters in radial distribution systems with linear and nonlinear loads[J]. Applied Soft Computing, 2015, 29: 345- 356
doi: 10.1016/j.asoc.2015.01.021
[14]   杨帆, 葛红娟, 党润芸, 等 一种双直流输入多电平双Buck逆变器[J]. 电工技术学报, 2018, 33 (6): 1320- 1327
YANG Fan, GE Hong-juan, DANG Run-yun, et al A dual-DC-input multi-level dual-buck inverter[J]. Transactions of China Electrotechnical Society, 2018, 33 (6): 1320- 1327
[15]   中国民用航空局. 中国民用航空技术标准规定 航空静止变流器: CTSO-C73 [S]. 北京: [s.n], 2019.
[16]   ZHANG L, GE H J, MA Y, et al Multi-objective optimization design of a notch filter based on improved NSGA-II for conducted emissions[J]. IEEE Access, 2020, 8: 83213- 83223
doi: 10.1109/ACCESS.2020.2991576
[17]   YANG F, GE H J, YANG J F, et al A Family of dual-buck inverters with an extended low-voltage DC-input port for efficiency improvement based on dual-input pulsating voltage-source cells[J]. IEEE Transactions on Power Electronics, 2017, 33 (4): 3115- 3128
[18]   胡存刚, 姚培, 张云雷, 等 高效非隔离单相并网MOSFET逆变器拓扑及控制策略[J]. 电工技术学报, 2016, 31 (13): 82- 91
HU Cun-gang, YAO Pei, ZHANG Yun-lei, et al Topology and control strategy for high-efficient non-isolated single-phase grid-connected MOSFET inverter[J]. Transactions of China Electrotechnical Society, 2016, 31 (13): 82- 91
doi: 10.3969/j.issn.1000-6753.2016.13.010
[19]   全国电磁兼容标准化管理委员会. 电磁兼容 试验和测量技术供电系统及所连设备谐波、谐间波的测量和测量仪器导则: GB/T 17626.7—2008 [S]. 北京: [s.n.], 2009.
[20]   叶海云, 马海啸 三相四桥臂逆变器输出滤波器的优化设计[J]. 电力电子技术, 2015, 49 (5): 93- 95
YE Hai-yun, MA Hai-xiao The optimal design of the output filter for three-phase four-leg inverter[J]. Power Electronics, 2015, 49 (5): 93- 95
[21]   郑征, 高照阳, 张展 基于虚拟电阻的PWM逆变器LC输出滤波器的研究[J]. 测控技术, 2017, 36 (3): 127- 131
ZHENG Zheng, GAO Zhao-yang, ZHANG Zhan Research on PWM inverter LC output filter based on virtual resistance[J]. Measurement and Control Technology, 2017, 36 (3): 127- 131
[22]   全国能源基础与管理标准化技术委员会. 并网光伏发电专用逆变器技术条件: CGC/GF 004: 2011(CNCA/CTS 0004-2009A) [S]. 北京: [s.n.], 2011.
[23]   LI X, LI X, WANG K, et al Achievement scalarizing function sorting for strength Pareto evolutionary algorithm in many-objective optimization[J]. Neural Computing and Applications, 2021, 33: 6369- 6388
doi: 10.1007/s00521-020-05398-1
[24]   毕晓君, 王朝 基于超平面投影的高维多目标进化算法[J]. 浙江大学学报: 工学版, 2018, 52 (7): 1284- 1293
BI Xiao-jun, WANG Chao Many-objective evolutionary algorithm based on hyperplane projection[J]. Journal of Zhejiang University: Engineering Science, 2018, 52 (7): 1284- 1293
[1] Ting-fang YU,Ling SONG. Performance analysis and optimization of supercritical CO2 Brayton cycle waste heat recovery system[J]. Journal of ZheJiang University (Engineering Science), 2023, 57(2): 404-414.
[2] Wan-liang WANG,Ya-wen JIN,Jia-cheng CHEN,Guo-qing LI,Ming-zhi HU,Jian-hang DONG. Multi-objective particle swarm optimization algorithm with multi-role and multi-strategy[J]. Journal of ZheJiang University (Engineering Science), 2022, 56(3): 531-541.
[3] Jun-heng XU,Xiao-jun YANG,Bing LI. Design of wing mechanism with variable camber based on cross-spring flexural pivots[J]. Journal of ZheJiang University (Engineering Science), 2022, 56(3): 444-451, 509.
[4] Qi-lin DENG,Juan LU,Yong-hui CHEN,Jian FENG,Xiao-ping LIAO,Jun-yan MA. Optimization method of CNC milling parameters based on deep reinforcement learning[J]. Journal of ZheJiang University (Engineering Science), 2022, 56(11): 2145-2155.
[5] Yi-quan ZOU,Hao-zhou HUANG,Xu-yong XIA,Xin WANG. Design optimization of curved curtain wall based on genetic algorithm under cost orientation[J]. Journal of ZheJiang University (Engineering Science), 2022, 56(10): 2049-2056.
[6] Jun-jie CHEN,Hong-jun LI,Zhang-hua CAO. Performance-aware resource allocation algorithm for core network control plane[J]. Journal of ZheJiang University (Engineering Science), 2021, 55(9): 1782-1787.
[7] Xiao-zhu LI,Wei-qing WANG. Bi-level robust game optimal scheduling of regional comprehensive energy system[J]. Journal of ZheJiang University (Engineering Science), 2021, 55(1): 177-188.
[8] Kai-jun LOU,Feng YU,Tang-dai XIA,Jian MA. Stability analysis of diaphragm wall retained structure in clay[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(9): 1697-1705.
[9] Xiang-fei MENG,Ren-guang WANG,Yuan-li XU. Torque distribution strategy of pure electric driving mode for dual planetary vehicle[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(11): 2214-2223.
[10] Hua HUANG,Wen-qiang DENG,Yuan LI,Run-lan GUO. Mass matching design of machine tool parts based on spatial dynamics optimization[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(10): 2009-2017.
[11] Jia-shuang FAN,Sui-huai YU,Jian-jie CHU,Hui WANG,Chen CHEN,Wen-zhe CUN,Tian CHEN,Jia-yan GUO. Optimal decision-making method of design scheme in cloud service mode[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(1): 143-151.
[12] Yong-qiang OUYANG,Xin-yan ZHANG. Design of energy-saving automated storage and retrieval system considering acceleration and deceleration of storage and retrieval machine[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(9): 1681-1688.
[13] Jian CHEN,Rong MO,Sui-huai YU,Jian-jie CHU,Deng-kai CHEN,Jing GONG. Multi-objective group decision method for crowdsourcing product modeling design scheme in cloud environment[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(8): 1517-1524.
[14] Hong-wu GUO,Lei PU,Yu-xie ZHANG,Jing WU,Rui ZHAO,Zhong-fu TAN. Optimization model for integrated complementary system of wind-PV-pump storage based on rough set theory[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(4): 801-810.
[15] Cheng ZHANG,Tao JIN,Pei-qiang LI,Hui-qiong DENG. Wide-area coordination control strategy for power system using multi-objective bat algorithm[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(3): 589-597.