An Improved Sequential Model Predictive Control Strategy for T-Type Three-Level Inverter System
Tian Yazhuo1, Liu Chenwei1, Zhang Yongjun1,2, Xiao Xiong1,2
1. National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing University of Science and Technology Beijing Beijing 100083 China; 2. Institute of Engineering Technology University of Science and Technology Beijing Beijing 100083 China
Abstract：The T-type three-level inverter is known for its good output waveform, high efficiency, and ability to provide high voltage and power outputs, which can meet the requirements of control strategies. One common strategy of T-type three-level inverter systems is predictive direct torque control. The unified cost function can directly describe the constraint conditions of multiple control objectives and select the optimal space voltage vector for the next control cycle acting on the inverter through traversal. The approach offers good control performance and simple control strategies. However, when dealing with multiple control objectives, appropriate weighting factors must be designed to adjust the contribution of each objective. The design of weighting factors has become a research hotspot. Sequential model predictive control adopts a sequential structure to evaluate the cost function of each control objective, avoiding the weighting factor design. However, the control performance for low-priority objectives is limited and cannot meet the equal weight control requirements of similar priority objectives. Therefore, this paper proposes an improved sequential model predictive control based on a sequential-parallel hybrid structure for coordinate control of multiple objectives. Firstly, this paper proposes an enhanced multi-objective cost function of a T-type three-level inverter system based on model predictive direct torque control. The cost function includes electromagnetic torque, stator flux, common-mode voltage, and switching frequency. Secondly, the priorities of each control objective are considered. The electromagnetic torque and stator flux, which have similar priorities, are classified as the primary set. The common-mode voltage and switching frequency, which optimize system performance, are classified as the secondary set. Herein, the primary set takes priority over the secondary set, and the control objectives within the same set have similar priorities. A proposed sequential-parallel hybrid structure improves the sequential model predictive control. The parallel synchronously optimizes objectives with similar priorities, and the sequential structure sequentially controls objectives with different priorities. Thus, multi-objective predictive control of the system is achieved while maintaining the weighting factor design, improving system performance. An experimental platform is built using a high-speed DSP (TMS320F28335) and FPGA as core components. The experimental results show that the proposed strategy can effectively suppress the common-mode voltage and reduce the switching frequency, thus reducing system power loss. Meanwhile, the system’s high-performance steady-state and dynamic responses are maintained. The computational burden is moderate and can meet the real-time requirements. The proposed strategy has the advantages of simple structure and easy implementation.
[1] 申永鹏, 王帅兵, 梁伟华, 等. T型三电平逆变器合成脉冲宽度调制相电流重构策略[J]. 电工技术学报, 2022, 37(20): 5302-5312. Shen Yongpeng, Wang Shuaibing, Liang Weihua, et al.T-type three-level inverter composite pulse width modulation phase current reconstruction strategy[J]. Transactions of China Electrotechnical Society, 2022, 37(20): 5302-5312. [2] 李永东, 徐杰彦, 杨涵棣, 等. 多电平变换器拓扑结构综述及展望[J]. 电机与控制学报, 2020, 24(9): 1-12. Li Yongdong, Xu Jieyan, Yang Handi, et al.Overview and prospect of multilevel converter topology[J]. Electric Machines and Control, 2020, 24(9): 1-12. [3] 李珍国, 孙启航, 王鹏磊, 等. 无刷直流电机无直轴电枢反应的非正弦转子磁场定向矢量控制技术[J]. 电工技术学报, 2022, 37(16): 4094-4103. Li Zhenguo, Sun Qihang, Wang Penglei, et al.Non-sinusoidal rotor field oriented vector control tech-nology without d-axis armature reaction in brushless DC motor[J]. Transactions of China Electrotechnical Society, 2022, 37(16): 4094-4103. [4] 周长攀, 刘海峰, 景国秀, 等. 双三相永磁同步电机缺相容错运行虚拟矢量间接修正方法及其在直接转矩控制中应用[J]. 电工技术学报, 2023, 38(2): 451-464. Zhou Changpan, Liu Haifeng, Jing Guoxiu, et al.The indirect correction method of virtual vectors for dual three-phase permanent magnet synchronous motors under the open-phase fault and its application in the direct torque control[J]. Transactions of China Elec-trotechnical Society, 2023, 38(2): 451-464. [5] 周汉斌, 杨建, 黄连生, 等. 基于有限状态机的三电平逆变器双矢量模型预测控制策略[J]. 电力系统自动化, 2023, 47(11): 155-164. Zhou Hanbin, Yang Jian, Huang Liansheng, et al.Double-vector model predictive control strategy of three-level inverter based on finite state machine[J]. Automation of Electric Power Systems, 2023, 47(11): 155-164. [6] 兰志勇, 罗杰, 李延昊, 等. 基于快速选择表的永磁同步电机模型预测转矩控制[J]. 电工技术学报, 2023, 38(21): 5749-5757. Lan Zhiyong, Luo Jie, Li Yanhao, et al.Model prediction torque control for permanent magnet synchronous motor based on the fast selection table[J]. Transactions of China Electrotechnical Society, 2023, 38(21): 5749-5757. [7] 林宏民, 吴晓新, 乐胜康, 等. 基于三电平优化矢量的异步电机模型预测直接转矩控制[J]. 电机与控制学报, 2018, 22(8): 65-74. Lin Hongmin, Wu Xiaoxin, Le Shengkang, et al.Model predictive direct torque control of induction motor based on three level optimization vector[J]. Electric Machines and Control, 2018, 22(8): 65-74. [8] Yu Bin, Song Wensheng, Guo Yongqi, et al.Virtual voltage vector-based model predictive current control for five-phase VSIs with common-mode voltage reduction[J]. IEEE Transactions on Transportation Electrification, 2021, 7(2): 706-717. [9] 李家祥, 汪凤翔, 柯栋梁, 等. 基于粒子群算法的永磁同步电机模型预测控制权重系数设计[J]. 电工技术学报, 2021, 36(1): 50-59, 76. Li Jiaxiang, Wang Fengxiang, Ke Dongliang, et al.Weighting factors design of model predictive control for permanent magnet synchronous machine using particle swarm optimization[J]. Transactions of China Electrotechnical Society, 2021, 36(1): 50-59, 76. [10] Geyer T.Algebraic weighting factor selection for predictive torque and flux control[C]//2017 IEEE Energy Conversion Congress and Exposition (ECCE), Cincinnati, OH, USA, 2017: 357-364. [11] 颜黎明, 郭鑫, 徐玺声, 等. 基于新型解析权重因子配置的感应电机模型预测转矩控制[J]. 电工技术学报, 2023, 38(20): 5421-5433. Yan Liming, Guo Xin, Xu Xisheng, et al.Model predictive torque control of induction machine drives using novel analytic weighting factor assignment[J]. Transactions of China Electrotechnical Society, 2023, 38(20): 5421-5433. [12] Novak M, Xie Haotian, Dragicevic T, et al.Optimal cost function parameter design in predictive torque control (PTC) using artificial neural networks (ANN)[J]. IEEE Transactions on Industrial Elec-tronics, 2021, 68(8): 7309-7319. [13] Guazzelli P R U, de Andrade Pereira W C, de Oliveira C M R, et al. Weighting factors optimization of predictive torque control of induction motor by multiobjective genetic algorithm[J]. IEEE Transa-ctions on Power Electronics, 2019, 34(7): 6628-6638. [14] 李耀华, 秦辉, 苏锦仕, 等. 永磁同步电机模糊自适应变开关次数权重系数模型预测转矩控制[J]. 电机与控制学报, 2021, 25(2): 102-112. Li Yaohua, Qin Hui, Su Jinshi, et al.Model predictive torque control of permanent magnet synchronous/rmotor based on adaptive dynamic weight coefficient using fuzzy control[J]. Electric Machines and Control, 2021, 25(2): 102-112. [15] Wang Youcheng, Yang Yong, Chen Shengwei, et al.An improved model predictive voltage control with reduced computational burden for T-type three-phase three-level inverters[J]. IEEE Transactions on Power Electronics, 2024, 39(2): 2115-2127. [16] Zhang Yongchang, Yang Haitao.Two-vector-based model predictive torque control without weighting factors for induction motor drives[J]. IEEE Transa-ctions on Power Electronics, 2016, 31(2): 1381-1390. [17] 赵勇, 黄文新, 林晓刚, 等. 基于权重系数消除和有限控制集优化的双三相永磁容错电机快速预测直接转矩控制[J]. 电工技术学报, 2021, 36(1): 3-14. Zhao Yong, Huang Wenxin, Lin Xiaogang, et al.Fast predictive direct torque control of dual three-phase permanent magnet fault tolerant machine based on weighting factor elimination and finite control set optimization[J]. Transactions of China Electro-technical Society, 2021, 36(1): 3-14. [18] 成庶, 欧阳泽铿, 张璐琳, 等. 无权重系数的三相八开关模型预测电流控制[J]. 电工技术学报, 2021, 36(增刊1): 265-273. Cheng Shu, Ouyang Zekeng, Zhang Lulin, et al.A model predictive current control method without weighting factors for eight-switch three-phase inverter[J]. Transactions of China Electrotechnical Society, 2021, 36(S1): 265-273. [19] 郭磊磊, 孙怡舒, 李琰琰, 等. PMSM无权重系数转矩预测控制方法[J]. 太阳能学报, 2021, 42(8): 426-433. Guo Leilei, Sun Yishu, Li Yanyan, et al.Torque predictive control method for PMSM unweighted factor[J]. Acta Energiae Solaris Sinica, 2021, 42(8): 426-433. [20] 谢昊天, 汪凤翔, 柯栋梁, 等. 基于集成优化的感应电机无权重系数预测转矩控制[J]. 电工技术学报, 2022, 37(12): 2992-3003. Xie Haotian, Wang Fengxiang, Ke Dongliang, et al.Ensemble optimization based weighting factor-less predictive torque control for induction machines[J]. Transactions of China Electrotechnical Society, 2022, 37(12): 2992-3003. [21] Norambuena M, Rodriguez J, Zhang Zhenbin, et al.A very simple strategy for high-quality performance of AC machines using model predictive control[J]. IEEE Transactions on Power Electronics, 2019, 34(1): 794-800. [22] Garcia C, Rodriguez J, Norambuena M, et al.Performance evaluation between SMPTC and PTC for PMSM drives[C]//2019 10th International Conference on Power Electronics and ECCE Asia (ICPE 2019-ECCE Asia), Busan, Korea (South), 2019: 1-5. [23] 孙旭霞, 王凯, 裴妮娜, 等. 基于SMPTC优化策略的PMSM调速系统研究[J]. 电力电子技术, 2021, 55(9): 59-62, 89. Sun Xuxia, Wang Kai, Pei Nina, et al.Research on PMSM speed control system based on SMPTC optimization strategy[J]. Power Electronics, 2021, 55(9): 59-62, 89. [24] Long Bo, Shen Dawei, Cao Tianxu, et al.Power losses reduction of T-type grid-connected converters based on tolerant sequential model predictive control[J]. IEEE Transactions on Power Electronics, 2022, 37(8): 9089-9103. [25] Zhang Yongchang, Zhang Boyue, Yang Haitao, et al.Generalized sequential model predictive control of IM drives with field-weakening ability[J]. IEEE Transa-ctions on Power Electronics, 2019, 34(9): 8944-8955. [26] Rodriguez J, Kennel R M, Espinoza J R, et al.High-performance control strategies for electrical drives: an experimental assessment[J]. IEEE Transactions on Industrial Electronics, 2012, 59(2): 812-820.
2024, Vol. 39 
