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一種三電平NPC整流?逆變調速系統的無權重系數模型預測控制策略

Model predictive control strategy for three-level NPC rectifier–inverter drive system without weighting factor

  • 摘要: 針對異步電機三電平中點鉗位(Neutral point clamped,NPC)整流–逆變驅動系統的高性能高效控制,搭建了三電平整流–逆變系統的預測與損耗模型,構建了包含中點電壓平衡與損耗優化的代價函數,提出了一種基于序列并行結構的無權重系數模型預測控制. 策略在傳統的序列模型預測控制中引入了直流母線中點電壓和變換器開關頻率控制,構建了包含多個控制目標的統一代價函數. 根據整流–逆變系統在運行中對各控制目標的實際需求,將代價函數中的多個控制目標分為主要和次要控制目標并歸類為兩個序列優化集,對不同的序列集進行順序優化. 在相同的序列集內部,采用自適應并行尋優來選擇最優開關狀態,保證了同級序列內各控制目標的同步優化,避免了權重系數的設計. 仿真和實驗結果驗證了該方法具有良好的控制性能和參數魯棒性,并能有效控制中點電壓波動和降低系統損耗.

     

    Abstract: The three-level converter has become the mainstream converter topology because of its good output power quality and high power factor. The three-level dual pulse width modulation frequency speed control system with rectifier–inverter structure has become a research hotspot in academic circles because of its advantages of bidirectional energy flow, high power quality, and controllable intermediate direct current (DC) voltage. Aiming at the high-performance and high-efficiency control of the three-level neutral point clamped (NPC) rectifier–inverter drive system of an induction motor, this study builds a prediction and loss model of the three-level rectifier–inverter system, constructs a cost function including the midpoint voltage balance and loss optimization, and proposes a model predictive control without weighting factors based on a sequential parallel structure. With the development of the field of power electronics, the control performance and efficiency of the converter have gradually improved, and the model predictive control applied to the converter is no longer limited to the traditional control objectives. The proposed strategy introduces the DC bus midpoint voltage and converter switching frequency control to the traditional sequential model predictive control and constructs a unified cost function with multiple control objectives. According to the actual requirements of the multiple control objectives in the operation of the rectifier–inverter system, the control objectives in the cost function are divided into primary and secondary control objectives and classified into two sequence optimization sets, and different sequence sets are sequentially optimized. In the same sequence set, adaptive parallel optimization is used to select the optimal switching state, which ensures the synchronous optimization of each control object in the sequence, thus avoiding the need for weighting factors. The parallel structure can rank multiple control targets, reduce the number of sequences to increase the number of optional voltage vectors between each sequence and increase the control effect of nonprimary control targets. Moreover, synchronous optimization of control targets of the same importance is realized at the same level, which solves the problem that targets of similar importance must be sequentially optimized in conventional sequential model predictive control, solves the problem that the priority of different targets is difficult to adjust, and has stronger applicability for the complex topology structure with multiple control requirements. The simulation and experimental results showed that the proposed algorithm can improve the steady-state and dynamic performance of the system, reduce the midpoint voltage bias, reduce the switching frequency of the rectifier and inverter, reduce the total harmonic bias, and adjust the midpoint voltage unbalance.

     

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