本文選題：永磁同步電動機 + 無傳感器控制　； 參考：《華南理工大學》2014年博士論文

【摘要】：永磁同步電動機由于具有體積小、功率密度和效率高，運行性能好等優(yōu)點，在理論研究和實際應用中得到廣泛重視；目前，永磁同步電動機作為控制系統(tǒng)執(zhí)行元件的核心已廣泛地應用于數(shù)控機床、機器人以及航空、航天和航海等領域中。本文結合電動汽車應用的需要，以無位置傳感器永磁同步電動機驅動系統(tǒng)為研究對象，有針對性地對電機轉子位置和轉速的在線估計、電機的控制策略以及死區(qū)補償?shù)葐栴}進行了較為深入的研究。目的是為了降低電動汽車電氣驅動系統(tǒng)的成本與復雜性，進一步提高控制系統(tǒng)的可靠性和控制性能。 在研究課題中，首先根據(jù)坐標變換理論推導了永磁同步電動機在兩相靜止坐標系下的電機模型，并結合擴展卡爾曼濾波器理論設計了相應的轉子速度、位置觀測器。雖然擴展卡爾曼濾波算法能實現(xiàn)電機的自啟動，但由于轉子初始位置角未知，算法在啟動中可能會出現(xiàn)的收斂錯誤和失速問題，本文針對這一問題給出了詳細解釋并討論了相關的解決方法。由于噪聲協(xié)方差矩陣對估計性能有很大的影響，本文通過仿真分析了不同矩陣取值對結果產生的影響，并總結了一套參數(shù)試湊方法。 由于擴展卡爾曼濾波器的估計精度受電機模型參數(shù)變化影響，通過仿真總結了參數(shù)變化對估計精度影響的規(guī)律。針對這一問題，對自適應漸消擴展卡爾曼濾波器進行了較為深入的研究。引入衰減因子對原擴展卡爾曼濾波器的誤差協(xié)方差矩陣進行加權，這樣能夠減小陳舊量測值對估計的影響，強化新的量測數(shù)據(jù)在濾波中所起的校正作用，，從而能提高跟蹤速度和估計精度�？紤]到卡爾曼濾波器在高階時計算量大的問題，引入一種兩段式結構將擴展卡爾曼濾波器分解成兩個并行的低階濾波器，達到節(jié)省運算量的目的，通過乘法和加法運算量的對比體現(xiàn)出兩段擴展卡爾曼濾波器在運算量上所具有的優(yōu)勢，利用濾波器之間的等效性驗證了所提出濾波器的穩(wěn)定性。結合自適應擴展卡爾曼濾波器和雙段擴展卡爾曼濾波器各自的特點，提出一種新的自適應雙段擴展卡爾曼濾波器，并采用相同的等效性證明驗證了其穩(wěn)定性，這種濾波器是將雙段結構應用到自適應擴展卡爾曼濾波器上而得出，同時具有自適應濾波器強跟蹤、魯棒性好和雙段濾波器節(jié)省運算量的優(yōu)點。 在電流控制中，針對已有的線性比例微分控制策略存在的動態(tài)響應速度慢，對控制器參數(shù)的依賴度高等問題，采用一種無差拍預測電流控制方法來進行永磁同步電動機的電流控制。由于這類基于模型的控制方法對參數(shù)精確度要求較高，設計了擾動觀測器來估計未建模的不確定項，針對電壓型逆變器中的死區(qū)時間和非線性等因素造成的電壓損失，通過相應的死區(qū)電壓觀測器在線估計，并將兩個觀測器的估計值加入到電壓指令值中進行補償。由于速度環(huán)PI控制器的非線性飽和特性，提出了一種變結構抗飽和PI速度控制器來提高轉速控制性能。 針對自適應雙段擴展卡爾曼濾波器和無差拍預測電流控制方法，設計了基于Expert3系統(tǒng)的全數(shù)字無位置傳感器永磁同步電動機控制系統(tǒng)。在此基礎上，對各研究內容進行了深入的仿真研究和實驗驗證。
[Abstract]:Permanent magnet synchronous motor (PMSM) has been widely used in theoretical research and practical application because of its advantages of small size, high power density, high efficiency and good operating performance. At present, permanent magnet synchronous motor (PMSM), as the core of the actuating components of control system, has been widely used in the fields of CNC machine tools, robots, aerospace and navigation. In this paper, based on the needs of the application of electric vehicle, the research object of the permanent magnet synchronous motor drive system without position sensor is the research on the on-line estimation of the rotor position and speed, the control strategy of the motor and the dead zone compensation. The purpose is to reduce the electric drive system of the electric vehicle. The cost and complexity of the system further improve the reliability and control performance of the control system.
In the study, the motor model of the permanent magnet synchronous motor in the two phase stationary coordinate system is derived according to the coordinate transformation theory, and the corresponding rotor speed and position observer are designed with the extended Calman filter theory. Although the extended Calman filter algorithm can realize the self starting of the motor, the initial position angle of the rotor is due to the initial position angle of the rotor. Unknown, the convergence error and stall of the algorithm may appear in the start up of the algorithm. This paper gives a detailed explanation of this problem and discusses the related solutions. Because the noise covariance matrix has a great influence on the performance of the estimation, this paper analyzes the effects of the different moment array values on the results by simulation and summarizes a set of results. Parameter test method.
Because the estimation accuracy of the extended Calman filter is influenced by the change of the parameter of the motor model, the influence of the parameter variation on the estimation accuracy is summarized by simulation. In this problem, the adaptive fading and expanding Calman filter is deeply studied. The error covariance of the attenuating dependent son on the original extended Calman filter is introduced. The difference matrix is weighted, which can reduce the influence of the old measurement value to the estimation, strengthen the correction function of the new measurement data in the filtering, and thus improve the tracking speed and the estimation precision. Considering the problem that the Calman filter has a large computation in the high order, a two segment structure is introduced to decompose the extended Calman filter into the problem. Two parallel low order filters achieve the purpose of saving the computation. By comparing the multiplication and addition operations, the advantages of the two extended Calman filter are demonstrated. The stability of the proposed filter is verified by the equivalence between the filters. The adaptive extended Calman filter and the two segment expansion are combined. A new adaptive double segment extended Calman filter is proposed, and its stability is verified by the same equivalence proof. This filter is used to apply the double segment structure to the adaptive extended Calman filter, and has the strong robustness and two segments of adaptive filter with strong tracking of adaptive filter. The filter saves the advantage of the amount of operation.
In current control, the current linear proportional differential control strategy has a slow dynamic response and a high dependence on the parameters of the controller. A current control method is used to control the current of the permanent magnet synchronous motor. The disturbance observer is designed to estimate the unmodeled uncertainty. The voltage loss caused by dead time and nonlinear factors in the voltage inverter is estimated by the corresponding dead range voltage observer, and the estimated values of the two observers are added to the voltage instruction value to be compensated. Because of the speed loop PI controller, A variable structure anti saturation PI speed controller is proposed to improve the speed control performance.
In this paper, a full digital sensorless permanent magnet synchronous motor control system based on Expert3 system is designed for the adaptive two segment extended Calman filter and the non difference beat prediction current control method. On this basis, the research contents are thoroughly simulated and tested.
【學位授予單位】：華南理工大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TM341

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