基于卡爾曼濾波器的永磁同步電機無位置傳感器控制
發(fā)布時間：2018-07-24 12:57
【摘要】：電機是一種把電能轉換機械能的裝置，作為清潔、高效的代名詞，電機在人們的生產(chǎn)生活已經(jīng)在各個角落中嶄露頭角。永磁同步電機擁有構造簡單、體積小、效率高和調(diào)速范圍寬等優(yōu)勢，同時驅(qū)動系統(tǒng)可以滿足多數(shù)情況下的高性能要求，使得其在近年來的電機體系中漸漸占據(jù)越來越重要的位置。 本文通過電機的基本數(shù)學模型和兩種坐標變換方法，推導出在d-q坐標系下的模型及公式，繼而提出了多種應用于永磁同步電機控制的控制方法。當前在電機控制領域廣泛使用的控制方法是矢量控制技術，結合SVPWM（空間矢量脈寬調(diào)制）實現(xiàn)對永磁同步電機的精確控制，這種控制系統(tǒng)目前在諸多領域中被科研工作者用來作為永磁同步電機的主要控制方案。 在永磁同步電機矢量控制（FOC）中，自適應反饋系統(tǒng)是需要知道電機轉子的位置和速度的，某些電機結構中包含了位置傳感器，控制系統(tǒng)就可以從傳感器中獲取轉速和角度信息，但是很多場合的電機中是沒有位置傳感器的，這時需要通過軟件層面的算法來對轉速和角度進行估算。本文提到了幾種廣泛使用的無位置傳感器的控制策略，，在眾多觀測器中重點介紹卡爾曼濾波器算法原理和應用。由于電機系統(tǒng)是非線性的，因此需要對其進行線性化操作，繼而衍生出了擴展卡爾曼濾波器（EKF）。并且提出了在坐標系下的EKF數(shù)學公式，以及在本文電機參數(shù)下的誤差參數(shù)矩陣。 本文在設計PMSM控制系統(tǒng)過程中，利用MATLAB-Simulink對電機系統(tǒng)實現(xiàn)模型的搭建和系統(tǒng)的仿真驗證。在之前介紹的坐標系下的EKF數(shù)學公式的基礎上，搭建整套系統(tǒng)的模型，包括矢量控制（FOC）、空間矢量脈寬調(diào)制（SVPWM）以及卡爾曼濾波器等等幾個部分。在模型搭建的過程中有一些會影響仿真結果的細節(jié)需要關注，文章中給予了指出。對永磁同步電機在低速狀態(tài)下和改變電機參數(shù)之后卡爾曼濾波器的工作狀況進行了仿真實驗，發(fā)現(xiàn)在一定范圍內(nèi)其依然保持優(yōu)秀的性能。最后對本文所研究的內(nèi)容需要進一步完善的地方做了說明，同時也對下一階段的工作進行了展望。
[Abstract]:Motor is a mechanical energy conversion device, as a clean, efficient pronoun, the motor in people's production and life has emerged in every corner. PMSM has the advantages of simple structure, small size, high efficiency and wide speed range, and the drive system can meet the requirements of high performance in most cases. It gradually occupies a more and more important position in the motor system in recent years. Based on the basic mathematical model and two coordinate transformation methods of the motor, this paper deduces the model and formula in d-q coordinate system, and then puts forward a variety of control methods applied to the permanent magnet synchronous motor (PMSM) control. At present, vector control technology is widely used in the field of motor control. The precise control of permanent magnet synchronous motor (PMSM) is realized by combining with SVPWM (Space Vector Pulse width Modulation). This control system is used as the main control scheme of PMSM by researchers in many fields. In the (FOC) of permanent magnet synchronous motor (PMSM) vector control, the adaptive feedback system needs to know the position and speed of the motor rotor. Some motor structures contain the position sensor, and the control system can obtain the rotational speed and angle information from the sensor. However, there is no position sensor in the motor in many cases, so it is necessary to estimate the rotation speed and angle by software level algorithm. In this paper, several widely used sensorless control strategies are presented, and the principle and application of Kalman filter algorithm are emphasized in many observers. Because the motor system is nonlinear, it needs to be linearized, and then the extended Kalman filter (EKF).) is derived. The EKF mathematical formula in the coordinate system and the error parameter matrix under the parameters of the motor in this paper are also presented. In the process of designing the PMSM control system, the realization model of the motor system and the simulation verification of the system are built by MATLAB-Simulink. Based on the EKF mathematical formula in the coordinate system, the model of the whole system is built, including vector control (FOC), space vector pulse width modulation (SVPWM) and Kalman filter and so on. Some details that will affect the simulation results need to be paid attention to in the process of modeling, which is pointed out in this paper. In this paper, the simulation experiments on the working condition of the permanent magnet synchronous motor (PMSM) at low speed and after changing the parameters of the PMSM are carried out, and it is found that the PMSM still has excellent performance in a certain range. Finally, the contents of this paper need to be further improved, and the next stage of the work is also prospected.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM341
本文編號：2141454
[Abstract]:Motor is a mechanical energy conversion device, as a clean, efficient pronoun, the motor in people's production and life has emerged in every corner. PMSM has the advantages of simple structure, small size, high efficiency and wide speed range, and the drive system can meet the requirements of high performance in most cases. It gradually occupies a more and more important position in the motor system in recent years. Based on the basic mathematical model and two coordinate transformation methods of the motor, this paper deduces the model and formula in d-q coordinate system, and then puts forward a variety of control methods applied to the permanent magnet synchronous motor (PMSM) control. At present, vector control technology is widely used in the field of motor control. The precise control of permanent magnet synchronous motor (PMSM) is realized by combining with SVPWM (Space Vector Pulse width Modulation). This control system is used as the main control scheme of PMSM by researchers in many fields. In the (FOC) of permanent magnet synchronous motor (PMSM) vector control, the adaptive feedback system needs to know the position and speed of the motor rotor. Some motor structures contain the position sensor, and the control system can obtain the rotational speed and angle information from the sensor. However, there is no position sensor in the motor in many cases, so it is necessary to estimate the rotation speed and angle by software level algorithm. In this paper, several widely used sensorless control strategies are presented, and the principle and application of Kalman filter algorithm are emphasized in many observers. Because the motor system is nonlinear, it needs to be linearized, and then the extended Kalman filter (EKF).) is derived. The EKF mathematical formula in the coordinate system and the error parameter matrix under the parameters of the motor in this paper are also presented. In the process of designing the PMSM control system, the realization model of the motor system and the simulation verification of the system are built by MATLAB-Simulink. Based on the EKF mathematical formula in the coordinate system, the model of the whole system is built, including vector control (FOC), space vector pulse width modulation (SVPWM) and Kalman filter and so on. Some details that will affect the simulation results need to be paid attention to in the process of modeling, which is pointed out in this paper. In this paper, the simulation experiments on the working condition of the permanent magnet synchronous motor (PMSM) at low speed and after changing the parameters of the PMSM are carried out, and it is found that the PMSM still has excellent performance in a certain range. Finally, the contents of this paper need to be further improved, and the next stage of the work is also prospected.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM341
【參考文獻】
相關期刊論文 前2條
1 李耀華;劉衛(wèi)國;;永磁同步電機矢量控制與直接轉矩控制比較研究[J];電氣傳動;2010年10期
2 江俊,沈艷霞,紀志成;基于EKF的永磁同步電機轉子位置和速度估計[J];系統(tǒng)仿真學報;2005年07期
本文編號：2141454
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