基于卡爾曼濾波器的永磁同步電機(jī)無(wú)位置傳感器控制
發(fā)布時(shí)間：2018-07-24 12:57
【摘要】：電機(jī)是一種把電能轉(zhuǎn)換機(jī)械能的裝置，作為清潔、高效的代名詞，電機(jī)在人們的生產(chǎn)生活已經(jīng)在各個(gè)角落中嶄露頭角。永磁同步電機(jī)擁有構(gòu)造簡(jiǎn)單、體積小、效率高和調(diào)速范圍寬等優(yōu)勢(shì)，同時(shí)驅(qū)動(dòng)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(lái)的電機(jī)體系中漸漸占據(jù)越來(lái)越重要的位置。 本文通過電機(jī)的基本數(shù)學(xué)模型和兩種坐標(biāo)變換方法，推導(dǎo)出在d-q坐標(biāo)系下的模型及公式，繼而提出了多種應(yīng)用于永磁同步電機(jī)控制的控制方法。當(dāng)前在電機(jī)控制領(lǐng)域廣泛使用的控制方法是矢量控制技術(shù)，結(jié)合SVPWM（空間矢量脈寬調(diào)制）實(shí)現(xiàn)對(duì)永磁同步電機(jī)的精確控制，這種控制系統(tǒng)目前在諸多領(lǐng)域中被科研工作者用來(lái)作為永磁同步電機(jī)的主要控制方案。 在永磁同步電機(jī)矢量控制（FOC）中，自適應(yīng)反饋系統(tǒng)是需要知道電機(jī)轉(zhuǎn)子的位置和速度的，某些電機(jī)結(jié)構(gòu)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(zhuǎn)速和角度信息，但是很多場(chǎng)合的電機(jī)中是沒有位置傳感器的，這時(shí)需要通過軟件層面的算法來(lái)對(duì)轉(zhuǎn)速和角度進(jìn)行估算。本文提到了幾種廣泛使用的無(wú)位置傳感器的控制策略，，在眾多觀測(cè)器中重點(diǎn)介紹卡爾曼濾波器算法原理和應(yīng)用。由于電機(jī)系統(tǒng)是非線性的，因此需要對(duì)其進(jìn)行線性化操作，繼而衍生出了擴(kuò)展卡爾曼濾波器（EKF）。并且提出了在坐標(biāo)系下的EKF數(shù)學(xué)公式，以及在本文電機(jī)參數(shù)下的誤差參數(shù)矩陣。 本文在設(shè)計(jì)PMSM控制系統(tǒng)過程中，利用MATLAB-Simulink對(duì)電機(jī)系統(tǒng)實(shí)現(xiàn)模型的搭建和系統(tǒng)的仿真驗(yàn)證。在之前介紹的坐標(biāo)系下的EKF數(shù)學(xué)公式的基礎(chǔ)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(gè)部分。在模型搭建的過程中有一些會(huì)影響仿真結(jié)果的細(xì)節(jié)需要關(guān)注，文章中給予了指出。對(duì)永磁同步電機(jī)在低速狀態(tài)下和改變電機(jī)參數(shù)之后卡爾曼濾波器的工作狀況進(jìn)行了仿真實(shí)驗(yàn)，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(duì)本文所研究的內(nèi)容需要進(jìn)一步完善的地方做了說明，同時(shí)也對(duì)下一階段的工作進(jìn)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(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM341
本文編號(hào)：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(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM341
【參考文獻(xiàn)】
相關(guān)期刊論文 前2條
1 李耀華;劉衛(wèi)國(guó);;永磁同步電機(jī)矢量控制與直接轉(zhuǎn)矩控制比較研究[J];電氣傳動(dòng);2010年10期
2 江俊,沈艷霞,紀(jì)志成;基于EKF的永磁同步電機(jī)轉(zhuǎn)子位置和速度估計(jì)[J];系統(tǒng)仿真學(xué)報(bào);2005年07期
本文編號(hào)：2141454
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