【摘要】：開(kāi)關(guān)磁阻電機(jī)(Switched Reluctance Motor, SRM)具有結(jié)構(gòu)簡(jiǎn)單、制造成本低、系統(tǒng)可靠性強(qiáng)、能量轉(zhuǎn)換效率高和調(diào)速范圍廣等優(yōu)點(diǎn)，是未來(lái)純電動(dòng)汽車(chē)產(chǎn)業(yè)理想的驅(qū)動(dòng)電機(jī)之一。開(kāi)關(guān)磁阻電機(jī)已在航空、采礦、紡織等領(lǐng)域得到有效的應(yīng)用，但電機(jī)在低速運(yùn)行時(shí)的較大的轉(zhuǎn)矩脈動(dòng)及由此而引發(fā)的振動(dòng)噪音嚴(yán)重制約了其在控制要求較高領(lǐng)域的廣泛應(yīng)用。由于開(kāi)關(guān)磁阻電機(jī)特殊雙凸極的結(jié)構(gòu)特點(diǎn)和開(kāi)關(guān)式的供電模式使其電磁特性呈強(qiáng)非線(xiàn)性，無(wú)法有效地建立精確的電機(jī)數(shù)學(xué)模型，而且傳統(tǒng)的控制算法對(duì)強(qiáng)非線(xiàn)性對(duì)象不能達(dá)到滿(mǎn)意的控制效果，這給設(shè)計(jì)減少轉(zhuǎn)矩脈動(dòng)的電機(jī)控制方法帶來(lái)了很大困難。為了減少SRM的低速轉(zhuǎn)矩脈動(dòng)，本文提出了如下兩種控制策略： (1)提出了基于大腦情感學(xué)習(xí)模型的SRM電流分配控制策略，通過(guò)調(diào)節(jié)電流間接對(duì)轉(zhuǎn)矩進(jìn)行控制。外環(huán)采用大腦情感學(xué)習(xí)模型調(diào)節(jié)器實(shí)現(xiàn)轉(zhuǎn)速偏差到母線(xiàn)參考電流的轉(zhuǎn)換，，母線(xiàn)參考電流通過(guò)電流分配函數(shù)得到三相參考電流。三相電流偏差經(jīng)過(guò)內(nèi)環(huán)的滯環(huán)電流控制單元得到的三相控制信號(hào)實(shí)現(xiàn)了電機(jī)的平滑換相，有效地降低了電機(jī)的轉(zhuǎn)矩脈動(dòng)。 (2)針對(duì)SRM強(qiáng)非線(xiàn)性和高度耦合性的特點(diǎn)，借鑒傳統(tǒng)直接瞬時(shí)轉(zhuǎn)矩控制(DirectInstantaneous Torque Control, DITC)策略，提出了基于所構(gòu)造的柔性神經(jīng)網(wǎng)絡(luò)(FlexibleNeural Network, FNN)的SRM直接瞬時(shí)轉(zhuǎn)矩控制策略。該控制策略外環(huán)采用不完全微分模糊PID對(duì)速度進(jìn)行調(diào)節(jié)，內(nèi)環(huán)采用以轉(zhuǎn)矩誤差的平方為性能指標(biāo)函數(shù)的FNN自適應(yīng)PID對(duì)轉(zhuǎn)矩進(jìn)行調(diào)節(jié)，達(dá)到了較為理想的控制效果。 在MATLAB/SIMULINK環(huán)境下，仿真結(jié)果表明上述兩種控制策略均能有效地抑制轉(zhuǎn)矩脈動(dòng)。在仿真研究的基礎(chǔ)上，對(duì)基于大腦情感學(xué)習(xí)模型的SRM電流分配控制策略、SRM直接瞬時(shí)轉(zhuǎn)矩控制策略和SRM電壓斬波控制策略在SRM實(shí)驗(yàn)平臺(tái)上進(jìn)行了實(shí)驗(yàn)測(cè)試。實(shí)驗(yàn)結(jié)果表明前兩種控制策略的轉(zhuǎn)矩脈動(dòng)抑制效果明顯優(yōu)于傳統(tǒng)的電壓斬波控制策略。
[Abstract]:The switched reluctance motor (Switched Reluctance Motor, SRM) has the advantages of simple structure, low manufacturing cost, strong system reliability, high efficiency of energy conversion and wide range of speed regulation. It is one of the ideal driving motors in the future pure electric vehicle industry. Switched reluctance motor (SRM) has been effectively applied in aviation, mining, textile and other fields. However, the large torque ripple and vibration noise caused by SRM in low speed operation seriously restrict its wide application in the field of high control requirements. Because of the special double salient structure of switched reluctance motor (SRM) and the switching mode of power supply, the electromagnetic characteristics of SRM are strongly nonlinear, so it is impossible to establish an accurate mathematical model of SRM effectively. Moreover, the traditional control algorithm can not achieve satisfactory control effect for the strong nonlinear object, which brings great difficulties to the design of the motor control method to reduce the torque ripple. In order to reduce the low speed torque ripple of SRM, two control strategies are proposed in this paper: (1) the SRM current allocation control strategy based on the brain emotional learning model is proposed, and the torque is indirectly controlled by adjusting the current. The external loop adopts the brain emotional learning model regulator to realize the conversion from the rotational speed deviation to the bus reference current, and the busbar reference current is obtained by the current distribution function. The three-phase current deviation obtained from the hysteresis current control unit of the inner loop realizes the smooth commutation of the motor and effectively reduces the torque ripple of the motor. (2) aiming at the characteristics of strong nonlinearity and high coupling of SRM, Based on the traditional direct instantaneous torque control (DirectInstantaneous Torque Control, DITC) strategy, a SRM direct instantaneous torque control strategy based on the constructed flexible neural network (FlexibleNeural Network, FNN) is proposed. The outer loop of the control strategy uses incomplete differential fuzzy PID to adjust the speed, and the inner loop adopts FNN adaptive PID with the square of torque error as the performance index function to adjust the torque. Simulation results under MATLAB/SIMULINK environment show that the two control strategies can effectively suppress torque ripple. Based on the simulation research, the SRM current allocation control strategy based on the brain emotional learning model and the SRM voltage chopper control strategy are tested on the SRM platform. The experimental results show that the torque ripple suppression effect of the first two control strategies is obviously better than that of the traditional voltage chopping control strategy.
【學(xué)位授予單位】：桂林電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TM352

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 潘再平;羅星寶;;基于迭代學(xué)習(xí)控制的開(kāi)關(guān)磁阻電機(jī)轉(zhuǎn)矩脈動(dòng)抑制[J];電工技術(shù)學(xué)報(bào);2010年07期

2 李珍國(guó);闞志忠;;開(kāi)關(guān)磁阻電機(jī)的高效率直接瞬時(shí)轉(zhuǎn)矩控制[J];電工技術(shù)學(xué)報(bào);2010年08期

3 黃海宏;王海欣;張志全;張學(xué);;迭代學(xué)習(xí)控制減小開(kāi)關(guān)磁阻電機(jī)轉(zhuǎn)矩脈動(dòng)[J];電氣應(yīng)用;2006年07期

4 黃操;張奕黃;;開(kāi)關(guān)磁阻電機(jī)的滑模變結(jié)構(gòu)控制[J];電力自動(dòng)化設(shè)備;2006年12期

5 荊建立;呂明;;開(kāi)關(guān)磁阻電動(dòng)機(jī)控制方法研究[J];電氣傳動(dòng)自動(dòng)化;2012年04期

6 王勉華;;SRM直接轉(zhuǎn)矩控制調(diào)速系統(tǒng)結(jié)構(gòu)研究[J];電氣傳動(dòng);2012年08期

7 鐘銳;曹彥萍;徐宇柘;屈嚴(yán);彭富林;;三角函數(shù)的開(kāi)關(guān)磁阻電機(jī)磁鏈解析模型[J];電機(jī)與控制學(xué)報(bào);2013年01期

8 邵偉;李曉寧;董明;;永磁同步電機(jī)伺服系統(tǒng)控制策略綜述[J];電氣自動(dòng)化;2013年01期

9 程勇;林輝;;開(kāi)關(guān)磁阻電機(jī)伺服系統(tǒng)的L_2增益魯棒控制方法[J];電力自動(dòng)化設(shè)備;2013年05期

10 劉景林;王帥夫;;數(shù)控機(jī)床用多步進(jìn)電機(jī)伺服系統(tǒng)控制[J];電機(jī)與控制學(xué)報(bào);2013年05期

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