本文關(guān)鍵詞： 永磁同步電機(jī) 逆變器非線性補(bǔ)償 MFAC 參數(shù)辨識 無模型電流預(yù)測控制　出處：《合肥工業(yè)大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：“十三五”規(guī)劃提出,到2020年建立起完善的電動汽車動力系統(tǒng)科技體系和產(chǎn)業(yè)鏈技術(shù)系統(tǒng),實(shí)現(xiàn)各類電動汽車的產(chǎn)業(yè)化,促進(jìn)新能源汽車戰(zhàn)略新興產(chǎn)業(yè)進(jìn)入快速成長期。大力發(fā)展電動汽車產(chǎn)業(yè)是我國在汽車行業(yè)對國外品牌實(shí)現(xiàn)彎道超車的重要契機(jī)。永磁同步電機(jī)(PMSM)以其優(yōu)越的性能成為電動汽車電驅(qū)動系統(tǒng)的主要驅(qū)動電機(jī),車用永磁同步電機(jī)驅(qū)動系統(tǒng)不僅要求調(diào)速范圍寬,而且要求轉(zhuǎn)矩輸出精度高,受逆變器非線性和電機(jī)復(fù)雜運(yùn)行工況導(dǎo)致電機(jī)參數(shù)變化的影響,傳統(tǒng)基于PI控制的PMSM驅(qū)動系統(tǒng)難以實(shí)現(xiàn)轉(zhuǎn)矩的準(zhǔn)確控制。此外,逆變器非線性亦會導(dǎo)致PMSM出現(xiàn)輸出轉(zhuǎn)矩脈動和定子電流畸變,直接影響PMSM參數(shù)在線辨識精度。為此,論文重點(diǎn)研究PMSM參數(shù)辨識及其無模型電流預(yù)測控制,其研究對于提高PMSM參數(shù)辨識精度及PMSM控制器抗參數(shù)變化的魯棒性,無疑具有重要的理論研究價值和工程應(yīng)用價值。論文首先分析逆變器非線性對逆變器輸出電壓的影響,并綜述了目前主要的補(bǔ)償方案。在此基礎(chǔ)上,建議了基于無模型參考自適應(yīng)的逆變器非線性補(bǔ)償方案,并通過系統(tǒng)建模和仿真驗(yàn)證建議方案的可行性和有效性�？紤]到永磁同步電機(jī)參數(shù)辨識對其控制系統(tǒng)設(shè)計和電驅(qū)動系統(tǒng)運(yùn)行狀況的實(shí)時監(jiān)控非常重要,由于電動汽車的復(fù)雜運(yùn)行工況導(dǎo)致PMSM參數(shù)變化范圍較大,必需對電機(jī)參數(shù)實(shí)施在線辨識。為此,論文基于現(xiàn)有電機(jī)參數(shù)辨識方法的梳理分析和總結(jié),給出了基于微分代數(shù)的永磁同步電機(jī)多參數(shù)在線辨識方案,通過系統(tǒng)仿真證實(shí)建議的電機(jī)參數(shù)辨識方案能夠解決現(xiàn)有的電機(jī)參數(shù)辨識方案中存在的多參數(shù)在線辨識模型欠秩和辨識精度亟需提升等關(guān)鍵問題。電動汽車永磁同步電機(jī)驅(qū)動系統(tǒng)通常采用傳統(tǒng)的雙閉環(huán)PI控制,當(dāng)系統(tǒng)在寬調(diào)速范圍和參數(shù)變化條件下運(yùn)行時,PI控制易出現(xiàn)飽和失調(diào)甚至運(yùn)行失穩(wěn)等問題；傳統(tǒng)永磁同步電機(jī)電流預(yù)測控制雖然可以解決PI控制存在的部分不足,但是敏感依賴于電機(jī)參數(shù),為此,論文最后研究永磁同步電機(jī)的無模型電流預(yù)測控制,旨在擺脫P(yáng)MSM控制對電機(jī)參數(shù)的依賴且兼顧提升系統(tǒng)的性能,并且通過系統(tǒng)仿真驗(yàn)證其技術(shù)優(yōu)勢。
[Abstract]:According to the 13th Five-Year Plan, by 2020, a sound scientific and technological system of electric vehicle power system and a technical system of industrial chain will be established to realize the industrialization of all kinds of electric vehicles. The development of electric vehicle industry is an important opportunity for our country to realize the bend overtaking of foreign brands in the automobile industry. PMSMM (permanent Magnet synchronous Motor) has its superior performance. Become the main driving motor of electric vehicle electric drive system, The drive system of vehicle permanent magnet synchronous motor (PMSM) not only requires a wide range of speed regulation, but also requires a high torque output precision, which is affected by the variation of motor parameters caused by nonlinear inverter and complex operating conditions of motor. The traditional PMSM drive system based on Pi control is difficult to realize the accurate torque control. In addition, the nonlinear inverter will also lead to the output torque ripple and stator current distortion of PMSM, which directly affect the accuracy of on-line identification of PMSM parameters. This paper focuses on PMSM parameter identification and model-free current predictive control, which can improve the accuracy of PMSM parameter identification and the robustness of PMSM controller against parameter change. Undoubtedly, it has important theoretical research value and engineering application value. Firstly, the paper analyzes the influence of inverter nonlinearity on inverter output voltage, and summarizes the main compensation schemes. A nonlinear compensation scheme for inverter based on modelless reference adaptive is proposed. The feasibility and validity of the proposed scheme are verified by system modeling and simulation. Considering that the parameter identification of PMSM is very important to the design of PMSM control system and the real-time monitoring of the operation of the electric drive system, Due to the large range of PMSM parameters due to the complex operating conditions of electric vehicles, it is necessary to carry out on-line identification of motor parameters. A multi-parameter on-line identification scheme for PMSM based on differential algebra is presented. It is proved by system simulation that the proposed scheme of motor parameter identification can solve the key problems such as the lack of rank of multi-parameter on-line identification model and the need to improve the precision of identification of permanent magnet of electric vehicle existing in the existing scheme of motor parameter identification. The traditional double closed loop Pi control is usually used in the drive system of synchronous motor. When the system is running in a wide speed range and variable parameters, the Pi control is prone to saturation misadjustment or even operational instability, while the traditional PMSM current predictive control can solve some shortcomings of Pi control. However, the sensitivity depends on the motor parameters. Therefore, this paper studies the model-free current predictive control of permanent magnet synchronous motor (PMSM) in order to get rid of the dependence of PMSM control on motor parameters and improve the performance of PMSM. The technical advantages are verified by system simulation.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TM341;U469.72

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