【摘要】：電動(dòng)汽車采用電力驅(qū)動(dòng)系統(tǒng),可實(shí)現(xiàn)高效節(jié)能、低污染,同時(shí)促進(jìn)了非石油資源的利用和開發(fā),促進(jìn)了電動(dòng)汽車未來的發(fā)展方向。由于直流無刷電機(jī)具有體積小、效率高、性能可靠、調(diào)速范圍廣、噪聲低等特點(diǎn),在電動(dòng)汽車中得到了廣泛應(yīng)用和發(fā)展。 針對(duì)電動(dòng)汽車驅(qū)動(dòng)系統(tǒng)的設(shè)計(jì)要求,在分析了國內(nèi)外電動(dòng)汽車及其驅(qū)動(dòng)系統(tǒng)的發(fā)展?fàn)顩r的基礎(chǔ)上,使用無位置傳感器直流無刷電機(jī)作為電動(dòng)汽車的驅(qū)動(dòng)電機(jī)。通過對(duì)直流無刷電機(jī)的結(jié)構(gòu)特性、工作原理、控制策略進(jìn)行了深入的探討和研究,并查閱了相關(guān)國外論文著作,基于現(xiàn)有無位置傳感器檢測技術(shù)的優(yōu)缺點(diǎn)和應(yīng)用場合的限制,使用擴(kuò)展卡爾曼濾波算法(EKF)對(duì)直流無刷電機(jī)位置和轉(zhuǎn)速進(jìn)行估算。在對(duì)轉(zhuǎn)速的實(shí)際控制過程中,當(dāng)被控對(duì)象特性發(fā)生變化需要調(diào)節(jié)參數(shù)作相應(yīng)調(diào)整,基于傳統(tǒng)PID控制算法沒有參數(shù)“自適應(yīng)”整定功能,所以在傳統(tǒng)PID控制器基礎(chǔ)上提出了一種基于RBF神經(jīng)網(wǎng)絡(luò)PID控制器的設(shè)計(jì)方法,并在MATLAB中建立直流無刷電機(jī)電動(dòng)汽車驅(qū)動(dòng)系統(tǒng)仿真模型,通過對(duì)電機(jī)轉(zhuǎn)速、轉(zhuǎn)矩、電流、估計(jì)轉(zhuǎn)速和位置的仿真結(jié)果進(jìn)行分析,從而驗(yàn)證控制算法的可行性和正確性�；赟TM32F407完成了電動(dòng)汽車電機(jī)驅(qū)動(dòng)控制系統(tǒng)的設(shè)計(jì)方案,并對(duì)其軟硬件部分的設(shè)計(jì)進(jìn)行了詳細(xì)的介紹。 綜合整篇文章,主要針對(duì)無位置傳感器的直流無刷電機(jī)作為電動(dòng)汽車驅(qū)動(dòng)電機(jī)的控制方法及轉(zhuǎn)子位置估算進(jìn)行了研究,并結(jié)合RBF神經(jīng)網(wǎng)絡(luò)算法和擴(kuò)展卡爾曼濾波算法(EKF),實(shí)現(xiàn)了本課題的需求。
[Abstract]:The electric vehicle adopts electric drive system, which can realize high efficiency and energy saving, low pollution, promote the utilization and development of non-oil resources, and promote the future development direction of electric vehicle. DC brushless motor has been widely used and developed in electric vehicles because of its small size, high efficiency, reliable performance, wide speed range and low noise. Based on the analysis of the development of electric vehicle and its drive system at home and abroad, the sensorless DC brushless motor is used as the driving motor of electric vehicle. The structure characteristics, working principle and control strategy of brushless DC motor are discussed and studied deeply, and related foreign papers are consulted. Based on the advantages and disadvantages of the existing sensorless detection technology and the limitation of its application, The extended Kalman filter (EKF) algorithm is used to estimate the position and speed of brushless DC motor. In the actual speed control process, when the characteristics of the controlled object change, the parameters need to be adjusted accordingly. Based on the traditional PID control algorithm, there is no "adaptive" tuning function of the parameters. Based on the traditional PID controller, a design method of PID controller based on RBF neural network is put forward, and the simulation model of drive system of DC brushless motor electric vehicle is established in MATLAB. The simulation results of the estimated speed and position are analyzed to verify the feasibility and correctness of the control algorithm. The design scheme of electric vehicle motor drive control system based on STM32F407 is completed, and the design of its hardware and software is introduced in detail. In this paper, the control method and rotor position estimation of sensorless DC brushless motor as driving motor of electric vehicle are studied, and combined with RBF neural network algorithm and extended Kalman filter algorithm (EKF),. The requirement of this subject is realized.
【學(xué)位授予單位】：安徽理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM33

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本文編號(hào)：2381329