簡易檢索 / 詳目顯示

研究生: 謝聖祥
Hsieh, Sheng-Hsiang
論文名稱: 利用基因演算法於降低直流無刷馬達轉矩漣波之研究
Study of Genetic Algorithm for Reducing Torque Ripple of Brushless DC Motor
指導教授: 陳添智
Chen, Tien-Chi
學位類別: 碩士
Master
系所名稱: 工學院 - 工程科學系
Department of Engineering Science
論文出版年: 2005
畢業學年度: 93
語文別: 英文
論文頁數: 80
中文關鍵詞: 基因演算法轉矩漣波直流無刷馬達
外文關鍵詞: Genetic Algorithm, Torque Ripple, Brushless DC Motor
相關次數: 點閱:96下載:1
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  •   為了得到良好的控制性能以及快速的暫態響應,轉矩漣波的改善已被廣泛的需求在許多的應用上。因此如何將速度變動、震動以及雜訊等因素所造成的影響最小化,是目前改善直流無刷馬達轉矩漣波的主要研究方向。最常被應用來研究消除轉矩漣波的方法為傅立葉分析、有限元素法以及最小平方等。而這些方法因為分析上較為複雜,因此在計算上比較容易發生計算錯誤,或是浪費太多時間在分析和計算上。因此,本論文提出一個新方法,利用基因演算法的原理來改善直流無刷馬達的轉矩漣波。

      此方法是在反電動勢波形已知的條件下,利用基因演算法來搜尋最合適的三相定子電流的傅立葉係數。並將所搜尋到的傅立葉係數重新組成三相的電流波形,而此電流波形即是最適合已知的反電動勢波形,因為用此電流來驅動直流無刷馬達,只要此電流被成功地實現,所得到的轉矩漣波將會最小。而此方法的優點為無論反電動勢波形為弦波、梯形波或者兩者皆不是,只要在反電動勢已知的條件下,即可利用此方法來找出最理想的三相電流波形,不需經過複雜的分析或是計算,因此這方法具有良好的便利性。本論文分別利用Matlab-Simulink和TMS320F2812 DSP實驗版來模擬跟實驗所提出方法的效能跟實用性。其中,將所得到的三相理想電流波形和三相的反電動勢波形皆是以建表的方式來呈現,並根據轉子角度位置和速度來決定適當的輸出波形。由所得到的模擬跟實驗結果可知,本論文所提出的方法可以有效的改善直流無刷馬達的轉矩漣波。在反電動勢波形已知的條件下,只要利用所提出的方法即可成功的找到理想的三相電流波形,而且用此電流來驅動馬達所得到的轉矩漣波即為最小。

     Torque ripple reduction of the brushless DC motor has been the main issue of the servo driving systems in which the speed fluctuation, vibration, and acoustic noise should be minimized. Most methods for suppressing the torque ripples usually require Fourier series analysis, finite element analysis or least-mean-square minimization etc. These methods might lead to error during the complex Fourier series analysis and cost much time on calculation. In this thesis, a new method to improve the torque ripple based on the Genetic Algorithm is presented.

     The proposed method which is depended on Genetic Algorithm is to search the Fourier coefficients of three-phase stator currents for the given back-EMF waveforms which can be the pure sinusoidal and the pure trapezoidal shape or not. Then these Fourier coefficients can be used to recompose the three-phase optimum current commands for a three-phase balanced brushless DC motor driving. Therefore, the torque ripple must be expected to improve through this way, if the stator currents are perfectly achieved. The validity and practical applications of the proposed method are verified from the simulations and experimental results by using Matlab-Simulink tool and TMS320F2812 DSP respectively. In the simulation and experiment structure, the three-phase optimum current commands and the measured three-phase back-EMFs are set up as the tables. And they are obtained according to the rotor angle and speed information from the encoder. From the simulation and experiment results can prove that the proposed method provides a simple and efficient way to obtain three-phase optimum stator currents for the given back-EMF waveforms and the minimum torque ripple will be acquired too.

    摘要 I Abstract II Acknowledgement III Contents IV List of Tables VI List of Figures VII Symbols X Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Outline of This Thesis 4 Chapter 2 Brushless DC Motor 5 2.1 Brushless DC Motor Evolution 5 2.2 Basic BLDC Configuration 6 2.3 Modeling of BLDC 9 2.4 General Driving for BLDC 10 2.5 Typical Torque Ripple in BLDC 12 Chapter 3 Genetic Algorithm Applied to Reduce Torque Ripple 13 3.1 Basic Principle 14 3.2 The Proposed Method 15 3.2.1 Genetic Algorithm Introduction 15 3.2.2 Initial Population 15 3.2.3 Encoding and Decoding 17 3.2.4 Fitness 18 3.2.5 Reproduction 19 3.2.6 Crossover 19 3.2.7 Mutation 20 3.2.8 Termination Condition 21 3.3 Summary 21 Chapter 4 Experiment Hardware Structure 23 4.1 Control Structure of Experiment System 23 4.2 Digital Signal Processor 25 4.3 Experimental Circuits 27 4.3.1 Voltage Source Inverter Circuit 27 4.3.2 Current Measurement Circuit 28 4.3.3 Isolated Circuit 30 4.3.4 Time delay Circuit 31 Chapter 5 Simulation Results 32 5.1 Measurement of Back-EMF Waveform 33 5.2 Torque Ripple with Typical Current 35 5.3 Optimum Current Waveform 38 5.4 Speed Control Scheme 40 5.5 Summary 50 Chapter 6 Experiment 51 6.1 The Experimental Results 51 Case I: Speed command is 200 rpm. 51 Case II: Speed command is 1000 rpm. 59 6.2 Summary 68 Chapter 7 Conclusion and Suggestion 69 Reference 71 Appendices 74 Vita 80

    [1] D. C. Hanselman, Brushless Permanent-Magnet Motor Design, McGraw-Hill International Editions, 1991.
    [2] B. K. Bose, Modern Power Electronics and AC Drives, Prentice Hall PTR, 2002.
    [3] T. J. E. Miller, Brushless Permanent-Magnet and Reluctance Motor Drives, Clarendon Press Oxford, 1989.
    [4] F. Sahin, H. B. Ertan and K. Leblebicioglu, “Optimum Geometry for Torque Ripple Minimization of Switched Reluctance Motors,” IEEE Trans. on Energy Conversion, Vol. 15, No. 1, pp. 30-39, Mar. 2000.
    [5] S. Chen, C. Namuduri and S. Mir, “Controller-Induced Parasitic Torque Ripples in a PM Synchronous Motor,” IEEE Trans. on Industrial Electronics, Vol. 38, No. 5, pp. 1273-1281, Oct. 2002.
    [6] I. G. Bird and H. Zelaya De La Parra, “Fuzzy Logic Torque Ripple Reduction for DTC Based AC Drives,” IEE Electronic Letters, Vol. 33, Issue 17, pp. 1501-1502, Aug. 1997.
    [7] D. C. Hanselman, “Minimum Torque Ripple, Maximum Efficiency Excitation of Brushless Permanent Magnet Motors,” IEEE Trans. on Industrial Electronics, Vol. 41, No. 3, pp. 292-300, June 1994.
    [8] S. J. Park and H. W. Park, “A New Approach for Minimum-Torque-Ripple Maximum-Efficiency Control of BLDC Motor,” IEEE Trans. on Industrial Electronics, Vol. 47, No. 1, pp. 109-114, Feb. 2000.
    [9] J. Y. Hung and Z. Ding, “Minimization of Torque Ripple in Permanent Magnet Motors,” IEEE Trans. on Industrial Electronics, Vol. 22, pp. 459-463, Nov. 1992.
    [10] T. M. Jahns, “Torque Production in Permanent-Magnet Synchronous Motor Drive with Rectangle Current Excitation,” IEEE Trans. Industrial Application, Vol. IA-20, pp. 803-813, July/Aug. 1984.
    [11] J.Y. Hung and Z. Ding, “Design of Current to Reduce Torque Ripple in Brushless Permanent Magnet Motors,” IEE Proceedings Electronic, Vol. 140, No. 4, pp. 260-266, July 1993.
    [12] T. Sebastian, “Analysis of Induced EMF Waveforms and Torque Ripple in a Brushless Permanent Magnet Machine,” IEEE Trans. on Industrial Electronics, Vol. 32, No. 1,pp. 195-200, Jan. 1996.

    [13] S. K. Safi, P. P. Acarnley and A. G. Jack, “Analysis and Simulation of the High-Speed Torque Performance of Brushless DC Motor Drives,” IEE Proceedings Electronic, Power Proceedings Electronic, Vol. 142, No. 3, pp. 191-200, May 1995.
    [14] Y. H. Kim, Y. S. Kook and Yo Ko, “A New Technique of Reducing Torque Ripples for BDCM Drives,” IEEE Trans. on Industrial Electronics, Vol. 44, No. 5, pp.135-139, Oct. 1997.
    [15] S. H. Park, T. S. Kim, S. C. Ahn and D. S. Hyun, “A Simple Current Control
    Algorithm for Torque Ripple Reduction of Brushless DC Motor Using Four
    Switch Three-Phase Inverter,” IEEE Trans. on Industrial Electronics, Vol. 2,
    No. 3, pp. 574-579, June 2003.
    [16] C. Bi, Z. J. Liu and S. X. Chen, “Estimation of Back-EMF of PM BLDC Motors Using Derivative of FE Solutions,” IEEE Trans. on Magnetic. Vol. 36, No. 4, pp. 697-700, July 2000.
    [17] R. Carlson, “Analysis of Torque Ripple Due to Phase Commutation in Brushless DC Machines,” IEEE Trans. on Industrial Electronics, Vol. 28, No. 3, pp. 632-639, May 1992.
    [18] Y. Murai, “Torque Ripple Improvement for Brushless DC Miniature Motors,” IEEE Trans. on Industrial Electronics, Vol. 25, No. 3, pp. 441-450, May. 1989.
    [19] T. D. Batzel and K. Y. Lee, “Commutation Torque Ripple Minimization for Permanent Synchronous Machines with Hall Effect Position Feedback,” IEEE Trans. on Energy Conversion, Vol. 13, No. 3, pp. 257-263, Sept. 1998.
    [20] M. Markovic, M. Jufer and Y. Perriard, “Reducing the Cogging Torque in
    Brushless DC Motors by Using Conformal Mappings,” IEEE Trans. on
    Magnetic, Vol. 40, No. 2, pp. 451-456, Mar. 2004.
    [21] H. C. Chen, M. S. Huang, C. M. Liaw, Y. C. Chang, P. Y. Yu and J. M. Huang, “Robust Current Control for Brushless DC Motors,” IEE Power Proceedings Electronic, Vol. 147, No. 6, pp. 503-511, Nov. 2000.
    [22] J. R. Koza, Genetic Programming: on the Programming of Computers by Means of Natural Selection, A Brodford Book, The MIT Press Cambridge, Massachusetts London, England, 1992.
    [23] J.A. Miller, W. D. Potter, R. V. Gandham and C. N. Lapena, “An Evaluation
    of Local Improvement Operators for Genetic Algorithm,” IEEE Trans. on
    Industrial Electronics, Vol. 23, No. 5, pp. 1340-1351, Sept. 1993.
    [24] M. A. Marra and B. L. Walcott, “Stability and Optimality in Genetic Algorithm Control,” IEEE Proceedings on International Symposium, pp. 492-496, Sept. 1996.
    [25] S. O. Orero and M.R. Irving, “Economic Dispatch of Generators with Prohibited Operating Zones: A Genetic Algorithm Approach,” IEEE Trans. on Industrial Electronics, Vol. 143, Issue 6, pp. 174-179, Nov. 1996.
    [26] J. A. Vasconcelos, J. A. Ramirez, R.H.C. Takahashi and R.R Saldanha, “Improvements in Genetic Algorithms,” IEEE Trans on Industrial Electronics, Vol. 37, Issue 5, pp. 3414-3417, Sept. 2001.
    [27] M. A. S. Masoum; M. Ladjevardi, A. Jafarian; E. F. Fuchs, “Optimal Placement, Replacement and Sizing of Capacitor Banks in Distorted Distribution Networks by Genetic Algorithms,” IEEE Trans on Power Delivery, Vol. 19, Issue 4, pp. 1794-1801, Oct. 2004.
    [28] D. S. Weile and E. Michielssen, “The Control of Adaptive Antenna Arrays with Genetic Algorithms Using Dominance and Diploidy,” IEEE Trans on Antennas and Propagation, Vol. 49, Issue 10, pp. 1424-1433, Oct. 2001.

    下載圖示 校內:2006-08-01公開
    校外:2007-08-01公開
    QR CODE