开关磁阻电机磁链特性检测与位置信号估计
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摘要
针对开关磁阻电机磁链检测过程复杂、实现困难的问题,提出一种基于dSPACE在线磁链特性检测系统。利用SIMULINK建立磁链计算模型,应用ControlDesk丰富的虚拟控件在线优化模型,采用阶跃电压法,简便快速检测磁链特性。针对开关磁阻电机简化磁链位置估计方法中换相位置不好确定、位置估计精确度低的缺点,提出一种基于特征位置磁链特性检测的改进型简化磁链位置估计方法。以相电感曲线的交点为特征位置,该位置磁链密度不高,因而该方法比传统的简化磁链位置估计方法精确度高。为减小电机加工工艺误差对特征位置磁链特性检测的影响,引入算术平均值的方法。实验结果验证了该磁链特性检测和改进型简化磁链位置估计方法的有效性。
As the flux linkage of the switched reluctance motor(SRM) is difficult to be detected,a flux linkage characteristic detection system based on dSPACE is proposed.The simulation model was proposed in the system.The system model was on-line optimized by the virtual control of the ControlDesk.The process of the flux linkage characteristic detection was simplified by step voltage.Based on flux linkage characteristic detection,an improved simplified flux linkage sensorless method was presented based on the special position,and the special position was the point of intersection of the phase inductance curves.As the special position magnetic density was sparse,the accuracy of the position estimate was higher than the traditional simplified flux linkage sensorless method.The arithmetic mean value was proposed for the special position flux linkage characteristic detection,and it avoided the influence of the error in the working course.At last,experiments verify the validity of the flux linkage characteristic detection and the sensorless scheme.
As the flux linkage of the switched reluctance motor(SRM) is difficult to be detected,a flux linkage characteristic detection system based on dSPACE is proposed.The simulation model was proposed in the system.The system model was on-line optimized by the virtual control of the ControlDesk.The process of the flux linkage characteristic detection was simplified by step voltage.Based on flux linkage characteristic detection,an improved simplified flux linkage sensorless method was presented based on the special position,and the special position was the point of intersection of the phase inductance curves.As the special position magnetic density was sparse,the accuracy of the position estimate was higher than the traditional simplified flux linkage sensorless method.The arithmetic mean value was proposed for the special position flux linkage characteristic detection,and it avoided the influence of the error in the working course.At last,experiments verify the validity of the flux linkage characteristic detection and the sensorless scheme.
引文
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[12]李珍国,李彩红,阚志忠,等.基于改进型简化磁链法的开关磁阻电机无位置传感器速度控制[J].电工技术学报,2011,26(6):62-66.LI Zhenguo,LI Caihong,KAN Zhizhong,et al.Switched reluc-tance motor sensorless speed control based on the improved sim-plified flux method[J].Transactions of China ElectrontechnicalSociety,2011,26(6):62-66.
[2]蔡燕,许镇琳,高超.基于DSP的开关磁阻电动机特性检测[J].组合机床与自动化加工技术,2005(11):22-24.CAI Yan,XU Zhenlin,GAO Chao.Method of characteristicsmeasurement for switched reluctance motor by DSP[J].ModularMachine Tool&Automatic Manufacturing Technique,2005(11):22-24.
[3]曹家勇,周祖德,陈幼平,等.开关磁阻电机特性检测与参数辨识方法研究[J].电工技术学报,2004,19(11):25-30.CAO Jiayong,ZHOU Zude,CHEN Youping,et al.Methods of char-acteristic measurement and model parameter identification forswitched reluctance motors[J].Transactions of China Electrotech-nical Society,2004,19(11):25-30.
[4]WANG S C,CHEN W S,LIAO W B,et al.A PC-based measure-ment system for determining magnetic characteristics of switchedreluctance motors[C]//International Conference on Power SystemTechnology,October 13-17,2002,Kunming,China.2002,4:2256-2260.
[5]薛梅,夏长亮,王慧敏,等.基于DSP的开关磁阻电机磁链特性检测与神经网络建模[J].电工技术学报,201126(2):68-73.XU Mei,XIA Changliang,WANG Huimin,et al.Flux linkagecharacteristic measurement based on DSP and artificial neural net-work modeling for switched reluctance motor[J].Transactions ofChina Electrotechnical Society,2011,26(2):68-73.
[6]夏长亮,王明超.基于RBF神经网络的开关磁阻电机单神经元PID控制[J].中国电机工程学报,2005,25(15):162-165.XIA Changliang,WANG Mingchao.Single neuron PID control forswitched reluctance motors based on RBF neural network[J].Pro-ceedings of the CSEE,2005,25(15):162-165.
[7]纪良文,蒋静坪,何峰,等.基于径向基函数神经网络的开关磁阻电机建模[J].电工技术学报,2001,16(4):7-11.JI Liangwen,JIANG Jingping,HE Feng,et al.Modeling ofswitched reluctance motors based on radial basis function neuralnetworks[J].Transactions of China Electrotechnical Society,2001,16(4):7-11.
[8]郑洪涛,蔡际令,蒋静坪.基于变结构模糊神经网络的开关磁阻电动机非线性模型[J].电工技术学报,2001,16(6):1-6.ZHENG Hongtao,CAI Jiling,JIANG Jingping.Nonlinear model-ing of switched reluctance motors based on variable structure fuzzy-neural networks[J].Transactions of China Electrotechnical Socie-ty,2001,16(6):1-6.
[9]郑洪涛,蒋静坪,徐德鸿,等.开关磁阻电动机无位置传感器能量优化控制[J].中国电机工程学报,2004,24(1):153-157.ZHENG Hongtao,JIANG Jingping,XU Dehong,et al.Switchedreluctance motor sensorless drive with energy optimizing controlstrategy[J].Proceedings of the CSEE,2004,24(1):153-157.
[10]KOBLARA T,SORANDARU C,MUSUROI S,et al.A lowvoltage sensorless switched reluctance motor drive using flux link-age method[C]//2010 12th International Conference on Optimi-zation of Electrical and Electronic Equipment(OPTIM),May 20-22,2010,Basov,Romania.2010:665-672.
[11]邱亦慧,詹琼华,马志源,等.基于简化磁链法的开关磁阻电机间接位置检测[J].中国电机工程学报,2001,21(10):59-62.QIU Yihui,ZHAN Qionghua,MA Zhiyuan,et al.The indirectposition sensing of SRM on the basis of simplified flux method[J].Proceedings of the CSEE,2001,21(10):59-62.
[12]李珍国,李彩红,阚志忠,等.基于改进型简化磁链法的开关磁阻电机无位置传感器速度控制[J].电工技术学报,2011,26(6):62-66.LI Zhenguo,LI Caihong,KAN Zhizhong,et al.Switched reluc-tance motor sensorless speed control based on the improved sim-plified flux method[J].Transactions of China ElectrontechnicalSociety,2011,26(6):62-66.