感应电机矢量控制系统的参数辨识研究

发布时间：2018-01-10 20:21

本文关键词：感应电机矢量控制系统的参数辨识研究　出处：《天津理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着电机的新型控制策略和高性能的微控制器的出现,交流感应电机由于其结构和性能方面的优点,在众多的领域里得到了广泛应用。矢量控制技术具有控制精度高、动态响应快的优点。但是该方法高度依赖电机的动态模型,所以对电机参数估算的准确性有较高的要求。本文围绕感应电机的矢量控制技术,对其参数辨识问题展开研究,开发了参数辨识系统,具体工作如下:首先,介绍了SVPWM技术原理及其实现的关键问题,以坐标变换和电机动态模型为基础,阐述了基于转子磁场定向(FOC)的矢量控制技术原理,并对其数字化实现过程进行了详细分析。然后,重点对以飞思卡尔DSC MC56F84789控制器为核心的电机矢量控制和参数辨识系统的硬件平台设计做了论述。特别是对三个设计模块中的DSP核心控制板、辅助电源及驱动板的电路设计做了详细的说明。此外,对系统功率主电路模块的结构做了简要的说明。接下来,对感应电机的参数辨识方法进行了深入的研究。说明了电机出厂测试常用的电机参数的空载堵转试验方法,并以此方法得到的参数值为标准值,对下面的参数辨识方法进行评估。分析了感应电机矢量控制技术下的参数离线辨识策略,其原理就是基于电机的静态模型,充分利用硬件平台的资源,进行电机的直流试验、单相试验和空载试验,并根据实际条件进行一些简化处理,从而计算出电机参数。电机参数的离线辨识方法具有方法思想简单的特点,是电机参数在线辨识的基础,具有重要的研究和应用价值。讨论了基于递推最小二乘法的电机参数在线辨识原理。最后,以飞思卡尔控制器独有的集成开发环境CodeWarrior及其内置的Processor Expert为工具,进行了系统平台的软件设计,给出了部分软件流程图及程序,包括电机矢量控制算法和感应电机参数辨识相关算法。针对实验室的一台11kW的感应电动机进行了参数的辨识试验,得到了具有较高精度的电机参数值,验证了系统硬件开发平台的可靠性和软件设计的合理性。
[Abstract]:With the emergence of new control strategies and high performance microcontrollers, AC induction motors have many advantages in structure and performance. It has been widely used in many fields. Vector control technology has the advantages of high control precision and fast dynamic response. But this method is highly dependent on the dynamic model of the motor. Therefore, the accuracy of motor parameter estimation has high requirements. This paper focuses on the vector control technology of induction motor, the parameter identification problem is studied, and the parameter identification system is developed. The specific work is as follows: first. Based on coordinate transformation and motor dynamic model, the principle of vector control based on rotor magnetic field orientation (SVPWM) is introduced. And the digital realization process is analyzed in detail. Then. Focus on Freescale DSC. MC56F84789 controller is the core of the motor vector control and parameter identification system hardware platform design, especially for the three design modules of the DSP core control board. The circuit design of auxiliary power supply and drive board is described in detail. In addition, the structure of the power main circuit module of the system is briefly explained. The parameter identification method of induction motor is deeply studied, and the no-load shutoff test method of motor parameters commonly used in motor factory testing is explained, and the parameter value obtained by this method is standard value. The following parameter identification methods are evaluated. The off-line parameter identification strategy based on vector control technology of induction motor is analyzed. The principle is based on the static model of the motor and makes full use of the resources of the hardware platform. The DC test, single-phase test and no-load test of the motor are carried out, and some simplified treatment is carried out according to the actual conditions, so as to calculate the parameters of the motor. The off-line identification method of the parameters of the motor has the characteristics of simple method. It is the basis of on-line identification of motor parameters and has important research and application value. The principle of on-line identification of motor parameters based on recursive least square method is discussed. The software design of the system platform is carried out by using the integrated development environment CodeWarrior and its built-in Processor Expert, which is unique to the Freescale controller. Some software flow charts and programs are given, including motor vector control algorithm and induction motor parameter identification algorithm. The parameter identification experiments are carried out for a 11kW induction motor in the laboratory. The motor parameters with high accuracy are obtained, and the reliability of the hardware development platform and the rationality of software design are verified.
【学位授予单位】：天津理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM346;TP273

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