永磁同步电机节能控制系统研究

发布时间：2018-12-12 23:03

【摘要】：能源短缺是社会一大热点问题,伴随着技术的发展,整个社会用电量不断攀升。我国电机用电量占全国总电量的一半以上,而且电机控制系统运行效率普遍比较低。对电机控制系统节能优化运行进行研究有着巨大的经济效益和现实需求。永磁同步电机具有效率高、可靠性好等优点,可以满足运动控制系统高效、节能的市场需求,现已成为节能控制系统的首选。永磁同步电机是一个非线性的机/电能量转换系统,其控制系统中存在如电流耦合、磁链饱和、参数变化等诸多干扰,这些干扰直接影响永磁同步电机控制系统的性能。论文研究提高永磁同步电机节能控制系统的性能以及鲁棒性,有着非常高的理论和实践意义。电机参数变化对控制系统产生干扰,论文由永磁同步电机参数在线估计着手。电机参数在线估计可分为动态模型线性化和辨识算法两部分。论文首先对永磁同步电机动态模型线性化过程进行改进,使用帕德线性化方法获得更高精度的永磁同步电机动态线性模型。然后,引入多新息递推最小二乘算法对永磁同步电机参数进行在线参数估计,使用模糊控制算法改进在线参数估计算法中遗忘因子大小选择策略,使得永磁同步电机多参数在线估计在精度、速度和稳定性等方面都有了较为明显的提升。永磁同步电机常用的两种节能控制策略为损耗模型法和输入功率搜索法。损耗模型是根据电机参数对可控损耗(电气损耗)建立的数学模型。控制器根据损耗模型计算得到电流参考值,损耗模型精度及鲁棒性受电机参数影响。因此永磁同步电机参数在线估计的研究有助于提高损耗模型控制器的性能和鲁棒性。本文使用上述在线参数估计算法实时估算电机参数,把参数估计值带入损耗模型控制器,获得更准确的电流参考值。在线参数估计降低了电机参数变化对损耗模型的干扰,增强了控制算法的鲁棒性,实现了电机控制系统更高效的运行。输入功率搜索法是一种局部寻优算法。搜索法通过检测逆变器直流侧功率,控制电机输入电压,最终找到电机输入功率最低的稳定工作点。输入功率搜索控制策略存在收敛速度慢、转矩波动大等缺点。本文利用电机损耗模型计算输入功率最低工作点存在区间,大大的降低了搜索法初始搜索范围,进而提高了算法收敛速度。最后文章在dSPACE半实物实验平台上搭建了永磁同步电机基于损耗模型节能策略的控制系统。通过实验验证了在线参数估计算法对于损耗模型节能策略效率及鲁棒性的提升。
[Abstract]:Energy shortage is a hot issue in society. With the development of technology, the electricity consumption of the whole society is rising. The electric power consumption in China accounts for more than half of the total electricity consumption in China, and the efficiency of motor control system is generally low. It has great economic benefit and realistic demand to study the energy saving optimization operation of motor control system. Permanent magnet synchronous motor (PMSM) has the advantages of high efficiency and good reliability. It can meet the market demand of high efficiency and energy saving of motion control system. It has become the first choice of energy-saving control system. Permanent magnet synchronous motor (PMSM) is a nonlinear mechanical / electrical energy conversion system. There are many disturbances in the control system such as current coupling, flux saturation, parameter change and so on. These disturbances directly affect the performance of PMSM control system. The research on improving the performance and robustness of PMSM energy-saving control system is of great theoretical and practical significance. The parameters of permanent magnet synchronous motor (PMSM) are estimated on line. The on-line estimation of motor parameters can be divided into two parts: dynamic model linearization and identification algorithm. Firstly, the linearization process of PMSM dynamic model is improved, and the PMSM dynamic linear model with higher precision is obtained by using Pad linearization method. Then, multi-innovation recursive least square algorithm is introduced to estimate the parameters of PMSM on line, and fuzzy control algorithm is used to improve the selection strategy of forgetting factor in the on-line parameter estimation algorithm. It can improve the precision, speed and stability of PMSM. Loss model method and input power search method are two common energy saving control strategies for permanent magnet synchronous motor (PMSM). The loss model is a mathematical model based on the parameters of the motor to control the loss (electrical loss). The controller calculates the current reference value according to the loss model. The precision and robustness of the loss model are affected by the motor parameters. Therefore, the on-line parameter estimation of PMSM is helpful to improve the performance and robustness of the loss model controller. In this paper, the on-line parameter estimation algorithm is used to estimate the motor parameters in real time, and the parameter estimation value is brought into the loss model controller to obtain more accurate current reference value. On-line parameter estimation reduces the disturbance of motor parameters to the loss model, enhances the robustness of the control algorithm, and realizes the more efficient operation of the motor control system. Input power search is a local optimization algorithm. By detecting the DC side power of the inverter and controlling the input voltage of the motor, the search method finally finds the stable working point with the lowest input power of the motor. The input power search control strategy has some disadvantages, such as slow convergence speed and high torque fluctuation. In this paper, the minimum operating point of input power is calculated by using the motor loss model, which greatly reduces the initial search range of the search method and improves the convergence speed of the algorithm. At last, the control system of PMSM based on loss model is built on the dSPACE hardware-in-the-loop experimental platform. Experimental results show that the online parameter estimation algorithm can improve the efficiency and robustness of the energy saving strategy of the loss model.
【学位授予单位】：江南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273;TM341

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