基于矢量控制的异步电机效率优化控制研究

发布时间：2018-12-13 21:27

【摘要】：当今社会，电机作为主要的动力设备已经被广泛应用于工业、农业、运输业等各个行业，尤其是异步电机的用电量已经占了工业用电量的60%以上。但是在很多场合，异步电机的效率却很低，对于能源需求不断增加的今天，提高异步电机的效率有重要的现实意义。论文首先对异步电机的损耗进行分析，在此基础上搭建了考虑异步电机铁耗的仿真模型。采用转子磁链定向控制的电压空间矢量和双闭环控制保证了系统的快速响应性和稳定性，为下文的效率优化研究奠定了基础。目前异步电机效率优化控制方法主要有三种：损耗模型优化控制，定子电流最小化优化控制和输入功率最小化优化控制。损耗模型优化控制易受电机参数变化影响，对优化效果不利；定子电流最小是局部最优；输入功率最小优化控制既可以不受电机参数影响又可以做到全局最优，本文采用输入功率最小优化控制。论文在深入研究了黄金分割法和模糊搜索控制的基础上，给出了一种新型的混合控制方法，该方法在线获得系统的输入功率，不受电机参数变化的影响。该方法解决了黄金分割在搜索初始阶段步长较大引起电磁转矩波动较大的问题，在模糊控制中设计了合理的比例因子和隶属度函数，保证了在初始阶段搜索步长根据电机工况进行在线调整，减小转矩波动；并针对弱磁情况，给出了一种动态电流分配法提高系统动态响应速度。对比仿真结果，可以看出黄金分割法具有确定的收敛速度，在优化的后半段中接入黄金分割法可以有效解决模糊控制在最优点附近震荡问题和收敛速度慢问题，保证了系统的稳定性。本文设计的混合控制方法结合了黄金分割法和模糊搜索控制法的优点，不仅有效提高了系统的效率，也明显提高了系统的稳定性，由于不受电机参数的影响，，具有较好的鲁棒性。仿真结果验证了动态电流分配法有效性和新型混合搜索法的正确性，在此基础上又对混合搜索法在不同工况下的优化效果做了进一步的研究，对比分析了混合控制方法的优点。
[Abstract]:Nowadays, as the main power equipment, motor has been widely used in industry, agriculture, transportation and other industries, especially in the asynchronous motor power consumption has accounted for more than 60% of the industrial electricity consumption. However, in many cases, the efficiency of asynchronous motor is very low, which has an important practical significance to improve the efficiency of asynchronous motor. Firstly, the loss of induction motor is analyzed, and a simulation model considering the iron loss of asynchronous motor is built. The voltage space vector and double closed loop control of rotor flux oriented control can guarantee the system's fast response and stability, which lays a foundation for the efficiency optimization research in this paper. At present, there are three kinds of optimal control methods for induction motor efficiency: loss model optimization control, stator current minimization optimization control and input power minimization optimization control. The optimal control of loss model is easy to be affected by the parameters of the motor, which is unfavorable to the optimization effect, and the minimum stator current is the local optimum. The input power minimum optimal control can not only be influenced by the motor parameters, but also be globally optimal. In this paper, the input power minimum optimization control is adopted. Based on the research of golden section method and fuzzy search control, a new hybrid control method is proposed in this paper. This method can get the input power of the system online and is not affected by the change of motor parameters. This method solves the problem that the large step size of golden section in the initial stage of searching leads to large electromagnetic torque fluctuation, and designs a reasonable proportion factor and membership function in fuzzy control. In the initial stage, the searching step size is adjusted online according to the motor working condition to reduce the torque ripple. For weak magnetic field, a dynamic current allocation method is proposed to improve the dynamic response speed of the system. Compared with the simulation results, we can see that the golden section method has certain convergence speed, and the golden section method can effectively solve the problem of fuzzy control oscillating near the best point and the slow convergence speed in the second half of the optimization. The stability of the system is guaranteed. The hybrid control method designed in this paper combines the advantages of golden section method and fuzzy search control method. It not only effectively improves the efficiency of the system, but also obviously improves the stability of the system, because it is not affected by the parameters of the motor. It has good robustness. The simulation results verify the validity of the dynamic current distribution method and the correctness of the new hybrid search method. On this basis, the optimization effect of the hybrid search method under different working conditions is further studied, and the advantages of the hybrid control method are compared and analyzed.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM343

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