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作 者:姚培煜 冯国栋 吴轩[2] 彭卫文 丁北辰 YAO Peiyu;FENG Guodong;WU Xuan;PENG Weiwen;DING Beichen(School of Intelligent Systems Engineering,Sun Yat-sen University,Shenzhen 518107,China;College of Electrical and Information Engineering,Hunan University,Changsha 410082,China;School of Advanced Manufacturing,Sun Yat-sen University,Shenzhen 518107,China)
机构地区:[1]中山大学智能工程学院,广东深圳518107 [2]湖南大学电气与信息工程学院,湖南长沙410082 [3]中山大学先进制造学院,广东深圳518107
出 处:《电机与控制学报》2024年第2期142-151,共10页Electric Machines and Control
基 金:国家自然科学基金(52105079,62103455)。
摘 要:针对永磁同步电机转子初始位置估计的精度与收敛速度受限问题,提出一种基于高频信号注入的非线性建模与拟合实现的初始位置估计方法。首先,建立初始位置与高频信号响应的关联模型,表明高频响应可用于直接计算初始位置,但直接计算结果在大部分转子位置易受测量噪声的影响。为此,提出基于多项式模型建立位置估计非线性模型,选取合适的模型参数,利用少量测试点拟合该模型,即可实现初始位置的快速精确估计,有效提高了估计精度与系统抗干扰能力。实验与仿真结果表明,相比现有方法,提出的方法易于实现,无需复杂滤波器与观测器设计,仅需要选取少量测试点即可快速估计精确转子初始位置,在保证估计精度的同时改进了传统估计方法收敛速度慢问题。Aiming at the problem that the accuracy and convergence speed of rotor initial position estimation of permanent magnet synchronous motor are limited,a nonlinear modeling and fitting method based on high-frequency signal injection was proposed.Firstly,the correlation model between the initial position and the high-frequency signal response was established,which shows that the high-frequency response can be used to calculate the initial position directly,but the direct calculation results are vulnerable to the measurement noise in most rotor positions.To solve this issue,a polynomial model was used to establish the nonlinear model of location estimation,suitable model parameters were selected and a few of test points were used to fit the polynomial model to achieve rapid and accurate calculation of the initial position,which effectively improves the estimation accuracy and anti-interference ability of the system.The experimental and simulation results show that compared with the existing methods,in the proposed method it is easy to implement,complex filter and observer design is not needed,and only a few test points need to be selected to quickly estimate the initial position of the precise rotor,which ensures the estimation accuracy and improves the problem of slow convergence of the traditional estimation methods.
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