摘要
针对实心转子感应电机转子因集肤效应导致电阻和漏感随工况动态变化,从而导致传统基于固定参数的数学模型及矢量控制方法存在较大误差的问题,提出了一种基于分布式参数模型的实心转子感应电机建模方法与矢量控制策略。首先,通过建立多转子回路的分布式参数等效电路模型,推导电机状态方程及矢量控制方程,解决了传统模型因集肤效应导致的参数失配问题;然后,通过电机频率特性拟合方法确定等效转子电阻与漏感,结合差分进化算法对转子参数辨识过程进行了优化。仿真结果表明:所提模型及控制策略在空载启动、转速跟踪、负载突变等工况下,转速、磁链及转矩响应快速且稳态误差小,验证了方法的有效性,为实心转子感应电机的高性能控制提供了理论依据与技术参考。
Solid rotor induction motors are widely applied in medium and high-speed fields owing to their simple structure,high mechanical strength,and excellent thermal stability.However,the dynamic variations in rotor resistance and leakage inductance due to the skin effect under different opera-ting conditions introduce significant errors into traditional fixed-parameter mathematical models and vector control methods.To address this issue,a modeling and vector control strategy for SRIM based on distributed parameter models was proposed.Firstly,by constructing a multi-loop distributed parameter equivalent circuit model of the rotor,the state equations and vector control equations were drived,thereby mitigating the parameter mismatch caused by the skin effect in conventional models.Secondly,the equivalent rotor resistance and leakage inductance were determined through the fitting method of motor frequency characteristics.Furthermore,the identification process of rotor parameters was optimized using the differential evolution algorithm.Simulation results demonstrate that the proposed model and control strategy exhibit rapid and stable responses during no-load startup,speed tracking,and load transient conditions,thus validating the effectiveness of the proposed approach.This research provides a robust theoretical foundation and technical reference for achieving high-performance control of SRIM.
作者
冉光普
赵镜红
严思念
RAN Guangpu;ZHAO Jinghong;YAN Sinian(Naval Univ.of Engineering,Wuhan 430030,China)
出处
《海军工程大学学报》
北大核心
2025年第6期66-73,共8页
Journal of Naval University of Engineering
基金
海军工程大学自主立项基金资助项目(2022504040)。
关键词
实心转子感应电机
分布式参数模型
矢量控制
参数辨识
solid rotor induction motor
distributed parameter model
vector control
parameter identification
