首页|考虑边端效应及参数变化的直线感应电机MRAS速度观测方法

考虑边端效应及参数变化的直线感应电机MRAS速度观测方法

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  • 国家科技期刊平台
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  • NSTL
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以轨道交通直线感应电机(Linear Induction Motor,LIM)牵引驱动系统速度观测器为研究对象,针对边端效应及电机参数变化导致辨识结果实时性、鲁棒性不足的问题,提出一种基于二阶超螺旋滑模的改进模型参考自适应系统(Model Reference Adaptive System,MRAS)速度观测方法.首先,以计及动态边端效应的初次级电压电流磁链方程为核心,设计直线感应电机标准MRAS速度观测器,降低边端效应对速度辨识性能的影响.然后,进一步分析初级集肤效应和初次级横向错位对标准MRAS速度观测器辨识性能的影响.在此基础上,基于二阶超螺旋算法对MRAS参考模型进行改进,利用主滑模面和辅助滑模面对次级磁链观测的干扰项进行补偿,同时抑制由于滑模算法引入的系统抖振,提高了速度观测器的鲁棒性和动态性能.最后,搭建仿真和硬件在环实验环境进行算法验证.实验结果表明:励磁互感及其他电机参数随边端效应修正因子变化,标准MRAS观测器在突加负载、引入测量误差和电机参数突变的工况下,速度辨识误差明显;改进的MRAS观测器能够实现直线感应电机速度的快速、准确辨识,基于该速度观测器的矢量控制策略,在突加负载、引入测量误差和电机参数突变的工况下,控制性能满足设计要求.研究结果能为轨道交通直线感应电机无速度传感器牵引驱动系统的研究提供一定借鉴.
MRAS velocity observation method for a linear induction motor considering edge effects and parameter variations
This study focused on the speed observer of a linear induction motor(LIM)traction drive system in the context of addressing real-time and robust limitations caused by edge effects and variations in motor parameters.An improved model reference adaptive system(MRAS)speed observation method was proposed based on the second-order super-twisting sliding mode.Initially,a standard MRAS speed observer for LIM was designed by incorporating dynamic edge effects into the primary voltage-current magnetic link equation,mitigating the impact of edge effects on speed identification performance.Subsequently,the influence of the primary skin effect and primary lateral misalignment on the identification performance of the standard MRAS speed observer was analyzed.Building upon this,an enhanced MRAS reference model using a second-order super-twisting algorithm was developed to compensate for disturbances in secondary magnetic link observation using the primary sliding mode surface and an auxiliary sliding mode surface.This enhancement not only suppressed system oscillations introduced by sliding mode algorithms but also enhanced the robustness and dynamic performance of the speed observer.Simulation and hardware-in-the-loop experiments were conducted to validate the proposed algorithm.The experimental results demonstrate that the standard MRAS observer exhibits significant speed identification errors due to changes in the excitation mutual inductance and other motor parameters resulting from edge effect correction factors,particularly under sudden load changes,measurement errors,and motor parameter variations.In contrast,the enhanced MRAS observer achieves rapid and accurate speed identification for linear induction motors,meeting design requirements for control performance in scenarios involving abrupt load changes,measurement errors,and motor parameter variations.The outcomes of this research can provide valuable insights for the study of speed sensorless traction drive systems in linear induction motors for rail transportation applications.

linear induction motorspeed sensorlessmodel reference adaptive systemedge effectsecond-order super-twisting sliding mode algorithm

胡海林、陈维金、虞诗焱、丰富、汪涛

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江西理工大学 电气学院,江西 赣州 341000

国家铁路局 磁浮技术铁路行业重点实验室,上海 201804

江西省磁悬浮技术重点实验室,江西 赣州 341000

直线感应电机 无速度传感器 模型参考自适应系统 边端效应 二阶超螺旋滑模算法

国家重点研发计划同济大学磁浮技术铁路行业重点实验室开放基金江西省磁悬浮技术重点实验室开放基金

2023YFB4302100204205100004

2024

10.19713/j.cnki.43-1423/u.T20231060

铁道科学与工程学报
中南大学 中国铁道学会

铁道科学与工程学报

CSTPCD北大核心EI
影响因子：0.837
ISSN：1672-7029
年,卷(期)：2024.21(4)
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