开心呀Achilles 发表于 2022-10-23 23:36

基于凌鸥创芯LKS32MC08x的电感参数辨识方法在电机控制中的应用

本帖最后由 开心呀Achilles 于 2022-10-24 14:11 编辑

#申请原创#
       今天介绍下我最近预研的一种基于高频注入的电机电感参数辨识的方法,辨识精度还是比较理想的,文末会展示下辨识结果。这篇小文章主要从硬件平台、为什么参数辨识、选择什么方案、理论如何实现、实验过程、实验结果、结论和探讨,七个部分来介绍吧,也欢迎评论区大家一起探讨更好的方法。1、硬件介绍:      软件实现离不了优秀的硬件做后盾,FOC这种控制对于电压、电流的采样要求还是有点高的,如果没有可靠的电流采样,相信你是得不到什么可靠算法结论的。。。      首先,介绍下具体实现的硬件平台吧,MCU采用南京凌鸥创芯的LKS32MC081C8T6。 M0+DSP的双核架构,ARM和DSP都具有96Mhz主频,8KB RAM,64KB的FLASH空间,完全满足辨识算法对运算能力的要求。三电阻采样电流方案,利用MCU内部的差分运放电路+内置12位的ADC实现,这样三相采样电流全了,电压利用率也可以保证。预研的辨识算法主要应用在大家电的室内风机、室外风机上,220V 交流供电,调试时候最好注意下仿真器的隔离。2、为什么要进行参数辨识呢?      对于一个控制器适应多款电机的情况,商品损坏后不宜维修。如果控制器有参数辨识功能,可以实现即插即用,方便售后服务。当然参数辨识也可以用于改善电机的控制性能。随着温度、负载电流的变化,PMSM电机的电感、电阻、永磁体磁通都会变化,引起电机所需要的控制模型、无感观测模型逐渐偏离设计模型。3、选择什么方案?      搜索文献,电机参数辨识的文献比较多了,常见的离线方法有稳态下辨识出电阻(电压/电流),然后给定一个电压脉冲,通过电流响应上升时间计算出电感L。最小二乘辨识法在参数中也比较常用,适用性强,限制条件少;模型参考自适应方法有老师说效果也不错,该方法依赖于自适应率设计的好坏;扩展卡尔曼滤波方法可以同时辨识出多个参数,运算量稍大些;本文选择了高频注入方法实现电感的辨识,主要考虑这种方法受转子位置转动的影响比较小,可以实现离线辨识,也可以实现在线辨识,甚至可以辨识电感的同时实现电机转子位置的估计。4、理论如何实现?      高频注入法(HFI)主要应用在低速和零速运行时候的转子位置检测上;常规包括旋转高频注入,脉振高频注入,方波高频注入,以及上述方法衍生出来的多种方法。具体原理如下:不考虑定子电阻和转子电频率,忽略交直轴的耦合,旋转坐标系下永磁同步电机的高频数学模型可写为:data:image/png;base64,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    向电机的静止alpha \beta坐标系注入高频电压信号Uh;具体如下如公式2:data:image/png;base64,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**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**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式中:Uh为高频注入电压幅值,Wh为高频电压注入角频率,t表示高频注入电压信号的时间。    静止坐标系下的高频注入电压信号式(2)变换到同步旋转坐标系下:   将式(3)带入式(1)中,经过积分运算,得到旋转坐标系下的高频电流响应表达式:   将式(4)写成矢量形式:其中,正负序电流分别为:   将式5变换到静止坐标系下得到高频响应电流:   公式6可以看出,只需要准确的提取出高频电流响应信号的正负序电流的幅值,就可以辨识出交直轴电感了。通过正负序电流计算电感的计算式为:    本案例采用旋转高频注入方法实现电感的辨识,无感控制以及电感辨识的结构框图如下: 基于旋转高频注入的电感辨识结构图5、实现过程      具体实现过程中,涉及到滤波器的设计,高频注入信号的频率一般小于PWM载波的1/10,且远高于电机的基波频率。应用上,综合速度、精度与系统稳定性的考虑, 信号注入频率 fh 选取为系统控制频率fc的1/20 即可, 同时滤波器截止频率选择为信号的注入频率。在此频率点附近, 既能满足估算的快速性, 又能够保证估算精度的需求。 最低的注入频率选取应大于Rs/Ld。本案例PWM的载波频率16khz,选取500hz注入频率。注入电压幅值一般选择额定电压的10%~15%左右。      具体设计滤波器的系数,可以利用MATLAB里的FDA工具,附一个IIR带通滤波的设计图。具体实验的波形,利用JSCOPE进行抓取:
5.1、同步旋转轴上的正序电流alphabeta的分量5.2、同步旋转轴上的负序电流的alpha、beta的分量   5.3、正负序电流的alphabeta轴分量的均方根得到 正序电流和负序电流的幅值,如下图:得到正序电流、负序电流的幅值,又一直注入电压的幅值以及频率,利用公式7,可计算出电机的直、交轴电感。6、实验结果表1为多个不同一个应用的参数辨识的结果,可以看出辨识的电感范围覆盖到了13.987mh~155.871mh,与用LCR仪器测出来的电感(1V,1000khz检测条件)在15%内的误差内。其他电感段的电机,没有实物电机,暂时没有测试。电机电阻电感参数辨识表1:
电机种类Ld电感(mh)Lq电感(mh)辨识相电阻(欧姆)
洗衣机#1电机14.19117.9322.68
风扇#1电机13.98721.2721.06
风扇#2电机18.39719.7231.56
100W风扇#1123.779155.87112.31
100W风扇#281.718109.31114.54
100W风扇#353.27156.87116.82
900W风扇#116.15422.9961.02

下图为某100W的普通风扇,辨识电阻、电感后即可正常运行,100w额定功率附近的三个电机,一个控制器都可以兼容正常运行。7、结论、探讨      采用高频注入可以实现电感参数的辨识,由于高频注入固有的噪声的缺点,所以后续还可以进行降低噪声的改进,具体方向也许是优化注入信号的方法,采用注入随机信号将频谱分散,进而降低噪声。      高频注入方案可以实现在辨识电感的同时,将电机的转子初始位置辨识出来,知道转自初始位置后,可以减小定位带来的抖动,以及缩短启动时间。
参考文献:《现代永磁同步电机控制原理及MATLAB仿真》 袁雷

21小跑堂 发表于 2022-10-24 10:30

欢迎参与原创文章活动~下次记得 @21小跑堂 噢~ 这样跑堂可以更容易找到您

memory24746 发表于 2022-10-24 12:41

先点赞收藏,再学习,{:lol:}

上下而求索 发表于 2022-10-25 08:51

感谢大佬的认可{:smile:}。专业,有深度,后续应用有想法、建议,可以随时和公司联系,欢迎大家来交流。

weifeng90 发表于 2022-12-6 19:12

写的详细,干货贴啊。

xu@xupt 发表于 2022-12-7 16:25

够专业,有深度{:biggrin:}

Innercourage 发表于 2023-1-12 15:02

分析的比较到位

liubinghui 发表于 2024-6-26 15:17

      值得学习下!

yg.f 发表于 2024-8-31 08:23

厉害

gangong 发表于 2024-10-25 14:35

非常棒

这是神魔节奏 发表于 2024-12-13 09:19

公式5后边的正负序电流公式是怎么推导出了的,烦请指点

gly1041 发表于 2025-5-13 20:59

非常棒
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