CN112713835A - 一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法 - Google Patents

一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法 Download PDF

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CN112713835A
CN112713835A CN202011523548.6A CN202011523548A CN112713835A CN 112713835 A CN112713835 A CN 112713835A CN 202011523548 A CN202011523548 A CN 202011523548A CN 112713835 A CN112713835 A CN 112713835A
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vector
prediction
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permanent magnet
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顾贤
刘鹏
马继光
马健东
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Nantong Smile Precision Equipment Co ltd
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/22Current control, e.g. using a current control loop
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/06Linear motors
    • H02P25/064Linear motors of the synchronous type
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P27/00Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters
    • H02P27/08Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation
    • H02P27/12Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation pulsing by guiding the flux vector, current vector or voltage vector on a circle or a closed curve, e.g. for direct torque control

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Abstract

本发明公开了一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法;首先,获取实时的三相定子电流在dq坐标系下分量;其次,建立预测模型,将其分解为无源分量与有源分量;再次,对无源分量进行评估,同时,挑选两个线性无关的矢量作为基底,计算他们对应的dq坐标系下分量;然后,根据预测模型中无源分量、有源分量信息,以及计算得到的基底矢量相关信息进行电流预测,获取不同电压矢量对应的电流预测值;最后,利用最小化价值函数的方法挑选出最优电压矢量并将其对应的开关状态作用于逆变器。本发明提供的永磁同步直线电机模型预测电流控制能够极大降低控制器计算负担,从而提升系统动稳态性能。

Description

一种计及预测模型分解的永磁同步直线电机模型预测电流控 制方法
技术领域
本发明涉及一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法,属于电机驱动及控制领域。
背景技术
永磁同步直线电机由于其简单的结构、高功率密度、高过载能力等优越性能,受到了广泛关注。同时,比起传统电机,直线电机能够直接获得直线机械位移而无需传动装置,这大大降低了系统的机械损耗,提升了整体效率。模型预测控制由于其控制思想简单、动态响应快、易于实现多目标控制等优势,已成功应用于电机控制领域。然而,模型预测控制在每个控制周期内需要对逆变器可以提供的所有矢量进行评估,该过程涉及大量的乘除运算,给控制器带来了极大的计算负担。因此,研究一种可以降低控制器计算负担、提高系统动态性能的模型预测算法,具有广阔的应用前景。
发明内容
技术问题:针对上述现有技术,提出一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法,能够大大降低控制器计算负担。
技术方案:一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法,包括如下步骤:
步骤1:采样三相定子电流is,利用Park变换(1)计算定子电流在dq坐标系下分量,id与iq
步骤2:利用模型分解模块(2)对预测模型中的无源部分P以及有源部分A进行计算;
步骤3:选取两个线性无关的电压矢量作为一组基底矢量[v1,v2]T,利用基底矢量评估模块(3)计算其在dq坐标系下的电压分量ud(v1,2)与uq(v1,2);
步骤4:根据P,A,ud(v1,2)与uq(v1,2),利用电流预测模块(4)计算不同矢量对应的电流预测值is k+1(ui),i为0-7;
步骤5:利用动子速度外环PI控制器(5)获得q轴电流参考值iq *,并给定d轴电流参考值id *=0;进而,利用价值函数最小化模块(6)挑选出最优电压矢量uopt,将其对应的的开关状态Sabc opt作用于逆变器(7),实现对永磁同步直线电机(Permanent MagnetSynchronous Linear Motor,PMSLM)的有效控制。
进一步的,步骤2所述的预测模型无源与有源部分具体为:
PMSLM电流预测方程为
Figure BDA0002847752510000021
式中,id k+1与iq k+1分别为d轴与q轴电流预测值;id k与iq k分别为d轴与q轴电流采样值;Ld与Lq分别为绕组电感的d轴与q轴分量;Rs为绕组内阻值;Ts为采样周期;v为电机动子速度;τ为极距;ψf为永磁体磁链;ud k与uq k分别为定子电压d轴与q轴分量;
从式(1)可以看出,电流预测值包含两部分,一部分与作用的定子电压无关,因此称之为无源部分,而另一部分取决于作用的定子电压,因此称之为有源部分,即
Figure BDA0002847752510000022
Figure BDA0002847752510000023
基于此,所述的无源部分P=[Pd,Pq]T,所述的有源部分A=[Ad,Aq]T
进一步的,步骤3所述的基底矢量[v1,v2]T具体为:
对于三相逆变器能够提供的8个基本电压矢量u0-u7,线性无关的矢量组合包括:[u1,u2]T,[u1,u3]T,[u1,u5]T,[u1,u6]T,[u2,u3]T,[u2,u4]T,[u2,u6]T,[u3,u4]T,[u3,u5]T,[u4,u5]T,[u4,u6]T,[u5,u6]T;基底矢量[v1,v2]T可以为上述线性无关矢量组合中的任意一组。进一步的,步骤4所述的电流预测方法具体为:
根据式(1)-(3),对于任意矢量ui,其对应的电流预测值is k+1(ui)=[id k+1(ui),iq k+1(ui)]可以表示为
Figure BDA0002847752510000031
式中,ki1,ki2,ki3以及ki4为矢量ui对应的常系数,取决于基底矢量;
具体的,若选择[u1,u2]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[0,1,0,1],[k31,k32,k33,k34]=[-1,1,-1,1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[0,-1,0,-1],[k61,k62,k63,k64]=[1,-1,1,-1];
若选择[u1,u3]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[1,1,1,1],[k31,k32,k33,k34]=[0,1,0,1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[-1,-1,-1,-1],[k61,k62,k63,k64]=[0,-1,0,-1];
若选择[u1,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[-1,-1,-1,-1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[1,1,1,1];
若选择[u1,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[1,-1,1,-1],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[-1,1,-1,1],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u2,u3]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,-1,1,-1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[0,1,0,1],[k41,k42,k43,k44]=[-1,1,-1,1],[k51,k52,k53,k54]=[-1,0,-1,0],[k61,k62,k63,k64]=[0,-1,0,-1];
若选择[u2,u4]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[0,-1,0,-1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[1,1,1,1],[k41,k42,k43,k44]=[0,1,0,1],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[-1,-1,-1,-1];
若选择[u2,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,1,1,1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[-1,-1,-1,-1],[k51,k52,k53,k54]=[-1,0,-1,0],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u3,u4]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[0,-1,0,-1],[k21,k22,k23,k24]=[1,-1,1,-1],[k31,k32,k33,k34]=[1,0,1,0],[k41,k42,k43,k44]=[0,1,0,1],[k51,k52,k53,k54]=[-1,1,-1,1],[k61,k62,k63,k64]=[-1,0,-1,0];
若选择[u3,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,-1,-1,-1],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[1,0,1,0],[k41,k42,k43,k44]=[1,1,1,1],[k51,k52,k53,k54]=[0,1,0,1],[k61,k62,k63,k64]=[-1,0,-1,0];
若选择[u4,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,0,-1,0],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[1,-1,1,-1],[k41,k42,k43,k44]=[1,0,1,0],[k51,k52,k53,k54]=[0,1,0,1],[k61,k62,k63,k64]=[-1,1,-1,1];
若选择[u4,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,0,-1,0],[k21,k22,k23,k24]=[-1,-1,-1,-1],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[1,0,1,0],[k51,k52,k53,k54]=[1,1,1,1],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u5,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,1,-1,1],[k21,k22,k23,k24]=[-1,0,-1,0],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[1,-1,1,-1],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[0,1,0,1]。
进一步的,步骤5所述的最优矢量挑选方法具体为:
构建基于电流误差的价值函数,如下
Figure BDA0002847752510000041
根据步骤4得到的电流预测值is k+1(ui),对8个基本电压矢量进行评估,选取令价值函数最小的矢量为最优矢量uopt,即
Figure BDA0002847752510000042
有益效果:1)采用改进的电流预测算法,大大降低了控制器计算负担;
2)保留了传统模型预测控制算法动态响应快与跟踪精度高的优势;
3)间接地,由于大大降低了计算负担,系统能够采用更高的采样频率,从而提供稳态控制精度。
附图说明
图1为本发明一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法的控制框图,图中,1-Park变换器,2-模型分解模块,3-基底矢量评估模块,4-电流预测模块,5-PI控制器,6-价值函数最小化模块,7-两电平逆变器,8-PMSLM。
图2为本发明一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法的两电平逆变器空间矢量分布图。
图3为本发明计及预测模型分解的永磁同步直线电机模型预测电流控制方法的定子电流,转矩与动子速度稳态仿真波形,此时,负载转矩设为100N·m,动子速度给定设为2m/s。
图4为本发明计及预测模型分解的永磁同步直线电机模型预测电流控制方法的定子电流,转矩与动子速度在变负载转矩条件下的仿真波形,此时,负载转矩在0.2s时由100N·m突变为150N·m,动子速度给定保持在2m/s。
图5为本发明计及预测模型分解的永磁同步直线电机模型预测电流控制方法的定子电流,转矩与动子速度在变转速给定条件下的仿真波形,此时,负载转矩保持在150N·m,转速给定在0.35s时由2m/s突变为3m/s。
具体实施方式
下面结合附图并通过实施例对本发明作进一步的详细说明,以下实施例是对本发明的解释而本发明并不局限于以下实施例。
一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法,包括如下步骤:
步骤1:采样三相定子电流is,利用Park变换(1)计算定子电流在dq坐标系下分量,id与iq
步骤2:利用模型分解模块(2)对预测模型中的无源部分P以及有源部分A进行计算。具体的,PMSLM电流预测方程为
Figure BDA0002847752510000051
式中,id k+1与iq k+1分别为d轴与q轴电流预测值;id k与iq k分别为d轴与q轴电流采样值;Ld与Lq分别为绕组电感的d轴与q轴分量;Rs为绕组内阻值;Ts为采样周期;v为电机动子速度;τ为极距;ψf为永磁体磁链;ud k与uq k分别为定子电压d轴与q轴分量。
从式(1)可以看出,电流预测值包含两部分,一部分与作用的定子电压无关,称之为无源部分,而另一部分决定于作用的定子电压,因此称之为有源部分,即
Figure BDA0002847752510000052
Figure BDA0002847752510000061
基于此,所述的无源部分P=[Pd,Pq]T,所述的有源部分A=[Ad,Aq]T
步骤3:选取两个线性无关的电压矢量作为一组基底矢量[v1,v2]T,利用基底矢量评估模块(3)计算其在dq坐标系下的电压分量ud(v1,2)与uq(v1,2)。具体的,对于三相逆变器能够提供的8个基本电压矢量u0-u7,如图2所示,线性无关的矢量组合包括:[u1,u2]T,[u1,u3]T,[u1,u5]T,[u1,u6]T,[u2,u3]T,[u2,u4]T,[u2,u6]T,[u3,u4]T,[u3,u5]T,[u4,u5]T,[u4,u6]T,[u5,u6]T。基底矢量[v1,v2]T可以为上述线性无关矢量组合中的任意一组。
步骤4:根据P,A,ud(v1,2)与uq(v1,2),利用电流预测模块(4)计算不同矢量对应的电流预测值is k+1(ui),i为0-7。具体的,根据式(1)-(3),对于任意矢量ui,其对应的电流预测值is k+1(ui)=[id k+1(ui),iq k+1(ui)]可以表示为
Figure BDA0002847752510000062
式中,ki1,ki2,ki3以及ki4为矢量ui对应的常系数,取决于基底矢量。
具体的,若选择[u1,u2]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[0,1,0,1],[k31,k32,k33,k34]=[-1,1,-1,1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[0,-1,0,-1],[k61,k62,k63,k64]=[1,-1,1,-1];
若选择[u1,u3]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[1,1,1,1],[k31,k32,k33,k34]=[0,1,0,1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[-1,-1,-1,-1],[k61,k62,k63,k64]=[0,-1,0,-1];
若选择[u1,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[-1,-1,-1,-1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[1,1,1,1];
若选择[u1,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[1,-1,1,-1],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[-1,1,-1,1],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u2,u3]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,-1,1,-1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[0,1,0,1],[k41,k42,k43,k44]=[-1,1,-1,1],[k51,k52,k53,k54]=[-1,0,-1,0],[k61,k62,k63,k64]=[0,-1,0,-1];
若选择[u2,u4]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[0,-1,0,-1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[1,1,1,1],[k41,k42,k43,k44]=[0,1,0,1],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[-1,-1,-1,-1];
若选择[u2,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,1,1,1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[-1,-1,-1,-1],[k51,k52,k53,k54]=[-1,0,-1,0],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u3,u4]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[0,-1,0,-1],[k21,k22,k23,k24]=[1,-1,1,-1],[k31,k32,k33,k34]=[1,0,1,0],[k41,k42,k43,k44]=[0,1,0,1],[k51,k52,k53,k54]=[-1,1,-1,1],[k61,k62,k63,k64]=[-1,0,-1,0];
若选择[u3,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,-1,-1,-1],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[1,0,1,0],[k41,k42,k43,k44]=[1,1,1,1],[k51,k52,k53,k54]=[0,1,0,1],[k61,k62,k63,k64]=[-1,0,-1,0];
若选择[u4,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,0,-1,0],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[1,-1,1,-1],[k41,k42,k43,k44]=[1,0,1,0],[k51,k52,k53,k54]=[0,1,0,1],[k61,k62,k63,k64]=[-1,1,-1,1];
若选择[u4,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,0,-1,0],[k21,k22,k23,k24]=[-1,-1,-1,-1],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[1,0,1,0],[k51,k52,k53,k54]=[1,1,1,1],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u5,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,1,-1,1],[k21,k22,k23,k24]=[-1,0,-1,0],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[1,-1,1,-1],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[0,1,0,1]。
本例中,选取[u1,u2]T作为基底矢量。
步骤5:利用转速外环PI控制器(5)获得q轴电流参考值iq *,并给定d轴电流参考值id *=0。进而,利用价值函数最小化模块(6)挑选出最优uopt,将其对应的的开关状态Sabc opt作用于逆变器(7),实现对PMSLM的有效控制。具体的,最优矢量挑选方法为:
构建基于电流误差的价值函数,如下
Figure BDA0002847752510000081
根据步骤4得到的电流预测值is k+1(ui),对8个基本电压矢量进行评估,选取令价值函数最小的矢量为最优矢量uopt,即
Figure BDA0002847752510000082
在负载转矩为100N·m,动子速度给定为2m/s的条件下,实施本发明公开的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,定子电流、电磁转矩与动子速度波形如图3所示,可以看出,定子电流正弦,幅值约为3A,电磁转矩保持为100N.m,动子速度稳定为2m/s。
在0.2s将负载转矩突变为150N·m,动子速度给定2m/s,为实施本发明公开的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,定子电流、电磁转矩与转速波形如图4所示,可以看出,负载转矩突变后,定子电流增大至4.5A,电磁转矩迅速达到150N·m,满足负载要求,动子速度略有降低后再次稳定在2m/s。
在0.35s将动子速度给定突变为3m/s,负载转矩保持为150N·m,实施本发明公开的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,定子电流、电磁转矩与转速波形如图5所示,可以看出,动子速度给定突变后,定子电流增大至8A,电磁转矩输出约300N·m,动子速度呈线性上升,速度到达3m/s后,电磁转矩回到150N·m,动子速度稳定在3m/s。
本说明书中所描述的以上内容仅仅是对本发明所作的举例说明。本发明所属技术领域的技术人员可以对所描述的具体实施例做各种修改或补充或采用类似的方式替代,只要不偏离本发明说明书的内容或者超越本权利要求书所定义的范围,均应属于本发明的保护范围。

Claims (5)

1.一种计及预测模型分解的永磁同步直线电机模型预测电流控制方法,其特征在于,包括如下步骤:
步骤1:采样三相定子电流is,利用Park变换(1)计算定子电流在dq坐标系下分量,id与iq
步骤2:利用模型分解模块(2)对预测模型中的无源部分P以及有源部分A进行计算;
步骤3:选取两个线性无关的电压矢量作为一组基底矢量[v1,v2]T,利用基底矢量评估模块(3)计算其在dq坐标系下的电压分量ud(v1,2)与uq(v1,2);
步骤4:根据P,A,ud(v1,2)与uq(v1,2),利用电流预测模块(4)计算不同矢量对应的电流预测值is k+1(ui),i为0-7;
步骤5:利用动子速度外环PI控制器(5)获得q轴电流参考值iq *,并给定d轴电流参考值id *=0;进而,利用价值函数最小化模块(6)挑选出最优电压矢量uopt,将其对应的的开关状态Sabc opt作用于逆变器(7),实现对永磁同步直线电机(Permanent Magnet SynchronousLinear Motor,PMSLM)的有效控制。
2.根据权利要求1所述的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,其特征在于,步骤2所述的预测模型无源与有源部分具体为:
PMSLM电流预测方程为
Figure FDA0002847752500000011
式中,id k+1与iq k+1分别为d轴与q轴电流预测值;
Figure FDA0002847752500000012
与iq k分别为d轴与q轴电流采样值;Ld与Lq分别为绕组电感的d轴与q轴分量;Rs为绕组内阻值;Ts为采样周期;v为电机动子速度;τ为极距;ψf为永磁体磁链;ud k与uq k分别为定子电压d轴与q轴分量;
从式(1)可以看出,电流预测值包含两部分,一部分与作用的定子电压无关,因此称之为无源部分,而另一部分取决于作用的定子电压,因此称之为有源部分,即
Figure FDA0002847752500000013
Figure FDA0002847752500000021
基于此,所述的无源部分P=[Pd,Pq]T,所述的有源部分A=[Ad,Aq]T
3.根据权利要求1所述的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,其特征在于,步骤3所述的基底矢量[v1,v2]T具体为:
对于三相逆变器能够提供的8个基本电压矢量u0-u7,线性无关的矢量组合包括:[u1,u2]T,[u1,u3]T,[u1,u5]T,[u1,u6]T,[u2,u3]T,[u2,u4]T,[u2,u6]T,[u3,u4]T,[u3,u5]T,[u4,u5]T,[u4,u6]T,[u5,u6]T;基底矢量[v1,v2]T可以为上述线性无关矢量组合中的任意一组。
4.根据权利要求1所述的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,其特征在于,步骤4所述的电流预测方法具体为:
根据式(1)-(3),对于任意矢量ui,其对应的电流预测值is k+1(ui)=[id k+1(ui),iq k+1(ui)]可以表示为
Figure FDA0002847752500000022
式中,ki1,ki2,ki3以及ki4为矢量ui对应的常系数,取决于基底矢量;
具体的,若选择[u1,u2]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[0,1,0,1],[k31,k32,k33,k34]=[-1,1,-1,1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[0,-1,0,-1],[k61,k62,k63,k64]=[1,-1,1,-1];
若选择[u1,u3]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[1,1,1,1],[k31,k32,k33,k34]=[0,1,0,1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[-1,-1,-1,-1],[k61,k62,k63,k64]=[0,-1,0,-1];
若选择[u1,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[-1,-1,-1,-1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[1,1,1,1];
若选择[u1,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,0,1,0],[k21,k22,k23,k24]=[1,-1,1,-1],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[-1,0,-1,0],[k51,k52,k53,k54]=[-1,1,-1,1],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u2,u3]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,-1,1,-1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[0,1,0,1],[k41,k42,k43,k44]=[-1,1,-1,1],[k51,k52,k53,k54]=[-1,0,-1,0],[k61,k62,k63,k64]=[0,-1,0,-1];
若选择[u2,u4]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[0,-1,0,-1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[1,1,1,1],[k41,k42,k43,k44]=[0,1,0,1],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[-1,-1,-1,-1];
若选择[u2,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[1,1,1,1],[k21,k22,k23,k24]=[1,0,1,0],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[-1,-1,-1,-1],[k51,k52,k53,k54]=[-1,0,-1,0],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u3,u4]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[0,-1,0,-1],[k21,k22,k23,k24]=[1,-1,1,-1],[k31,k32,k33,k34]=[1,0,1,0],[k41,k42,k43,k44]=[0,1,0,1],[k51,k52,k53,k54]=[-1,1,-1,1],[k61,k62,k63,k64]=[-1,0,-1,0];
若选择[u3,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,-1,-1,-1],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[1,0,1,0],[k41,k42,k43,k44]=[1,1,1,1],[k51,k52,k53,k54]=[0,1,0,1],[k61,k62,k63,k64]=[-1,0,-1,0];
若选择[u4,u5]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,0,-1,0],[k21,k22,k23,k24]=[0,-1,0,-1],[k31,k32,k33,k34]=[1,-1,1,-1],[k41,k42,k43,k44]=[1,0,1,0],[k51,k52,k53,k54]=[0,1,0,1],[k61,k62,k63,k64]=[-1,1,-1,1];
若选择[u4,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,0,-1,0],[k21,k22,k23,k24]=[-1,-1,-1,-1],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[1,0,1,0],[k51,k52,k53,k54]=[1,1,1,1],[k61,k62,k63,k64]=[0,1,0,1];
若选择[u5,u6]T作为基底矢量,则[k01,k02,k03,k04]=[k71,k72,k73,k74]=[0,0,0,0],[k11,k12,k13,k14]=[-1,1,-1,1],[k21,k22,k23,k24]=[-1,0,-1,0],[k31,k32,k33,k34]=[0,-1,0,-1],[k41,k42,k43,k44]=[1,-1,1,-1],[k51,k52,k53,k54]=[1,0,1,0],[k61,k62,k63,k64]=[0,1,0,1]。
5.根据权利要求1所述的计及预测模型分解的永磁同步直线电机模型预测电流控制方法,其特征在于,步骤5所述的最优矢量挑选方法具体为:
构建基于电流误差的价值函数,如下
Figure FDA0002847752500000041
根据步骤4得到的电流预测值is k+1(ui),对8个基本电压矢量进行评估,选取令价值函数最小的矢量为最优矢量uopt,即
Figure FDA0002847752500000042
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