CN104836501A - Method for permanent-magnet synchronous motor parameter on-line identification - Google Patents

Method for permanent-magnet synchronous motor parameter on-line identification Download PDF

Info

Publication number
CN104836501A
CN104836501A CN201510167080.4A CN201510167080A CN104836501A CN 104836501 A CN104836501 A CN 104836501A CN 201510167080 A CN201510167080 A CN 201510167080A CN 104836501 A CN104836501 A CN 104836501A
Authority
CN
China
Prior art keywords
formula
steady
state
value
parameter
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510167080.4A
Other languages
Chinese (zh)
Other versions
CN104836501B (en
Inventor
徐政
黄河清
陈锐坚
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Graduate School Tsinghua University
Original Assignee
Shenzhen Graduate School Tsinghua University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Graduate School Tsinghua University filed Critical Shenzhen Graduate School Tsinghua University
Priority to CN201510167080.4A priority Critical patent/CN104836501B/en
Publication of CN104836501A publication Critical patent/CN104836501A/en
Application granted granted Critical
Publication of CN104836501B publication Critical patent/CN104836501B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Abstract

The invention relates to a method for permanent-magnet synchronous motor (PMSM) parameter on-line identification. The method is based on a speed sensorless vector control system of a virtual dc-qc coordinate system. The method comprises: 1) for a non-salient PMSM, establishing a qc-axis steady-state equation considering motor parameter error influence, the equation being u<qc> is approximately equal to R<s>i<qc>+ [omega]L<d>i<dc>+[omega][phi], wherein R<s> is the resistor of a stator winding, L<d> is an direct axis inductor, the [phi] is a magnetic linkage, [omega] is rotor angular velocity, u<qc> is qc-axis voltage, i<qc> is qc-axis current, i<dc> is dc-axis current; 2) and properly adjusting motor operating states repeatedly, and recording the steady-state value of each variable in the steady-state value, substituting into the equation to obtain a plurality of groups of steady-state relations, and obtaining the identification values of motor parameters through calculation of state variable increment. The method just duly adds short-time small disturbance of i<dc> and [omega] instructions in an original control strategy, having not influence on original control flow and system normal operation. The method is simple and fast in algorithm, and can realize non-salient or salient-pole PMSM parameter on-line identification in low cost.

Description

A kind of method of permanent magnet synchronous motor on-line parameter identification
Technical field
The invention belongs to electric drive and electric and electronic technical field, be specifically related to a kind of method being applied to permanent magnet synchronous motor on-line parameter identification.
Background technology
The advantages such as permanent magnet synchronous motor (PMSM:Permanent Magnet Synchronous Motor) has that specific power is high, efficient energy-saving, control are accurate, obtain in every field and apply more and more widely []].The high performance control method of PMSM mainly contains vector control and direct torque control etc.Wherein, the senseless control system that system cost is low, environmental suitability is strong becomes study hotspot.
The performance of PMSM senseless control system largely depends on the estimation accuracy of rotor-position and rotating speed, and detection method can be divided into two classes.The first kind is by injecting signal specific, estimating Position And Velocity, have insensitive to the parameter of electric machine, be suitable for the advantages such as velocity interval is wide, but desirable hypothesis has been done to motor characteristic, as high-frequency signal injection [2]need the saliency utilizing motor, INFORM method [3]suppose that back-emf is completely sinusoidal, and calculation of complex, higher to the requirement of control chip.Equations of The Second Kind is the evaluation method based on first-harmonic excitation and back-emf, as virtual coordinate system method [4], sliding mode observer method [5].These class methods calculate simple, easily realize, but stronger to the dependence of the parameter of electric machine.
PMSM parameter has stator winding resistance R s, d-axis inductance L d, quadrature axis inductance L qand magnetic linkage the different installation forms of permanent magnet, determine the difference of d-axis inductance and quadrature axis inductance.Permanent magnet submerged installation be salient-pole machine, L d≠ L q, and surface-pasted be non-salient pole machine, L d=L q.Experimental result shows, motor temperature can cause the parameter of electric machine to change, but limited extent; When frequency control runs, R smainly there is change by a relatively large margin by the impact of skin effect; L dcomparatively stable, L qobvious change is there is along with load; mainly stablize the impact with demagnetization characteristic by magnet steel.For ensureing the effect of Equations of The Second Kind method, need the on-line identification parameter of electric machine.Traditional parameter identification method, as model reference adaptive method [6], extended Kalman filter method [7], least square method [8]deng, all suppose that rotor-position and tach signal are error free, there is no the impact that consideration brings identification result in the error of Speedless sensor situation upper/lower positions and tach signal.
Different control method to the demand of parameter of electric machine information and susceptibility different, be also the basis of on-line identification, based on the speed-less sensor vector control system of virtual dc-qc coordinate system structure as shown in Figure 1.State observation module exports according to voltage and current feedback estimates rotor speed and position, needs to use motor model and parameter; Phase-locked control module regulates the rotating speed of dc-qc coordinate system according to the position angular difference of dc-qc coordinate system and d-q coordinate system (rotor synchronous frame); Rotational speed control module according to the bias adjustment voltage vector of rotating speed, and adds to motor stator winding by space voltage vector modulation (SVPWM); Because simple possible, easily low cost realize, obtain applying comparatively widely.In Fig. 1, dotted portion is parameter identification module of the present invention, based on motor model and state variable feedback, and the on-line identification parameter of electric machine.
With the physical location of rotor magnetic pole for benchmark, set up synchronous d-q coordinate system, then the model of PMSM is as follows:
In formula, p is differential operator, u dand u qbe respectively d-axis and quadrature-axis voltage, ω is rotor velocity (=p θ), and θ is rotor position angle.
As shown in Figure 2, vector control is with rotor position angle estimated value θ cfor launching in the dc-qc coordinate system of benchmark, it differs Δ θ=θ with d-q co-ordinate system location angle c-θ, alpha-beta is rest frame.The transformational relation of state variable is
u dc or i dc u qc or i qc = cos &Delta;&theta; sin &Delta;&theta; - sin &Delta;&theta; cos &Delta;&theta; u d or i d u q or i q - - - ( 2 )
Then motor model becomes:
u dc=R si dc+pL di dccL qi qc-(L d-L q)i qcpΔθ+E 0xsinΔθ (3)
u qc=R si qc+pL di qccL qi dc+(L d-L q)i dcpΔθ+E 0xcosΔθ (4)
In formula, ω cfor the dc-qc coordinate system angular speed that phase-locked control obtains, θ c=∫ ω cdt.
During stable state, can ignore differential term, voltage equation and position angle deviation are respectively
u dc=R si dccL qi qc+E 0xsinΔθ (6)
u qc=R si qccL qi dc+E 0xcosΔθ (7)
tan &Delta;&theta; = u dc - R s i dc + &omega; c L q i qc u qc - R s i qc - &omega; c L q i dc - - - ( 8 )
The phase-locked link of Systematical control is by regulating ω c, make Δ θ asymptotic convergence in 0.If the parameter of electric machine used in formula (8) is accurate, during stable state, dc-qc coordinate system will overlap with d-q coordinate system, and namely rotating speed is all consistent with true value with the estimation result of position; But if the parameter of electric machine has error, then two coordinate systems will have deviation all the time.
If the steady state deviation angle of two coordinate systems is Δ θ ', definition parameter of electric machine error is as follows:
ΔR s=R′ s-R s,ΔL d=L′ d-L d,ΔL q=L′ q-L q
Wherein, R s, L dand L qfor parameter of electric machine true value, R ' s, L ' dwith L ' qfor the set point of the parameter of electric machine in control program.Due to R s, i dcand Δ θ ' is all less, formula (8) is done with lower aprons,
Then the impact of parameter of electric machine error on rotor position estimation is as follows:
It can thus be appreciated that, although increase along with frequency, Δ R sobviously increase because of skin effect, but Δ R s/ ω reduces on the contrary, and i dcusually very little, therefore Δ R slimited to estimation Influence on test result; Δ L qon impact and the load current i of estimation result qcrelevant, affect little during underloading, during heavy duty, impact is large; Δ L destimation result is not affected substantially.
The error of the parameter of electric machine not only affects the dynamic characteristic of control system, also can cause the deviation of vector control during stable state, and motor operational efficiency reduces.Therefore, on-line parameter identification is significant for the performance of guarantee and raising senseless control system.
Pertinent literature:
[1] Wang Xiuhe. magneto [M]. the second edition. Beijing: China Electric Power Publishing House, 2010;
[2]Guo Qingding,Luo Ruifu,Wang Limei.Neural Network Adaptive Observer Based Positionand Velocity Sensorless Control of PMSM.AMC'96,1996:41-46;
[3]Schroedl M.Sensorless Control of AC Machines at Low Speed and Standstill Based onthe"INFORM″Method.IEEE Conference on Industrial Application,1996:270-277;
[4]Kiyoshi Sakamoto,Yoshitaka Iwaji,Tsunehiro Endo.Position and Speed SensorlessControl for PMSM Drive Using Direct Position Error Estimation.IECON’01:The 27 thAnnual Conference of the IEEE Industrial Electronics Society,2001:1680-1685;
[5]Song Chi,Longya Xu.Position Sensorless Control of PMSM Based on Novel SlidingMode Observer over Wide Speed Range.IEEE IPEMC 2006(3):1-7;
[6] Chen Zhenfeng, Zhong Yanru, Li Jie. the identification of embedded permagnetic synchronous motor self adaptation on-line parameter. Electric Machines and Control, 2010,14 (4): 9-13;
[7]X.Jiang,Z.Zhang,P.Sun and Z.Zhu.Estimation of Temperature Rise in Stator Windingand Rotor Magnet of PMSM Based on EKF.IEEE ICCEE 2010vol.8:24-27;
[8] Li Ping. the modeling of permagnetic synchronous motor and parameter identification. Computer Simulation, 2011,28 (8): 401-404.
Summary of the invention
The invention provides the method for a kind of permanent magnet synchronous motor (PMSM) on-line parameter identification, the method is realized by the speed-less sensor vector control system of virtual dc-qc coordinate system, effectively can improve the performance of this control system.
The inventive method is the on-line identification technology based on the systematic steady state characterisitic parameter under microvariations input and multiple running status.
Owing to using R ' in above-mentioned formula (8) swith L ' q, under phase-locked control action, Δ θ → 0, the steady state voltage equation (3) of dc axle is forced to be locked as
u dc=R′ si dc-ωL′ qi qc(10)
So cannot parameter identification be used for, belongs to typical and owe order problem.
And the steady-state equation of qc axle (4) is by the impact of motor parameter error, become
For non-salient pole PMSM, L d=L q, above formula (11) becomes formula (12)
Obviously, only under single running status, the on-line identification to multiple parameter of electric machine cannot be realized.
The inventive method takes following steps:
1), with reference to mentioned above, for non-salient pole PMSM (L d=L q), set up the qc axle steady-state equation (12) after considering parameter of electric machine error effect:
Wherein, R sfor stator winding resistance, L dfor d-axis inductance, for magnetic linkage, ω is rotor velocity, u qcfor qc shaft voltage, i qcfor qc shaft current, i dcfor dc shaft current;
2), repeatedly motor operating state suitably to be regulated, and the steady-state value of each variable under recording lower state, substitute into qc axle steady-state equation (12) and obtain and organize steady state relation more, and calculate R by state variable increment s, L d, identifier
Specific implementation process is as shown in on-line identification flow chart 4:
21), keep rotating speed constant, setting i dc *=0, enforcement controls and records the steady-state value ω of each variable 0, u qc0and i qc0, substitute into formula (12) and obtain formula (13):
22), slightly i is changed dc *, setting i dc *=Δ i dc≠ 0, implement to control and record corresponding steady-state value u qc1and i dc1, substitute into formula (12) and obtain formula (14):
Due to rotating speed and load constant, then i qc1≈ i qc0, formula (14) and formula (13) are subtracted each other, and arrangement can obtain L didentifier
L ^ d = u qc 1 - u qc 0 &omega; 0 i dc 1 - - - ( 15 )
23), slightly ω is regulated *, setting ω *0+ Δ ω, and keep i dc *=0, implement to control and record corresponding steady-state value ω 1, u qc2and i qc2, substitute into formula (12) and formula (16) can be obtained:
In view of slightly regulating ω in short-term *time, load torque is constant, i qc2≈ i qc0, formula (13) × ω 1with formula (16) × ω 0subtract each other, the identifier of Rs can be obtained
R ^ s = &omega; 1 u qc 0 - &omega; 0 u qc 2 ( &omega; 1 - &omega; 0 ) i qc 0 - - - ( 17 )
Formula (16) and formula (13) are subtracted each other, and can obtain identifier
Thus the on-line identification achieved 3 parameters of electric machine.
For salient pole PMSM (L d≠ L q), cannot directly identification quadrature axis inductance L in said method principle q.But can utilize and be provided by electric machine manufacturer or quadrature axis inductance L that off-line identification obtains qwith d-axis inductance L d, precalculate its ratio K=L q/ L d, then by following formula approximate estimation quadrature axis inductance L qidentifier
L ^ q = K &CenterDot; L ^ d - - - ( 19 )
Wherein, for step 22) the d-axis inductance L that obtains didentifier.
Above-mentioned steps 22) in, described Δ i dcvalue be the 3-6% of Rated motor electric current, preferably 5%.
Above-mentioned steps 23) in, the value of described Δ ω is run the 1-3% of angular speed, preferably 2%.
Steady-state value based on low-pass filtering calculates and feedback, ensures stability and the accuracy of on-line identification.The impact of the controlled characteristic of real system, load characteristic and the effect of PWM voltage, can not be in completely desirable stable state, voltage and electric current all have certain pulsation.The change of each state variable steady-state value caused by above-mentioned microvariations input is very little, often lower than its ripple amplitude.Therefore, according to the instantaneous values feedback of voltage and electric current under different running status in on-line identification, the change of steady-state value may be pulsed flood, identification result accurately cannot be obtained.Matlab software platform establishes detailed motor and controller model to the PMSM of a 1.1kW/380V/3000rpm, switching frequency 8kHz, voltage vector control cycle 250 μ s, rotating speed control cycle 5ms.Under action of small disturbance, the simulation waveform of voltage and electric current as shown in Figure 3, and wherein (a) is original waveform, and (b) is the waveform obtained after carrying out root wood filtering process to continuous 1000 sampled datas.As can be seen here, the ripple amplitude of voltage is about 10V, and the ripple amplitude of electric current is greater than 1A.After low-pass filtering treatment, just can obtain the effective information of steady-state value change under action of small disturbance.Work as i dc *when becoming 0.4A from 0, u qcadd about 1.5V; Work as N r *when becoming 1530rpm from 1500, u qcadd about 2.9V.
Therefore, the step 21 in embodiment), 22), 23) all low-pass filtering treatment has been carried out to voltage and current signal in control procedure, thus improve stability and the accuracy of on-line identification further.
Permanent magnet synchronous motor on-line identification method of the present invention only in time adds i in original control strategy dcand the microvariations in short-term of ω instruction, normally run not impact to original control flow and system, and do not increase any state variable, algorithm is simple and direct, can realize the on-line identification of non-salient pole or the inapparent PMSM parameter of electric machine of saliency at low cost.
Accompanying drawing explanation
Fig. 1 is the structure chart of the speed-less sensor vector control system based on virtual dc-qc coordinate system;
Fig. 2 is synchronous coordinate system graph of a relation, and wherein, alpha-beta is rest frame, and d-q is rotor synchronous frame, and dc-qc is hypothetical rotor synchronous coordinate system;
Fig. 3 is the simulation waveform of voltage and electric current under action of small disturbance, (a) original waveform, the waveform after (b) low-pass filtering;
Fig. 4 on-line identification flow chart of the present invention;
Fig. 5 is the actual measurement Parameters variation characteristic of PMSM, (a) temperature characterisitic, (b) frequency characteristic.
Embodiment
The inventive method is applicable to non-salient pole or the inapparent PMSM control system of saliency, can easily realize by wherein adding corresponding software program in variable frequency control.
Embodiment: the System's composition of embodiment is identical with Fig. 1, as previously mentioned, it adopts frequency-variable controller and the eddy-current brake load of applicant's independent development to system configuration.Tested motor nonideal non-salient pole PMSM, tested rating of electric machine parameter is as shown in table 1:
The tested parameter of electric machine of table 1
(DC va method measures R to use LCR electric bridge and off-line parameter identification method s, direct current attenuation method measures L dand L q, idle end voltage method measures ) detect the parameter of electric machine, confirm its variation characteristic.
Fig. 5 (a) is observed temperature characteristic.Along with the rising of motor temperature T, R s, L dand L qincrease, and slightly reduce.When temperature rises to 100 DEG C from 25 DEG C, R s, L dand L qincrease 7.5%, 7.5% and 15% respectively, reduce 8.1%.
Fig. 5 (b) is practical frequency characteristic (using LCR electric bridge).Along with the rising of Injection Current frequency f, because winding conducting wire is comparatively thick, skin effect is obvious, R senlarge markedly.When injecting 100Hz electric current, R s129%, L is increased when injecting than direct current dand L qreduce 7.7% and 7.3% respectively.
First carry out emulation to the inventive method to confirm.R s, L dwith true value be set to 2 Ω, 12mH and 0.46Wb respectively, and the initial set value in control program is respectively 0.5 Ω, 13.3mH and 0Wb.The simulation waveform of parameter identification process as shown in Figure 3, wherein, i dc *: 0 → 0.4A; N r *: 1500 → 1530rpm; A () illustrates original waveform, (b) illustrates the waveform after low-pass filtering treatment.R s, L dwith identification result be respectively 1.98 Ω, 12.1mH and 0.459Wb, error is respectively 0.8% ,-4% and-0.2%.
The control chip of frequency-variable controller adopts the SH71253 of Renesas, switching frequency 8kHz, voltage vector control cycle 250 μ s, rotating speed control cycle 5ms.On-line parameter identification subprogram shown in Fig. 4 is added, R in original control program sand L qinitial set value be respectively 1.7 Ω and 16.7mH, all have larger deviation with true value.Set different running status, carry out repeatedly identification.In identification process, current i dcdisturbance input be 0.125A, rotating speed N rdisturbance input be 24rpm.Table 2 is part of test results.
Table 2 on-line identification experimental result
From table 2 experimental result, along with rotating speed rising, load down, R sincrease gradually, L dslightly reduce, and identification result have faint reduction trend because of saliency approximate error, with offline inspection result coincide.

Claims (8)

1. a method for permanent magnet synchronous motor (PMSM) on-line parameter identification, based on the speed-less sensor vector control system of virtual dc-qc coordinate system, comprises the following steps:
1) for non-salient pole PMSM (L d=L q), set up the qc axle steady-state equation (12) after considering parameter of electric machine error effect:
Wherein, R sfor stator winding resistance, L dfor d-axis inductance, for magnetic linkage, ω are rotor velocity, u qcfor qc shaft voltage, i qcfor qc shaft current, i dcfor dc shaft current;
2) repeatedly motor operating state suitably to be regulated, and the steady-state value of each variable under recording lower state, substitute into qc axle steady-state equation (12) and obtain and organize steady state relation more, and calculate R by state variable increment s, L d, identifier
2. the method for claim 1, is characterized in that comprising further: step 3) estimation quadrature axis inductance L q, for salient pole PMSM (L d≠ L q), quadrature axis inductance L qidentifier pass through estimation, wherein, for step 2) L that obtains didentifier, K=L q/ L d, L q, L dfor electric machine manufacturer provide or off-line identification obtain quadrature axis inductance and d-axis inductance.
3. method as claimed in claim 1 or 2, is characterized in that: step 2) specific implementation process as follows:
21) keep rotating speed constant, setting i dc *=0, enforcement controls and records the steady-state value ω of each variable 0, u qc0and i qc0, substitute into formula (12) and obtain formula (13):
22) slightly i is changed dc *, setting i dc *=Δ i dc≠ 0, implement to control and record corresponding steady-state value u qc1and i dc1, substitute into formula (12) and obtain formula (14):
Due to rotating speed and load constant, then i qc1≈ i qc0, formula (14) and formula (13) are subtracted each other, and arrangement can obtain L didentifier
23) slightly ω is regulated *, setting ω *0+ Δ ω, and keep i dc *=0, implement to control and record corresponding steady-state value ω 1, u qc2and i qc2, substitute into formula (12) and obtain formula (16):
In view of slightly regulating ω in short-term *time, load torque is constant, i qc2≈ i qc0, formula (13) × ω 1with formula (16) × ω 0subtract each other, the identifier of Rs can be obtained
Formula (16) and formula (13) are subtracted each other, and can obtain identifier
4. method as claimed in claim 3, is characterized in that: in step 21), 22), 23) all low-pass filtering treatment is carried out to voltage and current signal in control procedure.
5. method as claimed in claim 3, is characterized in that: step 22) in, described Δ i dcvalue be the 3-6% of Rated motor electric current.
6. method as claimed in claim 3, is characterized in that: step 23) in, the value of described Δ ω is run the 1-3% of angular speed.
7. method as claimed in claim 3, is characterized in that: step 22) described in Δ i dcvalue be the 3-6% of Rated motor electric current; Step 23) described in the value of Δ ω be run the 1-3% of angular speed.
8. method as claimed in claim 7, is characterized in that: step 22) described in Δ i dcvalue be 5% of Rated motor electric current; Step 23) described in the value of Δ ω be run angular speed 2%.
CN201510167080.4A 2015-04-09 2015-04-09 A kind of method of permasyn morot on-line parameter identification Expired - Fee Related CN104836501B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510167080.4A CN104836501B (en) 2015-04-09 2015-04-09 A kind of method of permasyn morot on-line parameter identification

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510167080.4A CN104836501B (en) 2015-04-09 2015-04-09 A kind of method of permasyn morot on-line parameter identification

Publications (2)

Publication Number Publication Date
CN104836501A true CN104836501A (en) 2015-08-12
CN104836501B CN104836501B (en) 2017-07-28

Family

ID=53814179

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510167080.4A Expired - Fee Related CN104836501B (en) 2015-04-09 2015-04-09 A kind of method of permasyn morot on-line parameter identification

Country Status (1)

Country Link
CN (1) CN104836501B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105227023A (en) * 2015-10-28 2016-01-06 广东美的制冷设备有限公司 A kind of permagnetic synchronous motor ac-dc axis inductance on-line identification method and system
CN105974311A (en) * 2016-05-25 2016-09-28 广东美的制冷设备有限公司 Zero-speed fault detection method and apparatus for permanent-magnet synchronous motor
CN110112975A (en) * 2019-05-14 2019-08-09 安徽首智新能源科技有限公司 A kind of parameter of electric machine on-line identification method and system

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030062870A1 (en) * 2001-09-28 2003-04-03 Semyon Royak Stator and rotor resistance identifier using high frequency injection
CN102386835A (en) * 2010-08-27 2012-03-21 永济新时速电机电器有限责任公司 Method for acquiring parameters of permanent magnet synchronous motor (PMSM)
KR101196028B1 (en) * 2011-07-20 2012-10-30 엘에스산전 주식회사 A method of estimating stator resistance of a motor
CN103248306A (en) * 2013-05-24 2013-08-14 天津大学 Online decoupling identification method of multiple parameters of PMSM (permanent magnet synchronous motor)
CN103825524A (en) * 2014-03-14 2014-05-28 中冶南方(武汉)自动化有限公司 Offline identification method for basic electric appliance parameters of permanent-magnet synchronous motor

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030062870A1 (en) * 2001-09-28 2003-04-03 Semyon Royak Stator and rotor resistance identifier using high frequency injection
CN102386835A (en) * 2010-08-27 2012-03-21 永济新时速电机电器有限责任公司 Method for acquiring parameters of permanent magnet synchronous motor (PMSM)
KR101196028B1 (en) * 2011-07-20 2012-10-30 엘에스산전 주식회사 A method of estimating stator resistance of a motor
CN103248306A (en) * 2013-05-24 2013-08-14 天津大学 Online decoupling identification method of multiple parameters of PMSM (permanent magnet synchronous motor)
CN103825524A (en) * 2014-03-14 2014-05-28 中冶南方(武汉)自动化有限公司 Offline identification method for basic electric appliance parameters of permanent-magnet synchronous motor

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
RAJA RAMAKRISHNAN ET AL.: "Real Time Estimation of Parameters for Controlling and Monitoring Permanent Magnet Synchronous Motors", 《2009 IEEE INTERNATIONAL ELECTRIC MACHINES AND DRIVES CONFERENCE》 *
杨光 等: "感应电机参数静止辨识的误差特性分析", 《电气传动》 *
杨宗军 等: "表贴式永磁同步电机的多参数在线辨识", 《电工技术学报》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105227023A (en) * 2015-10-28 2016-01-06 广东美的制冷设备有限公司 A kind of permagnetic synchronous motor ac-dc axis inductance on-line identification method and system
CN105227023B (en) * 2015-10-28 2018-04-17 广东美的制冷设备有限公司 A kind of permanent magnet synchronous motor ac-dc axis inductance on-line identification method and system
CN105974311A (en) * 2016-05-25 2016-09-28 广东美的制冷设备有限公司 Zero-speed fault detection method and apparatus for permanent-magnet synchronous motor
CN110112975A (en) * 2019-05-14 2019-08-09 安徽首智新能源科技有限公司 A kind of parameter of electric machine on-line identification method and system
CN110112975B (en) * 2019-05-14 2022-04-29 安徽首智新能源科技有限公司 Motor parameter online identification method and system

Also Published As

Publication number Publication date
CN104836501B (en) 2017-07-28

Similar Documents

Publication Publication Date Title
Odhano et al. Self-commissioning of interior permanent-magnet synchronous motor drives with high-frequency current injection
CN103036499B (en) Detection method of permanent magnet motor rotor position
CN102931906B (en) Method for asynchronous motor rotor flux linkage observation and rotation speed identification
Kim et al. Sensorless control of AC motor—Where are we now?
KR101087581B1 (en) Sensorless control method of permanent magnet synchronous motor
Zhu et al. A simplified high frequency injection method for PMSM sensorless control
CN109672383B (en) Salient pole type permanent magnet synchronous motor online parameter identification method
CN110350835A (en) A kind of permanent magnet synchronous motor method for controlling position-less sensor
Yan et al. Sensorless control of PMSMs based on parameter-optimized MRAS speed observer
CN104836501A (en) Method for permanent-magnet synchronous motor parameter on-line identification
Wang et al. Simple and effective online position error compensation method for sensorless SPMSM drives
Li et al. Sensorless control of surface-mounted permanent magnet synchronous motor drives using nonlinear optimization
Li et al. A novel on-line MRAS rotor resistance identification method insensitive to stator resistance for vector control systems of induction machines
Fan et al. Induction motor parameter identification based on T-model equivalent circuit
JP2017073879A (en) Controller for synchronous motor
Zhang et al. An improved off-line identification technology for parameters of surface permanent magnet synchronous motors
KR101623672B1 (en) Device for controlling alternating current rotating machine
CN110649851B (en) Multi-parameter decoupling online identification method for asynchronous motor
CN105958875A (en) High precision speed regulation control method of speed sensorless permanent magnet synchronous motor
KR101449872B1 (en) A modified current control scheme of Permanent Magnet Synchronous Motor
Rao et al. Parameter sensitivity of rotor time constant estimation based on MRAS for induction motors
CN108155841B (en) Sensorless speed estimation method for induction motor
Siu et al. A high-frequency signal injection based sensorless drive method for brushless DC motor
Chougala et al. Self-commissioning of induction motor drives-A critical review
Purti et al. Performance assessment of rotor flux and reactive power based MRAS for speed sensorless induction motor drive in a common test rig

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
EXSB Decision made by sipo to initiate substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20170728

Termination date: 20210409