Online Multiparameter Identification of Surface-Mounted PMSM Considering Inverter Disturbance Voltage

Deng, Weitao; Xia, Changliang; Yan, Yan; Geng, Qingbo; Shi, Tingna

doi:10.1109/tec.2016.2621130

Cited by 71 publications

(27 citation statements)

References 21 publications

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“…Equation 23, it can be seen that the speed estimation ˆr ω can be adjusted to control the ˆd I and ˆq I which are the outputs of the start-up estimation algorithm. The error between the estimated current ˆd I , ˆq I and the measured current d I , q I is used to correct the speed estimation ˆr ω according to Equation (32). Finally, the outputs of the start-up estimation algorithm ˆd I , ˆq I can follow the The middle of Figure 12a represents the error between theî q estimated by start-up estimation algorithm and the real measured current i q according to the design scheme shown in Figure 6.…”

Section: Description and Analysis Of The Experimental Resultsmentioning

confidence: 99%

“…From Equation 23, it can be seen that the speed estimationω r can be adjusted to control theÎ d andÎ q which are the outputs of the start-up estimation algorithm. The error between the estimated currentÎ d ,Î q and the measured current I d , I q is used to correct the speed estimationω r according to Equation (32). Finally, the outputs of the start-up estimation algorithmÎ d ,Î q can follow the measured I d , I q .…”

Section: Description and Analysis Of The Experimental Resultsmentioning

confidence: 99%

“…In [29,30], although the torque and flux linkage of PMSM can be controlled under variable parameters, the control method of these references is applied to low-power PMSMs. In addition, the online parameter identification [31][32][33][34] can also solve this problem. The details on parameter identification are discussed in [35], where the results of parameter identification are imbedded into an intelligent drive algorithm to correct the PMSM model in real time.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems

Zhou

2018

Energies

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A large number of permanent magnet synchronous motors (PMSMs) are used to drive coal conveyer belts in coal enterprises. Sensorless energy conservation control has important economic value for these enterprises. The key problem of sensorless energy conservation control for PMSMs is how to decompose the stator current through estimating the rotor position and speed accurately. Then a double closed loop control for stator current and speed is formed to make the stator current drive the motor as an entire torque current. In this paper, the proposed startup estimation algorithm can utilize the current model of PMSM as reference model to estimate the rotor speed and position in the startup stages. It is not dependent on the back electromotive force (EMF) which is used by the general estimation algorithm. However, the resistance will change with the temperature shift of stator windings, and these changes will cause the reference current model to be inaccurate and influence the rotor speed and position estimation precision. Thus, startup estimation algorithm switches to the proposed operation estimation algorithm which is based on the robust sliding mode theory and is not dependent on the motor parameters. The advantages of startup estimation algorithm and operation estimation algorithm are combined to form a hybrid observer. This hybrid observer realizes the accurate estimation of the rotor speed and position from start-up to operation. The stator current is precisely decomposed. The excitation current is controlled to 0. Meanwhile, the double closed-loop control of current and speed is achieved. The stator current is as entire torque current to drive motor. The closed-loop control, which is based on the proposed rotor position and speed estimation algorithm, achieve the most efficient conversion of electrical energy.

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Section: Description and Analysis Of The Experimental Resultsmentioning

confidence: 99%

Section: Description and Analysis Of The Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems

Zhou

2018

Energies

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“…References [5][6][7] develop an observer to reduce the number of sensors in the PMSM control system. In order to obtain more accurate parameters in motor control, references [8,9] study PMSM parameter identification technologies. Predictive torque control (PTC) is applied to PMSM control systems in order to give comprehensive consideration to the dynamic and steady performance of the motor system, which is simple in principle and easy to implement online, and has received extensive attention in academia and industry [10,11].…”

Section: Introductionmentioning

confidence: 99%

Dual-Vector Predictive Torque Control of Permanent Magnet Synchronous Motors Based on a Candidate Vector Table

Shi

Yan

2019

Energies

Self Cite

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In order to reduce the torque ripple of permanent magnet synchronous motors (PMSMs), this paper proposes a dual-vector predictive torque control strategy based on a candidate vector table. The main feature of this strategy is that two vectors are acted in a control period to form a vector combination, and the vector combination can be either an effective-zero combination or an effective-effective combination. In the process of establishing the vector combinations, the switching frequency is also taken into account, therefore avoiding a high switching frequency, while effectively reducing the motor torque ripple. The candidate vector table is constructed offline, and three sets of candidate vectors and their duty cycles can be determined by looking up the table. Then the cost function is used to screen the action vectors from the three sets candidate vectors, so the two vectors acted in one control period and their duty cycles can be obtained simultaneously. Finally, the feasibility and effectiveness of the proposed method are verified on a 5.2 kW two-level inverter-fed PMSM drive system.

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“…In order to effectively control IPMSM in EVs, several current sensors are installed for each motor drive to provide the feedback signals for the micro-controller as illustrated in Fig.1 [6], [7]. By good design, the drive achieves excellent performance at the beginning [8]. However, after a long time of use, the accuracy of the multiple current sensors inevitably degrades with different degrees because of ageing, interference and temperature drift [9]- [11].…”

mentioning

confidence: 99%

Mutual Calibration of Multiple Current Sensors With Accuracy Uncertainties in IPMSM Drives for Electric Vehicles

Chen

et al. 2020

IEEE Trans. Ind. Electron.

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This paper proposes a mutual calibration strategy for multiple current sensors in an electric vehicle motor drive. The motor drive usually consists of three current sensors, i.e., a DC-bus current sensor and two phase current sensors. Due to the aging effect and harsh operating environment, the accuracy uncertainty issue is inevitable in these crucial sensors, which results in poor driving performance. In this paper, the detection voltage injection (DV-Injection) method is proposed for mutual calibration of the aforementioned current sensors. Two opposite basic vectors are set together to detect and eliminate the offset error of the DC-bus current sensor. Then, both the directly measured phase-current values by the phase-current sensors and the indirectly measured values by the DC-bus current sensor are sampled. These values are utilized for mutual calibration of the phase-current sensor offset errors and scaling error differences among all the current sensors. Meanwhile, the DV-Injection process is only applied in the period of calibration process, whereas in the remaining intervals the space vector pulse width modulation (SVPWM) technology is utilized. Finally, the effectiveness of the proposed scheme is verified by simulation study in Matlab/Simulink and experimental results on a 5kW IPMSM motor prototype. Index Terms-Accuracy uncertainty, error compensation, interior permanent magnet synchronous motor (IPMSM), mutual calibration. I. INTRODUCTION LECTRIC vehicles (EVs) are typically the large-scale power applications that operate under harsh conditions,

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Online Multiparameter Identification of Surface-Mounted PMSM Considering Inverter Disturbance Voltage

Cited by 71 publications

References 21 publications

Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems

Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems

Dual-Vector Predictive Torque Control of Permanent Magnet Synchronous Motors Based on a Candidate Vector Table

Mutual Calibration of Multiple Current Sensors With Accuracy Uncertainties in IPMSM Drives for Electric Vehicles

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