Comparative Evaluation of a Permanent Magnet Machine Saliency-Based Drive with Sine-Wave and Square-Wave Voltage Injection

Chen, Jyun-You; Yang, Shih-Chin; Tu, Kai-Hsiang

doi:10.3390/en11092189

Cited by 6 publications

(4 citation statements)

References 34 publications

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“…As expected, the superimposed stator current vector consists of two separate vector components, where i iγδp is the positively rotating vector with angular speed ω i and i iγδn is the negatively rotating vector with angular speed [-ω i + d(2∆θ)/dt]. It is worth noting that the average inductance is included into Equation (27), while the differential inductance ∆L and the double error of rotor position 2∆θ are included in Equation (28). Applying signal processing and filtering, the information regarding rotor position, stator inductance and magnetic saliency could be retrieved.…”

Section: Analysis Of High Frequency Stator Current In γδ Reference Framementioning

confidence: 75%

“…Saliency depended terms, such as (L d − L q )i d , are embedded into the modified rotor flux in γδ allowing minimization the PMSM model approximations. Despite of the extended EMF or saliency back-EMF model, the modified γδ model is advantageous, since speed has no effect on the modified rotor flux instead [1,12,21,28,29]. As is proven, the γδ inductance matrix L γδ is transformed from the original L dq based on the angle difference between dq and γδ.…”

Section: Modified Pmsm Voltage and Flux/current Model In γδmentioning

confidence: 99%

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Sensorless Control of Permanent Magnet Synchronous Machine with Magnetic Saliency Tracking Based on Voltage Signal Injection

Ilioudis

2020

Machines

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This paper presents a sensorless control method of a permanent magnet synchronous machine (PMSM) with magnetic saliency estimation. This is based on a high-frequency injection (HFI) technique applied on the modified PMSM model in the γδ reference frame. Except for sensorless control, an emphasis is placed on the magnetic saliency estimation to indicate a practical approach in tracking PMSM inductance variations. The magnetic saliency is determined using calculations embedded in the speed and position algorithm through current measurements. A notable characteristic of the modified PMSM model is that the corresponding rotor flux integrates both permanent magnet and saliency term fluxes. In applying a HFI technique for sensorless control, the structure of the PMSM flux model is formatted accordingly. A novel inductance matrix is derived that is completely compatible with the HFI methodology, since its elements include terms of angle error differential and average inductances. In addition, a sliding mode observer (SMO) is designed to estimate the speed and angle of rotor flux based on equivalent control applying a smooth function of the angle error instead of a sign one to reduce the chattering phenomenon. The control strategy is principally based on the adequacy of the proposed modified model and on the appropriateness of the SMO structure to successfully track the rotor flux position with the required stability and accuracy. Simulation results demonstrate the performance of the PMSM sensorless control verifying the effectiveness of the proposed algorithm to detect PMSM saliency, speed and position in steady state and transient modes successfully. Keywords: sensorless control of PMSM; sliding mode observer (SMO); magnetic saliency estimation; modified rotor flux; high frequency injection (HFI) Notation u d , u q = dq axis stator voltages i d , i q = dq axis stator currents λ d , λ q = dq axis stator magnetic fluxes λ m = rotor magnetic flux L d , L q = dq axis inductances ΣL =(L d +L q )/2 = average inductance ∆L = (L d -L q )/2 = differential inductance r s = stator resistance u γ , u δ = γδ axis stator voltages i γ , i δ = γδ axis stator currents λ γ , λ δ = γδ axis stator magnetic fluxes p = number of pole pairs θ = θ e = electrical angular position ω = ω e = electrical angular speed Machines 2020, 8, 14 3 of 20However, the observers in the αβ stationary reference frame suffer from phase delay between the real and the estimated EMF, since the real extended EMF is a sinusoidal signal [18,20]. This undesired phase delay is due to the observer operation, which is similar to signal filtering. Despite the αβ stationary frame, PMSM variables, such as flux and extended EMF, are constant quantities in the dq (direct-quadrature) synchronous rotating reference frame that, however, cannot be applied directly. An advantageous alternative proposal is to express PMSM mathematical model in the γδ reference frame, which is rotating at estimated angular velocityω and lagging behind the dq synchronous reference frame by electrical...

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Section: Analysis Of High Frequency Stator Current In γδ Reference Framementioning

confidence: 75%

Section: Modified Pmsm Voltage and Flux/current Model In γδmentioning

confidence: 99%

Sensorless Control of Permanent Magnet Synchronous Machine with Magnetic Saliency Tracking Based on Voltage Signal Injection

Ilioudis

2020

Machines

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“…To extend the sensorless operation range, the saliency-based method is used in the low-speed range. It is well known that the injection of high frequency signal increases the signal-to-noise ratio, thereby improving low speed performances significantly [9][10][11][12]. In particular, it enables full torque operation at standstill.…”

Section: Introductionmentioning

confidence: 99%

Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range

Choi

2021

Energies

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A new linear regression form is derived for a flux observer and a position observer is designed. In general, the observability of the permanent-magnet synchronous motor is lost at zero speed. In this work, the proposed regressor vector contains current derivative terms in both directions (dq-axis), and it gives the chance for the model-based flux observer to operate at zero speed. When an excitation signal is injected into d and q axes with the proposed flux observer, it helps to satisfy the persistent excitation condition in the low-speed range. Therefore, the sensorless performance of the model-based is improved greatly, even at zero speed. However, it appears with a disturbance term, which depends on the derivative of the d-axis current. Thus, the disturbance does not vanish when an excitation signal is injected. In this work, the disturbance term is also taken care of in constructing an observer. It results in an observer which allows signal injection. Thus, high frequency signal can be injected in the low speed region and turned off when it is unnecessary as the speed increases. This model-based approach utilizes the signal injection directly without recurring to a separate high frequency model. In other words, it provides a seamless transition without switching to the other algorithm. The validity is demonstrated by simulation and experimental results under various load conditions near zero speed.

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“…In general, sensorless methods are divided into two categories which are based on signal injection and machine model according to speed region. At low speeds, the signal injection is generally adopted to realize rotor estimation [9][10][11]. However, it can cause the extra loss and torque ripple.…”

mentioning

confidence: 99%

A Super-Twisting Sliding-Mode Stator Flux Observer for Sensorless Direct Torque and Flux Control of IPMSM

Chen

et al. 2019

Energies

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The scheme based on direct torque and flux control (DTFC) as well as active flux is a good choice for the interior permanent magnet synchronous motor (IPMSM) sensorless control. The precision of the stator flux observation is essential for this scheme. However, the performance of traditional observers like pure integrator and the low-pass filter (LPF) is severely deteriorated by disturbances, especially dc offset. Recently, a sliding-mode stator flux observer (SMFO) was proposed to reduce the dc offset in the estimated stator flux. However, it cannot eliminate the dc offset totally and will cause the chattering problem. To solve these problems, a novel super-twisting sliding-mode stator flux observer (STSMFO) is proposed in this paper. Compared with SMFO, STSMFO can reduce the chattering and fully eliminate the dc offset without any amplitude and phase compensation. Then, the precision of the stator flux and rotor position can be greatly improved over a wide speed region. The detailed mathematical analysis has been given for comparing it with another three traditional observers. The numerical simulations and experimental testing with an IPMSM drive platform have been implemented to verify the capability of the proposed sensorless scheme.

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Comparative Evaluation of a Permanent Magnet Machine Saliency-Based Drive with Sine-Wave and Square-Wave Voltage Injection

Cited by 6 publications

References 34 publications

Sensorless Control of Permanent Magnet Synchronous Machine with Magnetic Saliency Tracking Based on Voltage Signal Injection

Sensorless Control of Permanent Magnet Synchronous Machine with Magnetic Saliency Tracking Based on Voltage Signal Injection

Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range

A Super-Twisting Sliding-Mode Stator Flux Observer for Sensorless Direct Torque and Flux Control of IPMSM

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