Inverter Nonlinear Error Compensation Using Feedback Gains and Self-Tuning Estimated Current Error in Adaptive Full-Order Observer

Sun, Wei; Jie, Gao; Liu, Xiaofeng; Yu, Yong; Wang, Gaolin; Xu, Dianguo

doi:10.1109/tia.2015.2480852

Cited by 23 publications

(9 citation statements)

References 37 publications

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“…In general, the PWM inverter contained the deadtime effect, affecting the current regulation, especially at low speed. In this paper, the dead-time compensation was applied based on the direct voltage compensation dependent on the phase current polarity [ 25 ]. In contrast, at high speed, as shown in Figure 10 b, a visible magnitude and phase difference between I LA and I A were observed due to the high magnitude of I CA .…”

Section: Experiments Resultsmentioning

confidence: 99%

Sensorless LC Filter Implementation for Permanent Magnet Machine Drive Using Observer-Based Voltage and Current Estimation

Liang

Lin

Chen

et al. 2021

Sensors

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For pulse width modulation (PWM) inverter drives, an LC filter can cascade to a permanent magnet (PM) machine at inverter output to reduce PWM-reflected current harmonics. Because the LC filter causes resonance, the filter output current and voltage are required for the sensorless field-oriented control (FOC) drive. However, existing sensors and inverters are typically integrated inside commercial closed-form drives; it is not possible for these drives to obtain additional filter output signals. To resolve this integration issue, this paper proposes a sensorless LC filter state estimation using only the drive inside current sensors. The design principle of the LC filter is first introduced to remove PWM current harmonics. A dual-observer is then proposed to estimate the filter output current and voltage for the sensorless FOC drive. Compared to conventional model-based estimation, the proposed dual-observer demonstrates robust estimation performance under parameter error. The capacitor parameter error shows a negligible influence on the proposed observer estimation. The filter inductance error only affects the capacitor current estimation at high speed. The performance of the sensorless FOC drive using the proposed dual-observer is comparable to the same drive using external sensors for filter voltage and current measurement. All experiments are verified by a PM machine with only 130 μH phase inductance.

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Section: Experiments Resultsmentioning

confidence: 99%

Sensorless LC Filter Implementation for Permanent Magnet Machine Drive Using Observer-Based Voltage and Current Estimation

Liang

Lin

Chen

et al. 2021

Sensors

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“…Then, the average voltage loss within a switching cycle is calculated and compensated through feedforward. The method of online compensation is mainly to indirectly realize the compensation of the deadtime effect by suppressing the current harmonics introduced by the deadtime [6].…”

Section: Previous Solutionsmentioning

confidence: 99%

The Online Parameter Identification Method of Permanent Magnet Synchronous Machine under Low-Speed Region Considering the Inverter Nonlinearity

Zhang

Fan

2022

Energies

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To realize the high-performance control of a servo system, parameter accuracy is very important for the design of the controller. Thus, the online parameter identification method has been widely researched. However, the nonlinearity of the inverter will lead to an increase in resistance identification error and the fluctuation of inductance identification results. Especially in the low-speed region, the influence of the inverter is more obvious. In this paper, an offline neural network is proposed considering the parasitic capacitance to identify the nonlinearity of the inverter. Based on the Kirchhoff equation in the static state of the motor, the nonlinear voltage equation is established, and the gradient direction of the weight coefficients has been re-derived. Using the gradient descent method, the identification error can converge to zero. Moreover, the d-axis voltage equation is established considering the nonlinearity of the inverter and an online adaptive observer was proposed. Based on the Lyapunov equation, the adaptive laws are derived. Further, the decoupling of the deadtime voltage and resistance voltage is realized by using the result of neural network identification. With the proposed algorithm, nonlinear identification of the inverter characteristics is realized, and the resistance and inductance identification accuracy in the low-speed region is improved. The effectiveness of the proposed methods is verified through experimental results.

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“…The compensation voltage Dx can be obtained using various methods, which can be classified into datasheet model [2], offline measurement and online compensation. The offline measurement is often executed at motor standstill, and the inverter voltage-current characteristics, i.e., the U-I curve, are recorded for look-up table (LUT) or curve fitting purposes [3], [5], [6]. Particularly in [3], both current amplitude and angle dependencies of Dx are measured and stored as a 2D-LUT.…”

Section: Introductionmentioning

confidence: 99%

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

Mei

Yuan

Zuo

et al. 2022

IEEE Trans. Ind. Electron.

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This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is "plateau voltage", and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.

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Inverter Nonlinear Error Compensation Using Feedback Gains and Self-Tuning Estimated Current Error in Adaptive Full-Order Observer

Cited by 23 publications

References 37 publications

Sensorless LC Filter Implementation for Permanent Magnet Machine Drive Using Observer-Based Voltage and Current Estimation

Sensorless LC Filter Implementation for Permanent Magnet Machine Drive Using Observer-Based Voltage and Current Estimation

The Online Parameter Identification Method of Permanent Magnet Synchronous Machine under Low-Speed Region Considering the Inverter Nonlinearity

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

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