Sensorless Control of Brushless Doubly Fed Induction Machine Using a Control Winding Current MRAS Observer

Abstract

In order to realize sensorless control for brushless doubly-fed induction machine (BDFIM), this paper presents a model reference adaptive system (MRAS) observer, designed based on the error of the control winding current. Furthermore, a phase-locked loop (PLL) is employed to estimate the current winding position and rotor speed. Consequently, a detailed theoretical derivation proves that the MRAS observer is stable and the dynamic performance is good. Thus, it does not cause any estimated speed error in steady state. Moreover, the estimated position error is bounded and trivial, thus its effects on the sensorless control of the BDFIM are neglected. The correctness, feasibility, and robustness of the proposed sensorless control method are verified by means of experimental validation on a 30kW test rig. Index Terms-Brushless doubly-fed induction machines, model reference adaptive system observer, sensorless control, angular velocity control. NOMENCLATURE v, i, ψ Voltage, current and flux R, L Resistance and self-inductance Lhp Coupling inductance between power winding (PW) and rotor Lhc Coupling inductance between control winding (CW) and rotor τe, τL Electromagnetic torque and load torque P Number of pole pairs ωr Rotor mechanical angular speed ωp Electrical angular speed of the grid θr, θp Angular positions of rotor and PW flux frame

Internal Model Current Control of Brushless Doubly Fed Induction Machines

“…The total resistance and the total leakage inductance are measured by an impedance analyzer, which are 1.63183 Ω and 0.009 H, respectively. Figure 9 shows the experimental rig of the BDFIM system, the PW stator of the BDFIM is directly connected to the power grid (380 V/50 Hz), and the CW stator of the BDFIM is fed by a PWM inverter, and more details are discussed in [25]. The CW current control algorithm is implemented by the digital signal processor (DSP, TMS32028335), and the field-programmable gate array (FPGA, EP2C8J144C8N) generates the drive signals for the insulated gate bipolar transistor (IGBT).…”

“…On the basis of the grid-flux orientation frame, the basic mathematical model of the BDFIM [25] is expressed as: …”

“…In the BDFIM drive system, both the power generation and rotor speed control can be achieved by properly adjusting the CW current as discussed in [22,25,26], where a well-designed current controller is a prerequisite for the normal operation of the BDFIM system. In this part, the design details of the CW current controller are discussed, which aims to track the CW current command under the disturbance of the coupling terms and BDFIM parametric errors as shown in Equation (8).…”

Neuro-fuzzy Sliding Mode Controller Based on a Brushless Doubly Fed Induction Generator

“…This gives rise to the chattering phenomenon, which consists of sudden and rapid variations in the control signal, which can excite the high frequencies of the process and damage it. Indeed, to remedy the drawback of this phenomenon, several works have been performed [11][12][13][14][15].…”

Advanced control of electrical machines in marine applications

“…Additionally, an optimal law is employed to find the largest stability region for a reduced-order observer in [94]. Furthermore, the model reference adaptive system (MRAS) observer-based method is implemented in [95][96][97]. Its stability and dynamic performance have been proven.…”