In high-performance control of ac machines through variable frequency drives, the knowledge of machine parameters plays a decisive role. The accuracy with which machine parameters can be known is directly related to the time and effort put in testing and commissioning process. In the ever-demanding industrial environments, the time spent on parameter identification translates into loss of production. To reduce commissioning times, research in this direction has focused on automatizing the identification procedure without loss of accuracy. This paper reviews different lines of research adopted over the past few decades for machine parameter identification. Parameter estimation of ac machines is considered because of their widespread applications from servomechanisms to traction to aviation. The surveyed works include self-commissioning schemes that have become an integral part and salient feature of modern electric drives. This feature enables the drives to automatically identify machine parameters and tune the control loops.

Finite Set Model Predictive Control (FS-MPC) has many advantages, such as a fast dynamic response and an intuitive implementation. For these reasons, it has been thoroughly researched during the last decade. However, the wave form produced by FS-MPC has a switching component whose spread spectrum remains a major disadvantage of the strategy. This paper discusses a modulated model predictive control that guarantees a spectrum switching frequency in the linear modulation range and extends its optimized response to the overmodulation region. Due to the equivalent high gain of the predictive control, and to the limit on the voltage actuation of the power converter, it is expected that the actuation voltage will enter the overmodulation region during large reference changes or in response to load impacts. An optimized overmodulation strategy that converges towards FS-MPC’s response for large tracking errors is proposed for this situation. This technique seamlessly combines PWM’s good steady-state switching performance with FS-MPC’s high dynamic response during large transients. The constant switching frequency is achieved by incorporating modulation of the predicted current vectors in the model predictive control of the currents in a similar fashion as conventional Space-Vector Pulse Width Modulation (SV-PWM) is used to synthesize an arbitrary voltage reference. Experimental results showing the proposed strategy’s good steady-state switching performance, its FS-MPC-like transient response and the seamless transition between modes of operation are presented for a permanent magnet synchronous machine drive.

This paper proposes a simple procedure for accurate identification of the magnetic model of permanent-magnet synchronous machines through inverter supply. The proposed method accounts for the magnetic saturation and the cross-saturation effects. The identification methods reported in the literature may require a servomotor to drive the motor under test at controlled constant speed or the motor itself must accelerate and decelerate. The technique proposed here can be applied at standstill with or without rotor locking and uses a dc+ac injection strategy to identify the machine inductances to construct its magnetic model. The direct current sets the operating point, whereas the superimposed ac component estimates the inductance at that particular point. Small ac signal is injected to ensure local linearity of the magnetic characteristic. Saturation effects are automatically accounted for by the dc bias level, and cross-saturation effects are quantified through maintaining a constant current along the cross-axis. The magnetic model thus obtained can be used for optimal control of the machine and for accurate torque estimation in vector-controlled drives.

In this paper, a loss-minimizing strategy is proposed for induction motor drives to ensure maximum efficiency operation for a given torque demand. The proposed strategy directly regulates the machine stator flux, according to the desired torque, using an optimal stator flux reference. Therefore, the proposed strategy is suitable for motor control schemes that are based on direct flux regulation, such as direct torque control or direct flux vector control. The maximum efficiency per torque (MEPT) stator flux map is computed offline using the traditional no-load and short-circuit test data. An iron loss model based on the stator flux and frequency is also proposed for the calibration of the machine loss model and also for online monitoring of the iron losses during motor operation. The proposed MEPT strategy has been validated on a 2.2-kW induction machine, and the motor efficiency has been measured for different speed values and variable load conditions. The experimental results confirm the effectiveness of the proposed solution.

In this paper, a simple and robust method for parameter estimation at rotor standstill is presented for interior permanent magnet (IPM) synchronous machines. The estimated parameters are the stator resistance through dc test, the dq inductances using high-frequency injection, and the permanent magnet flux by means of a closed-loop speed control maintaining rotor stationary. The proposed method does not require either locking the rotor or additional/special power supplies. The validity of the suggested method has been verified by implementation on two IPM motor prototypes. Finally, the estimated parameters have been compared against results obtained through finite-element simulations and with machine magnetic characterization, separately performed, to validate the method's effectiveness. Saturation and cross-saturation effects are taken care of through amplitude modulation and cross-axis current application, respectively.