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Today’s modern control strategies of an induction motor (IM) drive require a power source with an adjustable output voltage frequency and amplitude. The most commonly used converter topology is a two-level voltage-source inverter (VSI). However, the utilization of a VSI introduces additional voltage and current distortion, which leads to additional power losses in the machine’s magnetic circuit. Both the transistor switching frequency and the type of the inverter control determine the total harmonic distortion (THD) of the motor’s phase currents. In this paper, the influence of the inverter DC-link voltage on the iron losses of an IM controlled by a predictive torque control (PTC) is presented. It is shown that if the IM drive operates below the rated speed, it is possible to modify the PTC algorithm to reduce the additional iron losses caused by the non-harmonic inverter output voltage. The control of the DC-link voltage is achieved by using a silicon-controlled rectifier. Experiments were conducted on a 5.5 kW IM controlled by PTC, and the results are compared against a sinusoidal voltage supply created by a synchronous generator.

Although still widely used due to its robustness, reliability, and low cost, induction motor (IM) has a disadvantage of more complicated mathematical description than permanent magnet AC machines. In high-demanding applications, the decoupled control of the machine's flux and torque along with the proper function of selected efficiency-improving and flux-weakening algorithms can be achieved only if the IM parameters are known with sufficient accuracy. For parameter estimation, many algorithms have been proposed in the literature so far. Due to its simple and straightforward implementation, one of the popular estimation strategies is the model reference adaptive system (MRAS). However, MRAS-based algorithms for a specific parameter estimation tend to be sensitive to other machine parameters. For instance, most of the proposed MRAS algorithms do not consider the influence of the phenomena such as iron losses and load-dependent saturation. Since one of the most performance-decisive parameters of the popular rotor flux-oriented control (RFOC) are the magnetizing inductance and the rotor resistance, this paper aims to present a novel MRAS-based magnetizing inductance estimator (Lm-MRAS) with the included effect of iron losses. Furthermore, to enable the identification of the load-dependent saturation, another MRAS with included iron losses based on reactive power is proposed to work parallelly with Lm-MRAS, since under load conditions, the rotor resistance mismatch causes RFOC detuning. The adaptation law of the Lm-MRAS is obtained using the Lyapunov function approach and further examined using small-signal analysis. The proposed algorithms are verified on a 3.6 kW IM drive both in simulations and experiments.

The simplest mathematical models of the induction motor (IM) use the presumption of the machine's linear magnetising characteristics. However, this may hold only in a limited operating range of the electric drive. It is well known that the magnetising inductance saturates as a function of the magnetising current due to the non-linear properties of the magnetic circuit. However, this is not the only type of saturation. Depending on the design of the rotor, the machine's magnetising and leakage inductances may also saturate as a function of the rotor current. A new experimental method is proposed here. It identifies the dependence of the T equivalent circuit magnetising inductance on the rotor flux and torque producing current component using parallel operation of the so-called current and voltage model of the IM.

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