Ing. Ondřej Lipčák, Ph.D.

This paper introduces a novel overmodulation strategy tailored for dual-inverter topologies with galvanically isolated DC-links and evenly distributed DC-link voltage. The core contribution of the paper is the utilization of the multilevel capabilities of the dual-inverter topology. At the maximum modulation index, the presented overmodulation method achieves what is referred to as a 12-step operation. The 12-step operation improves the voltage waveform and offers superior harmonic performance compared to the conventional 6-step operation. The utilized approach leverages a hybrid Space Vector Pulse Width Modulation (SVPWM) method, a well-established technique in two-level inverters, to achieve this extended operation range. Furthermore, the paper presents a nonlinear gain compensation characteristic vital for real-time motor control applications and provides a comparative analysis of the modulation's harmonic performance. The proposed approach is validated through simulations and experiments. The experiments were conducted using a custom inverter based on Gallium-Nitride (GaN) transistors where simple volt/hertz control of an induction motor was programmed. The results of these experiments affirm the strategy's effectiveness, showcasing superior current waveform quality and a smooth transition from linear mode to 12-step operation while keeping a simple implementation of the algorithm.

The increasing popularity of electric drives employing an isolated dual-inverter (DI) topology is motivated by their superior DC-link voltage and power utilization, fault-tolerant operation, and potential for multilevel operation. These attributes are significant in battery-powered transportation, such as electric vehicles and aviation. Given the considerable freedom in modulation and control of the DI topology, this paper researches the impact of reference voltage vector distribution between the two individual inverters. The study also evaluates the influence of two well-established asynchronous modulation strategies—Space Vector PWM (SVPWM) and Depenbrock’s Discontinuous Modulation (DPWM1). Since simulation tools nowadays play a crucial role in power electronics design and concept verification, the results are based on extensive and detailed models in Matlab/Simulink. Employing the basic field-oriented control of a 12 kW induction motor with precisely parameterized SiC switching devices for accurate loss calculation, this research reveals the possibility of significant energy savings at multiple operating points. Notably, optimal efficiency is achieved when one inverter operates up to half of the nominal speed while the other solely establishes a neutral point for the winding. Moreover, the results highlight DPWM1 as a superior strategy for the DI topology, showcasing reduced converter losses. Overall, it is shown that the system’s losses can be significantly reduced just by the design of the voltage vector distribution in the drive’s operating range and the modulation strategy selection.

This paper investigates the optimal stator voltage angle in a rotor flux-oriented system of an induction machine drive, aiming to maximise machine torque while operating in a deep field weakening region. Here, torque maximisation leads to maximum torque per voltage control, as only voltage constraints are relevant in this region due to high back‑electromotive force. Previous studies have predominantly focused on field‑weakening operation and torque maximisation, assuming a constant synchronous speed. However, for a given rotor speed, the variation in the dq voltage components impacts the slip speed, thereby influencing the synchronous speed. Therefore, enhanced analytical expressions are proposed in this paper to address this limitation. It is shown that after a linearisation around a suitable operating point, a closed-form algebraic equation for calculating the speed and parameter-dependent optimal voltage angle for torque maximisation can be obtained. The theoretical analysis is supported by numerical and experimental results. The presented linearised expression is proven to be an effective tool for the analytical calculation of the optimal voltage angle, making it suitable for real-time control applications. It is shown that the proposed approach achieves higher drive torque and efficiency than the conventional voltage component distribution.

The ever-increasing demands on the efficiency and power density of power electronics convert-ers lead to the replacement of traditional silicon-based components with new structures. One of the promising technologies represents devices based on Gallium-Nitride (GaN). Compared to silicon transistors, GaN semiconductor switches offer superior performance in high-frequency converters, since their fast switching process significantly decreases the switching losses. How-ever, when used in hard-switched converters such as voltage-source inverters (VSI) for motor control applications, GaN transistors increase the power dissipated due to the current conduc-tion. The loss increase is caused by the current-collapse phenomenon, which increases the dy-namic drain-source resistance of the device shortly after the turn-on. This disadvantage makes it hard for GaN converters to compete with other technologies in electric drives. Therefore, this paper offers a purely software-based solution to mitigate the negative consequences of the cur-rent-collapse phenomenon. The proposed method is based on the minimum pulse length opti-mization of the classical 7-segment space-vector modulation (SVM) and is verified within a field-oriented control (FOC) of a three-phase permanent magnet synchronous motor (PMSM) supplied by a two-level GaN VSI. The compensation in the control algorithm utilizes an offline measured look-up table dependent on the machine input power.

The current and torque ripple of inverter-fed induction motor drives is an inherent problem of control strategies working with switching frequencies in the range of multiple kilohertz, such as direct torque and, more recently, predictive torque control. If the drive operates in a wide-speed and wide-torque range and is equipped with a machine with an accessible terminal block whose winding is nominally connected in delta, then the current and torque ripple can be reduced by utilizing the delta-star winding changeover technique. When the winding configuration is switched from delta to star, the instantaneous motor phase voltage peak is lowered, and its total harmonic distortion is reduced. However, the control strategy must be adjusted according to the actual winding topology, mainly due to the difference in the coordinate transformations of the measured currents and the difference between the phase voltage vectors obtained from the inverter. This paper proposes a predictive torque control of an induction motor drive with a switchable delta-star winding configuration. The paper is supported by theoretical background, and the key idea is verified by simulations in MATLAB/Simulink and experiments conducted on a dSPACE-controlled 5.5-kW laboratory drive. The simulations validated the presented equations and show the effects of not respecting the actual winding topology. The experiments mainly focused on analyzing the total harmonic distortion of the currents and consumed electrical power in multiple operating points.

Most of the control algorithms of variable speed drives with induction motor require the knowledge of the stator voltage vector applied to the motor ter-minals. This vector is usually reconstructed from the known microcontroller’s PWM signals or the commanded voltage for the inverter is used within the con-trol algorithm. However, these solutions require a DC-link voltage sensor and compensation of the nonlinear inverter behavior. In this paper, stator voltage es-timator based on the Extended Kalman filter is proposed. This approach requires neither the knowledge of the DC-link voltage nor the nonlinear model of the in-verter. Only the knowledge of the stator currents and the rotational speed is need-ed. The proposed estimator is verified within the simulation of predictive-torque control of induction motor drive in Matlab Simulink where the comparison of the applied and the estimated voltage vector is presented along with their harmonic analysis. The accuracy of the estimated voltage vector shows its suitability for further inverter nonlinearities investigation.

Mathematical models of induction motor (IM) used in direct field‑oriented control (DFOC) strategies are characterized by parametrization resulting from the IM equivalent circuit and model‑type selection. The parameter inaccuracy causes DFOC detuning, which deteriorates the drive performance. Therefore, many methods for parameter adaptation were developed in the literature. One class of algorithms, popular due to their simplicity, includes estimators based on the model reference adaptive system (MRAS). Their main disadvantage is the dependence on other machines’ parameters. However, although typically not considered in the respective literature, there are other aspects that impair the performance of the MRAS estimators. These include, but are not limited to, the nonlinear phenomenon of iron losses, the effect of necessary discretization of the algorithms and selection of the sampling time, and the influence of the supply inverter nonlinear behavior. Therefore, this paper aims to study the effect of the above-mentioned negative aspects on the performance of selected MRAS estimators: active and reactive power MRAS for the stator and rotor resistance estimation. Furthermore, improved reduced‑order models and MRAS estimators that consider the iron loss phenomenon are also presented to examine the iron loss influence. Another merit of this paper is that it shows clearly and in one place how DFOC, with the included effect of iron losses and inverter nonlinearities, can be modeled using simulation tools. The modeling of the IM and DFOC takes place in MATLAB/Simulink environment.

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.

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.

Accurate knowledge of induction machine parameters has a direct impact on the overall performance of field-oriented control strategies. In the case of rotor flux oriented control, parameter mismatch causes a discrepancy in the estimated rotor flux position and amplitude. Magnetising inductance is one of the parameters whose detuning has a direct impact on the setpoints of the control loops and estimation of hardly or non-measurable quantities. Conventional iron saturation, which can be obtained by a standard no-load test, is not the only type of saturation occurring in the machine. Depending on the rotor design, the magnetising inductance and the rotor leakage inductance may also strongly saturate as a function of load and, thus, rotor current. Based on our previous work, a new, improved experimental method for identifying the load-dependent saturation of induction motor, which takes into account variation of the inverse rotor time constant, is proposed. Experimental results conducted on 12 kW motor show improved static and dynamic behaviour of the drive compared to the constant parameter model.

Omission of the speed sensor in induction motor based electric drive is very actual topic because of cost savings. When omitting the speed sensor, induction machine mathematical model that does not require information about rotor speed has to be used, such as voltage model. The quality of control then depends on the model stability and accuracy of induction motor parameter identification. This paper strives to discuss most important quantities that influence stability and accuracy of the voltage model.

This paper proposes a new method leading to a reduction in the current and torque ripple of an Induction Motor (IM) drive controlled by a Predictive Torque Control (PTC). The method lies within the optimisation of DC-link voltage magnitude by a three-phase thyristor bridge rectifier. Using a controlled rectifier, the DC-link voltage can be adjusted in such way that the ripple of the IM state variables, caused mainly by treating the inverter as a source of only eight voltage vectors, is significantly reduced. Another positive consequence of the proposed algorithm is the reduction of DC-link-dependent switching losses. The DC-link optimisation algorithm is integrated within the PTC that is used for the torque and flux control. The theoretical analysis of the DC-link voltage influence on the drive behaviour is supported by simulation and experimental results conducted on a 5.5 kW IM drive, which confirms the benefits of the PTC with the DC-link voltage optimisation.

Gallium nitride (GaN) devices are becoming more popular in power semiconductor converters. Due to the absence of the freewheeling substrate diode, the reverse conduction region is used in GaN transistors to conduct the freewheeling current. However, the voltage drop across the device in the reverse conduction mode is relatively high, causing additional power losses. These losses can be optimized by adequately adjusting the dead-time issued by the microcontroller. The dead-time loss minimization strategies presented in the literature have the common disadvantage that either additional hardware or specific converter data are needed for their proper operation. Therefore, this paper’s motivation is to present a novel dead-time loss minimization method for GaN-based high-frequency switching converters for electric drives that does not impose additional requirements on the hardware design phase and converter data acquisition. The method is based on optimizing the current controllers’ output with a simple perturb-and-observe tracker. The experimental results show that the proposed approach can minimize the dead-time losses over the whole drive’s operating range at the cost of only a moderate increase in software complexity.

Many algorithms of induction motor sensorless control need accurate knowledge of the stator voltage vector. However, the machine is in most cases supplied by a two-level voltage-source inverter; therefore, the voltage is distorted by the inserted dead-time and also by nonlinearities of the semiconductor switches. This paper analyzes a distortion caused by the dead-time and delayed IGBT switching in terms of distorting voltage vector. An offline measurement is performed to obtain the inverter model. Then, an analysis of two simple volt-seconds-based compensation methods (compensation of the reference voltage vector and duty cycle, respectively) on the accuracy of the speed estimation of a sensorless field-oriented control based on the rotor flux model reference adaptive system is performed. The analyzed methods use either the full inverter model implemented as a look-up table or its trapezoidal approximation. Outline on computational complexity and discussion on finding optimal coefficients for the trapezoidal model are given, too.

Jedna z možných a výpočetně poměrně nenáročných metod bezsenzorového vyhodnocování otáček asyn-chronního motoru je adaptivní systém s referenčním modelem (angl. Model Reference Adaptive System - MRAS) založený na rotorovém toku. V rámci této strategie jsou paralelně vyhodnocovány proudový a napě-ťový model asynchronního motoru. Stabilita a přesnost celého řízení se pak odvíjí od stability a přesnosti obou modelů. Do napěťového modelu vstupuje statorové napětí, které je však tvořené pulzy zkreslenými ochrannými mrtvými dobami a nelineárním chováním střídače. Tento článek představuje jednoduchou a snadno implementovatelnou metodu pro identifikaci a kompenzaci zkreslení ochrannými dobami a zpoždě-ným spínáním IGBT tranzistorů. Součástí článku jsou výsledky experimentálního ověření na 12kW motoru.

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 nonlinear 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 in this paper. 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.

The accuracy of induction motor (IM) drive with employed field-oriented control depends on precise identification of the IM equivalent circuit parameters. Those parameters can change significantly during the drive operation. Therefore, an adaptation of the IM model parameters is needed for a high-performance drive. Estimators based on model reference adaptive system (MRAS) are not computationally demanding, but they a priori exhibit sensitivity to the other, non-estimated parameters. This paper analyses the influence of the proper knowledge of the magnetizing inductance on the accuracy of the rotor resistance estimator based on the traditional reactive power MRAS. The paper also takes into account the load-dependent saturation of the IM, which is often omitted during the analysis and shows that the implemented load-dependent magnetization characteristic improves the MRAS and drive performance. Simulation and experimental results conducted on 12 kW IM are presented.

Important parameters of an induction motor drives include dynamics and efficiency. Both attributes are tightly associated with accurate acquisition of hardly measurable quantities such as magnetic flux (and its position) and motor torque. The mathematical model of the induction machine is used for calculation of these quantities. The model usually comprises of a set of differential equations, that have to be numerically solved inside drive's controller. Computation time requirement and accuracy of the resulting estimation are important parameters of the selected solver. For this purpose, Euler's method was usually used in engineering applications, but with increasing computational throughput of DSP, more complicated numerical methods can be applied too. This paper strives to compare Euler's method with 4 th order Runge-Kutta method.