Modern Electrical Drives: Trends, Problems, and Challenges

Citation: Szabat, K.; Pajchrowski, T.;
Tarczewski, T. Modern Electrical
Drives: Trends, Problems, and
Challenges. Energies 2022,15, 160.
https://doi.org/10.3390/en15010160
Received: 17 December 2021
Accepted: 23 December 2021
Published: 27 December 2021
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energies
Editorial
Modern Electrical Drives: Trends, Problems, and Challenges
Krzysztof Szabat 1,*, Tomasz Pajchrowski 2and Tomasz Tarczewski 3
1
Department of Electrical Machines, Drives and Measurment, Wrocław University of Science and Technology,
50-370 Wroclaw, Poland
2Institute of Robotics and Machine Intelligence, Poznan University of Technology, 60-965 Poznan, Poland;
[email protected]
3Institute of Engineering and Technology, Nicolaus Copernicus University in Torun, 87-100 Torun, Poland;
ttarczewski@fizyka.umk.pl
*Correspondence: [e-mail]
1. Introduction
Modern electrical drives possess many advantages. Electrical energy, compared to
other sources, is easy to transport and can be environmentally friendly (if it comes from
renewable sources). Electrical drives convert energy with high efficiency and have flexible
control characteristics. They offer a wide range of speed, torque, and power operations.
Furthermore, in general, they can serve as electrical generators.
With the growing demand for high-performance electrical drives, many universities
and industrial researchers have focused on the problems surrounding the efficient, robust,
precise, and fault-tolerant controls of these drives. In various industries, accurate control of
electrical drives is crucial, from high-power drives evident in mining and petrochemical
areas, to medium (automotive industries, robot arm drives, CNC machines) and small
power drives (actuators), MEMS, etc.
In this Special Issue, the topics related to trends, problems, and challenges linked
to the design and exploitation of modern electrical drives are presented. The submitted
manuscripts, and those finally selected for publication in this Special Issue, focus on the
trends, problems, and challenges in modern electrical drives. Very often, they are multidis-
ciplinary works. In this Special Issue, 10 manuscripts were published that deal with the
following topics: control strategies for different types of electrical motors [ 1 – 3 ], estimations
of non-measurable states and parameters [ 3 ], sensorless control of electrical drives [ 1 , 2 ], the
application of advanced control methodologies for high performance control of electrical
drives [ 4 – 6 ], diagnoses, monitoring, and prognoses in electrical drives [ 7 – 10 ], and control
of complex mechatronic systems, while taking the mechanical part of the system into
account [3,4,6].
This publication is divided into two important sections: a short review of the contribu-
tions, where important contributions to the development of electric drives are presented,
and a summary of the work.
2. A Short Review of the Contributions in This Issue
The main idea of the article [ 1 ] is to create a buffer power supply system for an
asynchronous electrical drive, and to develop a strategy for a control system for this
buffer power by using a bidirectional DC–DC converter. The article describes the process of
creating a model of an electric drive, buffer source, control system, and frequency regulation
based on MATLAB–Simulink. Simulations of the operations of this system were carried
out together with a buffer source based on the supercapacitors. The adequacy and accuracy
of the calculated mathematical expressions were proven. An algorithm for the operation of
the control system for the buffer power source was proposed.
In [ 2 ], Bednarski et al. proposed and experimentally examined a family of generalized
microstepping signal shapes for stepper motors. The authors provided the mathematical
Energies 2022,15, 160. https://doi.org/10.3390/en15010160 https://www.mdpi.com/journal/energies

Energies 2022,15, 160 2 of 4
formula to derive the p-norm signals responsible for generation reference currents for
stepper motors. The developed signals represent a middle ground between the smooth
operation of sine–cosine and the high peak torque output of quadrature microstepping.
Based on the numerous experimental tests, it can be concluded that the optimal signal
shape (in the sense of positioning accuracy) is neither sin–cos nor quadrature. The best
results in the considered test scenario are obtained for three-norm (p3) microstepping. The
findings of this paper are valuable for developers of 3D printers, CNC machines, and other
positioning devices, where a precise movement with a well-defined angular resolution
is important.
The paper [ 3 ] presents an identification workflow of a multi-resonant mechanical part
in a direct drive with up to three high-frequency mechanical resonances. The knowledge
of a direct-drive model with a complex mechanical part is important in the syntheses of
control algorithms and in the predictive maintenance of digital twins. The identification of
two-mass drive systems with one low mechanical resonance frequency is often described
in the literature. Previous research has focused on multi-mass drive systems with high
mechanical resonance frequencies, in ranges up to 500 Hz. In the first approach, the author
used only an output signal in frequency domains with a custom search algorithm. Anti-
resonance frequencies were not identified by this algorithm, and a second drawback is
its accuracy of around ± 3 Hz. This algorithm was successfully tested and compared with
manual identification used in control systems, with variable mechanical parameters with
three resonance frequencies of 105, 251, and 417 Hz. Literature studies in the paper [ 3 ]
showed that chirp signals give a smoother frequency response in comparison to PRBS,
as the frequency range is banded and the magnitude is flat. The paper presents an iden-
tification workflow of a multi-resonant mechanical part in direct drive with up to three
high-frequency mechanical resonances in a continuous-time (CT) representation. The usage
of a nonlinear least-square algorithm with constraints, as a fitting algorithm, allows solving
the issue of modeling multi-mass direct-drive systems in the frequency domain. The second
finding in paper [ 3 ] is a comparison of different cost functions evaluated to choose the best
complex number representation for the identification of multi-mass direct-drive systems.
The article by Szczepanski et al. [ 4 ] describes an application of a nature-inspired meta-
heuristic optimization algorithm in the controller’s auto-tuning. To fulfill the requirements
related to the precise control of a complex plant, the original objective function minimized
during the automatic synthesis process of the controller has been proposed. An artificial
bee colony algorithm for auto-tuning a two-mass system was explored. In the results,
optimal coefficients of the state speed feedback controller has been obtained. These assure
high-performance and robust operation of the drive with a complex mechanical structure.
The proposed auto-tuning method may find application in many industrial machines,
such as conveyor belts, servo systems, robot arms, and rolling-mill machines, to provide
satisfactory product quality and extend the lifetime of the machine’s mechanical part, due
to the reduced coupling shaft stress.
Application of the adaptive control structure for a drive system with an elastic connec-
tion is described in the paper [ 5 ]. The proposed algorithm is based on the direct adaptive
control concept. As a speed controller, the recurrent neural network is applied. The model
of the system is inspired by Elman nets. The properties of the system depend on the control
coefficients significantly; therefore, a method based on the particle swarm optimization
algorithm is proposed here. Additionally, the ADALINE model is used in order to filter the
signal used in the control structure. The properties of the proposed control structure are
tested under simulation and experimental studies.
In [ 6 ], an application of the D-decomposition method for a control structure of a drive
system with a flexible connection is presented. The proposed method allows a detailed
analysis of the closed-loop control structure properties. The stability regions for constant
and changeable parameters of the drive can be specified. Furthermore, the additional
delays caused by the torque control loop, as well as the torque and speed sensor, can be
included in the analysis. Furthermore, the properties of the drive system with the controller,

Energies 2022,15, 160 3 of 4
tuned with the help of classical pole placement methodology, is analyzed. The limitations
of both approaches are pointed out. Then, a tuning algorithm based on the connection
of D-decomposition and pole placement techniques is proposed. It allows reducing the
oscillations in the state variable transients effectively. The theoretical considerations are
supported by experimental studies.
Ewert [ 7 ] presents the effectiveness of a bispectrum analysis for the detection of the
rotor unbalance of an induction motor supplied by the mains and a frequency converter.
Two diagnostic signals, as well as the stator current and mechanical vibrations of the
tested motors were analyzed. The experimental tests were conducted for two low-power
induction motors with one and two pole pairs, respectively. The unbalance is modeled
using a test mass mounted on a specially prepared disc and directly on the rotor, and the
influence of this unbalance location was tested and discussed. On the basis of the conducted
analyses, it can be stated that the vibration acceleration signal is a better information carrier
in the case of rotor unbalance than the stator current signal. The changes in the amplitudes
that are characteristic of the unbalance symptoms occurring in the mechanical vibration
analysis are a few (or sometimes even more than a dozen) times higher than those observed
in the stator current analysis. Therefore, the analysis of the mechanical vibration signal is a
better solution in the detection of rotor unbalance.
Hajnrych et al. [ 8 ] propose the parameterized models of the yokeless axial flux (AF)
machine with different rotor parameters using the advanced 3D finite element analysis.
The impact of the number of rotor poles on the cogging torque amplitudes and their ripple
factors is investigated. The results indicate that the best drive torque density with a low
torque ripple and low back-EMF total harmonic distortion are obtained for the pole span of
around 0.8 of full pole pitch. On the basis of the above-mentioned findings, efficient and
smaller motors with permanent magnets can be designed, which is essential for application
in electric vehicles. Finally, the authors recommend the yokeless AF machines for low-speed
direct-drive applications requiring a low cogging torque and a high output torque density.
The article by Pajchrowski et al. [ 9 ] presents concepts of three-phase power rectifiers
with improved quality of converted electrical power. This effect is obtained by modulating
the currents in the DC output circuits of the rectifiers by means of current sources con-
trolled by power electronics, working as so-called current modulators. For further quality
improvement of the grid currents of the analyzed systems, using an additional controlled
current source connected in parallel to the DC load was suggested (hereinafter referred to
as a supporting system). The original elaborated method of controlling this source was
presented. This solution is very attractive due to the ease of implementation in systems
already in use, which significantly reduces investment costs. It should be noted that already
in its basic version, this solution enables a significant reduction in undesirable harmonics
in the grid current, which has a positive effect on the quality of the converted energy. It
should also be emphasized that even a possible failure of these modules does not interrupt
the energy supply to the DC load.
The use of the D-decomposition technique for an analysis of the work of a boost
converter operating in continuous condition mode is described in [ 10 ]. The authors propose
the application of the genetic algorithm to select the optimal gain of PI coefficients. The
D-decomposition technique allows specifying the global stability region of the controlled
plant. Additionally, the design requirements based on the specified desired gain and phase
margin are introduced here. This problem is shown as a function that is further used in the
generic algorithm. Three different performance indexes are tested in the paper. The delay
evident in a controlled plant is taken into account. The identification procedure of the plant
is describe in the paper. The simulation and experimental results are included in the paper.
3. Conclusions
After analyzing the contributions selected for publication in this Special Issue, the
following conclusions were drawn. Modern control approaches (i.e., state feedback control,
adaptive control) and identification techniques are applied to improve the overall perfor-

Energies 2022,15, 160 4 of 4
mance of electrical drives with complex multi-mass systems. Advanced optimization tech-
niques (including the meta-heuristic approach) and analysis tools (i.e., D-decomposition)
play essential roles in developing complex control schemes, designing electrical machines
with respect to the considered performance indexes (e.g., mitigation of torque ripples,
efficiency maximization, dynamic property optimization), and investigating stability issues.
An accurate and robust estimation of the non-measurable states and parameters is still
of interest to researchers. Therefore, data-driven analyses supported by artificial neural
networks and advanced spectral approaches are employed. As a result, more accurate
models of the electrical drive (i.e., motor and power converter) are obtained, and fur-
ther phenomena are investigated. The presented approaches lead to more efficient and
high-performance electrical drives. Therefore, further development of intelligent control
algorithms and tools responsible for optimal design and analysis will be observed in the
near future.
Author Contributions: The authors contributed equally to this work. All authors have read and
agreed to the published version of the manuscript.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.
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