Larizza Delorme

High-performance sensorless operation in multiphase electric drives requires speed estimation techniques capable of providing fast dynamic response, reduced oscillatory behavior, and low implementation complexity. In this context, a sliding-mode observer (SMO) based on an exponential reaching law (ERL) is proposed for rotor speed estimation in asymmetrical six-phase induction machines operating under indirect rotor field-oriented control. Unlike conventional SMO implementations, the proposed approach avoids auxiliary low-pass filtering (LPF) stages by employing an ERL-based adaptive gain mechanism, thereby preventing the phase delay and bandwidth reduction commonly associated with LPF-based observers. As a result, the proposed observer preserves fast transient dynamics, attenuates chattering near the sliding surface, and improves the smoothness of the estimated signals. The proposed technique is particularly suitable for multiphase drive applications, where sensorless operation reduces hardware complexity and improves system reliability by eliminating mechanical speed sensors and associated wiring. A Lyapunov-based stability analysis is presented to demonstrate the convergence properties of the observer and discuss the influence of the ERL parameters on the estimation dynamics. Simulation and experimental results obtained on a real-time test bench validate the digital implementation of the proposed SMO + ERL, demonstrating improved transient tracking, smoother estimated signals, stable low-speed operation, satisfactory speed reversal performance, and effective operation under loaded conditions.

This paper addresses the regulation of stator currents in a six-phase asymmetrical induction machine during field-weakening operation, accounting for disturbances and parameter variations. Current control is performed in the d–q, α–β, and x–y reference planes. A novel double-loop current controller based on a discrete-time super-twisting algorithm is proposed to enhance current regulation, particularly under field-weakening conditions where current tracking errors typically deteriorate. This controller ensures precise current tracking with fast error convergence and improved robustness to uncertainties. Experimental results confirm the effectiveness of the controller under both transient and steady-state conditions, including during the field weakening operation.

Finite-control-set model predictive control (FCS-MPC) has become widely accepted in multiphase drives due to its adaptability and robust dynamic response. However, multiphase machines, characterized by low secondary plane ($x-y$) impedance, which is absent in their three-phase counterparts, often exhibit poor current quality under conventional FCS-MPC strategies. This paper proposes a novel predictive torque control (PTC) scheme based on virtual vectors to improve ($x-y$) current regulation by ensuring zero average ($x-y$) voltage generation. The proposed method is compared with classic PTC, which cannot achieve proper ($x-y$) current regulation because it uses a single switching state during the sampling period. Experimental validation includes a detailed comparison of torque and flux behavior, ($x-y$) current mean square error, and total harmonic distortion of the fundamental stator currents, demonstrating the effectiveness of the proposed control approach under various operating conditions. Experimental results confirm reductions of approximately 79.7% in computational burden and 98.4% in copper losses when using PTC-VV compared to classic PTC. An asymmetrical six-phase induction machine is used as the case study.

This paper presents the application of a sliding mode observer for speed sensorless control of a six-phase induction machine. The use of nonlinear sliding mode techniques yields acceptable performance for both low- and high-speed motor operations over a wide speed range. The effectiveness and accuracy of the developed sensorless scheme are verified by experimental results, which demonstrate the system’s performance under various operating conditions. These results demonstrate the advantages of the proposal as a valid alternative to the conventional method, which uses a mechanical speed sensor for multiphase machines. Additionally, the sensorless approach can also serve as a redundant backup in the event of mechanical sensor failure, thereby increasing the reliability of the overall drive system.

Finite-control-set model predictive control (FCS-MPC) has achieved superiority in managing multiphase induction machines due to its quick dynamic response, control flexibility, and overall good performance. Its advantages, including simplicity, computational efficiency, compensation for system perturbations, and effective handling of multivariable problems, have made it a competitive alternative in various industrial applications. Nevertheless, FCS-MPC has some limitations. It is highly dependent on the accuracy of the predictive model’s parameters. Unfortunately, the estimation of magnetizing inductance, the most critical factor, especially in the weakening field region, has not been studied yet. Focusing on this gap, this article proposes a technique to estimate the magnetizing inductance in the field weakening zone for a six-phase asymmetrical induction machine driven by the FCS-MPC. Experimental tests have verified the effectiveness of the proposed method, considering stator currents and rotor speed tracking, as well as a reduction in the (x − y) currents.

Multiphase machines are a hot research topic in control theory and industrial applications such as electric cars. However, the availability to buy them in the market is limited or null. For this reason, it is common to rewind it from a three-phase commercial machine. In this context, the aim of this paper is two-fold. First, to introduce a straightforward procedure to rewind a nine-phase induction machine from a three-phase one. For that purpose, a study of the three-phase induction motor was performed, which included selecting a new winding design, calculating stator coils, and simulating tests with ANSYS Maxwell software to validate the design. Secondly, a performance analysis comparing the power losses through experimental tests performed to obtain the electrical parameters of both nine-phase and three-phase topologies is presented.

The use of multiphase machines has become a suitable choice in high-performance industry applications through advantages such as lesser torque ripple, enhanced current distribution per phase, and fault-tolerance capability. Among different control approaches for the regulation of multiphase drives, model-based predictive current control (MPCC) is one of the most analyzed strategies due to its adaptability and good dynamic response. However, this approach presents some disadvantages, e.g., high $x-y$ currents and increased harmonic content in the fundamental $\alpha -\beta$ stator currents. Modulation strategies have been combined with MPCC to overcome these shortcomings. This article proposes a modulated MPCC with virtual vectors and space vector modulation for the regulation of an asymmetrical six-phase induction machine to minimize the $x-y$ currents, reduce the harmonic content, and perform improved stator currents tracking compared with other MPCC versions. Experimental tests are provided to demonstrate the quality of the proposed current control strategy.