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For non-sinusoidal electromotive force (NS-EMF) multiphase machines, this paper proposes a new strategy and control scheme to guarantee smooth torque under an open-phase fault. Notably, the conventional proportional-integral (PI) controllers implemented for vector control in healthy mode can be used in the faulty mode. The strategy is based on reduced-order transformations while the control scheme applies a simple artificial intelligence algorithm using a specific online-trained Adaptive Linear Neuron (ADALINE). Indeed, the inputs of ADALINE require the knowledge of rotor position and NS-EMF harmonic rank to optimize the learning time. The proposed strategy and control scheme are tested on a seven-phase machine with a strong Total Harmonic Distortion (THD) of NS-EMFs, containing numerous harmonics Hk (THD=38% with 100% H1, 32.3% H3, 9.4% H7, 12.5% H9, 10.3% H11). Numerical and experimental results are presented in this paper. This paper is accompanied by a video demonstrating the experimental results.

This two-part study proposes a new sensorless control strategy for non-sinusoidal multiphase permanent magnet synchronous machines (PMSMs), especially in integrated motor drives (IMDs). Based on the Sliding Mode Observer (SMO), the proposed sensorless control strategy uses the signals (currents and voltages) of all fictitious machines of the multiphase PMSMs. It can estimate the high-accuracy rotor position that is required in the vector control. This proposed strategy is compared to the conventional sensorless control strategy applying only current and voltage signals of the main fictitious machine, including the fundamental component of back electromotive force (back-EMF) of the non-sinusoidal multiphase PMSMs. Therefore, in order to choose an appropriate sensorless control strategy for the non-sinusoidal multiphase PMSMs, these two sensorless control strategies will be highlighted in terms of precision in the rotor position and speed estimations. Simulation and experimental results of a non-sinusoidal seven-phase PMSM will be shown to verify and compare the two sensorless control strategies. In this part of the study (part I), only the sensorless control in medium and high-speed range is considered. The sensorless control at zero and low-speed range will be treated in the second part of this study (part II).

Fault tolerance has been known as one of the main advantages of multiphase drives. When an open-circuit fault happens, smooth torque can be obtained without any additional hardware. However, a reconfiguration strategy is required to determine new reference currents. Despite advantages of non-sinusoidal electromotive forces (NS-EMFs) such as high torque density, multi-harmonics existing in NS-EMFs cause more challenges for control, especially under faulty conditions. Therefore, to guarantee high-quality vector control of multiphase drives with multi-harmonic NS-EMFs, this two-part study proposes control schemes using adaptive linear neurons (Adalines) to adaptively eliminate torque ripples. The proposed simple Adalines are efficient because of taking advantage of the knowledge of rotor position and of torque harmonic rank induced by the NS-EMFs. The control scheme using an Adaline for healthy mode was described in part I of this study. In this second part, the control scheme using another Adaline for an open-circuit operation, under the impacts of multi-harmonics in NS-EMFs, is proposed. Notably, smooth torque and similar copper losses in the remaining healthy phases can be obtained. Experimental tests are carried out on a seven-phase permanent magnet synchronous machine (PMSM) with a high total harmonic distortion (THD = 38%) of NS-EMFs. A demonstration video is provided with this paper.

More degrees of freedom not only enable multiphase drives to be fault-tolerant but also allow non-sinusoidal electromotive forces (NS-EMFs) in high-quality vector control. NS-EMFs lead to lower costs of design and manufacturing of electrical machines. However, the presence of multi-harmonics in NS-EMFs possibly generates pulsating torque in both healthy and faulty conditions of multiphase drives. To facilitate the use of NS-EMFs, this two-part study proposes control schemes to adaptively improve torque quality of multiphase drives in dealing with multi-harmonics of NS-EMFs. The proposed schemes are based on a simple but effective type of artificial intelligence, Adaptive Linear Neuron (Adaline). The knowledge of multiphase drives including the harmonic ranks of NS-EMFs and the rotor position is exploited to design the online-trained optimal Adalines. The first part of this study is to propose a control scheme using an Adaline for healthy mode with high-quality torque regardless of numerous harmonics in NS-EMFs. The second part of this study introduces a control scheme using another Adaline for open-circuit faults. The proposed schemes are numerically and experimentally validated on a seven-phase permanent magnet synchronous machine (PMSM) possessing a high total harmonic distortion (THD=38%) of NS-EMFs. A demonstration video is provided with this paper.

In the context of future Permanent Magnet Synchronous Machines (PMSMs) with a high number of phases (>7) in integrated drives, this paper proposes several control strategies when multiphase PMSMs with non-sinusoidal back electromotive forces (back-EMFs) operate in healthy and open-circuit faults. In all operation modes, the considered constraint on current is related to the maximum root mean square (RMS) current allowable in one phase of the machine. The constraint on voltage limits the maximum peak value of the phase voltage determined by the DC-bus voltage of the converter. When one or two phases are open-circuited, to maximize torque and respect the constraints, new current references obtained by several proposed methods in rotating and natural frames are imposed to the machine. Due to the non-sinusoidal waveform of back-EMFs and the considered constraints, numerical computations based on analytical formulations are required to obtain maximal torque-speed characteristics, including the flux-weakening operation. The usefulness of the proposed strategies is verified by numerical and experimental results.

This paper proposes several easy-to-implement control strategies when seven-phase axial flux brushless DC machines with trapezoidal back electromotive forces operate in normal and faulty modes by taking into account constraints on voltage and current. The constraints are related to the converter and machine design in terms of maximum values of current and voltage. The considered faults are cases in which one or two phases of the machine are open-circuited. Numerical computations based on analytical formulations are applied to obtain torque-speed characteristics, including the flux-weakening operation. The methods determine current references to ensure the torque optimizations while currents and voltages are within their limits. The usefulness of the methods is verified by numerical results.

This paper proposes a strategy using new transformation matrices to calculate new current references when a non-sinusoidal seven-phase permanent magnet synchronous machine (PMSM) has an open-circuited phase. The new current references allow to obtain a smooth torque with similar copper losses in the remaining healthy phases even when the back electromotive force (back-EMF) is non-sinusoidal. A real-time current learning process using an adaptive linear neural network (Adaline) is applied to extract from measured currents useful harmonic components in torque generation. It improves torque quality, especially at high speed, even when standard proportional-integral (PI) controllers are applied. In addition, similar copper losses in the remaining phases with the new current references can avoid overheating of windings. The effectiveness of the proposed control strategy is validated by numerical results.

This paper is to propose a control scheme, a combination of the classical field-oriented control (FOC) technique and artificial intelligence (AI), to obtain constant torques in multiphase non-sinusoidal permanent magnet synchronous machine (PMSM) drives. Higher torque density, easier fabrication, and lower costs are several advantages of non-sinusoidal back electromotive force (back-EMF) machines over sinusoidal ones. However, multi-harmonics existing in back-EMFs possibly generate torque ripples, reducing torque quality of the drive. Therefore, in this paper, an adaptive linear neuron (ADALINE), a simple type of AI, is combined with the classical FOC technique to eliminate these torque ripples. The proposed control scheme is validated by numerical results with a seven-phase PMSM. In addition, these results are compared with an existing strategy to prove its effectiveness.

This study is to deal with unwanted current harmonics in rotating (d-q) frames of a 7-phase non-sinusoidal permanent magnet synchronous machine (PMSM) in a wye-connected winding topology. The machine is supplied by a 7-leg voltage source inverter (VSI) fed by a DC-bus voltage. In control, cur-rent responses are expected to properly track their references. However, several unwanted harmonics of the non-sinusoidal back electromotive force (back-EMF) and the inverter nonlinearity generate unwanted harmonic com-ponents in d-q currents. These current harmonics cannot be nullified by con-trollers such as conventional proportional-integral (PI) controllers. Conse-quently, the current responses cannot track their references. In this study, a combination of conventional PI controllers and simple adaptive linear neu-rons (ADALINEs) is proposed to eliminate these current harmonics, improv-ing current control quality of the drive. The effectiveness of the proposed control structure is verified by experimental results.

This study aims at eliminating unwanted harmonics in current control of a five-phase non-sinusoidal permanent magnet synchronous machine (PMSM) in an open-end winding configuration. The machine is supplied by two voltage source inverters (VSIs) using a single DC-bus voltage. High-frequency harmonics, caused by the zero-sequence current with the inverter switching frequency, have been significantly reduced by using a proper pulse width modulation (PWM) strategy. Meanwhile, low-frequency current harmonics are generated by unwanted harmonics of the back electromotive force (back-EMF) and by the inverter nonlinearity. In this study, the low-frequency current harmonics are nullified by simple adaptive linear neural networks (ADALINEs) in rotor reference frames combined with the back-EMF compensation. As a result, the quality of current control is improved. The effectiveness of the proposed strategies is verified by numerical results.

Torque density is usually improved by injecting the third current harmonic for five-phase permanent magnet synchronous machine (PMSM). It increases the degrees of freedom of a multiphase drive. However, it also separates the current limitations of the motor and the transistors, respectively related to the RMS and peak values of the currents. These two constraints are represented by Maximum Torque Per Ampere (MTPA) strategy and Maximum Torque Per Peak Current (MTPPC) strategy. In this paper, these two strategies are studied and analyzed in order to optimize the generated torque with injection of the third current harmonic. Torque improvement principal and the optimizing algorithm considering two constraints are illustrated. Then, the analytical results of these two strategies are compared and discussed. It is shown that injecting the third current harmonic can improve the torque especially at flux-weakening region. Besides, compared with MTPA, MTPPC could produce higher torque for the same inverter current limit.

This paper presents new fault-tolerant control strategies for field-oriented control of 7-phase non-sinusoidal permanent magnet (PM) machines supplied by voltage source inverters (VSI). Single phase open-circuit fault is considered. The proposed strategies aim at finding waveforms of current references in natural frame in the way that post-fault currents create the same rotational magnetomotive force (MMF) as in healthy mode. Therefore, in the faulty mode, average torque can be maintained if no current limits are set. The proposed strategies are validated and compared to a previous strategy by numerical results in terms of joule losses, maximum RMS and peak phase currents, maximum phase voltage as well as their controllability with PI controllers.

This paper presents the modeling and control of an Electric Vehicle (EV) driven by a 5-phase Permanent Magnet Synchronous Machine (PMSM). The machine in an open-end winding configuration is supplied by two isolated 5-leg Voltage Source Inverters (VSIs). The inverters are fed by a Hybrid Energy Storage System (HESS) consisting of a battery and Supercapacitors (SCs). To increase the battery lifetime, the SCs are used to provide the high-power requirement during driving operations. In addition, an Energy Management Strategy (EMS) is proposed to take advantages of this EV architecture. Numerical results are derived to verify workability of the EV system.

Compared to sinusoidal machines, a bi-harmonic machine (with only two harmonics of similar value in the electromotive force spectrum) can develop torque of comparable values under three kinds of supply: with only first or both first and third sinusoidal currents. Therefore, more degrees of freedom for the control of the machine can be achieved. In this paper, the specificities of 7-phase bi-harmonic permanent magnet synchronous machine (PMSM) are investigated under different control strategies, such as maximum torque per ampere (MTPA) at low speed and fluxweakening strategies at high speed, both in healthy and faulty operation modes. The fault with one open-circuited phase are taken into account. The current references are calculated in order to maximize the output torque under the constraint on both voltage and current. The performances of the considered machine is validated by numerical results.

This paper studies control strategies using modified transformation matrices when five-phase machines operate in oneopen-phase faults. The basic idea of these methods is to maintain the rotating field under asymmetrical conditions as the same as in healthy condition by determining new transformation matrices. The dimension of the new matrices is equal to the number of remaining healthy phases in post-fault conditions. There have been different ways to determine the new transformation matrices applied for different types of five-phase machines in recent decades. In this study, an overview and analyses on these methods will be presented. In addition, advantages and drawbacks of these control strategies are clarified by numerical results.

This paper presents a novel 7-phase hybrid excitation permanent magnet (HEPM) machine with three rotors around one stator. Two rotors with PMs axially magnetized and the third rotor with PMs radially magnetized. Thanks to the addition of the third rotor, the inactive end-windings in the configuration with two rotors are then becoming active with a contribution to the torque with an increase of 30%. The impact of the third rotor on the torque density and on the pulsating torques is presented. The fault-tolerant characteristics of the proposed machine are also presented, which proves the interests of this machine for low speed applications.

This paper deals with control strategies when a seven-phase axial-flux brushless DC machine operates in one open-circuited phase fault by considering constraints on voltage and current. The constraints are related to the converter and machine design in terms of maximum values of voltage and current. In addition, the sensitivity of the torque control on parameters of new imposed current references under the base speed and in the flux-weakening region is analyzed. The current references taking into account only first and third harmonics in healthy phases are proposed to ensure the torque optimization while phase currents and voltages are within their limits. The usefulness of the control strategies and the parameter analyses are verified by numerical results.

The electrification of transportation has been considered as one of solutions to tackle the shortage of fossil energy sources and air pollution. Electric drives for electrified vehicles, including pure electric and hybrid electric vehicles, need to fulfil some specific requirements from automotive markets such as high efficiency, high volume power and torque densities, low-cost but safe-to-touch, high functional reliability, high torque quality, and flux-weakening control. In this context, multiphase permanent magnet synchronous machine (PMSM) drives have become suitable candidates to meet the above requirements. The main objective of this doctoral thesis is to propose and refine fault-tolerant control strategies for non-sinusoidal multiphase PMSM drives that require less constraints on their design. In addition, constraints on current and voltage defined by the inverter and the machine are considered to optimize the machine control under the non-sinusoidal condition without exceeding their allowable limits. Therefore, the system sizing is guaranteed, especially in flux-weakening operations. The proposed fault-tolerant control strategies, based on the mathematical model of multiphase drives, enrich the control field of multiphase drives by providing various control options. The selection of one of the proposed control options can be a trade-off between a high quality torque but a low average value and a high average torque but a relatively high ripple. The control and torque performances of the drives can be refined by using artificial intelligence with a simple type of artificial neural networks named ADALINE (ADAptive LInear NEuron). With self-learning ability, fast convergence, and simplicity, ADALINEs can be applied to industrial multiphase drives. All proposed control strategies in this doctoral thesis are validated with an experimental seven-phase PMSM drive. The non-sinusoidal back electromotive force (back-EMF) of the experimental seven-phase PMSM is complex with the presence of multi-harmonics. Experimental results verify the effectiveness of the proposed strategies, and their applicability in a multiphase machine with a complex non-sinusoidal back-EMF.