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This paper investigates a finite-control set model-predictive control (FCS-MPC) algorithm to enhance the performance of a synchronous reluctance machine drive. Particular emphasis is placed on the definition of the cost function enabling a computationally light implementation while targeting good transient and steady-state performance. In particular, this work proposes the inclusion of an integral term into the cost function to ensure zero steady-state errors thus compensating for any model inaccuracies. A control effort term is also considered in the formulation of the cost function to achieve a high ratio between the sampling frequency and the average switching frequency. After a comprehensive simulation study showing the advantages of the proposed approach over the conventional FCS-MPC for a wide range of operating conditions, several experimental test results are reported. The effectiveness of the proposed control approach, including a detailed analysis of the effect of the load and speed variations, is thus fully verified providing useful guidelines for the design of a direct model predictive controller of synchronous reluctance motor drives. acceptedVersion

This article investigates the dc-link voltage control of an active rectifier that is supplied by a variable speed permanent magnet synchronous generator. This configuration is commonly encountered in gearless wind energy conversion systems as well as in variable speed generating units. The proposed control strategy uses an optimal voltage vector based modulated model predictive control (MPC) to achieve direct power control. The studied scheme combines the advantages of finite control set MPC and control techniques that use pulsewidth modulator. The fast dynamics of the former are obtained during large transients, and the constant switching frequency operation, of the latter, is ensured in steady state. At each sampling instant, all the switching states are evaluated and the two adjacent states that give minimum error in the controlled variables are selected. The duty cycle of each of these vectors is computed through linear combination and appropriately limited for overmodulation. Simulations and cosimulation results presented in this article show interesting results. The control strategy has been developed on a field-programmable gate array control platform and experimental results at steady state are shown, with the aim to demonstrate the computational feasibility of the control strategy.

© 2013 IEEE. Finite-set model-predictive control (FS-MPC) has many advantages, such as a fast dynamic response and an intuitive implementation. For these reasons, it has been thoroughly researched during the last decade. However, the waveform produced by FS-MPC has a switching component whose spread spectrum remains a major disadvantage of the strategy. This paper discusses a modulated model-predictive control that guarantees a spectrum switching frequency in the linear modulation range and extends its optimized response to the overmodulation region. Due to the equivalent high gain of the predictive control and to the limit on the voltage actuation of the power converter, it is expected that the actuation voltage will enter the overmodulation region during the large reference changes or in response to load impacts. An optimized overmodulation strategy that converges toward the FS-MPC 's response for large tracking errors is proposed for this situation. This technique seamlessly combines PWM's good steady-state switching performance with FS-MPC 's high dynamic response during large transients. The constant switching frequency is achieved by incorporating modulation of the predicted current vectors in the model-predictive control of the currents in a similar fashion as the conventional space-vector pulsewidth modulation is used to synthesize an arbitrary voltage reference. Experimental results showing the proposed strategy's good steady-state switching performance, its FS-MPC -like transient response, and the seamless transition between modes of operation are presented for a permanent magnet synchronous machine drive.

This paper presents a finite control set model predictive control (FCS-MPC) method that improves the performance of a synchronous reluctance machine drive. As shown, when a high sampling-to-switching frequency ratio is used with FCS-MPC, the stator current distortions can be significantly reduced, allowing for less losses in the machine. Moreover, the FCS-MPC steady-state performance is enhanced by introducing an integrating element into the cost function to ensure accurate output reference tracking. Finally, the adopted drive model that relies on an identified accurate magnetic model of the machine further improves the robustness of the discussed control scheme. The presented simulation and preliminary experimental results verify the effectiveness of the discussed method. acceptedVersion

This paper proposes a sensorless cascaded model predictive control strategy applied to a doubly-fed induction machine. This technique is based on an improved stator flux estimator, and an extended Kalman filter to control encoder-less and independently the electromagnetic torque and the reactive power of the machine. The purpose of employing a model predictive-based control, is to achieve fast dynamic response and upgrading it with a modulation stage to mitigate the control variables ripple. The introduced control technique might be considered for adjustable speed application such as wind energy conversion systems.

Under the concept of transportation electrification, more electric aircraft (MEA) involves more electrical energy to reduce emissions. Phase-looked loops (PLLs) have been well developed for synchronizing different power sources in a grid. Since MEA operates at variable frequency from 360 Hz to 800 Hz, a third-order model based steady-state linear Kalman filter PLL (SSLKF-PLL) has been proposed in literature to achieve fast tracking performance during such grid frequency variations. To suppress the potential disturbances due to harmonics in the grid, sensor scaling errors/unbalances and d.c offsets while maintaining low computational burden, this paper aims to enhance the disturbance rejection ability of SSLKF-PLL by adding a repetitive observer (RO). Simulation tests show that RO allows stable and effective suppression of disturbances from all above-mentioned sources during variable frequency operation.

This article presents a direct power control method based on modulated model predictive control for a doubly fed induction machine. The modulated predictive control algorithm constructs an optimal voltage vector from two inverter states that give a minimum absolute error in the active and reactive power. This article focuses on the effects of magnetic saturation and its impact on the accuracy of computed reactive power when the stator current sensors are not installed. To reduce the impact of magnetic saturation on reactive power computation, the machine’s magnetizing characteristic is identified through a self-commissioning scheme introduced in this article. The identified magnetizing curve is utilized to construct a full-state stator flux observer, which is used to accurately estimate stator currents that appear in the reactive power equation. Experimental results are presented to demonstrate the accuracy of the reactive power computation in the absence of stator current sensors while conserving the rapid transient response offered by a modulated predictive control strategy for active and reactive power regulation.

The synchronization between the power grid and distributed power sources is a crucial issue in the concept of smart grids. For tracking the real-time frequency and phase of three-phase grids, phase-locked loop (PLL) technology is commonly used. Many existing PLLs with enhanced disturbance/harmonic rejection capabilities, either fail to maintain fast response or are not adaptive to grid frequency variations or have high computational complexity. This article, therefore, proposes a low computational burden repetitive controller (RC) assisted PLL (RCA-PLL) that is not only effective on harmonic rejection but also has remarkable steady-state performance while maintaining fast dynamic. Moreover, the proposed PLL is adaptive to variable frequency conditions and can self-learn the harmonics to be canceled. The disturbance/harmonic rejection capabilities together with dynamic and steady-state performances of the RCA-PLL have been highlighted in this article. The proposed approach is also experimentally compared to the synchronous rotation frame PLL (SRF-PLL) and the steady-state linear Kalman filter PLL (SSLKF-PLL), considering the effect of harmonics from the grid-connected converters, unbalances, sensor scaling errors, dc offsets, grid frequency variations, and phase jumps. The computational burden of the RCA-PLL is also minimized, achieving an experimental execution time of only $12~\mu \text{s}$ .

Sequential model predictive control is a recent innovation in the high-performance control of electric drives. The elimination of weighting factors and associated tuning work is among the biggest advantages of this MPC implementation. The cost function evaluation takes place in two steps with each step narrowing down the choice of optimal voltage vector to be applied at the next switching instant. Like the conventional finite control states MPC, the sequential MPC also has a disadvantage of variable switching frequency. In this paper, this problem is addressed by considering the sequential MPC implementation with a modulator. After two-step cost function evaluation, the optimal and second optimal voltage vectors’ duty cycles are computed based on the slope of the controlled variables. This preserves the optimality of the solution while, at the same time, guaranteeing constant switching frequency and reduced current and torque ripples in the drive response.

A lad-used servo permanent magnet synchronous motor has been accidentally damaged due to overcurrent. On the one hand, the mechanical damage, in the end, bearing and break part generates acoustic noise even when rotating the shaft by hand. On the other hand, the back electromotive force of the motor becomes unbalanced and exceedingly high torque ripple is produced. Such torque ripple results in intolerable speed ripple and will increase the acoustic noise. This article aims to reuse this damaged motor by adding a repetitive observer (RO) to the existing speed loop, both the speed control performance and the acoustic noise of the damaged motor can become comparable with its healthy version. The RO is functionally the same as a repetitive controller (RC), but the stability of the RO is independent of the feedback loop, while the stability of the RC will affect and be affected by the rest of the system. Therefore, RO can be applied for both the healthy motor and the damaged motor. This work opens the possibility of further enhancing the fault tolerance ability of a healthy motor or even reusing a damaged motor and still achieve high performance.

The paper deals with a newly developed sequential model predictive control strategy for the high-performance control of electric drives. The sequential nature of cost function evaluation allows to eliminate weighting factors whose tuning is not straightforward. In the first cost function evaluation, torque (or flux) error is minimized and, the second evaluation minimizes the flux (or torque) error. The first optimization generates two optimal voltage vectors that give minimum error for the controlled variable and the second optimization tests only the selected two vectors to find the global optimal. In this paper, a detailed analysis of the sequential MPC is carried out with a focus on the inversion of sequence of optimization with respect to the original algorithm. The paper also analyses the effect of selecting more than two vectors from the first evaluation and explains to the reader why some numbers of selected vectors produce flux and torque distortions while others do not control flux and torque at all

This paper presents a validation of the novel motor-shaped rotational inductor. To validate the concept, 12 slots 2 poles rotational inductor is tested at different supply frequencies and rotor speeds. Experimental results have shown that the iron losses reduce as the rotor speed increases to the synchronous speed of the stator supply. The performance of the integrated rotational inductor is also compared with traditional EE core inductor in terms of total losses, synchronous inductance, copper resistance, and total harmonic distortion (THD). The total loss-to inductance ratio of the rotational inductor is reduced by 22.5% when rotor is rotating at 18 kRPM and supply frequency is held at 300 Hz. A significant reduction in copper resistance-to-inductance is also noticed when supply frequency is varied from 0 Hz to 20 kHz. Furthermore, the synchronous inductance and voltage and current's %THD of rotational inductor is found to be superior to EE core inductor.

The compensation of converters’ nonlinear voltage error is crucial in encoder-less control of ac motor drives. In this paper, a new self-commissioning and compensation method is proposed for matrix converters (MC). Similar to what done in the past for voltage source inverters, the MC voltage error is identified before the drive start and stored in a look-up table (LUT), later used for error compensation and accurate voltage estimate. Different from what observed in the past, the effect of parasitic capacitors on nonlinear voltage error of MCs in four-step current based commutation is observed and studied. Eventually, this method is applied to the sensorless control of a synchronous reluctance (SyR) motor drive, using the direct flux vector control (DFVC) concept. Experimental results are presented to validate the effectiveness of proposed self-commissioning in improving the performance of sensorless control at standstill and low speed.

In high-performance control of ac machines through variable frequency drives, the knowledge of machine parameters plays a decisive role. The accuracy with which machine parameters can be known is directly related to the time and effort put during the testing and commissioning process. In the ever-demanding industrial environments, the time spent on parameter identification translates into loss of production. To reduce commissioning times, research in this direction has focused on automatizing the identification procedure without loss of accuracy. This paper reviews different lines of research adopted over the past few decades for machine parameter identification. Parameter estimation of ac machines is considered because of their widespread applications from servomechanisms to traction to aviation. The surveyed works include self-commissioning schemes that have become an integral part and a salient feature of modern electric drives. This feature enables the drives to automatically identify machine parameters and tune the control loops.

Model predictive control (MPC) presents important advantages in the control of the power converter and drives such as, fast dynamic response and capability to include nonlinear constrains. These have positioned MPC as a powerful and realistic control strategy, however, it also has disadvantages such as variable switching frequency and parameter sensitivity. This paper applied a modulated model predictive speed control that guarantees a fix switching frequency and, thanks to disturbance compensation, robustness to parameters variation. The strategy is validated and compared to finite set model predictive speed control through simulation results.

This paper investigates the DC-link voltage control of an active rectifier that is supplied by a variable speed permanent magnet synchronous generator. This configuration is commonly encountered in gearless wind energy conversion systems as well as in variable speed generating units. The proposed control strategy uses an optimal voltage vector based modulated model predictive control to achieve direct power control. The studied scheme combines the advantages of finite control set Model Predictive Control (MPC) and control techniques that use pulse width modulator. The fast dynamics of the former are obtained during large transients and constant switching frequency operation, of the latter, is ensured in steady state. At each sampling instant, all switching states are evaluated and the two adjacent states that give minimum error in the controlled variables are selected. The duty-cycle of each of these vectors is computed through linear combination and appropriately limited for over-modulation. Simulations and Co-simulation results presented in the paper show interesting results. The control strategy has been developed on an FPGA control platform and experimental results at steady state are shown, which guarantee the computational feasibility of the control strategy.

This paper proposes a new method for online identification of stator winding temperature for an open-end winding (OEW) permanent magnet synchronous motor (PMSM). The method exploits the zero sequence current (ZSC) due to the third harmonic back electromotive force (EMF) circulating in the system in order to estimate the phase resistance, which, in turn, is used to derive the winding temperature. In order to do this a proposed idea of maximum zero sequence current amplitude along with the actual ZSC amplitude and the electrical speed of the motor is used. The temperature is estimated without any additional sensors in a wide operating speed range. A single synchronous phase-locked loop (PLL) is utilised in order to obtain the required parameters. The independence of the rotor position grants the possibility for the exploitation of the proposed winding temperature estimation method in a variety of control techniques including the sensorless control to increase the robustness of the overall system.

While power networks evolve towards the new concept of smart grids, with the proliferation of power electronics embedded systems and distributed generation, the insurgence of system unbalance and voltage harmonic distortion, become more and more frequent. Also, often a noisy voltage sampling system can produce offsets in measurements. Such imperfections bring challenges to the phase identification using a traditional phase-lock loop (PLL), utilized in the control of all grid connected converters. However, since the imperfections lead to periodic harmonics in the corresponding dq-axis voltages, the repetitive controller (RC) can be useful for harmonic suppression. This paper presents a three-phase PLL using a feed-back RC. Specially, a novel running mean filter has been added to minimize the interaction between RC and the Proportional-Integral (PI) controller in the PLL. Simulation results show that the proposed PLL can track the phase of the three-phase voltage without being influenced by harmonic distortion.

Voltage source inverters with LC output filters are widely used for high-quality output of ac power supplies. They are also a potential solution for embedded electrical networks in more-electrical aircraft of the future. In this paper, a recently developed model predictive control technique that selects modulated optimal voltage vector is applied for high dynamic output voltage control of these systems especially when the required output frequency is well above the standard 50/60 Hz as required by aerospace applications. The studied predictive control optimizes the switch duty cycles when in linear regulation range by solving analytical equations. The over-modulation region is covered by optimized linear combination of the adjacent hexagon vertices unlike how it happens in classical space vector modulation. A load current observer is also designed in this paper which is made independent of output frequency for improving the disturbance rejection capability of the voltage control loop when the load current sensors are not present. Simulation and experimental results that validate the control and observer performance are presented under different steady state and dynamic operating conditions.

This paper proposes a new closed-loop control strategy which improves the quality of the torque output of an open-end winding (OEW) permanent magnet synchronous motor (PMSM) with common DC bus. Such a configuration provides a path for the zero sequence currents (ZSC) to flow in the windings. The analysis of the system revealed that these currents result in electromagnetic torque oscillation. It has also been established that the zero sequence currents are caused mainly by the third harmonic component of the back electromotive force (EMF). The research and a thorough analysis of the OEW PMSM showed that the existing methods of minimising the torque ripple cannot be applied when the leakage inductance of a machine is small, because the zero sequence component can no longer be considered as one additional degree of freedom that can be managed. Therefore, a new control strategy presented in this paper was proposed. The strategy is validated in simulation.

The paper presents an automatic parameter identification procedure for linear permanent magnet synchronous motors. The electrical parameters of a test machine are estimated by identification tests performed through the inverter. The method employs the available feedback signals that are needed by the control. The stator resistance and machine inductances are estimated through signal injection at standstill. The permanent magnets' flux-linkage identification instead requires carriage movement. Subsequently, the inverter nonlinearity characteristics are identified, again at standstill, through a flux-observer. The proposed self-commissioning process requires only the nameplate data of the machine and no datasheet information of the power electronic devices is needed. The developed techniques can be used both with and without a position sensor. The complete process is automatic and safe to run on its own and requires least intervention from the operator.

A model predictive control scheme for multiphase induction machines, configured as multi-three-phase structures, is proposed in this paper. The predictive algorithm uses a direct flux vector control scheme based on a multi-three-phase approach, where each three-phase winding set is independently controlled. In this way, the fault-tolerant behavior of the drive system is improved. The proposed solution has been tested with a multimodular power converter feeding a six-phase asymmetrical induction machine (10 kW, 6000 r/min). Complete details about the predictive control scheme and adopted flux observer are included. The experimental validation in both generation and motoring modes is reported, including open-winding postfault operations. The experimental results demonstrate full drive controllability, including deep flux-weakening operation.

In this paper, an optimal voltage vector based model predictive control strategy is investigated for the direct power control of a doubly fed induction machine. The model predictive control computes optimal voltage vector that minimizes the error in active and reactive power. The computed voltage vector, if within the linear regulation range, is passed onto a modulator to be applied in the next sampling instant. In the over-modulation range the voltage vector is linearly scaled down, before modulation, to maintain optimality. The paper also focuses on the saturation of main flux inside an induction machine and its impact on reactive power control when stator current sensors are not installed. The machine's saturation characteristic is fully utilized to realize full-state stator flux observer that is used to estimate stator currents which give accurate prediction of reactive power. Consequently, stator current sensors can be excluded. Simulations and experimental analyses are conducted on a test machine to verify fast dynamics of predictive control and the estimation accuracy of stator current.

This paper presents a sensorless control technique based on direct flux vector control (DFVC) method for synchronous reluctance (SyR) motor drives fed by a three-phase to three-phase matrix converter (MC). Rotor position is estimated based on active flux (AF) concept down to 50 [rpm]. Furthermore, the effect of nonlinear voltage errors of the MC is compensated, and a self-commissioning method capable of identifying the voltage error before compensation is presented and tested. The proposed drive combines the advantages of matrix converters and SyR motors in sensorless fashion, for application into a number of fields, spanning from compact drives for aviation to line-supplied drives for industry applications. Experimental results are provided to prove the feasibility of the proposed technique.

The study presents the direct flux and current vector control of an induction motor (IM) drive, which is a relatively newer and promising control strategy, through the use of model predictive control (MPC) techniques. The results highlight that the fast flux control nature of direct flux control strategy is further enhanced by MPC. Predictive control is applied in two of its variants, namely the finite control set and modulated MPC, and the advantages and limitations of the two are underlined. This work also highlights, through experimental results, the importance of prioritising the flux part of the cost function which is particularly significant in the case of an IM drive. The performance of the MPC-based approach is compared with the proportional-integral controller, which also prioritises the flux control loop, under various operating regions of the drive such as in the flux-weakening regime. Simulations show the performance expected with different control strategies which is then verified through experiments.

This work presents a simple method for obtaining the main parameters, such as the torque constant and the d - and q -axis inductances $L_{d}$ and $L_{q}$ , for a brushless internal permanent magnet motor by measuring the machine torque during testing. These tests are relatively simple to carry out compared with other test procedures described in the literature, and they neither require sophisticated and expensive test equipment nor are they affected by temperature effects as happens with other techniques. The machine under test is supplied through a dc supply at different rotor positions. The shaft torque is measured through a torque sensor during the tests. The test current magnitude is varied to take care of the saturation effects. From the measured torque data and known rotor position, the required parameters can be obtained. Tests performed on two different internal permanent magnet machines confirm the validity and effectiveness of the proposed method.

The paper summarizes the basic theoretical aspects concerning the speed regulation of surface mounted permanent magnet synchronous motors. In particular, the influence of the synchronous inductance is articulated considering the limitations imposed by the supply (maximum voltage and current) and the constraints for a specific variable-speed application. The study is conventionally approached, using the well-known single-phase equivalent circuit and the related steady-state vector diagrams. The involved key machine parameters are then discussed in term of sizing equations in order to predict the speed regulation capability since the initial electromagnetic design stage.

In this paper, a fault assessment of a multiphase permanent magnet generator designed for ‘more electric engine’ aeronautic applications is presented. The distribution of various electrical faults occurring in three-phase machines that is available in the literature helped the authors to identify the most probable fault types. The six-phase machine under observation is tested under these faults both in Finite Element Analysis (FEA) as well as experimentally. In the experimental analysis, the generator supplies a resistive load through rectifier bridges when faults are introduced at its terminals. For a variety of fault situations, the measured machine response is compared with the finite element results in order to validate the accuracy of the implemented FEA model. The comparison show an extremely good match between simulated and measured results, without the need of particular fine-tuning of the model.

This paper proposes a testing method for the evaluation of the inverter dead-time voltage error and the related compensation schemes using a hardware-in-the loop converter topology. The inverter under test is operated as a voltage source that is connected with another twin inverter acting as a virtual load. The virtual load is operated as a current-controlled voltage source converter that draws specified currents having a desired amplitude and phase displacement respect to the voltages generated by the inverter under test. The two converters share the same DC link, so the power required for the test must cover only the total converter losses. This testing approach allows a complete analysis and assessment of dead-time compensation schemes for any operating conditions, such as modulation index, current value and power factor.

This paper presents a method for obtaining the main parameters, such as the torque constant and the d- and q-axis inductances Ld and Lq, for a brushless internal permanent magnet motor by measuring the machine torque during testing. These tests are relatively simple to carry out compared to other test procedures described in the literature and do not require sophisticated equipment. The machine under test is supplied through a dc supply at different rotor positions. The shaft torque is measured through a torque sensor during the tests. The test current is varied to take care of the saturation effects. From the measured torque data and known rotor position, the required parameters can be obtained. Tests performed on two different internal permanent magnet machines confirm the validity and effectiveness of the proposed technique.

In this paper, a loss-minimizing strategy is proposed for induction motor drives to ensure maximum efficiency operation for a given torque demand. The proposed strategy directly regulates the machine stator flux, according to the desired torque, using an optimal stator flux reference. Therefore, the proposed strategy is suitable for motor control schemes that are based on direct flux regulation, such as direct torque control or direct flux vector control. The maximum efficiency per torque (MEPT) stator flux map is computed offline using the traditional no-load and short-circuit test data. An iron loss model based on the stator flux and frequency is also proposed for the calibration of the machine loss model and also for online monitoring of the iron losses during motor operation. The proposed MEPT strategy has been validated on a 2.2-kW induction machine, and the motor efficiency has been measured for different speed values and variable load conditions. The experimental results confirm the effectiveness of the proposed solution.

This paper proposes a simple procedure for accurate identification of the magnetic model of permanent-magnet synchronous machines through inverter supply. The proposed method accounts for the magnetic saturation and the cross-saturation effects. The identification methods reported in the literature may require a servomotor to drive the motor under test at controlled constant speed or the motor itself must accelerate and decelerate. The technique proposed here can be applied at standstill with or without rotor locking and uses a dc+ac injection strategy to identify the machine inductances to construct its magnetic model. The direct current sets the operating point, whereas the superimposed ac component estimates the inductance at that particular point. Small ac signal is injected to ensure local linearity of the magnetic characteristic. Saturation effects are automatically accounted for by the dc bias level, and cross-saturation effects are quantified through maintaining a constant current along the cross-axis. The magnetic model thus obtained can be used for optimal control of the machine and for accurate torque estimation in vector-controlled drives.

In this paper, a magnetizing characteristic identification method for an induction machine at standstill is proposed. The technique is based on machine testing with a single-phase ac supply generated through a standard inverter. This type of test strategy is available in the literature, however, it has been used for parameter identification at a single current level thus ignoring the effects of magnetic saturation. To reproduce accurately the magnetizing curve, the test current level must be varied in order to trace the entire curve. The method presented here takes care of the magnetic saturation and estimates the magnetizing curve for complete current range of the machine. The proposed scheme does not require any external supply, measurement or data acquisition system and works at standstill thus avoiding the need to isolate the machine from its load or to block the rotor. This strategy is suitable for self-commissioning of induction motor drives and for sensorless control applications as well.

Parameter identification of permanent magnet synchronous machines is a topic of utmost interest these days. The growing effort and investment in this field of research is largely due to the ever-expanding market share of these machines. The high-performance and efficient control of the drive depends on the accuracy with which the information about the machine connected to its terminals is available. The available identification methods are surveyed here and they are classified into offline and online strategies. Self-commissioning, in principle, is a subset of offline methods, yet it is treated separately for its importance in modern adjustable speed drives that tend to minimize the user intervention. Fully exploiting the power electronic converter and the computational power on-board a modern drive, the self-commissioning feature can be embedded in the start-up routine of the drive to estimate the parameters of the machine at hand. This paper presents a review of the parameter identification techniques and schemes investigated over the past few decades.

Multilevel inverters produce an output voltage with superior quality compared to the voltage obtained by two-level converters. They are controlled with pulse width modulation (PWM) methods and have a limited switching frequency due to semiconductor devices switching losses. This paper presents the implementation for multilevel converters of two generated PWM methods that were previously proposed for two level converters. The considered methods, sinusoidal carrier regulated by the slope of a trapezoidal waveform PWM (SLPWM) and frequency modulated triangular carrier PWM (HIPWM-FMTC), control the output voltage spectrum while keeping the number of commutations low for a given fundamental frequency.

The knowledge of electrical and mechanical parameters of high-performance electromechanical drive systems is of paramount importance for designing high-performance controllers and/or developing accurate simulation models. By high-performance control is meant least torque (position) ripple for torque (position) control. Machine parameters are typically load and temperature dependent. This makes their estimation a challenging task. In this paper, a simple and robust method for parameter estimation at rotor standstill is presented. The estimated parameters are stator resistance through dc test, dq inductances using high-frequency injection and permanent magnet flux by means of a closed-loop speed control maintaining rotor stationary. The proposed method does not require either locking the rotor or additional/special power supplies. The validity of the suggested method has been verified by implementation on Interior Permanent Magnet Synchronous Motors (IPMSMs). Finally, the estimated parameters have been compared against results obtained through finite element simulations and with machine magnetic characterization, separately performed, to validate the method's effectiveness. Saturation and cross-saturation effects are taken care of through amplitude modulation and cross-axis current application, respectively.

This paper proposes a simple procedure for accurate identification of the magnetic model of permanent-magnet synchronous machines through inverter supply. The proposed method accounts for the magnetic saturation and the cross-saturation effects. The identification methods reported in the literature may require a servomotor to drive the motor under test at controlled constant speed or the motor itself must accelerate and decelerate. The technique proposed here can be applied at standstill with or without rotor locking and uses a dc+ac injection strategy to identify the machine inductances to construct its magnetic model. The direct current sets the operating point, whereas the superimposed ac component estimates the inductance at that particular point. Small ac signal is injected to ensure local linearity of the magnetic characteristic. Saturation effects are automatically accounted for by the dc bias level, and cross-saturation effects are quantified through maintaining a constant current along the cross-axis. The magnetic model thus obtained can be used for optimal control of the machine and for accurate torque estimation in vector-controlled drives.

This paper analyses the detuning effects of machine electrical parameters on the performance of unified direct flux vector control (UDFVC) of induction motor drives. Drive self-commissioning is discussed as a way to estimate parameters for better control performance and accurate torque estimation. The potential of the unification of direct flux and current vector control has been recognized for both synchronous and asynchronous AC motor drives in the literature. This control operates in (ds, qs) stator flux coordinates with the stator flux being directly controlled by the ds axis voltage vector component. Machine torque is controlled using a current controller in qs-axis. Results for the effects of parameter mismatch on control performance are given. In this work, the detuning problem is overcome by drive self-commissioning which estimates machine parameters at start up through special tests at standstill.

This paper deals with the Maximum Torque per Ampere (MTPA) operation of induction motor drives using Unified Direct Flux Vector Control (UDFVC). The UDFVC has been introduced in the past as a unified direct flux and vector control approach for both synchronous and asynchronous AC motor drives. The control is implemented in stator flux coordinates with the stator flux being directly controlled by the ds-axis voltage component, while the machine torque is controlled through qs-axis current component regulation using the qs-axis voltage component. The stator flux amplitude is generated using only the torque demand as the input of an MTPA profile that is particular for the AC machine being controlled, without the need of other complex LUTs and motor mapping. In this way, the optimal machine exploitation is reduced to a proper stator flux reference computation that can be done offline using the data from the standard no-load and short-circuit tests. The effectiveness of the proposed solution is verified through intensive experimental tests conducted with a 2.2 kW induction machine. The steady-state MTPA operation, the drive efficiency performance and the transient drive performance are presented.