Direct Flux Vector Control of Synchronous Motor Drives: A Small-Signal Model for Optimal Reference Generation

A novel Direct Flux Vector Control (DFVC) scheme is presented based on the real-time use of the motor small-signal model for optimal reference generation without pre-processed look-up tables (LUTs). The control scheme is valid for Reluctance- and PM-Synchronous machines. The stator flux magnitude and the load angle are the controlled variables and the optimal reference values respecting maximum torque per ampere (MTPA), maximum torque per volts (MTPV), voltage and current limit conditions are computed in real-time from the small-signal model. Analytical expressions of MTPA and MTPV criteria are derived to enable online adaptation according to the small-signal approximation of the motor model. The motor parameters reside in the flux-map LUTs used in the flux observer; besides that, no additional tables are necessary. Furthermore, online parameter adaptation is proposed to further improve torque tracking accuracy against flux-map LUTs errors. The feasibility of proposed scheme is demonstrated through experiments on a 1.1. kW synchronous reluctance (SyR) machine test-bench. The proposed control scheme simplifies the implementation and calibration of the DFVC, while improving its MTPV control and its roughness against model parameter errors. Prospective fields of application are spindle and traction drives

Torque ripple minimization in non-sinusoidal synchronous reluctance motors based on artificial neural networks

This paper proposes a new method based on Artificial Neural Networks for reducing the torque ripple in a non-sinusoidal Synchronous Reluctance Motor. The Lagrange optimization method is used to solve the problem of calculating optimal currents in the d-q frame. A neural control scheme is then proposed as an adaptive solution to derive the optimal stator currents giving a constant electromagnetic torque and minimizing the ohmic losses. Thanks to the online learning capacity of neural networks, the optimal currents can be obtained online in real time. With this neural control, each machine’s parameters estimation errors and current controller errors can be compensated. Simulation and experimental results are presented which confirm the validity of the proposed method.Bourse de l'Ambassade de France au Vietna

Predictive Stator Flux and Load Angle Control of Synchronous Reluctance Motor Drives Operating in a Wide Speed Range

This paper presents a new simplified finitecontrol- set model predictive control strategy for synchronous reluctance motors operating in the entire speed range. It is a predictive control scheme that regulates the stator flux and the load angle of the synchronous reluctance motor, incorporating the ability to operate the drive in the field-weakening region and respecting the motor voltage and current limits as well as the load angle limitation needed to operate this type of motor in the maximum torque per voltage region. The proposed control strategy possesses some attractive features, such as no need for controller calibration, no weighting factors in the cost function, good robustness against parameter mismatch, and smaller computational cost compared to more traditional finite-control-set model predictive control algorithms. Simulation and experimental results obtained using a high-efficiency synchronous reluctance motor demonstrate the effectiveness of the proposed control scheme.info:eu-repo/semantics/publishedVersio

Sensorless Direct Flux Vector Control of Synchronous Reluctance Motors Including Standstill, MTPA and Flux Weakening

This paper proposes a sensorless direct flux vector control scheme for synchronous reluctance motor drives. Torque is controlled at constant switching frequency, via the closed loop regulation of the stator flux linkage vector and of the current component in quadrature with it, using the stator flux oriented reference frame. A hybrid flux and position observer combines back-electromotive force integration with pulsating voltage injection around zero speed. Around zero speed, the position observer takes advantage of injected pulsating voltage. Instead of the commonly used current demodulation, the position error feedback is extracted here at the output of the observer’s flux maps, thus resulting in immunity towards the cross-saturation position error. The Maximum Torque per Ampere (MTPA) strategy is used. A detailed analysis puts in evidence the key advantages and disadvantages related to the use of the MTPA in the sensorless control of the Synchronous Reluctance machine, for both the saliency based and the back-EMF based sensorless methods. Extensive experimental results are reported for a 2.2 kW synchronous reluctance motor prototype, showing the feasibility of the proposed method. These include speed response to step and sinusoidal load disturbances at standstill, up to 121% of rated torque, and speed response tests covering the flux weakening speed region

Contribution to the Synchronous Reluctance Machine Performance Improvement by Design Optimization and Current Harmonics Injection

This thesis is dedicated to the evaluation and the improvement of the synchronous reluctance machine’s performance for variable speed drive applications in general and for automotive applications in particular. The two axes of development are machine design and phase current harmonics injection. The rotor is an important element in the machine design and particular emphasis is placed to the design and evaluation of the rotor for enhancing the machine performance. An analytical procedure is proposed for the rotor design. The rotor elements like the ribs and the bridges that maintain the rotor mechanically strong as well as the q-axis insulation ratio (air-to-steel ratio) are studied. A computer-aided design study based on a parametric optimization problem is presented as well. The main three families of the optimization algorithms are evaluated for the optimization procedure: a gradient-based algorithm (Quasi Newton Algorithm), a non-gradient based non-evolutionary algorithm (Nelder Mead Simplex) and a non-gradient based evolutionary algorithm (Genetic Algorithm). The machine designs based on the analytical procedure and the optimization procedure are both manufactured and tested on a bench. The second axis of study of the thesis is the injection of harmonics in the phase currents of the synchronous reluctance machine. The interaction of current harmonics with the spatial inductance harmonics is studied and formalized for an m-phase machine. Then, the harmonics injection concept is evaluated in the particular case of a 2-phase machine. This study shows the benefi t of harmonics injection in the reduction of the machine torque ripple. A synchronous reluctance machine design is fi nally developed for an automotive application based on parametric optimization of the stator and rotor. This design is evaluated for the electromagnetic specifi cations imposed by a mid-power electric vehicle traction applicatio