An Improved Model Free Predictive Current Control for PMSM with Current Prediction Error Variations

Funding Agency: Key Areas of Guangdong Province through the Project “Integration and Industrialization of High Performance, Long Endurance, and Integrated Electric Drive System” (Grant Number: 2019B090910001)Peer reviewedPublisher PD

Predictive Trajectory Control with Online MTPA Calculation and Minimization of the Inner Torque Ripple for Permanent-Magnet Synchronous Machines

This paper presents an extended predictive trajectory control scheme combined with an inner torque ripple minimization considering the current-, flux-linkage-, and voltage-planes of permanent magnet synchronous machines. The extension of a fundamental machine model with flux-linkage harmonics allows the calculation of the inner torque ripple and enables its minimization. For this, the control is divided in two cases: (1) The dynamic operation or large signal behavior which uses the maximal torque gradient for the trajectory strategy during each control period for fastest dynamic operation, and (2) The stationary operation or small signal behavior, utilizing a real time capable polynomial approximation of the rotor position dependent torque hyperbolas (iso-torque curves) of permanent magnet synchronous machines for the ideal torque to current reference values. Since dynamic and steady-state operation is covered, torque to current look-up tables, such as maximum torque per ampere (MTPA)/maximum torque per volt/voltage (MTPV) look-up tables, are not required anymore. The introduced, new control approach is implemented in Matlab/Simulink based on finite element analysis and measured data. Furthermore, test-bench implementations based on measurement data are presented to show the real-time capability and precision

Self-Commissioning of Inverter Nonlinear Effects in AC Drives

The paper presents a novel technique for an accurate identification of the inverter nonlinear effects, such as the dead-time and on-state voltage drops. The proposed technique is very simple and it is based only on a current control scheme. If the inverter load is an AC motor, the inverter effects can be identified at drive startup using as measured quantities the motor currents and the inverter DC link voltage. The identified inverter error is stored in a Look-Up Table (LUT) that can be subsequently used by the vector control algorithm. The proposed method has been tested on a 1 kVA inverter prototype and the obtained results demonstrate the feasibility of the proposed solutio

Improved Model Predictive Current Control for SPMSM Drives With Parameter Mismatch

Model predictive current control (MPCC) can predict future motor behavior according to a motor model. In practice, however, motor parameters will vary at run time, and the parameter mismatch disturbances caused by the variation in motor parameters will deteriorate the MPCC performance. To suppress the parameter mismatch disturbances effectively, this paper proposes a modified MPCC with a current variation update mechanism. In contrast with the traditional current prediction equation that contains crude model parameters, the modified current prediction equation contains only measured information, taking advantage of the proposed current variation update mechanism, which can update the modified prediction equation within each sampling period. A simulation established by MATLAB software indicates that the proposed method can effectively suppress the parameter mismatch disturbances. Experiments are carried out to verify the correctness of the proposed method

Predictive Control of Multi-Phase Motor for Constant Torque Applications

Constant torque motors are needed for rotary screw compressors that are used for cooling and other applications. In such systems, the torque demanded by the load is approximately the same over the whole range of mechanical speeds. In this paper, the use of multi-phase induction machines is investigated for this type of application. The requirement of low stator current distortion is considered. A scheduled approach is used to provide the best possible tuning for each operating point, similar to the concept of gain scheduling control. Simulations and laboratory tests are used to assess the proposal and compare it with finite-state predictive control. The experiments show that a trade-off situation appears between the ripple content in stator currents in the torque-producing and harmonic planes. As a consequence, the controller tuning appears as an important step. The proposed method considers various figures of merit with cost function tuning, resulting in a scheduled scheme that provides improved results. It is shown that the approach leads to a reduction in current ripple, which is advantageous for this particular applicationMinisterio de Ciencia e Innovación - FEDER RTI2018-101897-B-I00Junta de Andalucía -FEDER P20_0054

A Low-Complexity Optimal Switching Time-Modulated Model-Predictive Control for PMSM With Three-Level NPC Converter

Conventional finite control set model-predictive control (FCS-MPC) presents a high computational burden, especially in three-level neutral-point-clamped (NPC) converters. This article proposes a low-complexity optimal switching time-modulated model-predictive control (OST-M2PC) method for a three-level NPC converter. In the proposed OST-M2PC method, the optimal switching time is calculated using a cost function. Compared with the conventional FCS-MPC, the proposed OST-M2PC method has a fixed switching frequency as well as better power quality. The proposed OST-M2PC can operate at a 20-kHz sampling frequency, reducing the computational burden of the processor. Simulation and experimental results validate the operation of the proposed method

Model Predictive Control for shunt active filters with fixed switching frequency

This paper presents a modification to the classical Model Predictive Control algorithm, named Modulated Model Predictive Control, and its application to active power filters. The proposed control is able to retain all the advantages of a Finite Control Set Model Predictive Control whilst improving the generated waveforms harmonic spectrum. In fact a modulation algorithm, based on the cost function ratio for different output vectors, is inherently included in the MPC. The cost function-based modulator is introduced and its effectiveness on reducing the current ripple is demonstrated. The presented solution provides an effective and straightforward single loop controller, maintaining an excellent dynamic performance despite the modulated output and it is self-synchronizing with the grid. This promising method is applied to the control of a Shunt Active Filter for harmonic content reduction through a reactive power compensation methodology. Significant results obtained by experimental testing are reported and commented, showing that MPC is a viable control solution for active filtering systems

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines