Design and Implementation of Modern Controls for Drive and Suspension of a High Speed Double Conical Bearingless Motor on a Real-Time System

In this work, modern control approaches for drive and suspension of a high speed double conical bearingless motor are designed. Firstly, the air gap flux density and the forces acting on the rotor are analytically calculated. Subsequently, an elaborate model of the magnetically levitated rotor is developed, which considers the non-collocation of position sensors and levitation windings as well as the presence of angular motion. Three different control approaches are designed and simulated. The first approach comprises a state controller augmented with integral action, with which the closed loop dynamics are freely defined after pole placement. The other two approaches concern Linear Quadratic Gaussian and Model Predictive control. The pole placement control approach is tested successfully on the test bench with the real motor. Sinusoidal disturbance forces, with the rotational frequency, can cause large rotor orbits and may drive the inverters to their limits. For this reason, two synchronous filtering control strategies are developed. Using Imbalance Force Compensation, the rotor can be driven with low orbits at relatively low speed and using Imbalance Force Rejection, the rotor can be driven with low levitation currents at high speed. The control performance is evaluated by measurements and the measured frequency response of the closed loop system is presented

Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results

This paper focuses on current control in a permanentmagnet synchronous motor (PMSM). The paper has two main objectives: The first objective is to develop a neural-network (NN) vector controller to overcome the decoupling inaccuracy problem associated with conventional PI-based vector-control methods. The NN is developed using the full dynamic equation of a PMSM, and trained to implement optimal control based on approximate dynamic programming. The second objective is to evaluate the robust and adaptive performance of the NN controller against that of the conventional standard vector controller under motor parameter variation and dynamic control conditions by (a) simulating the behavior of a PMSM typically used in realistic electric vehicle applications and (b) building an experimental system for hardware validation as well as combined hardware and simulation evaluation. The results demonstrate that the NN controller outperforms conventional vector controllers in both simulation and hardware implementation

Model predictive control of a free piston compressor/expander with an integrated linear motor/alternator

Linear positive displacement machines are becoming increasingly more attractive for applications that are normally known as unconquerable niches of rotary and scroll machines. Free-piston machines are characterized by the absence of a crank mechanism, since there is a direct transformation of electrical energy into the piston movement. From the point of view of manufacturing, these machines benefit from a higher robustness and reliability because of less mechanical components involved and reduced frictional losses associate with a conventional crank mechanism. However, the major challenge in replacing the rotary machines by linear ones is a lower efficiency at lower speeds which is unavoidable because of the nature of linear motion: continuous operation means a reciprocating movement within a stroke length with significantly long periods of acceleration and deceleration when the speed is far from its optimal value. However, the advantage of free-piston machines is the fact that the motion profile is freely configurable within physical constraints, which provides a possibility to optimize the speed given the efficiency map of particular linear motor. While the methods and results of the efficiency assessment for rotary machines are widely available, there is a lack of these analyses for linear machines. The current study provides in-depth analyses of a double-coil iron core linear motor also acting as a generator

Robust nonlinear generalized predictive control of a permanent magnet synchronous motor with an anti-windup compensator

This paper presents a robust nonlinear generalized predictive control (RNGPC) strategy applied to a permanent magnet synchronous motor (PMSM) for speed trajectory tracking and disturbance rejection. The nonlinear predictive control law is derived by using a newly defined design cost function. The Taylor series expansion is used to carry out the prediction in a finite horizon. No information about the external perturbation and parameters uncertainties are needed to ensure the robustness of the proposed RNGPC. Moreover, to maintain the phase current within the limits using saturation blocks, a cascaded structure is adopted and an anti-windup compensator is proposed. The validity of the proposed control strategy is implemented on a dSPACE DS1104 board driving in real-time a 0.25 kW PMSM. Experimental results have demonstrated the stability, robustness and the effectiveness of the proposed control strategy regarding trajectory tracking and disturbance rejection

Impact of PWM strategies on RMS current of the DC-link Voltage Capacitor of a dual-three phase drive

The major drawback of usual dual three-phase AC machines, when supplied by a Voltage Source Inverter (VSI), is the occurrence of extra harmonic currents which circulate in the stator windings causing additional losses and constraints on the power component. This paper compares dedicated Pulse Width Modulation (PWM) strategies used for controlling a dual three phase Permanent Magnet Synchronous machine supplied by a six-leg VSI. Since the application is intended for low-voltage (48V) mild-hybrid automotive traction, an additional major constraint arises: the compactness of the drive related to the size of the DC-bus capacitor. Thus, the PWM strategy must be chosen by taking into consideration its impact on both, the motor and the RMS value of DC-bus current

An Advanced Model Predictive Current Control of Synchronous Reluctance Motors

Synchronous reluctance motors (SynRMs) have, in recent years, attracted much attention due to their high-efficiency output and nature of their construction denoted by the lack of expensive magnetic materials, thus cheapening the overall cost whilst increasing in robustness. These benefits have made the SynRM a strong contender against other established electric motors in the market. Similarly, model predictive current control (MPCC) has recently become a powerful advanced control technology in industrial drives, being, therefore, a suitable choice for SynRM drives granting overall high control performance and efficiency. However, current prediction in MPCC requires a high number of voltage vectors (VVs) synthesizable by the converter, being therefore computationally demanding. Accordingly, the main goal of this work is the development and analysis of a more efficient and advanced MPCC for SynRMs whilst reducing the computational burden and delivering good control performance in contrast with the standard MPCC. Therefore, to achieve the intended levels of efficiency and control performance in SynRM drives, a combination of two control strategies is developed, which combines hysteresis current control (HCC) and MPCC, dubbed in this work HCC-MPCC. Furthermore, the SynRM dynamic model equations comprising the magnetic saturating effects and iron losses are presented through a detailed theoretical and computational analysis of the drive’s control. Conclusively, the developed HCC-MPCC for SynRM drives is analyzed through thorough and rigorous experimental tests alongside the standard MPCC, whose obtained results are detailed comprehensively.Os motores síncronos de relutância (SynRMs) têm, nos últimos anos, atraído muita atenção devido às suas características construtivas, designadamente pela falta de materiais magnéticos caros, depreciando assim o custo em geral; e simultaneamente pelo aumento em robustez. Esses benefícios tornaram o SynRM num forte concorrente face a outros motores elétricos existentes no mercado. Da mesma forma, o modelo preditivo de controlo de corrente (MPCC) tornou-se recentemente numa poderosa estratégia de controlo avançado em acionamentos industriais, sendo, portanto, uma escolha adequada para acionamentos envolvendo SynRMs, garantindo elevado desempenho e eficiência de controlo. No entanto, a previsão da corrente no MPCC requer um grande número de vetores de tensão (VVs) sintetizáveis pelo conversor, sendo, portanto, exigente computacionalmente. Consequentemente, o objetivo principal deste trabalho é o desenvolvimento e análise de um MPCC mais eficiente e avançado para SynRMs, reduzindo a carga computacional e, simultaneamente, demonstrando um bom desempenho de controlo em contraste com o MPCC clássico. Portanto, para atingir os níveis pretendidos de eficiência e desempenho de controlo em acionamentos com SynRMs, uma combinação de duas estratégias de controlo é desenvolvida, combinando o controlo de corrente de histerese (HCC) e MPCC, denominado neste trabalho HCC-MPCC. Além disso, as equações do modelo dinâmico do SynRM, compreendendo os efeitos de saturação magnética e as perdas de ferro, são apresentadas através de uma análise teórica e computacional detalhada do controlo do acionamento. Conclusivamente, o HCC-MPCC desenvolvido para acionamentos com SynRMs é analisado por meio de testes experimentais conjuntamente com o MPCC padrão, sendo os resultados obtidos detalhados de forma abrangente

Study of solution towards ground leakage current via inverter switching in different topologies for grid connected PV system

Renewable energy sources are major issues in order to address the energy problem. Among them, the PV (Photovoltaic) system will be dominant because its availability and reliability. One of the common problems that arise due to the formation of solar PV panels is capacitive ground current. Although transformer helps in reducing this problem, the poor side of having the transformer in PV systems is accounted to bulky in size and hard to install the entire PV system. Indirectly, the cost is higher and led to a lower efficiency due to higher losses of power. To solve this, transformerless inverter topology offers a solution for the efficiency, size and weight. The leakage current depends on both inverter topology and control strategy. In this report, different inverter topologies have been reviewed with respect to ground current formation due to inverter switching that causes varying common mode voltage that will excite the resonant circuit as well as causes the leakage current phenomenon. The transformerless inverter topologies that are considered are Bipolar H-Bridge, Modified HB-ZVR and NPC. In order to study the effect of having a transformer in eliminating the ground current, Bipolar H-Bridge inverter with transformer also include in this project. All proposed topologies are modelled and simulated to compare the pattern and behavior of ground leakage current with other existing topology. By comparing the pattern of the output from the simulation, a conclusion is given which proves that NPC topology are suitable for PV application due to low leakage current compared with other two topologies

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent-Magnet Synchronous Generator

Wind energy is an integral part of nowadays energy supply and one of the fastest growing sources of electricity in the world today. Accurate models for wind energy conversion systems (WECSs) are of key interest for the analysis and control design of present and future energy systems. Existing control-oriented WECSs models are subject to unstructured simplifications, which have not been discussed in literature so far. Thus, this technical note presents are thorough derivation of a physical state-space model for permanent magnet synchronous generator WECSs. The physical model considers all dynamic effects that significantly influence the system's power output, including the switching of the power electronics. Alternatively, the model is formulated in the $(a,b,c)$- and $(d,q)$-reference frame. Secondly, a complete control and operation management system for the wind regimes II and III and the transition between the regimes is presented. The control takes practical effects such as input saturation and integral windup into account. Thirdly, by a structured model reduction procedure, two state-space models of WECS with reduced complexity are derived: a non-switching model and a non-switching reduced-order model. The validity of the models is illustrated and compared through a numerical simulation study.Comment: 23 pages, 11 figure

Systems, Methods and Devices for Vector Control of Permanent Magnet Synchronous Machines using Artificial Neural Networks

An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error signals can be a difference between the d- and q-axis currents and reference d- and q-axis currents, respectively. The method can further include outputting a compensating dq-control voltage from the current-loop neural network and controlling the PWM converter using the compensating dq-control voltage