Analysis and investigation of different advanced control strategies for high-performance induction motor drives

Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing(DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; themodel predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared interm of operation in different operating conditions. Moreover, a comparisonof these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions

Analysis And Investigation Of Different Advanced Control Strategies For High-Performance Induction Motor Drives

Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing (DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; the model predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared in term of operation in different operating conditions. Moreover, a comparison of these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions

Direct Torque Control based on Virtual Voltage Vector for a Six-phase Induction Machine

[EN] Direct torque control (DTC) strategy is one of the methods used to control multiphase machines. This strategy has been popular in recent decades owing to its speed, robustness and simplicity in the control scheme. However, the appearance of the new secondary x-y currents components typical of multiphase systems can deteriorate the currents quality and increase the losses in the stator copper if they are not regulated properly. That is why the definition and use of the called virtual voltage vectors allow the reduction of these x-y components, thus alleviating the main problem of the direct extension of the DTC to systems with more than three phases. This paper presents the implementation of virtual voltage vectors in a direct torque control for the speed regulation of a six-phase induction machine, validating the goodness of the control strategy proposed by experimental results.[ES] La estrategia de control directo de par (DTC por sus siglas en inglés) es uno de los métodos empleados para el control de máquinas multifásicas. Esta estrategia ha sido popular en las últimas décadas gracias a su rapidez, robustez y simplicidad en el esquema de control. Sin embargo, la aparición de las nuevas componentes secundarias de corrientes x-y propias de los sistemas multifásicos pueden deteriorar la calidad de las corrientes y aumentar las pérdidas en el cobre del estator si no se regulan adecuadamente. Es por ello por lo que la definición y el uso de los denominados vectores virtuales de tensión permiten la reducción de estas componentes x-y, paliando así el principal problema de la extensión directa del DTC a sistemas con más de tres fases. 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The Essential Role and the Continuous Evolution of Modulation Techniques for Voltage-Source Inverters in the Past, Present, and Future Power Electronics

The cost reduction of power-electronic devices, the increase in their reliability, efficiency, and power capability, and lower development times, together with more demanding application requirements, has driven the development of several new inverter topologies recently introduced in the industry, particularly medium-voltage converters. New more complex inverter topologies and new application fields come along with additional control challenges, such as voltage imbalances, power-quality issues, higher efficiency needs, and fault-tolerant operation, which necessarily requires the parallel development of modulation schemes. Therefore, recently, there have been significant advances in the field of modulation of dc/ac converters, which conceptually has been dominated during the last several decades almost exclusively by classic pulse-width modulation (PWM) methods. This paper aims to concentrate and discuss the latest developments on this exciting technology, to provide insight on where the state-of-the-art stands today, and analyze the trends and challenges driving its future

Nonlinear model predictive control for thermal management in plug-in hybrid electric vehicles

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A nonlinear model predictive control (NMPC) for the thermal management (TM) of Plug-in Hybrid Electric Vehicles (PHEVs) is presented. TM in PHEVs is crucial to ensure good components performance and durability in all possible climate scenarios. A drawback of accurate TM solutions is the higher electrical consumption due to the increasing number of low voltage (LV) actuators used in the cooling circuits. Hence, more complex control strategies are needed for minimizing components thermal stress and at the same time electrical consumption. In this context, NMPC arises as a powerful method for achieving multiple objectives in Multiple input- Multiple output systems. This paper proposes an NMPC for the TM of the High Voltage (HV) battery and the power electronics (PE) cooling circuit in a PHEV. It distinguishes itself from the previously NMPC reported methods in the automotive sector by the complexity of its controlled plant which is highly nonlinear and controlled by numerous variables. The implemented model of the plant, which is based on experimental data and multi- domain physical equations, has been validated using six different driving cycles logged in a real vehicle, obtaining a maximum error, in comparison with the real temperatures, of 2C. For one of the six cycles, an NMPC software-in-the loop (SIL) is presented, where the models inside the controller and for the controlled plant are the same. This simulation is compared to the finite-state machine-based strategy performed in the real vehicle. The results show that NMPC keeps the battery at healthier temperatures and in addition reduces the cooling electrical consumption by more than 5%. In terms of the objective function, an accumulated and weighted sum of the two goals, this improvement amounts 30%. Finally, the online SIL presented in this paper, suggests that the used optimizer is fast enough for a future implementation in the vehicle.Accepted versio

Guidelines for Weighting Factors Adjustment in Finite State Model Predictive Control of Power Converters and Drives

INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY () (.2009.VICTORIA, AUSTRALIA)Model Predictive Control with a finite control set has emerged as a promising control tool for power converters and drives. One of the major advantages is the possibility to control several system variables with a single control law, by including them with appropriate weighting factors. However, at the present state of the art, these coefficients are determined empirically. There is no analytical or numerical method proposed yet to obtain an optimal solution. In addition, the empirical method is not always straightforward, and no procedures have been reported. This paper presents a first approach to a set of guidelines that reduce the uncertainty of this process. First a classification of different types of cost functions and weighting factors is presented. Then the different steps of the empirical process are explained. Finally, results for several power converters and drives applications are analyzed, which show the effectiveness of the proposed guidelines to reach appropriate weighting factors and control performance

Improving the torque generation in self-sensing BLDC drives by shaping the current waveform

Brushless DC drives are widely used in different fields of application because of their high efficiency and power density. Torque ripple can be considered one of the drawbacks of these drives. This paper proposes a method to reduce the torque ripple in BLDC drives. For this reason, the current amplitude is adapted to the rotor position rather than to be kept constant as done in a conventional commutation method. This is done by computing an optimum reference current based on the phase back-EMF waveform. The proposed approach is implemented in a self-sensing drive so its applicability to self-sensing BLDC motor drives is verified. Simulation and experimental results are given and discussed to show that the proposed method actually is able to improve torque production

FPGA implementation of online finite-set model based predictive control for power electronics

Recently there has been an increase in the use of model based predictive control (MBPC) for power-electronic converters. MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. The computational burden for this control scheme however is very high and often restrictive for a good implementation. This means that a suitable technology and design approach should be used. In this paper the implementation of finite-set MBPC (FS-MBPC) in field-programmable gate arrays (FPGAs) is discussed. The control is fully implemented in programmable digital logic by using a high-level design tool. This allows to obtain very good performances (both in control quality, speed and hardware utilization) and have a flexible, modular control configuration. The feasibility and performance of the FPGA implementation of FS-MBPC is discussed in this paper for a 4-level flying-capacitor converter (FCC). This is an interesting application as FS-MBPC allows the simultaneous control of the output current and the capacitor voltages, yet the high number of possible switch states results in a high computational load. The good performance is obtained by exploiting the FPGA’s strong points: parallelism and pipe-lining. In the application discussed in this paper the parallel processing for the three converter phases and a fully pipelined calculation of the prediction stage allow to realize an area-time efficient implementation

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