Direct field oriented control scheme for space vector modulated AC/DC/AC converter fed induction motor

This paper investigates a Luenberger flux observer with speed adaptation for a direct field oriented control of an induction motor. An improved method of speed estimation that operates on the principle of speed adaptive flux and current observer has been proposed. An observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltage and current. Simulation results show that the proposed direct field oriented control with the proposed observer provides good performance dynamic characteristics. The induction motor is fed by an indirect power electronics converter. This indirect converter is controlled by a sliding mode technique that enables minimization of harmonics introduced by the line converter, as well as the control of the power factor and DC-link voltage. The robustness of the overall system is studied using simulation for different operating modes and varied parameters.

A Comparative Overview of Indirect Field Oriented Control (IFOC) and Deadbeat-Direct Torque and Flux Control (DB-DTFC) for AC Motor Drives

Indirect field oriented control(IFOC)has become a widely adopted solution for AC motor drives.Standard IFOC controls torque and rotor flux linkage via q-and d-axis current.Alternatively,deadbeat-direct torque and flux control(DB-DTFC)has emerged as a promising motor control strategy for the future,which manipulates Volt-sec.vector directly.Air-gap torque and stator flux linkage are decoupled and independently controlled over each switching period.Stator flux linkage is used as a separated degree-of-freedom to manipulate losses dynamically without compromising torque dynamics and torque ripple.In voltage-limited operations,direct selection of Volt-sec.allows DB-DTFC to fully utilize the dc bus voltage and produce fast torque.A single control law is used over a wide speed range.This paper aims to provide a comparative overview of the two motor controls regarding their sensitivity to parameters,current-and voltage-limited operation,loss manipulation,and torque ripple during signal injection.Based on the comparison,the ultimate objective is to demonstrate the opportunities and remaining challenges in DB-DTFC.

Real-time Control Oriented HCCI Engine Cycle-to-cycle Dynamic Modelling

For homogeneous charge compression ignition （HCCI） combustion, the auto-ignition process is very sensitive to in-cylinder conditions, including in-cylinder temperature, in-cylinder components and concentrations. Therefore, accurate control is required for reliable and efficient HCCI combustion. This paper outlines a simplified gasoline-fueled HCCI engine model implemented in Simulink environment. The model is able to run in real-time and with fixed simulation steps with the aim of cycle-to-cycle control and hardware- in-the-loop simulation. With the aim of controlling the desired amount of the trapped exhaust gas recirculation （EGR） from the previous cycle, the phase of the intake and exhaust valves and the respective profiles are designed to vary in this model. The model is able to anticipate the auto-ignition timing and the in-cylinder pressure and temperature. The validation has been conducted using a comparison of the experimental results on Ricardo Hydro engine published in a research by Tianjin University and a JAGUAR V6 HCCI test engine at the University of Birmingham. The comparison shows the typical HCCI combustion and a fair agreement between the simulation and experimental results.

Driving and Braking Control of PM Synchronous Motor Based on Low-resolution Hall Sensor for Battery Electric Vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor （PMSM） based on low-resolution Hall sensors. Field oriented control （FOC） based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces （EMF）, thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

PSO Based Controlled Six-phase Grid Connected Induction Generator for Wind Energy Generation

This paper deals a detailed performance investigation of asymmetrical six-phase grid connected induction generator(GCIG)in two proposed configurations in variable speed operation.During the system development,regulation of DC-link voltage has been proposed using particle swarm optimization(PSO)based PI controller,ensuring the power flow to utility grid through back to back converters.The closed loop operation of asymmetrical six-phase GCIG using indirect field oriented control in different configurations has been carried out in Matlab/Simulink environment.Analytical results have been verified using real time test results on virtual platform of Typhoon HIL supported with some experimental validation.

Torque-based Optimal Acceleration Control for Electric Vehicle

The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin＇s maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle（EV） has not been reported. In this paper, the permanent magnet synchronous motor（PMSM） is controlled by the field oriented control（FOC） method and the electric drive system for the EV（including the PMSM, the inverter and the battery） is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming（DP）. This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV＇s acceleration process and the analytical algorithm is easy to be implemented in real-time control.

The effects of orientation control via tension-compression on microstructural evolution and mechanical behavior of AZ31 Mg alloy sheet

The grain orientation control via twinning activity on deformation features is of great significance to offer a key insight into understanding the deformation mechanism of Mg alloy sheets.The{10–12}twinning were performed by pre-strain paths,i.e.,tension(6%)and compression(5%)perpendicular to the c-axis along extrusion direction(ED),to investigate the microstructural evolution and mechanical properties of AZ31 Mg alloy sheets.The distinction in the texture evolution and strain hardening behavior was illustrated in connection with the pre-strain paths for the activities of twinning and slip.The result shows that the activation of the deformation mode was closely bound up with the grain orientation and the additional applied load direction.The{10–12}twin-texture components with c-axis//ED were generated by precompression,which can provide an appropriate alternative to accommodate the thin sheet thickness strain and enhance the room temperature formability of Mg alloy sheet.

Starting Control of Free Piston Stirling Linear Generator System Based on FOC

Aiming at the problem of poor system dynamic performance caused by low parameter matching in the coordinated control of Stirling engine and linear generator in the starting stage control of free piston Stirling linear generator system,a joint control method of free piston Stirling permanent magnet synchronous linear generator system based on field orientation control is proposed,based on the theoretical derivation of the mathematical model of the system and the principle of controller parameters setting,the simulation experiments of the system starting stage under several Stirling engine working conditions are carried out under simulation.The experimental results show that the stability and rapidity of the system are improved,and the dynamic response speed of generator parameters under different working conditions is accelerated,what fully verifies the correctness and effectiveness of the method.It provides an effective way to improve the control performance of the system and stabilize the power generation operation.

Simulating unmanned aerial vehicle flight control and collision detection

An unmanned aerial vehicle(UAV)is a small,fast aircraft with many useful features.It is widely used in military reconnaissance,aerial photography,searches,and other fields;it also has very good practical-application and development prospects.Since the UAV’s flight orientation is easily changeable,its orientation and flight path are difficult to control,leading to its high damage rate.Therefore,UAV flight-control technology has become the focus of attention.This study focuses on simulating a UAV’s flight and orientation control,and detecting collisions between a UAV and objects in a complex virtual environment.The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment.A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper,to improve the system performance and accelerate the collision-detection process.This provides a practical method for future studies on UAV flight position and orientation control,collision detection,etc.

Integration of Wind and PV Systems Using Genetic-Assisted Artificial Neural Network

The prominence of Renewable Energy Sources(RES)in the process of power generation is exponentially increased in the recent days since these sources assist in minimizing the environmental contamination.A grid-tied DFIG(Doubly Fed Induction Generator)based WECS(Wind Energy Conversion System)is introduced in this work,in which a Landsman converter is implemented to impro-vise the output voltage of PV without anyfluctuations.A novel GA(Genetic Algorithm)assisted ANN(Artificial Neural Network)is employed for tracking the Maximum power from PV.Among the rotor and grid side controllers,the for-mer is implemented by combining the statorflux with d-q reference frame and the latter is realized by the PI controller.The proposed approach delivers better per-formance in the compensation of real and reactive power along with the DC link voltage control.The controlling mechanism is verified in both MATLAB and experimental bench setupby using an emulated wind turbine for the concurrent control of DC link potential,active and reactive powers.The source current THD is observed as 1.93%and 2.4%for simulation and hardware implementation respectively.

Robust Sliding Mode Control Using Adaptive Switching Gain for Induction Motors

A robust sliding mode approach combined with a field oriented control （FOC） for induction motor （IM） speed control is presented. The proposed sliding mode control （SMC） design uses an adaptive switching gain and an integrator. This approach guarantees the same robustness and dynamic performance of traditional SMC algorithms. And at the same time, it attenuates the chattering phenomenon, which is the main drawback in actual implementation of this technique. This approach is insensitive to uncertainties and permits to decrease the requirement for the bound of these uncertainties. The stability and robustness of the closed- loop system are proven analytically using the Lyapunov synthesis approach. The proposed method attenuates the effect of both uncertainties and external disturbances. Experimental results are presented to validate the effectiveness and the good performance of the developed method.

Overview of Advanced Control Strategies for Electric Machines

Control strategies play a key role for operation of electric machines,which would directly affect the whole system performance.In fact,different control strategies have been executed and explored for electric machines,which bring great impacts to industrial development and human society.This paper investigates and discusses the advantages control strategies for electric machines,including the field oriented control(FOC),direct torque control(DTC),finite control set model predictive control(FCS-MPC),sensorless control,and fault tolerant control(FTC).The corresponding control principles,control targets,fundamental approaches,advanced approaches,methodologies,merits and shortcomings are revealed and analyzed in detail.

Overview of Model Predictive Control for Induction Motor Drives

Model predictive control(MPC)has attracted widespread attention in both academic and industry communities due to its merits of intuitive concept,quick dynamic response,multi-variable control,ability to handle various nonlinear constraints,and so on.It is considered a powerful alternative to field oriented control(FOC)and direct torque control(DTC)in high performance AC motor drives.Compared to FOC,MPC eliminates the use of internal current control loops and modulation block,hence featuring very quick dynamic response.Compared to DTC,MPC uses a cost function rather than a heuristic switching table to select the best voltage vector,producing better steady state performance.In spite of the merits above,MPC also presents some drawbacks such as high computational burden,nontrivial weighting factor tuning,high sampling frequency,variable switching frequency,model/parameter dependence and relatively high steady ripples in torque and stator flux.This paper presents the state of the art of MPC in high performance induction motor(IM)drives,and in particular the progress on solving the drawbacks of conventional MPC.Finally,one of the improved MPC is compared to FOC to validate its superiority.It is shown that the improved MPC has great potential in the future high performance AC motor drives.

Classical state feedback controller for nonlinear systems using mean value theorem： closed Ioop-FOC of PMSM motor application

The problem of state feedback controllers for a class of Takagi-Sugeno （T-S） Lipschitz nonlinear systems is investigated. A simple systematic and useful synthesis method is proposed based on the use of the differential mean value theorem （DMVT） and convex theory. The proposed design approach is based on the mean value theorem （MVT） to express the nonlinear error dynamics as a convex combination of known matrices with time varying coefficients as linear parameter varying （LPV） systems. Using the Lyapunov theory, stability conditions are obtained and expressed in terms of linear matrix inequalities （LMIs）. The controller gains are then obtained by solving linear matrix inequalities. The effectiveness of the proposed approach for closed loop-field oriented control （CL-FOC） of permanent magnet synchronous machine （PMSM） drives is demonstrated through an illustrative simulation for the proof of these approaches. Furthermore, an extension for controller design with parameter uncertainties and perturbation performance is discussed.

Super twisting sliding mode approach applied to voltage orientated control of a stand-alone induction generator

To enhance the robustness and dynamic performance of a self-excited induction generator (SEIG) used in a stand-alone wind energy system (WES), a virtual flux oriented control (VFOC) based on nonlinear super-twisting sliding mode control (STSMC) is adopted. STSMC is used to replace the conventional proportional-integral-Fuzzy Logic Controller (PI-FLC) of the inner current control loops. The combination of the proposed control strategy with space vector modulation (SVM) applied to a PWM rectifier brings many advantages such as reduction in harmonics, and precise and rapid tracking of the references. The performance of the proposed control technique (STSMC-VFOC-SVM) is verified through simulations and compared with the traditional technique (PI-FLC-VFOC-SVM). It shows that the proposed method improves the dynamics of the system with reduced current harmonics. In addition, the use of a virtual flux estimator instead of a phase-locked loop (PLL) eliminates the line voltage sensors and thus increases the reliability of the system.