TMS320F28335 Digital Signal Processor Research Articles

Short-Circuit Fault Diagnosis on the Windings of Three-Phase Induction Motors through Phasor Analysis and Fuzzy Logic

An induction motor is an electric machine widely used in various industrial and commercial applications due to its efficiency and simple design. In this regard, a methodology based on the electric phasor analysis of line currents and the variations in the phase angles among these line currents is proposed. The values in degrees of the angles between every pair of line currents were introduced to a fuzzy logic algorithm based on the Mamdani model, developed using the Matlab toolbox for detection and isolation of the inter-turn short-circuit faults on the windings of an induction motor. To carry out the analysis, the induction motor was modified in its stator windings to artificially induce short-circuit faults of different magnitudes. The current signals are acquired in real time using a digital platform developed in the Delphi 7 high-level language communicating with a float point unit Digital Signal Processor (DSP) TMS320F28335 by Texas Instruments. The proposed method not only detects the short circuit faults but also isolates the faulty winding.

Implementation of Shunt Active Power Filter Using DSP Controller Based on Synchronous Reference Frame for Harmonic Mitigation

This research paper introduces the concept of a shunt active power filter (SAPF) that leverages synchronous-reference-frame (SRF) theory to mitigate harmonics in the power system. The SAPF works by injecting a compensating current at the point of common coupling (PCC) to counteract the harmonics in the line and restore sinusoidal current waveforms. It employs a three-phase current-controlled voltage source inverter (VSI) with a DC link capacitor for active filtering. An SRF algorithm is designed for a low-voltage laboratory prototype utilizing the TMS320F28335 Digital Signal Processor (DSP). The experimental findings affirm that the control strategy effectively aligns with the recommended harmonic standard limits of IEEE 519-1992.

Enhanced Volts-per-Hertz Sensorless Starting of Permanent Magnet Motor with Heavy Loads in Long-Cable Subsea Applications

Permanent magnet (PM) motors are gaining prominence in subsea applications such as drilling, pumping, and boosting for oil and natural gas extraction. These motors are gradually replacing traditional induction motors. However, starting and operating PM motors at low speeds under heavy loads poses significant challenges. This is because of unknown initial rotor positions and resistive voltage drops due to the presence of a sinewave filter, transformer, and long cable. An unknown rotor position may result in temporary reverse speed, which may cause a loss of synchronism; therefore, initial rotor position estimation is preferable. Additionally, addressing the voltage drop issue requires careful voltage compensation to avoid transformer core saturation. In this paper, an enhanced V/Hz starting of a PM motor is proposed with initial position detection (IPD) and voltage compensation to start the motor reliably with a heavy load. The proposed control method is verified with controller hardware in the loop (C-HIL) real-time simulation using a Typhoon HIL-604 emulator and a Texas Instruments TMS320F28335 digital signal processor (DSP) control card.

Experimental evaluation of the backstepping‐based input resistance controller in step‐up DC–DC converter for maximum power point tracking of the thermoelectric generators

AbstractIn this paper, a novel non‐linear model‐based approach is presented for maximum power point (MPP) tracking of thermoelectric generators (TEGs) using the backstepping controller. Considering the output voltage range of the thermoelectric devices, a step‐up DC–DC converter is employed as an interface between the load and input power source. According to the maximum power transfer theorem, if the equivalent input resistance of the converter (Rin) is equal to the internal resistance of the input source (RTEG), the TEG operation at the MPP will be achieved. Hence, defining the RTEG as a reference value and Rin as a feedback variable for a closed‐loop controller, the backstepping non‐linear controller is developed for input resistance control of the boost DC–DC converter. Owing to the non‐linear nature of the error variable in the input resistance control of the converters, conventional linear controllers cannot guarantee the system's closed‐loop stability within an extensive operational range. However, despite changes in generator's open‐circuit voltage (VOC) and RTEG, the designed closed‐loop controller can successfully stabilize the thermoelectric converter in different operational conditions. Considering the Lyapunov theorem and the Barbalat lemma, the asymptotic stability of the backstepping controller is proved. During the steady‐state operation, the actual values of the VOC and RTEG are updated periodically by the measurement of the converter input voltage/current values. To verify the functionality of the designed control method, PC‐based simulations are carried out in MATLAB/Simulink software. Moreover, by using TMS320F28335 digital signal processor from Texas Instruments and a simple thermoelectric simulator, the experimental response of the proposed controller is evaluated in dynamic and steady‐state conditions. The developed closed‐loop system can track the MPP of a TEG with zero steady‐state error, regardless of uncertain parameter variations.

Lyapunov-Based Control Strategy for a Single-Input Dual-Output Three-Level DC/DC Converter

This paper proposes a robust control strategy using direct Lyapunov strategy (DLS) for a single-input dual-output three-level dc-dc converter (SIDO-TLC) while the output loads and voltage references are disturbed. The first proceeding is to concurrently focus on the current and voltage dynamics of the converter buck and boost segments for exerting the related variable errors to the DLS-based function. Accordingly, through a comprehensive analysis based on the outcome of this proceeding, the PI controller coefficients allotted to the current reference design process are enabled to reach their maximum robustness capabilities against any output voltage variation. Moreover, the converter reference current tracking-based assessment leads to several smooth hyperbolic curves with their unique geometric properties. Consequently, the alteration trend of these curves facilitates the Lyapunov coefficients to be adjusted commensurate with the dynamic operation of the converter while converging to zero steady-state errors. Using a TMS320F28335 digital signal processor (DSP), disparate experimental results are conducted on the SIDO-TLC to verify the accurate and robust performance of the proposed control strategy.

Research and Design of Arc Welding Parameters Control and Environment Monitoring System Based on DSP

In the process of the welding operation, a large number of welding smoke, toxic gas, and other pollutants will be produced, which can cause a variety of respiratory diseases. Therefore, the welder’s health is affected and the atmospheric environment is polluted. To monitor the detrimental soot substances produced in the arc welding process, an arc welding parameters control and environmental monitoring system was built by taking high-performance DSP (Digital Signal Processor) TMS320F2812 as the control core, which uses wireless communication technology. Multi-information sensing and welding parameters control can be carried out through the system in the arc welding process. The concentration of welding smoke, harmful gas, and other substances in the arc welding environment can be monitored in real time and the real-time environmental conditions are displayed visually. The functions of audible and visual alarms, automatic ventilation, and telecommunication are provided by the system. A lot of experimental verification and debugging results show that parameters control in the arc welding process and the monitor welding environment in real time could be realized by the built system and is running well.

Design and Measurement of a Frequency Converter with SPWM Modulation of Output Voltage for a Two-Phase Induction Motor

This paper deals with the design, implementation, and measurements of a frequency converter with bipolar sinusoidal pulse width modulation (SPWM) of output voltage for two-phase induction motors. The paper is dedicated to an analysis of the operation of a two-phase frequency converter and its implementation. The inverter has a single-phase H-bridge topology with split DC link and bipolar switching to minimise the number of components. Insulated gate bipolar transistors (IGBTs) are used in the realisation of the inverter power section. The inverter is controlled using a digital signal processor (DSP) TMS320F28335. Measurements with a 0.12 kW two-phase induction motor were performed to verify the correct operation of the inverter. The influence of the switching frequency on the motor current ripple is measured for frequencies of the first harmonic up to 100 Hz.

Design and DSP implementation in HIL of nonlinear observers for a doubly fed induction aero-generator

This paper reports on the conception and digital signal processor (DSP)-based hardware-in-the-loop realisation of a nonlinear observer for a grid-connected variable speed wind turbine using a doubly fed induction generator (DFIG). The objective of this work is to build some observation structure based on the extended Kalman filter (EKF), the sliding mode observer (SMO) and the adaptive model reference adaptive system (MRAS) observer to observe certain quantities of the wind power system connected to the electrical grid in order to reduce the complexity and the cost of the hardware, to achieve an increased mechanical robustness, to operate in hostile environments, to have a higher reliability and to ensure an unchanged inertia of the system. The proposed observers will be combined with robust nonlinear controls based on the backstepping approach to control the wind energy conversion system (WECS). The whole will be implemented on a TMS320F28335 DSP board. A comparative analysis of the proposed observers will be carried out. Through the results of the DSP implementation in hardware in the loop (HIL), we will prove that this improved combination increases the desired performance.

A fully digital power supply system for TLS corrector magnets

This study focuses on the development of a fully digital power supply system (FDPSS) for the Taiwan Light Source (TLS) storage ring corrector magnet, which includes the fully digital correction power supply (FDCPS), digital communication card (DCC), and a virtual operation interface. The DCPS adopts a full-bridge circuit architecture, with the TI TMS320F28335 digital signal processor (DSP) as the core, combined with an 18-bit high-resolution A/D converter and discrete PID algorithm to achieve closed-loop current control, ensuring a stable output current value of the system. The DCC can control eight DCPS modules through an RS485 protocol with a virtual instrument control interface. This new system can replace the analog signal-modulated Bira MCOR30A power supply system, which has been in operation for 25 years in the TLS storage ring and can be upgraded to an FDPSS. This article aims to discuss the design concepts, hardware implementation, and testing of FDCPS and DCC to demonstrate the advantages of full digital control and to achieve the goal of independently researching and developing the prototype of FDPSS. Ultimately, after long-term testing and verification, the system's output current stability is less than ± 20ppm, indicating that this new system has high-precision and high-stability output current characteristics. In this study, upgrading the TLS storage ring corrector magnet power supply system to full digital control significantly improves output current stability and accuracy.

Design and Implementation of an Isolated Bidirectional Phase-Shift Full-Bridge Converter With High Transformation Ratio

In this paper, a bidirectional full-bridge phase-shift converter with high transformation ratio scheme is proposed. The main architecture of this converter is dual active full-bridge circuit. By using phase-shift modulation, the energy can be transmitted between high-voltage-side and low-voltage-side, and also can make the power switches have the function of soft-switching. This converter is designed with the transmission power of 1kW and the digital signal processor TMS320F28335 is utilized as the main system controller core. Finally, it realizes the bidirectional power conversion mechanism between battery 50 Vdc and DC grid 400 Vdc. The experimental results show that the maximum conversion efficiency of this converter when operating in the forward charging mode (G2V mode) is up to 92.25 %, and in the reverse discharging mode (V2G mode), the maximum conversion efficiency is up to 93.02 %. In comparison with the related studies for dual active full-bridge converters, the conventional transformation ratio is lower or equal to 4. This study with high transformation ratio can reach 8 for practical high-low voltage bidirectional applications. After the validation for both modes, the proposed concept is practical in the high transformation scenarios.

A novel adaptive invasive weed optimization technique and least square regression for harmonics minimization in standalone PV applications

SummaryA novel adaptive invasive weed optimization technique is presented in this paper for harmonics minimization in standalone system based on three‐phase two‐level voltage source inverter. The low switching frequency techniques are preferred to produce good quality waveform and at the same time to reduce the switching losses and device stresses. Nonetheless, the challenging task is to compute the firing angles from the set of highly nonlinear transcendental system of equations. The proposed technique shows faster convergence and capability to compute in wide rage of modulation index. Moreover, multiple solutions also have been obtained in most of the range of modulation index. Various cases have been evaluated and simulation results have been given to validate conceptual results. The closed loop operation and the real‐time implementation of the proposed technique under dynamic operating conditions have been verified for a three‐phase induction motor load using PI controller. The least square regression is used for real‐time implementation of the proposed technique. The TMS320F2812 digital signal processor (DSP) has been employed to generate the pulse width modulated pulses generated from the computational results. The experimental results obtained are in very close concurrence to the computational and simulation results.

Computationally Efficient Deadbeat Direct Torque Control Considering Speed Dynamics for a Surface-Mounted PMSM Drive

In this article, a computationally efficient deadbeat (DB) direct torque and flux control is investigated for surface-mounted permanent magnet synchronous motor (SPMSM) drives. Unlike conventional DB direct torque control (DB-DTC), the proposed DB-DTC technique simultaneously manipulates the electromagnetic torque and stator flux along with rotor speed in a combined DB controller structure. Moreover, a simple and computationally efficient DB-DTC structure is achieved through a novel DB controller design in the stationary reference frame and it ensures an improved transient performance within finite time steps. The feedforward terms are properly designed to mitigate the effects of system uncertainties. The stability of the proposed DB-DTC has been proven and discussed in detail through Lyapunov theory and eigenvalue analysis. The designed DB-DTC strategy has been simulated via MATLAB/Simulink software and practically evaluated on a laboratory SPMSM drive with TI digital signal processor TMS320F28335. Extensive comparative evaluation with conventional proportional-integral (PI)-DTC and DB-DTC corroborate an improved control performance in speed/torque dynamic response (fast rise time) as well as reductions in torque and flux ripples under tough practical conditions (e.g., speed and torque step-changes, and speed reversal test cases) with significantly reduced computational complexity.

Implementation of TMS320f28335 DSP code based on SVPWM Technique for Driving VSI with Induction Motor

<span lang="EN-US">The ability to control the speed of three-phase induction motors is a complex and arduous task using conventional control methods because the induction motor still inherits traditional design problems such as nonlinear and multivariate reactive dynamic behavior that leads to difficult design of the motor's mathematical model, and the strict overlap between decades of mathematical parameters. This causes more complex relationships with changing loads. This complexity results in unacceptable behavior of the system, and the difficulty of controlling its speed without affecting the torque, and thus the specific calculations of engine efficiency are almost low. Therefore, the current research provides the implementation of devices for the V / F control method that is fed via Inverter of the voltage source using the new generation of digital signal processor TMS320F28335 according to the theory of space vector pulse width modulation (SVPWM) for the application of motor control. The results obtained from practical experience show the possibility of obtaining a wide range of control and thus reduce the damage to the system in the event of The load thus ensuring the reliability of The proposed control scheme is built on DSP</span><em><span lang="AR-SA" dir="RTL">.</span></em>

Sliding mode based adaptive linear neuron proportional resonant control of Vienna rectifier for performance improvement of electric vehicle charging system

With a strong expansion of transportation electrification, electric vehicle charging systems are becoming very important part of the electrified powertrain. This paper proposes a sliding mode based adaptive linear neuron (ADALINE)-proportional resonant (PR) control solution to enhance performance of Vienna rectifier (VR), an AC–DC converter, as a charger for series-linked battery packs of electric vehicles (EVs) operating under unbalanced and distorted grid conditions. A sliding-mode control (SMC) has been utilized for the fast and robust regulation of DC-link voltage while ADALINE-PR control is proposed to regulate the source current errors through the real-time adaptation of the controller gains. Another contribution of this paper is to derive reference current signals without complex positive and negative sequences component separation, coordinate transformation and phase-locked loop. Besides, constant and pure battery current during charging/discharging is achieved in contrast to the previous studies. The proposed control algorithm achieves superior dynamic and steady-state performances and eliminate harmonics of source currents and ripples in active power, DC-link voltage and battery current compared to the existing studies. The proposed method has been implemented in a digital signal processor (DSP) TMS320F28335 within a processor in the loop (PIL) quasi-real-time setting. Extensive comparative results demonstrate the effectiveness of proposed control algorithm.

Computational efficient model predictive current control for interior permanent magnet synchronous motor drives

The standard model predictive control (MPC) of three-phase motors requires heavy calculation efforts for evaluating all voltage vectors (VV) in addition to the variable switching frequency, large current harmonics, and torque ripples. To deal with these problems, a computational efficient model predictive current control (MPCC) is proposed for a three-phase interior permanent magnet synchronous motor (IPMSM). Initially, to avoid the protracted enumeration process, the reference voltage vector (RVV) is directly calculated by using the reference current generated by the maximum torque per ampere technique (MTPA), which is an additional control objective. The position of the RVV is utilized to define three candidate voltage vectors to be examined using the cost function, which determines the optimal vector. Secondly, an optimal duty cycle (ODC) is designed to minimize the error between the optimal vector and the reference vector reducing the current ripples. Furthermore, the proposed scheme is compared with the conventional MPCC techniques using MATLAB simulation and hardware in loop (HIL) with TMS320F28335 digital signal processor (DSP) experiments. A comprehensive analysis of the results for different operating conditions shows the effectiveness and robustness of the proposed method.

A Robust Iterative Learning Control Technique to Efficiently Mitigate Disturbances for Three-Phase Standalone Inverters

This article investigates a robust iterative learning control (ILC) technique that effectively rejects the influence of periodic and nonperiodic disturbances for a three-phase constant-voltage constant-frequency standalone voltage source inverter (VSI) with an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> filter under variable initial states. In conventional ILC, the learning dynamics are more complex when the initial iterative state is different at each iteration due to the fixed initial state value. Unlike conventional ILC, the proposed ILC follows a transformed dynamic model for robust learning rule convergence that is less restricted under varying initial states and significantly eliminates the impact of periodic and nonperiodic disturbances. Moreover, a simplified stability analysis is provided, and the conditions required for robust learning rule convergence are discussed. A comparative verification with the results of conventional ILC using a TI TMS320F28335 digital signal processor based prototype standalone VSI proves that the proposed ILC technique offers robust and effective steady-state performance, with benefits such as reduced steady-state errors and low total harmonic distortion under periodic disturbances. Finally, its improved robustness and fast transient-state performance are validated under nonperiodic disturbances due to the existence of tough load conditions, i.e., step-changes of linear, unbalanced, and nonlinear loads with significantly distorted model parameters.

Harmonic Suppression and Stability Enhancement of a Voltage Sensorless Current Controller for a Grid-Connected Inverter Under Weak Grid

This paper presents the harmonic suppression and stability enhancement of a grid voltage sensorless current controller for a grid-connected inverter under weak grid conditions. Given that inductive-capacitive-inductive (LCL) filters represented as higher-order dynamics cause resonance problems, a considerate resonance frequency damping process is required. In particular, the resonance phenomenon of the LCL filter crucially influences the current quality when the grid-connected inverter is connected to a weak grid with uncertain grid impedance and distorted harmonics. Additionally, there is a possibility that the control system will become unstable due to changes in system parameters, even after considerate resonance frequency damping. In order to solve these problems, this paper presents an active damping (AD) method by using integral variables in an integral state feedback current controller for a grid voltage sensorless inverter system, which significantly improves the current harmonics and stability of the grid-connected inverter under weak grid condition. The presented closed-loop current control scheme only requires the measurement of the injected grid currents and DC-link voltage. Compared to the traditional state feedback control methods, the reliability and robustness of the proposed control scheme are much improved even with reduced system cost. The stability and current control performance of the closed-loop system are investigated in the presence of uncertainty in the grid impedance and filter capacitor parameter under distorted grids. In order to support the theoretical analyses, the comprehensive simulation results are presented in terms of the grid current quality and control stability in an environment with both uncertain grid impedance and a distorted grid. Experimental results are also presented by using a 32-bit digital signal processor (DSP) TMS320F28335 controller for a 2 kVA grid-connected inverter to validate the feasibility of the proposed scheme practically.

Fotovoltaik Bir Sistemde, Maksimum Güç Noktası Takibi için Bulanık Mantık Tabanlı Bir Denetleme Algoritmasının Geliştirilmesi

In this study, a fuzzy logic based maximum power point tracking control algorithm was developed to obtain maximum power continuously from a simulation model of a PV system. Using this simulation model, codes suitable for the TMS320F28335 Digital Signal Processor (DSP) were generated by the embedded code generation method. In this way, the developed algorithm was generated, compiled, sent, and made ready for use in applications with an optimum code structure. The algorithm developed has the task of providing the power demanded by the load unit in a stable and continuous manner; It fulfills this task by providing maximum efficiency from PV panels by Tracking the Maximum Power Point and increasing the power obtained. In addition, the current and voltage of the DC bus as well as the PV panel unit are continuously monitored and used as input data for the algorithm's fuzzy logic controller.

Linear quadratic regulator controllers for regulation of the dc-bus voltage in a hybrid energy system: Modeling, design and experimental validation

In this paper, linear quadratic regulator (LQR) controllers for effective operation of a hybrid energy system consisting of ultracapacitor energy storage and wind energy system have been designed and implemented. The control objective is to regulate the dc-bus voltage to a target level while extracting the maximum power from the available wind. The dc-bus voltage regulation is achieved by controlling the charging and discharging of the ultracapacitor through a bidirectional converter, and tracking the maximum power points (MPPs) is achieved by controlling a boost converter interfacing the wind turbine with the dc-bus. In addition, a boost converter-based wind turbine emulator to behavior similar to a real wind generator has been developed for testing the proposed controllers. The performance of the proposed energy system incorporating the LQR controllers has been tested under several scenarios (both in simulations and experiments), and the results presented. The simulation tests were conducted in the environment of MATLAB/Simulink, and the experimental tests implemented based on low-cost Digital Signal Processor (DSP) TMS320F2812 eZdsp board. The simulation and experimental results demonstrate their consistency and the capability of the proposed LQR controllers to (1) track the reference voltages and currents, and (2) swiftly recover the nominal operating condition of the system at all conditions including any variation in wind speed or load demand.

An Experimental Study on Sensorless Determination of the Projectile Position by Artificial Neural Network in Magnetic Launcher Systems

Electromagnetic launchers are systems in which energy is converted from one form to another. The energy applied to the launcher is converted into magnetic energy in the coil and then into motion energy. The object to be launched follows the magnetic field created in one or more fixed coils. The coil can be fed by direct current (dc) or alternative current (ac) source. In dc systems, the capacitor charging time delays the serial launch. In ac systems, the absence of capacitors enables serial launching. In this study, the application of an ac electromagnetic launch system, which provides a serial launch, is proposed. The maximum force acting on the projectile can be achieved by timely cutting off the energy applied to the coil. Therefore, in electromagnetic launchers, it is critical to know the position of the projectile in the coil. In launcher systems fed with alternating current, the projectile position can be predicted from current changes without the need for an additional setup. In the study, TMS320F28335 digital signal processor (DSP) microprocessor with high processing capacity was used to detect the trigger moment from coil current. Time-delayed artificial neural network was used to estimate the position of the projectile within the coil by using the obtained current differences. The normalized values of the current differences were applied to the time-delayed multilayer neural network (MLNN) algorithm and the projectile position was estimated with 94.67% accuracy. The proposed system increases efficiency compared to systems using conventional sensors, as it prevents or reduces the retraction force.