Mechanical Speed Sensors Research Articles

Design and Implementation of VSI for Solar Water Pump Control

The hardware design, implementation, and digital control method for three-phase AC induction motors based on Field-Oriented Control is discussed in this work Solar-powered water pumping systems have become an practical option for remote irrigation and water supply as renewable energy sources obtain importance. This research enhances such systems performance and dependability by employing a Voltage Source Inverter. In order to optimize the energy transfer to the water pump, the recommended approach uses the Voltage Source Inverter capabilities to transform the variable DC output of the solar panels into a controlled AC supply. The research looks at the choice of power components, control algorithms, and modulation strategies while designing the Voltage Source Inverter. The most suitable modulation strategy is determined after an in-depth review of several different approaches to ensure greater pump performance. This research clarifies on how solar energy conversion and pump control work together to provide sustainable water management in off-grid areas. The research paper "Design and implementation of VSI for Solar Water Pump Control" demonstrates how solar water pumping systems can be optimized using power electronics and control. The project addresses efficiency difficulties and operational differences to create efficient and reliable solar-powered water delivery systems, which support environmental sustainability and rural development. Based on the power of the PV panel, the P&O MPPT method calculates the submersible pump speed. The sensorless speed control method eliminates the requirement for location or speed sensors. The Black Electro-Motives Force calculates speed by estimating the flux angle in the absence of mechanical speed sensors. This method reduces costs and simplifies the system simply by eliminating the requirement for expensive and complicated speed sensors. In order to determine steady-state and dynamic performance in varying insolation conditions, a prototype 5.5 KW inverter was constructed. In conclusion up, the research provided a thorough summary of the hardware and control aspects required for Field-Oriented Control in irrigation systems. The practical outcomes of this study have the potential to spur advancements in irrigation technology and the incorporation of renewable energy, resulting in substantial gains for agricultural productivity and environmental conservation.

Feedforward-loop phase-locked loop based estimation scheme for sensorless IPMSM drive system

The existence of mechanical speed sensors brings challenges of system reliability. Therefore, drives without speed and position sensors attract much popularity in interior permanent-magnet synchronous motor (IPMSM) drive system. This paper provides a new option for sensorless IPMSM drive system, in which a feedforward-loop phase-locked loop (FPLL) scheme is adopted to achieve acceptable estimation performance. Considering harmonics in the estimated back electromotive-force (BEMF) may cause estimation performance degradation, a pre-filter is assisted in the proposed FPLL scheme to address this issue. Moreover, in the proposed FPLL scheme, an amplitude normalization unit is introduced to eliminate the influence of BEMF amplitude variations. According to the derived small-signal model, the dynamic performance of the proposed FPLL scheme is accordingly elaborated, and its performance is compared with that of the conventional PLL scheme. Additionally, to further evaluate the performance of the proposed FPLL scheme, the parameter sensitivity analysis is also provided. Finally, the effectiveness of the proposed FPLL scheme has been experimentally verified.

Application Research of Pulse Vibration High-Frequency Voltage Injection Method Without Speed Sensor in New Energy Vehicles

The high-frequency voltage injection method of pulse vibration in the range of zero/low speed to medium-high speed has to be demonstrated for new energy vehicles., because it is very necessary and necessary to control the safety performance of the whole vehicle without speed sensor. The permanent magnet synchronous motor starts slowly to circle when the clean - energy vehicle cranked, and the correctness of the rotor’s startup position identification is significant. In order to achieve high-performance control of permanent magnet synchronous motor without speed sensor, this paper focuses mainly on how to estimate the rotor position of permanent magnet synchronous motor by amplifying the mathematical model of the motor. The high-frequency mathematical model of the permanent magnet synchronous motor’s voltage parameters are attained in the process of maintaining the motor’s preoperational position to address the problem of self-adaptability between the injected voltage and the likely phase current. The initial position identification of the rotor of a permanent magnet synchronous motor can be achieved by optimizing the adaptive method, and the pulse vibration highfrequency voltage anesthetic method also shows better efficiency and safety when the motor achieves a stable start and has sound output torque. The struggling to retain adaptive measurement device vibration high frequency voltage injection approaches is used by the light-duty low-speed new energy vehicle, which may minimize the mechanical speed sensor after becoming damaged, save the cost and improve the compactness of the electric vehicle space design, which is conducive to solving the situation of energy shortage in my country and alleviating environmental pollution. This is in line with the future development concept of society.

Performance analysis of DTC-SVM in a complete traction motor control mechanism for a battery electric vehicle

The transport sector is essential for socio-economic growth; however, the sector contributes a large portion of global carbon dioxide emissions. Consequently, electric vehicles have received increasing attention from various stakeholders in order to provide a solution to the current environmental impact of the transport industry. Current literature on electric vehicle powertrains show that electric vehicles are complex systems, with one of the most essential subsystems being the traction motor control mechanism. As a result, the objective of this paper is to add to the research conducted in the field of electric vehicle powertrains by carrying out comprehensive investigations into the suitability and performance of space vector modulation based direct torque control in the traction motor control system of an electric vehicle with a complete drive system. Initially, a conventional direct torque control mechanism was implemented for control of the traction motor system. The results of the investigation into implementation of conventional direct torque control highlighted the expected issues associated with the mechanism. Implementation of improvements to the conventional direct torque control model, such as the use of a space vector modulation based direct torque control model with closed loop torque control, field-weakening and sensorless control produced significantly favorable results, providing decreased torque and current ripples, operation over a wide speed range, and accurate speed control without the need for mechanical speed sensors. Such results demonstrate that the complete control mechanism investigated is well suited for use in electric vehicle applications.

Adaptive sensorless PMSM mechanical fault detection with varying speeds

In this paper, we propose to improve an OSG (Orthogonal Signal Generator) based technique in order to extract mechanical faults from a PMSM (Permanent Magnet Synchronous Motor) with variable mechanical speed. This technique is part of the MCSA (Motor Current Signal Analysis) family. In this particular case, we use a single current measurement. The technique can be used on-line and without a mechanical speed sensor. A stability analysis of the adaptive OSG method is presented in this paper. Order tracking extraction is added to ensure robust analysis and detection of variable speed faults. A comparison is made with the Concordia and TKEO (Teager Kaiser Enregy Operator) methods on an experimental bench with a mechanical fault emulator. A statistical study of the fault detection is conducted based on the experimental results

Toward the Optimization of a PMSG Wind Energy Conversion System On-Grid by a Robust Mixed Controller

The grid interconnected Wind Energy Conversion System (WECS) remains a major challenge. To deal with the effect of the intermittent nature of wind speed. This paper presents the design of a combined nonlinear controller based on a sliding mode controller (MSMC) for a wind system. This control technique includes a smooth switching sliding mode observer (SS-SMO) and a non-singular terminal sliding mode controller (NT-SMC). The SS-SMO is used to observe the torque/speed disturbances, while the NT-SMC is used as a regulator. A voltage control technique is adopted to maintain the voltage at the common DC-link. To control the electrical power injected into the grid a Backstepping controller is proposed. The WECS is built around a wind turbine coupled to a Permanent Magnet Synchronous Generator (PMSG). The proposed technique is robust against model uncertainties and external disturbances. In addition, the complexity of the system is reduced by replacing the mechanical speed and position sensors with the estimated parameter. The simulations results show the performances in terms of monitoring of set point, stability, and robustness with respect to the variation of wind speed.

Lyapunov Function Based Flux and Speed Observer Using Advanced Non-linear Backstepping DVC for PWM-Rectifier Connected Wind-turbine-driven PM Generator

In this paper, modeling, and speed/position sensor-less designed Direct Voltage Control (DVC) approach based on the Lyapunov function are studied for three-phase voltage source Space Vector Pulse Width Modulation (SVPWM) Rectifier Connected to a Permanent Magnet Synchronous Generator (PMSG) Variable Speed Wind Power Generation System (VS-WPGS). This control strategy is based on voltage orientation technique without mechanical speed sensor. Advanced Non-linear Integral Backstepping Control (IBSC) of the Generator Side Converter (GSC) has the ability to have a good regulation of the DC link voltage to meet the requirements necessary to achieve optimal system operation, regardless of the disturbances caused by the characteristics of the drive train or some changes into the DC load. The estimation of the speed is based on Model Reference Adaptive System (MRAS) method. This method consists in developing two models one of reference and the other adjustable for the estimation of the two d-q axis components of the stator flux from the measurement of currents, the speed estimated is obtained by canceling the difference between the reference stator flux and the adjustable one using Lyapunov criterion of hyper-stability. Some results of simulation using Matlab/Simulink® are presented, discussed to prove the efficiency and robustness of the system control policy for WPGS against external and internal perturbations.

Speed sensorless control of seven phase asynchronous motor drive system using extended Kalman filter

ABSTRACT In recent decades, multiphase motors are used in numerous applications instead of three-phase A synchronous motors, due to many advantages they offer. Eliminating mechanical position or speed sensor attractions for A synchronous motor (IM) adjustable speed drives. This results in lower maintenance, cost reduction and improved drive system reliability. Based on measured stator voltages and currents at motor terminals, the rotor mechanical speed is estimated to eliminate the speed sensor. This paper presents a seven-phase asynchronous motor Extended Kalman Filter System speed observer to improve the drive reliability of a seven-phase IM drive sensorless Indirect Rotor Field Oriented Control (IRFOC). The proposed scheme is simulation using the Matlab/Simulink package and evaluated experimentally. The proposed drive system provides good performance under various operating conditions.

Stator Current-Based Model Reference Adaptive Control for Sensorless Speed Control of the Induction Motor

This paper described that the stator current-based model reference adaptive system (MRAS) speed estimator is used for the induction motor (IM) indirect vector speed control without a mechanical speed sensor. Due to high sensitivity of motor parameters variation at low speed including zero, stability analysis of MRAS design is performed to correct any mismatch parameters value in the MRAS performed to estimate the motor speed at these values. As a result, the IM sensorless control can operate over a wide range including zero speed. The performance of the stator current-based MRAS speed estimator was analyzed in terms of speed tracking capability, torque response quickness, low speed behavior, step response of drive with speed reversal, sensitivity to motor parameter uncertainty, and speed tracking ability in the regenerative mode. The system gives a good performance at no-load and loaded conditions with parameter variation. The stator current-based MRAS estimator sensorless speed control technique can make the hardware simple and improve the reliability of the motor without introducing a feedback sensor, and it becomes more important in the modern AC IM. The sensorless vector control operation has been verified by simulation on Matlab and experimentally using Texas Instruments HVMTRPFCKIT with TMS320 F28035 DSP card and 0.18 kw AC IM.

Real time localization solution for land vehicle application using low-cost integrated sensors with GPS

The technique proposed in this research demonstrates a real time nonlinear data fusion solution based on extremely low-cost and grade inertial sensors for land vehicle navigation. Here, the utilized nonlinear multi-sensor data fusion (MSDF) is based on the combination between extremely low-cost micro electrical mechanical systems (MEMS) inertial, heading, pressure, and speed sensors in addition to satellite-based navigation system. The integrated navigation system fuses position and velocity states from the Global Positioning System (GPS), the velocity measurements from an odometer, heading angle observation from a magnetometer and navigation states from an inertial navigation system (INS). The implemented system performance is assessed through the post-processing of collected raw measurements and real time experimental work. The system that runs the real-time experiments is established on three connected platforms, two of them are based on a 32-bit ARMTM core and the third one is based 16-bit AVR ATMEL microcontroller. This microcontroller is connected to an on-board diagnostics (OBD) shield to collect the vehicle speed measurements. The raw data obtained from the integrated sensors is saved and post processed in MATLAB®. In normal conditions, the estimated position errors are reduced through the usage of INS/GPS integration with heading observation angle from a magnetometer. In GPS-denied environments, the integrated system uses the observations from INS, magnetometer in addition to the velocity from odometer to ensure a continuous and accurate navigation solution. A complementary filter (CF) is implemented to estimate and improve the pitch and roll angles calculations. In addition to that, an unscented Kalman filter (UKF) is used cascaded with the designed CF to complete the designed sensors fusion algorithm. Experimental results show that the designed MSDF can achieve a good level of accuracy and a continuous localization solution of a land vehicle in different GPS availability cases and can be implemented on the available in the market processors to be run in real time.

High-gain observer-based sensorless control of a flywheel energy storage system for integration with a grid-connected variable-speed wind generator

This paper introduces an induction machine-based flywheel energy storage system (FESS) for direct integration with a variable-speed wind generator (VSWG). The aim is to connect the FESS at the DC bus level of a permanent magnet synchronous generator-based VSWG in order to stabilize the DC bus voltage as well as the power flowing into the grid. A rotor flux-oriented control strategy is proposed for the FESS converter based on the actual speed of the flywheel rotor. Since mechanical speed sensors are prone to failure and increase the maintenance cost of the system, a sensorless technique is proposed to estimate the rotor speed through a specially synthesized high-gain observer (HGO). The proposed observer achieves accurate tracking of the flywheel speed and flux and reduces the adverse effects of variations in the rated rotor resistance. Simulation results obtained using the MATLAB-Simulink environment are presented to illustrate the theoretical synthesis and analysis of the proposed FOC and sensorless HGO control strategies.

Speed sensorless model predictive control method for a direct-drive wind energy conversion system

Considering the problems of the internal and external disturbances of wind speed in the direct-drive wind energy conversion system based on a permanent magnet synchronous generator, a novel model predictive control based on the extended state observer method without the accurate mathematical system model is proposed in this paper. First, a model predictive control method is employed as the feedback controller, while the mathematical model of the control system can be adjusted online via the rolling optimization strategy. Second, an extended state observer is introduced to estimate the state variables and lumped disturbances, that is, the internal disturbances including nonlinear characteristic, multi-variety coupling effect, uncertainties of system parameters, and external disturbances including variations of wind speeds and uncertainties of the natural environment. Third, the effect of lumped disturbances can be attenuated by the estimated disturbance value via a feedforward channel. In addition, in order to achieve the real-time speed control performance of the permanent magnet synchronous generator, a speed sensorless algorithm based on a flux observer is proposed to solve the problem of unsuitability of mechanical speed sensor. Finally, the simulation results with several wind speed types show that the proposed sensorless model predictive control with the extended state observer strategy is an effective way to improve the performance of anti-disturbance and ability of tracking maximum wind energy of the wind power control system.

UMV control via FOSMO

In this work, the speed and direction angle of an unmanned vehicle (UMV) are controlled by using a sliding mode controller (SMC). However, no mechanical speed or position sensor is used to control the speed and direction angle of the UMV. The speed and direction angle of the UMV are estimated using the fractional-order sliding mode observer (FOSMO), wherein the real UMV motor currents and voltages are measured by sensors and the kinematic modal of the UMV is used. The angular speeds of the UMV are approximated with the help of the estimated and real UMV motor currents. Then, the estimated speed and direction angle of the UMV are approximated by estimated angular speed of the UMV and those produced by the FOSMO are used in the SMC, which controls the speed and direction angle of a UMV. Given that fractional-order differential equations and algorithms are used in FOSMO, a more precise control than that in other controllers that use full-order differential equations is achieved. Lyapunov stability theory is also used to establish stability conditions for the observer. Experimental results show that the proposed observer can be perfectly implemented without a mechanical or position sensor and robustly follows different complex reference trajectories.

Adaptive Fuzzy-Based IRFOC of Speed Sensorless Six-Phase Induction Motor Drive System

In recent times, instead of three-phase induction motors (IM), multi-phase motors have been used in several applications, due to numerous advantages that they offer. Elimination of mechanical position or speed sensors allures for adjustable speed drives of IM. It leads to cost reduction, lesser maintenance and increased reliability of the motor drive. To eliminate the speed sensor, the rotor speed is estimated from measured stator currents and voltages at motor terminals. This paper proposes a scheme based on speed estimation method using Model Reference Adaptive System (MRAS) in conjunction with Adaptive Fuzzy Knowledge Based Controller (AFKBC) to improve the performance of a sensorless Indirect Rotor Field Oriented Control (IRFOC) of six-phase IM drive. AFKBC allows to operate at various operating conditions. A fitness function is defined for Queen Bee-based Genetic Algorithm (QBGA) to tune the scaling factor of AFKBC which improves the transient and steady state performances. The performance of the proposed scheme is evaluated by simulation on Matlab/Simulink package. The results of the proposed scheme are compared with conventional PI-based speed controller of the drive system. The proposed controller scheme improves the performance of the drive system at various operating conditions. The estimated speed algorithm gives good correlation between estimated and actual motor speed. The simulation results also illustrate that proposed scheme is robust and suitable for high performances six-phase IM drive.

A Composite Sliding Mode Controller for Wind Power Extraction in Remotely Located Solar PV–Wind Hybrid System

Ensuring electrification of remote locations continues to be a major challenge for power engineers. To deal with the effect of intermittent nature of wind, this paper presents the design and implementation of a composite sliding mode controller (CSMC) for a battery energy storage (BES) supported solar photovoltaic (PV)–wind hybrid system in a remote location. This control technique comprises of a soft-switching sliding-mode observer (SS-SMO) and a nonsingular terminal sliding mode controller (NTSMC). The SS-SMO is used to observe the disturbances, whereas the NTSMC is used as a speed controller. The chattering problem caused by the conventional sliding mode controller is alleviated by replacing the conventional signum switching function with the smooth hyperbolic tangent function in disturbance observer loop. The fast and finite time convergence NTSMC based speed controller along with the SS-SMO based disturbance rejection unit, serves the benefits of CSMC. This technique exhibits robustness against model uncertainties and external disturbances. Moreover, the complexity of the system is reduced by replacing the mechanical speed and position sensors with parameter estimation. A double-stage configuration using a dc/dc boost converter is adopted for a PV system. A comparative analysis is presented between the proposed and conventional techniques. A prototype of the hybrid system is developed in the laboratory with permanent magnet synchronous generator. The CSMC-based controller with disturbance rejection ability is implemented to harvest peak wind power. A perturb and observe maximum power point tracking technique is adopted to harvest peak solar power. A voltage control technique is adopted to maintain the voltage at the point of common coupling.

Modelling and Control Design for Energy Management of Grid Connected Hybrid PV-wind System

<p class="MsoNormal" style="margin-right: -14.15pt; text-align: justify; text-justify: inter-ideograph;">This paper deals with the control of hybrid PV-WIND power conversion structure. This paper develops a very important contribution which is the use of a single DC to DC converter, linearization of control of the three- level boost converter (TLBC) considering the imperfections of the passive components. The (TLBC) control provides balancing of capacitor voltages and maximum power operation of PV generator. For reasons of simplicity, a linearization based on the dynamic compensation of the disturbance is proposed. A sensorless maximum power point tracking (MPPT) algorithm is used to maximize a power extracted of the wind generator. The proportional relation between the rotational speed and the output voltage of the rectifier allows to use a voltage sensor to estimate the DC bus voltage reference instead of a mechanical speed sensor. The control of the three-phase inverter allows a transfer of the active power, the power factor close to the unit and thus a limitation of the reactive power injected into the grid. The external control loop performs the regulation of the common DC bus voltage while the internal control loop regulates the dq components of the currents injected into the grid. The simulation results showed the validity of the control approach. The proposed power conversion structure based on a single static converter has shown very good performance in terms of efficiency, the quality of the energy produced, complementarity between the two renewable sources and reliability. The paper ends with conclusions.</p>

Hybrid Computational Mechanical Sensorless Fuzzified Technique for Speed Estimation of Permanent Magnet Direct Current Brushed Motor

This paper proposes a novel fuzzified mechanical sensorless speed estimation technique for permanent magnet direct current (PMDC) brushed motor operated with pulse width modulation (PWM) based terminal voltage. For replacement of conventional mechanical speed sensors, few mechanical sensorless speed estimation techniques have been reported recently in the field of PMDC brushed motor. In this paper, a novel technique is applied over a recently reported semianalytical dynamic time-domain PMDC brushed motor model incorporating space-domain effects, namely slotting effect and commutation phenomenon to simulate the proposed estimation process. Ripple and back electromotive force based standalone estimation approaches are hybridized in order to eliminate uncertainties in all regions of estimation. In this paper, a discrete fuzzified hybrid speed estimation model has been proposed with adequate dynamic simulation responses. Further the proposed discrete speed estimation model has been applied experimentally over a PWM-driven 24-V, 12-teeth, 100-W PMDC brushed motor and various dynamic real-time responses have been compared with conventionally captured speed samples to validate the proposed model.

A Remotely Deployable Wind Sonic Anemometer

Communication and computing shape up base for explosion of Internet of Things (IoT) era. Humans can efficiently control the devices around their environment as per requirements because of IoT, the communication between different devices brings more flexibility in surrounding. Useful data is also gathered from some of these devices to create Big Data; where, further analysis assist in making life easier by developing good business models corresponding to user needs, enhance scientific research, formulating weather prediction or monitoring systems and contributing in other relative fields as well. Thus, in this research a remotely deployable IoT enabled Wind Sonic Anemometer has been designed and deployed to calculate average wind speed, direction, and gust. The proposed design is remotely deployable, user-friendly, power efficient and cost-effective because of opted modules i.e., ultrasonic sensors, GSM module, and solar panel. The testbed was also deployed at the roof of Computer & Information Systems Engineering (CIS) department, NED UET. Further, its calibration has been carried out by using long short-term memory (LSTM), a deep learning technique; where ground truth data has been gathered from mechanical wind speed sensor (NRG-40 H) deployed at top of Industrial & Manufacturing (IM) department of NED UET. The obtained results are satisfactory and the performance of designed sensor is also good under various weather conditions.

Discrete Adaptive Speed Sensorless Drive of Induction Motors

The use of mechanical speed sensor in the field of control of induction motors can cause some problems. Recently, many software are developed to estimate the speed by using only electrical measurements and machine parameters. This paper presents a new speed sensorless drive of induction motors for field oriented control. The proposed speed estimator is based on the Model Reference Adaptive Scheme (MRAS) and uses based the comparison of estimated and measured stator current. The reduction error is achieved by an appropriate unity transfer function as reference model. The estimator formulation is defined and developed in the discrete case. The proposed algorithm requires neither matrix calculation nor approximation on Taylor series of matrix exponential. To establish the stability of the discrete estimator, the hyperstability concept introduced by Popov in the discrete case is used. The influence of the sampling period on the algorithm stability of is studied. Some simulation results are presented, in order to valid the theoretical development.

Speed Sensorless Control of Six-Phase Asynchronous Motor Drive

Multi -phase ac motor drives are nowadays considered for various applications, due to many advantages that they offer when compared to three-phase motors. Cancellation of mechanical position or speed sensors at the motor shaft have the attractions for adjustable speed drives of induction motor to reduce the cost and increase the reliability. To replace the sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. This paper investigates speed estimation method using model reference adaptive system (MRAS) to improve the performance of a sensorless vector controller of six-phase induction motor (IM). In the proposed method, the stator current is used as the state variable to estimate the speed. Since the stator current error is represented as a function of the first degree for the error value in the speed estimation, the proposed method provides fast speed estimation and is also, more robust to variations in the stator resistance, compared with other MRAS methods. Consequently, this method can improve the performance of a sensorless vector controller in a low speed region and at zero-speed. The proposed method is verified by simulation using the Matlab/Simulink package. The performance of the proposed system is investigated at different operating conditions. The proposed controller is robust and suitable for high performance six-phase induction motor drives. Simulation results validate the proposed approaches.