Sensorless Brushless DC Motor Research Articles

Speed control of PM brushless DC motor using sensorless hybrid controller

In most industrial processes, rising productivity necessitates increased demand on electrical motors in order to minimize costs and improve drive system efficiency. The sensorless technique is preferred. Brushless DC (BLDC) motors compete with a wide range of different motor types in the motion control industry. The nonlinearity of BLDC motor characteristics is challenging to manage with a traditional proportional integral derivative (PID) controller. The PID controller's fuzzy logic allowed it to tune itself while operating online. Hybrid approaches outperform stand-alone algorithms because they can overcome their weaknesses without losing their advantage. The purpose of this study is to present a fuzzy PI+D controller that is simulated over a wide range of reference speeds, loads, and parameter variations. This paper presents a model of a sensorless BLDC motor with a speed controller. The responses of the rotor speed, electromagnetic torque, stator back electromotive force (EMF), and stator currents are effectively monitored. The findings from the simulation indicate that the hybrid controller presented in this study exhibits resilience to rapid load torque and parameter fluctuation. Furthermore, it demonstrates superior dynamic performance and exhibits notable enhancements in speed tracking and system stability. The performance of the system is enhanced through the utilization of the proposed hybrid intelligent controller.

Design and analysis of reconfigurable sensorless brushless DC motor drive for regenerative braking and battery charging in electric vehicle

SummaryThe expected depletion of fossil fuels has brought in an increased demand for electric vehicles with better performance in terms of easiness of control and reliability of operation and hence is a fertile area of research. In the present scenario, motoring, regenerative braking, and charging operations are performed in electric vehicles by separate converters. In this paper, an integrated scheme is developed, wherein the same voltage source inverter is employed to obtain all the three modes of operation, which in turn reduces the number of switching devices. Further, a sensorless control used in the proposed scheme improves the operational reliability. This novel approach adopts a simple switching scheme for voltage source inverter to operate as a dual‐boost DC‐DC converter during the regenerative braking period. This switching scheme enables reconfiguring voltage source inverter to a dual‐boost rectifier in conjunction with a LLC resonant converter in the charging mode. A comparison is also provided between the performance of single switch boost and dual‐boost converters used for braking operation. The performance of a prototype brushless DC (BLDC) motor drive with Li‐ion battery pack is evaluated in motoring, regenerative braking, and battery charging modes. This paper presents a detailed design of the scheme, the simulation of which is done on a MATLAB/SIMULINK platform and validated experimentally.

Improvement of speed control performance sensorless Brushless DC motor with finite control set model predictive control

Improvement of speed control performance sensorless Brushless DC motor with finite control set model predictive control

SMO Based Position Sensorless BLDC Motor Drive Employing Canonical Switching Cell Converter for Light Electric Vehicle

In this paper, an adaptive sliding mode observer (ASMO) based rotor position sensorless brushless DC (BLDC) motor drive with energy regeneration for light electric vehicle (LEV) is designed. A canonical switching cell (CSC) converter is introduced for optimized MPPT performance and soft starting of the motor is assured during sensorless start-up. The CSC converter provides ripple free current in the output to the voltage source inverter (VSI) and minimizes the losses. It also acts as a fundamental building block for a DC-DC converter with the least element counts. For position sensorless commutation of BLDC motor drive, ASMO technique with self-correction ability of commutation error is used. Estimation of rotor angular position and continuous speed tracking for closed loop control are achieved using this method. This control is robust and derived from linear model of BLDC motor. Proper stability analysis of the observer is derived and ensured using pole placement method. Optimal gain scheduling technique is used in ASMO, which reduces the order of the error function making the computation easier. This model is truly adaptive to any parameter variation and load perturbation. To ensure green mobility, a pulse-width modulated regenerative braking algorithm is also integrated using the same VSI, which avoids any additional converter. Experimental results validate this method as effective for EV applications

Speed and rotor position estimation for sensorless brushless DC motor drive based on particle filter

Speed and rotor position estimation for sensorless brushless DC motor drive based on particle filter

Solar PV Integration to E-Rickshaw With Regenerative Braking and Sensorless Control

This article proposes a novel drivetrain design of a solar-powered e-rickshaw with the controller. Hall-Effect position sensorless brushless dc (BLDC) motor drive often suffers from delayed commutation at high speed and even at low speed, conventional control does not work well due to low magnitude of back EMF. Here, the proposed sensorless control with commutation error compensation is implemented, which drives the motor over the entire range. A simple commutation error compensation algorithm is designed to detect the freewheeling pulses, reducing the control complexity for low-cost EV application and eliminating low pass filter requirement. Moreover, a zero-crossing detection (ZCD) algorithm is suggested, which inherently compensates the delay and removes the need of any additional phase compensator. A fixed delay digital filter is used to eliminate any unwanted spikes in ZCD circuit. For effective MPPT control, a modified Landsman converter is used, which provides ripple-free current at output and reduces the requirement of ripple filter at front end. The BLDC motor drive is capable of energy regeneration, which reduces the range anxiety for EV. The solar energy and the battery ensure that the vehicle never runs out of power irrespective of the climate conditions. The average distance covered by the vehicle on a single charge is improved <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">.</i>

Commutation Auto-Correction Method for Position Sensorless BLDCM With the Anti-Interference Ability Against Current Variation

Precise commutation is crucial to improve the sensorless brushless dc motor efficiency. In order to achieve the high-precision commutation, this article develops a commutation auto-correction method. Three challenges of the conventional correction method based on signal integral have been addressed. First, the line voltage difference of adjacent phases is integrated to construct the feedback quantity, which avoids the interference from the phase current variation. Second, the integration interval compression strategy is proposed, which avoids the impact of commutation freewheeling current. Third, a novel averaging circuit is designed, which realizes the high-precision acquisition of the integral. At last, by using the integral as the feedback quantity, a proportional integral controller is introduced to implement the commutation auto-correction. In contrast to the conventional method, the above three approaches ensure the accurate commutation in cases of the phase current variation and high motor speed. The effectiveness of the auto-correction method is verified by the experimental results on a magnetically suspended turbo molecular pump.

The Design &amp; Implementation of a Self-adaptive Hybrid Electric Skateboard

This paper proposes a novel electric skateboard control architecture to hybridize the skater's manual operation and electric motor drive. The proposed scheme does not need a handheld remote controller for steering; hence provides better man-machine coordination and enhances the safety of new skaters. For this purpose, a torque-speed control algorithm is designed to compensate for the manual acceleration force and rolling resistance by sensing the motor's speed, acceleration, and torque outputs. The compensation level is configurable according to the skater's comfortableness. The proposed electric control solution also enhances the battery mileage per charging and can be applied to various electric skateboards since it does not require a dedicated weight/pressure sensor to detect if the skater is on or off the board. The control scheme is simulated in MATLAB/Simulink and experimentally verified by a controller based on C2000 DSP that supports sensorless brushless DC(BLDC) motor drive.

Combined strategy for tuning sensor-less brushless DC motor using SEPIC converter to reduce torque ripple

The brushless DC motor (BLDCM) is widely used in computer numerical control (CNC) machines, aerospace applications and auto industry applications in the field of robotics. But it is still affected by the transmission torque ripple, which mostly depends on the speed and the transient line current at the transmission interval. This manuscript proposes a combined approach for tuning sensor-less brushless DC (BLDC) motors using a single-ended primary-inductor converter (SEPIC). The proposed technique is a combination of Golden Eagle Optimization (GEO) and Radial Basis Function Neural Network (RBFNN), hence it is called GEO-RPFNN. The control of speed and torque is to reduce the torque ripple in the motor. Here, the modified bridgeless single-ended primary-inductor converter is proposed to improve speed and torque control. The proposed method is used to adjust the parameters of proportional integral derivative (PID) controller and to improve the performance of PID controller. Therefore, the GEO–RBFNN technique is proposed to recover the control loop function. The proposed algorithm is explored to control the speed and torque error as BLDC motor. Nevertheless, the output of the proposed approach is subject to the input of speed and torque controllers. The proposed method is executed in MATLAB Simulink site. The performance of the proposed system is compared with existing FA and PSO methods. As per the state of comparison outcomes, the GEO–RBFNN gives better result than the existing techniques which has higher ability to conquer the related issues. The THD in stator current, power factor and torque ripple gives the value using proposed method is 1.26%, 0.9951 and 7.4.

Commutation Error Closed-Loop Correction Method for Sensorless BLDC Motor Using Hardware-Based Floating Phase Back-EMF Integration

Low pass filter (LPF) and comparator are usually adopted to obtain the commutation points in sensorless brushless DC (BLDC) motor. However, the LPF phase shift along with hardware and software delay results in the commutation error reducing the motor efficiency. In order to eliminate the commutation error, this paper presents a closed-loop correction method using the floating phase back-EMF integral. First, the relationship between the back-EMF integral and commutation error is analyzed. Then, a PI controller fed by the integral is introduced for correction. Because the inaccurate integral calculation resulting from insufficient sampling rate will seriously reduce the correction accuracy, a novel hardware configuration is proposed to convert the integral into a filtered analog voltage. By this way, the integral can be obtained precisely from sampling the analog voltage directly, which ensures a precise commutation correction. Finally, experiments on a magnetically suspended turbo molecular pump (TMP) show the effectiveness.

An enhanced whale optimized fractional order piλ controller based power quality improvement for sensorless brushless dc motor under dynamic operating conditions

This paper presents an Enhanced Whale Optimization Algorithm (EWO) approach for tuning to perfection of Fractional Order Proportional Integral and integral order Controller (FOPI λ) is used to sensorless speed control of permanent magnet Brushless DC (PMBLDC) motor under the operating dynamic condition such as (i) speed change by set speed command signal (ii) varying load conditions, (iii) integrated conditions and (iv) controller parameters uncertainty. On the other hand, it deals with a reduced THD (Total Harmonic Distortion) under dynamic operating conditions to improve the power quality for the above control system. Here present are three optimization techniques, namely (i) Enhanced Whale Optimization (EWO), (ii) Invasive Weed Optimization (IWO), and (iii) Social Spider Optimization (SSO) for fine-tuning of the FOPI λ controller parameters with reduction of THD. The proposed optimization algorithm optimized FOPI λ controller are compared under various BLDC motor operating conditions. Based on the results of MATLAB/Simulink models, the proposed algorithms are evaluated. Here, both the simulation and the results of the experiments are validated for the proposed controller technique. It demonstrates that the effectiveness of the proposed controllers is completely validated by comparing the three intelligent optimization techniques mentioned above. The EWO optimized FOPI λ controller for speed control of sensorless PMBLDC motor clearly outperforms the other two intelligent controllers by minimizing the time domain parameters, THD, performance Indices error, convergence time, control efforts, cost function, mean and standard deviation.

An internal power angle control strategy for high-speed sensorless brushless DC motors

High-speed Brushless DC Motors (BLDCMs) usually adopt a sensorless control strategy and operate in three-phase six-state drive mode. However, the sampling errors of the rotor position and the driving method increase the Internal Power Angle (IPA), resulting in a decrease in the efficiency of the system. Conventional IPA reduction strategies are either sensitive to motor parameters, or ignore diode freewheeling during the commutation process, or require additional current sensors. In this paper, a new strategy to reduce the IPA is proposed. Firstly, a Zero-Crossing Point (ZCP) detection method for the back-EMF without filter is proposed to reduce the sampling errors of the rotor position. Secondly, the relationship between the non-energized terminal voltage and the ZCP of the corresponding back-EMF is analyzed. The non-energized terminal voltage that has completed the diode freewheeling is divided into two triangles by half of the bus voltage. When the IPA is suppressed, the areas of the two triangles are equal. Thirdly, an advanced angle for reducing the IPA is obtained through a PI regulator which can eliminate the deviation between the two areas. Finally, both a simulation model and an experimental circuit are built to verify the proposed control strategy.

An improved incipient whale optimization algorithm based robust fault detection and diagnosis for sensorless brushless DC motor drive under external disturbances

In general, unexpected failures in sensorless brushless DC (BLDC) motors can result in production downtime, costly repairs, and safety concerns. BLDC motors are commonly used in home appliances, the medical sector, aerospace, small-scale, and large-scale industries under uncertain operating conditions. Therefore, the fault detection and diagnosis (FDD) of BLDC motor drives can play a very important role in increasing their performance, reliability, robustness control, and operational safety under uncertain operating conditions in critical real-time applications. To satisfy these issues of hall effect sensor, misplacement of a hall-effect sensor, inverter IGBT open-switch fault diagnosis, failure of hall effect sensor, lack of robustness speed control of BLDC motor, which has received substantial interest in academic and industry sectors to establish the proposed work optimization techniques approach FDD strategy for speed control of sensorless BLDC motor under uncertain operating conditions. The proposed optimization techniques such as Bat Algorithm (BA), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA) approach FDD strategies for BLDC motor drives. These FDD strategies simulated by the above optimization techniques on a sensorless BLDC motor with numerical Matlab/Simulink 2020a simulation results are verified. From the simulation results, out of three optimization techniques, the WOA-based FDD strategies are very effective for both bearing and stator winding faults detection and diagnosis in sensorless BLDC motor drives.

Implementation of speed control of sensorless brushless DC motor drive using H-infinity controller with optimized weight filters

&lt;span&gt;The hardware implementation of sensorless brushless direct current motor drive incorporating H-infinity control strategy with optimized weights by particle swarm optimization in the speed control is carried out in this work. The methodology involved in the design of brushless direct current (BLDC) motor control with sensorless position detection technique, the design of H-infinity speed controller, steps involved in particle swarm optimization for optimizing coefficients of its weights and the hardware implementation is discussed in detail in this paper. Texas Instruments microcontroller board C2000 Delfino Launchpad LAUNCHXL F28377S and driver BOOSTXL DRV8301 are used for realization of the speed controller. The code is developed using C2000 hardware support package in MATLAB/SIMULINK platform. A comprehensive performance analysis is accomplished during starting of the motor and during the fast application and removal of load. This strategy is found to be robust resulting in faster load disturbance rejection and better reference speed tracking. The experimental results of the proposed strategy are compared with that of conventional proportional-integral (PI) controller. The time domain parameters are also compared. It is found that the proposed strategy exhibits better performance characteristics during transients and sudden disturbances in load.&lt;/span&gt;

Systematic design of multi-objective enhanced genetic algorithm optimized fractional order PID controller for sensorless brushless DC motor drive

PurposeThe puspose of this paper, a novel systematic design of fractional order proportional integral derivative (FOPID) controller-based speed control of sensorless brushless DC (BLDC) motor using multi-objective enhanced genetic algorithm (EGA). This scheme provides an excellent dynamic and static response, low computational burden, the robust speed control.Design/methodology/approachThe EGA is a meta-heuristic-inspired algorithm for solving non-linearity problems such as sudden load disturbances, modeling errors, power fluctuations, poor stability, the maximum time of transient processes, static and dynamic errors. The conventional genetic algorithm (CGA) and modified genetic algorithm (MGA) are not very effective in solving the above-mentioned problems. Hence, a multi-objective EGA optimized FOPID (EGA-FOPID) controller is proposed for speed control of sensorless BLDC motor under various conditions such as constant load conditions, varying load conditions, varying set speed (Ns) conditions, integrated conditions and controller parameters uncertainty.FindingsThis systematic design of the multi-objective EGA-FOPID controller is implemented in MATLAB 2020a with Simulink models for optimal speed control of the BLDC motor. The overall performance of the EGA-FOPID controller is observed and evaluated for computational burden, time integral performance indexes, transient and steady-state characteristics. The hardware experiment results confirm that the proposed EGA-FOPID controller can precisely change the BLDC motor speed is desired range with minimal effort.Research limitations/implicationsThe conventional real time issues such as nonlinearity characteristics, poor controllability and stability.Practical implicationsIt is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.Originality/valueIt shows the effectiveness of the proposed controllers is completely verified by comparing the above three intelligent optimization algorithms. It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

A Fast Commutation Error Correction Method for Sensorless BLDC Motor Considering Rapidly Varying Rotor Speed

Accurate commutation point is essential to ensure the ideal torque performance and low power consumption for brushless DC (BLDC) motor. In order to achieve the precise sensorless commutation at a constant or the rapidly varying speed, a fast commutation error correction method is proposed in this article. First, it is pointed out that the controlled variable variation, the high rate of commutation error relative to the low speed and the nonlinearity of the correction loop are the main origins of commutation error when the speed varies rapidly. Then, a novel commutation error correction method is proposed through the following three aspects: first, constructing a controlled variable first utilized for commutation correction, which keeps constant at the rapidly varying speed; second, incorporating feedforward compensation for the phase shift caused by low-pass filter; third, using feedback linearization to reduce the nonlinearity of the correction loop. The proposed commutation error correction method not only corrects the commutation error fast at a constant speed, but also achieves precise commutation when the rotor speed changes rapidly. Moreover, the proposed method is based on the principle of closed-loop control, thus, it also has the advantage of anti-interference. At last, the experimental results are shown to validate the effectiveness of the proposed method.

Commutation Compensation Strategy for Brushless DC Motor Based on Terminal Voltage Reconstruction

In the sensorless brushless DC (BLDC) motor control system, the commutation signal is the key to measure the system performance. To improve the commutation accuracy, a commutation compensation strategy based on terminal voltage reconstruction is proposed. By analyzing the commutation process, the integral of ideal terminal voltage is adopted to determine the commutation error. Then considering the voltage clamping of the freewheel diode, the actual terminal voltage is analyzed in different periods. In the non-commutation period, a PWM cycle is divided into three regions, and the corresponding duration can be calculated by floating phase current, and then the equality of actual and ideal terminal voltage integrals is revealed. In the commutation period, the instantaneous value of back-electromotive force (back-EMF) at commutation point is used to construct the ideal terminal voltage and the commutation time is determined by the edge detection. In this way, the integral of terminal voltage can be calculated precisely. Then the error index is introduced and the relationship between the commutation error and the error index is presented. To eliminate the commutation error, the PI controller is adopted which outputs the compensation angle. The proposed strategy avoids the phase shift errors and the accumulation of integral errors, moreover the feasibility and effectiveness are verified by simulations and experiments under different conditions. In addition, the strategy can also be used to correct the installation error of Hall sensor.

Closed-Loop Compensation Strategy of Commutation Error for Sensorless Brushless DC Motors With Nonideal Asymmetric Back-EMFs

This article focuses on the sensorless commutation strategy of brushless DC (BLDC) motor with three-phase nonideal asymmetric back-EMFs (NAEMFs). To improve the torque performance and reduce power consumption, this article addresses two key issues: pointing out the accurate commutation positions of the BLDC motor with NAEMFs and proposing a novel closed-loop commutation error compensation strategy to obtain the accurate commutation positions. First, the accurate commutation positions are proved from the relationship between electromagnetical torque curve and commutation error on polar coordinates. Then, the novel feedback network and sampling subsystem are utilized to sample the back-EMFs of floating phases before and after the commutation positions separately. The deviation of the sampled voltages is employed as the controlled variable. Based on the controlled variable, the parallel control loops are incorporated to correct commutation positions in real time. When the controlled variable converges to zero, the commutation error is compensated synchronously. The proposed closed-loop compensation strategy utilizes any two back-EMFs of the BLDC motor, which can compensate the commutation error from the hardware and software. Furthermore, the commutation error induced by the asymmetric back-EMFs can also be eliminated. At last, the experimental results presented in this article validate the effectiveness of the proposed strategy.

Performance Assessment of a Canonical Switching Cell (CSC)Converter-fed Sensor-less Brushless DC Motor

Performance Assessment of a Canonical Switching Cell (CSC)Converter-fed Sensor-less Brushless DC Motor

Full-Region Sensorless BLDC Drive for Permanent Magnet Motor Using Pulse Amplitude Modulation With DC Current Sensing

This article improves the sensorless brushless dc (BLdc) motor drives using the pulse amplitude modulation (PAM) with dc current sensing. Comparing to conventional BLdc drives using pulsewidth modulation (PWM), PAM BLdc drives result in better drive efficiency especially at low speed. However due to six-step commutation, additional position detection issues are resultant for the sensorless operation. They consist of voltage spike at low speed and commutation delay at high speed. In this article, these BLdc position detection issues are improved based on the proposed continuous position estimation. At low speed, the commutation compensation with dc current sensing is developed to minimize the influence of voltage spike. At high speed, several voltage compensation schemes are applied to improve the commutation delay and maximizing high-speed operation region. A 320-W permanent magnet motor prototype is used for the experimental verification of proposed PAM BLdc drive. Comparing to the conventional BLdc drives, the PAM drive with proposed position estimation demonstrates the improvement on both low-speed dynamic response and high-speed steady state stability.