BLDC Motor Research Articles

Design and comparative analysis of motor position control based on traditional PID controller and fuzzy PID controller

Abstract. Using the PID algorithm to control electrical elements is a practical industrial application that have been studied for decades. This paper constructs a study on the difference between BLDC motor control and applying traditional PID and fuzzy PID. The simulation is done through Falstad and Matlab/Simulink. The math model of the transfer function of a BLDC motor is constructed by analyzing voltage and torque equilibrium. The parameters are determined approximately by looking up the datasheet of 2338 0006s. Then, Falstad establishes the operational amplifier model of the BLDC motor and traditional PID controller. The parameters are determined through both root locus and step response presented by Falstads scope. Next, Simulink is used to realize the fuzzy PID controller. The comparison study of traditional PID controller and fuzzy PID controller is constructed by looking at the scope and export data. After that, it is concluded that fuzzy PID controller performs better than traditional PID controller, it is robust and the influence of the input parameter is small. Finally, a lead lag compensator is applied to the whole system to improve the performance in the frequency domain.

Control of a BLDC Motor of an Electric Vehicle Powered by a Photovoltaic System based on Fuzzy Logic MPPT (FLC-MPPT)

Photovoltaic Systems (PV) represent a viable solution for converting solar energy into electricity without emitting harmful gases. This technology remains highly sought-after in the market, primarily due to its renewable characteristics and the absence of movable components, which renders it a low-maintenance option. This produced energy can be stored in batteries tobe used for example in operating electric vehicles. If the generated voltage is inadequate or requires regulation, a boost converter may be employed or a buck boost To manage energy during storage and discharge to provide the energy needed to run the induction motor. In this paper, we proposed the field-oriented control as an approach for controlling the speed of BLDC Motor drive electrical vehicles to improve the overall effectiveness of the proposed system, The BLDC Motor is powered by battery storage from a photovoltaic system. Furthermore, this work also addresses the specifics of modeling the Fuzzy logic control MPPT (FLC-MPPT) used for the energy management system (PV and batteries), as well as the proposed control approach for the electric vehicle motor, which are subsequently simulated in the MatLab environment.

Analysis and control of grid-interactive PV-fed BLDC water pumping system with optimized MPPT for DC-DC converter

In this study, a novel water pumping module fed by grid interactive Photo-Voltaic with a bidirectional Power Flow Control was proposed. In addition to improving the pumping system’s reliability, a water pump is powered by a brushless DC motor drive. This method enables the pump to work at its maximum capacity for the entirety of that day, regardless of the weather. The entire system becomes more reliable as a result of the motor’s increased use of photovoltaic (PV) generated power for pumping applications. Maximum Power Point Tracking (MPPT) controller incorporating Machine Learning algorithm drives bridgeless greater static gain DCDC converter to achieve higher power generation point and increment PV efficiency. The PV array’s operation would be managed using the ML back propagation technology to capture the most electricity under any ecological circumstance. A BLDC motor is fed by a Voltage Source Inverter (VSI) that includes a DC bus controlled in both directions by a unit vector template (UVT) approach incorporated in a single-phase voltage source converter (VSC). Additionally, utilizing a PI controller to manage the DC capacitor voltage in the UVT controller at a particular level is not appropriate for the increased PQ capabilities. However, due to tuning problems with the current controller, this controller is unpopular. The aforementioned problems are resolved by employing a unique intelligent-based fuzzy logic controller that achieves good performance features. In this technique, the function of a PV array at its Maximum Power Point (MPP), as well as power quality enhancements and a decrease in Total Harmonic Distortion (THD) of the grid are accomplished. The proposed PI controller attains a significant voltage THD of 3.736. The PI controller, on the other hand, managed to achieve a load voltage THD of 2.629%. The ANFIS method, whose value is 1.739%, is discovered to have a lower THD than all remotes with improved features, it lessens abrupt swings while maintaining steady DC-link voltage.

A novel power quality-improved high-step-up-gain Luo converter-powered BLDC motor drive with model reference adaptive controller for electric vehicles

A novel power quality-improved high-step-up-gain Luo converter-powered BLDC motor drive with model reference adaptive controller for electric vehicles

ANSYS-Based Broken Magnet, Demagnetization and Short Circuit Fault Evaluation for a BLDC Motor Designed for Light Electric Vehicle

ANSYS-Based Broken Magnet, Demagnetization and Short Circuit Fault Evaluation for a BLDC Motor Designed for Light Electric Vehicle

Modified Arithmetic Optimization Algorithm (MAOA) based torque ripple minimization for a sensorless BLDC motor

ABSTRACT Permanent magnet brushless DC (PM BLDC) motor drives outperform the induction motor drives in terms of performance and improved efficiency. Recent advancements in power electronics technology have improved the application of BLDC drives in a variety of home applications. However, the BLDC motor drives suffer from torque ripple, which causes machine vibration, speed oscillations, and acoustic noise, limiting the application range. In this prelude, an optimization tuning algorithm, namely Modified Arithmetic Optimization Algorithm (MAOA) is suggested in this paper for torque ripple minimization in a sensorless BLDC drive. In this paper, the cuk converter topology with PAM scheme is proposed for the sensorless BLDC drive, and MAOA algorithm is used to improve the gain of the controller. A MATLAB Simulink model is used to validate the results of MAOA tuned BLDC drive.

Development of Assistance Level Adjustment Function for Variable Load on a Forearm-Supported Robotic Walker.

With the progression of an aging society, the importance of walking assistance technology has been increasing. The research and development of robotic walkers for individuals requiring walking support are advancing. However, there was a problem that the conventional constant support amount did not satisfy the propulsion force required for the walking speed that users wanted. In this study, in order to solve this problem, we propose an algorithm for determining the support amount to maintain the walking speed when the average walking speed of each user is set as the target speed. A robotic walker was developed by attaching BLDC motors to an actual walker, along with a control algorithm for assistance based on sampling-type PID control. The effectiveness of the assistance determination algorithm and the usefulness of the parameters were demonstrated through experiments using weights loaded on the forearm support and target speeds. Subsequently, subject experiments were conducted to verify the ability to maintain target speeds, and a questionnaire survey confirmed that the assistance did not interfere with actual walking. The proposed algorithm for determining the assistance levels demonstrated the ability to maintain target speeds and allowed for adjustments in the necessary level of assistance.

An Optimized PID Controller Desing for BLDC Motor Using Nature-Inspired Algorithms

For the optimal control of speed in a brushless DC motor, it is crucial to appropriately adjust the parameters of the PID controller. This study addresses the determination of PID controller parameters using nature-inspired metaheuristic optimization algorithms. Initially, the dynamic model of the brushless DC motor is formulated in the MATLAB/Simulink environment. The grey wolf optimization algorithm, whale optimization algorithm, and firefly algorithm are successively applied to the simulation model to optimize the PID controller parameters. The integral time absolute error objective function is utilized to compare the error performances of these algorithms. Additionally, performance evaluations are conducted concerning parameters such as rise time, settling time, and maximum overshoot. As a result of the comparison based on the fitness criteria, it was determined that the grey wolf optimization algorithm is 35% more successful than the algorithm that provided the next closest result.

Augmenting microgrid control with GHNO for efficient BLDC motor integration and renewable energy utilization

Augmenting microgrid control with GHNO for efficient BLDC motor integration and renewable energy utilization

AIFIS controlled BLDC Motor Drive for Agricultural Application with Solar System

In India, it is of utmost significance to ensure that the agricultural fields receive supplies of water. Agricultural applications are the focus of this paper, which depicts the implementation of an advanced BLDC motor connected drive that is controlled by an adaptive neuro fuzzy inference system (ANFIS). In this work, the implementation of the bidirectional power flow among the load and the renewable energy source (RES) is carried out. In order to power the water pump, renewable energy sources (RES) are generated through the use of solar photovoltaic (PV) cells. Additionally, a BLDC motor load is connected to the water pump through a single phase bi-directional converter and a voltage source inverter (VSI) inside the design. The PV system is able to get the maximum amount of power while simultaneously lowering the main grid and enabling consumers to run their motors and loads at their maximum efficiency throughout the entire day. This is made possible by the integration of fusing into the solar generating framework. Using the suggested controller, the PV system is able to reduce conversion costs and total harmonic content of the grid, all while maintaining the power factor, good quality in power, and stability of the system.

Investigation on Noise Reduction in BLDC Motors with Chain Stator Cores for Vacuum Cleaners

Investigation on Noise Reduction in BLDC Motors with Chain Stator Cores for Vacuum Cleaners

Adaptive PID controller based direct torque control of fuel cell fed BLDC drive for industrial drives applications

Fuel cell fed Brushless DC motors (BLDC) are widely used in electrical applications due to their more efficiency, simple and compact volume. With a simple traditional PID controller, it is challenging to adjust the settings and produce highlights with full power. In order to effectively regulate the torque and speed of a BLDC drive, the adaptive PID (APID) Controller based Direct Torque Control (DTC) is proposed in this paper. The proposed controller depended on the extra error of a spin around controller indication to understand non-linearity, parameter fluctuations, and burden transit difficulties that arise in the BLDC motor drive framework, to maintain good torque control performance, DTC is used as a suitable control technique in industrial drives systems. The comparison tests are step changes in the motor drive’s reference speed and torque. Simulations with MATLAB/Simulink and also experimental outcomes are utilized to validate the operation and performance of various vector control methods.

Finite-time adaptive control based on output feedback and auxiliary variables for time-varying parameters and disturbances

This paper presents a finite-time adaptive control scheme tailored for a diverse range of unknown discrete-time systems, with a specific emphasis on BLDC motor position control. The approach leverages an auxiliary variable within an output feedback framework, adeptly circumventing the causality problem without necessitating the use of state or disturbance observers. Through the application of finite-time convergence techniques, the control law demonstrates robust performance even in the presence of time-varying parameters and compact disturbances. Additionally, the proposed time-varying estimator, based on multi-input fuzzy emulated network (MiFREN), offers a practical solution for handling unknown dynamics and disturbances, making it well-suited for real-world applications where accurate mathematical models may be unavailable. Extensive experimental validation is conducted to evaluate the efficacy of the proposed scheme, including comparisons with existing controllers. The results highlight the superiority of the approach, particularly in terms of tracking accuracy and robustness against disturbances.

Designing Fuzzy Logic Control for the BLDC Motor Based on Airfoil Bearing

Due to removing the mechanical brushes in BLDC motors, BLDC motors are widely used in many industrial applications. Therefore, they are maintenance-free and their control is easy to design, especially for high-speed applications. For example, eco-friendly vacuum cleaners prevent atopic dermatitis, allergic rhinitis, and asthma. Other applications are Micro Gas turbines or compressors with small impellers due to miniaturization, BLDC motors must rotate at very high speeds to maintain the compressor's compression ratio. Generally, airfoil bearings should be used instead of ball bearings because of the friction in high-speed motors. Unfortunately, the characteristics of airfoil bearings depend on rotational speed. In this work, a BLDC motor with an airfoil bearing is controlled by a PID controller, this work analyzed the BLDC SYSTEM to determine the PID coefficient using the feedback method. The proposed controller Fuzzy Logic is used for adaptive control. In addition, the controller of BLDC motors combines auto-tuning and self-tuning technology. The results demonstrate that the proposed method gives efficient control by reducing the settling time and maximum peek overshot. The designed controller for the airfoil-bearing BLDC motor has a good performance.

Assessing the potential and energy distribution calibration of ethanol-biodiesel based RCCI mode of compression ignition engine in a plugin parallel hybrid electric vehicle

The focus of this research is to develop the resilient powertrain to combat the enforcement of stringent emission regulations and elevate its feasibility to power with the sustainable fuels to support the fuel crisis. The current solution in the reliable and adaptability point of view is the low temperature combustion engine-based hybrid electric powertrain powered with sustainable fuel is the better choice. The present work proposes the concept of an ethanol-biodiesel fuel based RCCI plugin parallel hybrid electric vehicles (PHEVs). The significant examination of this work in the aspects of optimal torque structure and injector control parameter calibration. The calibration of the RCCI engine torque structure operation is performed based on the multi-objective constraints of variance of indicated mean effective pressure and the maximum rate of pressure rise for the combustion stability. While the equivalence ratio and combustion temperature with emphasis on limiting the amount of NOx and soot emissions. The maximum ethanol energy share proportion of 66.98% has been achieved. The RCCI engine is most frequently operating in the torque zone of 10 Nm and then 17.81 Nm while the BLDC motor is most frequently operated in the range of 55 Nm even at max torque of 60 Nm. When comparing to a standard diesel hybrid setup, the ethanol-biodiesel fuelled RCCI setup has a 18%–19% reduction in harmful NOx emissions, with an equivalent decrease of 22.7% in fuel economy. This is achieved by only having a 13.4% more CO emission while a minimal increase in soot emission throughout the overall course of the driving cycle. The result of this work shows evidence that implementing an ethanol-biodiesel fuelled RCCI engine in a parallel hybrid configuration achieves a significant reduction in NOx emissions while achieving the performance targets and managing the fuel and battery energy utilization over a driving cycle efficiently.

High speed BLDC motor for grid tied PV based EV system using hybrid PSO-spotted hyena optimized PI controller

High speed BLDC motor for grid tied PV based EV system using hybrid PSO-spotted hyena optimized PI controller

A new wedge shaped inner rotor for a BLDC motor: Performance analysis

Recently, Permanent Magnet Brushless DC (PM-BLDC) motor has emerged as the best magnetic motor for EVs due to its superior power density and high torque. The effects of leakage flux, cogging torque and vibration are the important key challenges in the PM-BLDC motor which deteriorate the performance of the motor. To address these issues, this study proposes the new model of PM-BLDC motor with a wedge-shaped PMs on the inner rotor core. This work proposes a new rotor design with the aim of decreasing the torque ripple and cogging torque. The proposed wedge-shaped PMBLDC motor’s performance is analysed for varying turns and compared to the circular and V-shaped PMBLDC motors using Finite Element Analysis (FEA) based MagNet tool. The position of the different shaped PMBLDC motors on the rotor is evaluated in terms of cogging torque, current density, copper loss, and iron loss. The vibration analysis is carried out by FEA based ANSYS CAD Software for detecting the mechanical issues in the proposed model.

Stator fault diagnosis of BLDC motor at varying speed operation using least square support vector machine

Stator fault diagnosis of BLDC motor at varying speed operation using least square support vector machine

Retraction Note: Deep perceptron neural network with fuzzy PID controller for speed control and stability analysis of BLDC motor

Retraction Note: Deep perceptron neural network with fuzzy PID controller for speed control and stability analysis of BLDC motor

Optimizing BLDC Motor Performance with Advanced Fuzzy Logic PID Controller under Dynamic Load Condition

Optimizing BLDC Motor Performance with Advanced Fuzzy Logic PID Controller under Dynamic Load Condition