Simulation Research of Fault Model of Detecting Rotor Dynamic Eccentricity in Brushless DC Motor Based on Motor Current Signature Analysis

基于Ansoft／Maxwell设置动态偏心故障，建立求解电机电感和磁链的有限元模型，通过仿真，证明了将感应电机动态偏心故障的特征频率经过简化后，同样适用于无刷直流电动机。基于Ansoft／Simplorer建立无刷直流电动机系统的仿真模型。在电机稳态运行下，对定子电流进行傅里叶分析，研究并建立基于定子电流监测动态偏心故障的仿真模型：动态偏心故障与特征频率的关系、动态偏心故障程度与特征频率幅值的关系。进而研究了无刷直流电动机稳态运行时转速波动对偏心故障监测的影响。仿真结果表明，转子偏心程度加大，特征频率的幅值增加。

基于模糊BP神经网络的智能轮椅BLDCM控制

现阶段多数轮椅电机仍使用传统PID控制,该控制方式存在控制精准度较低、超调量较大以及抗扰动能力差等问题。为解决以上问题,通过对无刷直流电机进行研究,在分析了其控制方法后,提出一种基于模糊BP神经网络的BLDCM控制方法。首先,研究了BLDCM结构并搭建数学模型。其次,在模型基础上构建了模糊BP神经网络PID控制器。最后,在Matlab/Simulink中搭建整个电机控制系统进行三种不同工况下的运动控制仿真,并与传统PID控制算法进行对比。实验结果表明:模糊BP神经网络PID控制策略能获得更好的PID控制参数,具有良好的抗扰动能力,有效的改善了整个轮椅控制系统的动态性能。

Robust Control Strategy for the Speed Control of Brushless DC Motor

Brushless DC motor ( BLDCM) speed servo system is multivariable,nonlinear and strong coupling. The parameter variation, the cogging torque and the load disturbance easily influence its performance. Therefore,it is difficult to achieve superior performance by using the conventional PID controller. To solve the deficiency,the paper represents the algorithm of active-disturbance rejection control ( ADRC) based on back-propagation ( BP) neural network. The ADRC is independent on accurate system and its extended-state observer can estimate the disturbance of the system accurately. However,the parameters of Nonlinear Feedback ( NF) in ADRC are difficult to obtain. So in this paper,these parameters are self-turned by the BP neural network. The simulation and experiment results indicate that the ADRC based on BP neural network can improve the performances of the servo system in rapidity,control accuracy,adaptability and robustness.

An Advance Commutation Control Method for Low Torque Ripple of Brushless DC Motors

该文给出一种优化的无刷直流电动机变母线电压六拍控制方法。既解决了传统六拍控制策略中由于绕组电感所造成的电流滞后问题,又改善了由于换相所造成的电流脉动问题。该方法是通过在每两拍之间插入一小段缓冲区来实现的,该缓冲区使下一拍将要切入的电流提前切入,同时使当前拍将要切出的电流延迟切出。通过确定缓冲区的起始位置,即超前换相角的大小,保证每一拍所对应的相电流的中心和反电动势的中心重合。通过选取缓冲区开关器件PWM调制的占空比,降低电机运行过程中的换相转矩脉动。该文方法只需根据负载大小选取超前换相角,一旦选定适用于所有转速。文中给出了该方法的理论推导过程和实验验证波形,从实验结果可以发现,电流滞后被消除,换相电流脉动显著减小,电机的利用率得到提高。

Comparative Study between the PID Regulator and the Fuzzy Regulator Applied to the Operation of a Brushless DC Motor

This paper presents the results of research on speed regulation of a brushless DC motor. This is mainly a comparative study between a PID regulator and a fuzzy regulator applied to the operation of this type of engine in order to find the best control. The BLDC engine must operate under various speed and load conditions with improved performance and robust and complex speed control. Because of this complexity, the traditional PID command encounters difficulties in controlling the speed of a BLDC. Another control technique is currently developing and is producing good results. This is the fuzzy controller that handles process control problems, that is, managing a process based on a given set point per action on the variables that describe the process. To achieve the desired results, the brushless DC machine model will be studied. With the model obtained, both types of regulator will be tested. A synthesis of the observed comparison results will enable a conclusion to be drawn on the performance of the two types of regulators driving a BLDC (Brushless DC).

基于参数自整定模糊PID的BLDC控制研究

为解决传统PID控制在无刷直流电机调速系统中的控制精度低、效果不佳等问题,设计了一种基于参数自整定模糊PID控制的调速系统。通过在Matlab/Simulink仿真软件中建立了无刷直流调速系统的模型,分别采用传统PID控制、模糊PID控制和参数自整定模糊PID控制来对转速环进行调控,而电流环则采用PID控制。通过对比研究结果发现,采用参数自整定模糊PID控制的调速系统具有许多优势。系统的超调量较小,控制效果较好,同时提高了系统的鲁棒性。通过搭建模型并进行仿真实验,证明了采用参数自整定模糊PID控制的调速系统在解决无刷直流电机调速系统控制精度低、效果不佳等问题方面具有优势。这一方法能够有效提升系统的控制性能,并增强系统的鲁棒性。该无刷直流电机的调速系统可以稳定、可靠运行,满足使用需求。

A neural network-based commutation optimization strategy and drive system design for brushless DC motor

An optimized commutation method based on backpropagation(BP)neural network is proposed to resolve the low stability and high-power consumption caused by inaccurate commutation point prediction in conventional commutation strategy during acceleration and deceleration.This article also builds a complete brushless DC motor drive system based on the GD32F103 micro control unit(MCU),with an Artix-7 XC7A35T field programmable gate array(FPGA)to meet the performance requirements of neural network calculation for real-time motor commutation control.Experimental results show that the proposed optimization strategy can effectively improve the system stability during system acceleration and deceleration,and reduce the current spikes generated during speed chan-ges.The system power consumption is reduced by about 11.7%on average.

Design and implementation of a position sensorless control method for brushless DC motors

Because brushless direct current(BLDC) motors have the advantages of a compact size, high power density, high efficiency, and long operating life time, they are widely used in many industrial products and electric traction systems. It is known that the BLDC motors have no brushes for commutation. They are commutated with electronically commutation. So, the rotor position information of the BLDC motors must be known to understand which winding will be energized according to the energizing sequence. In most of the existing BLDC motor drivers, rotor position information is detected by Hall effect sensors. This kind of mechanical position sensors will bring additional connections and costs, reliability decrease and noise increase. In order to improve the control performance and extend the range of speed regulation for BLDC motors, a position sensorless control method is proposed in this paper. In the proposed control method, rotor position information of the BLDC motors is detected from the back electromagnetic forces(back-EMFs) which are estimated by an unknown-input observer with line to line currents and line to line voltages. For the purpose of verifying the effectiveness of the proposed control method, a model is built and simulated on the Matlab/Simulink platform. The simulation results show that the speed regulation performance of BLDC motors is improved compared with using Hall effect sensors. At the same time, the reliability of the BLDC motors is improved and the costs of them are reduced because the position sensor is eliminated.

High temperature brushless DC motor system and its operation mode control

The high temperature (175 ℃) operation of a motor spells out special requirements for control algorithms, materials and elements. The stability of motor characteristic is guaranteed by the digital control strategy. Constant velocity operation is achieved by phase locked loop (PLL), and constant power operation is achieved by a current restricting circuit. A motor for constant speed and constant power operation has been built and the speed control system is tuned by MATLAB simulation. Experimental and simulation results for operation mode control of brushless DC motor are presented.

Analysis of torque-current characteristic of brushless DC motor driven by three-phase H-bridge

Presents the simulation and analysis of the steady state characteristic of a brushless DC motor studies the torque current characteristic of the motor as well and discusses the design of a current measure circuit for torque controlling.

开绕组BLDCM直接转矩控制电压矢量特性研究

基于直接转矩控制(DTC)的开绕组无刷直流电机(BLDCM)具有运行效率高、电压矢量多样、控制结构简单等优点,适用于工业领域。根据共直流母线开绕组BLDCM控制拓扑搭建了相应的数学模型,对该拓扑下电压矢量的特性进行理论分析及分类,并将电压幅值不为零的电压矢量分为大、中、小三类。分析结果表明:在相同的运行条件下,大矢量作用下转矩变化率最大,小矢量作用下转矩变化率最小,中矢量居于两者之间。仿真结果验证了理论分析的正确性和控制方法的可行性。

Analysis of Torque Ripple of Permanent Magnet Brushless DC Motor

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Analysis of the Magnetic Flux Density, the Magnetic Force and the Torque in a 3D Brushless DC Motor

As permanent magnet motors and generators produce torque, vibration occurs through the small air gap due to the alternating magnetic forces created by the rotating permanent magnets and the current switching of the coils. The magnetic force can be calculated from the flux density by finite element methods and the Maxwell stress tensor in cy-lindrical coordinates. In this paper the magnetic flux density, the magnetic force and the torque of a real three dimen-sional brushless DC motor are simulated using Maxwell 3 D V 11.1.

Temperature Research of Permanent Magnet Brushless DC Motor for Electric Balanced Vehicle

A power system structure composed of a brushless DC motor and a cycloidal reducer for electric balanced vehicle has been proposed, and the temperature of important components in this structure would be discussed. The loss generated by the cycloid reducer is negligible, it’s only need to analyze the thermal field of motor. Since the temperature change will affect the material properties of the target motor, the electromagnetic and temperature fields, involved in the motor, are selected for coupling calculation to determine whether the final temperature distribution can meet the requirements of vehicle for use.

Sensorless Control of Four-Switch Inverter for Brushless DC Motor Drive and Its Simulation

The major function of this proposed research is to control the speed of the brushless DC motor with sensor less control for four-switch three phase inverter. This proposed system is simplified the topological structure of the conventional six-switch three phase inverter. In this proposed method, a new structure of four-switch three phase inverter [1] with reduced number of switches for system is introduced to reduce the mechanical commutation, switching losses that occur in the six-switch method. The proposed inverter fed brushless DC motor used in sensorless control schemes which is used for sensing positioning signals. To improve sensor less control performance, four-switch electronic commutation modes based proportional intergral controller scheme is implemented. In this four-switch three phase inverter reduction of switches, low cost control and saving of hall sensor were incorporated. The feasibility of the proposed sensor less control four-switch three phase inverter fed brushless DC motor drive is implemented, analysed using MATLAB/SIMULINK, effective simulation results have been validated out successfully.

Solar PV System for Energy Conservation Incorporating an MPPT Based on Computational Intelligent Techniques Supplying Brushless DC Motor Drive

This paper proposes an effective Maximum Power Point Tracking (MPPT) controller being incorporated into a solar Photovoltaic system supplying a Brushless DC (BLDC) motor drive as the load. The MPPT controller makes use of a Genetic Assisted Radial Basis Function Neural Network based technique that includes a high step up Interleaved DC-DC converter. The BLDC motor combines a controller with a Proportional Integral (PI) speed control loop. MATLAB/Simulink has been used to construct the dynamic model and simulate the system. The solar Photovoltaic system uses Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) where the output signal governs the DC-DC boost converters to accomplish the MPPT. This proposed GA-RBF-NN based MPPT controller produces an average power increase of 26.37% and faster response time.

A New Method for Reducing Commutation Torque Ripples in BLDC Motors

A new compensation method and an algorithm for compensating for the commutation torque ripples of the trapezoidal EMF brushless DC motor are put forward. Simulation and experimental results show that this method is correct and practical.