This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

Abstrac/-Currently, for many applications, it is necessary to know the speecl and position oF motors. This can be achievecl nsing mechanical sensors coupled to the motor shaFt or using sensorless technic¡ues. The sensorless technic¡ues in brushed de motors can be classifiecl into two types: 1) technic¡ues basecl 011 the clynamic brushed de motor moclel ancl 2) technic¡ues basecl 011 the ripple componen! oF the curren!. This paper presents a new methocl, based on the ripple component, for speed ancl position estimation in brushed de motors, using support vector machines. The ¡>roposecl methocl only measures the curren! and detects the pulses in this signal. The motor speed is estimated by using the inverse clistance between the cletected pulses, and the position is estimat. ed by counting ali detected pulses. The ability to cletect ghost pulses and to discard false pulses is the main aclvantage oF this methocl over other sensorless methods. The perFormed tests on two fractional horsepower brushed de motors inclicate that lile methocl works correctly in a wicle range oF speeds ami situations, in which the speed is constan! or varíes clynamically. lndex Terms-Brushed de motor, curren! ripple, de motor, pattern recognition, position, sensorless, speed, support vector machines (SVMs). l. INTRODUCTIONS ENSORLESS techniques estímate the speed and position of motors without mechanical sensors coupled to the motor shaft, measuring only the current and/or the voltage of the mo tors. Sensorless techniques are not a recent idea. as is evidenced by the work of Allured and Strzelewigz [ 1 ]. Nevertheless, due to the complexity of these methods, they have not yet re placed conventional sensors such as encoders, potentiometers, lachometers, Hall effect sensors, or other mechanical sensors coupled to the motor shaft. The main advantages of these, compared to conventional sensors, are as follows: 1) decreased maintenance, number of connections. and cost of the final

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-The detection of position and speed in BLDC motors without using position sensors has meant many efforts for the last decades. The aim of this paper is to develop a sensorless technique for detecting the position and speed of BLDC motors, and to overcome the drawbacks of position sensorbased methods by improving the performance of traditional approaches oriented to motor phase voltage sensing. The position and speed information is obtained by computing the derivative of the terminal phase voltages regarding to a virtual neutral point. For starting-up the motor and implementing the algorithms of the detection technique, a FPGA board with a real-time processor is used. Also, a versatile hardware has been developed for driving BLDC motors through pulse width modulation (PWM) signals. Delta and wye winding motors have been considered for evaluating the performance of the designed hardware and software, and tests with and without load are performed. Experimental results for validating the detection technique were attained in the range 5-1500 rpm and 5-150 rpm under no-load and full-load conditions, respectively. Specifically, speed and position square errors lower than 3 rpm and between 10º-30º were obtained without load. In addition, the speed and position errors after full-load tests were around 1 rpm and between 10º-15º, respectively. These results provide the evidence that the developed technique allows to detect the position and speed of BLDC motors with low accuracy errors at starting-up and over a wide speed range, and reduce the influence of noise in position sensing, which suggest that it can be satisfactorily used as a reliable alternative to position sensors in precision applications.

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