Back EMF Observer Based Sensorless Four Quadrant Operation of Brushless DC Motor

Transcription

1 Back EMF Observer Based Sensorless Four Quadrant Operation of Brushless DC Motor Sanita C S PG Student Rajagiri School of Engineering and Technology, Kochi sanitasajit@gmail.com J T Kuncheria Professor Rajagiri School of Engineering and Technology, Kochi kuncheriajt@rajagiritech.ac.in Abstract Brushless DC (BLDC) motor drives are becoming more popular in industrial, traction applications. This makes the control of BLDC motor in all the four quadrants very vital- The motor is operated in four steady state operating modes of torque-speed plane. To control a BLDC machine it is generally required to measure the speed and position of rotor by using the sensor because the inverter phases, acting at any time, must be commutated depending on the rotor position. The position sensors make the motor system more complicated and mechanically unreliable. In Back EMF Observer based Sensorless Four Quadrant Operation of Three Phase BLDC Motor a Back EMF observer is employed to estimate the speed by using measurements of the stator line voltage and line current. Most existing sensorless methods of the BLDC motor have low performance at transients or low speed range and occasionally require an additional circuit. To overcome this problem, the estimation of a back-emf is carried out by to improve the performance of the system. Sensorless control method can remove problem on manufacture that is happened in circuit to detect rotor position and speed. Moreover the production of inexpensive motor controller may be possible because the additional circuit such as encoder is not necessity. Simulation of the proposed model was done using MATLAB/ SIMULINK. Keywords:-BLDC motor, Four quadrant operation, regeneration, Sensorless, back emf observer, fuzzy estimator 1. Introduction The brushless DC motor has been used in many applications such as appliances, computers, automatic office machines, robots for automation of manufacturing products, drives of many electronics and minuteness machines. The BLDC motor has several advantages of the DC motor such as simple control, high torque, high efficiency and compactness. Also, brush maintenance is no longer required, and many problems resulting from the mechanical wear of brushes and commutators are eliminated by electronic commutation. To replace the function of commutators and brushes, the BLDC motor [1] requires an inverter and a position sensor that detects rotor position for proper commutation of current. Efforts have been made to make this motor cost effective and reliable by avoiding the use of position sensors and employing estimators. The brushless DC motor has trapezoidal electromotive force and quasi-rectangular current waveforms. Normally, sensors are used for the estimation of the speed and position of brushless DC motor. Due to increase in cost of the sensor and less reliability, the sensorless operation of brushless DC motor has attracted wide attention in industries. Many sensorless drive methods have been proposed for improving the performance of BLDC motors without a position sensor [2], [3]. The existing sensor less drive methods of the BLDC motor which are being widely used now, have low performance and occasionally require additional circuits. To overcome this problem, the estimation of a back-emf is carried out by fuzzy logic techniques to improve the performance of the system. Here, the fuzzy logic technique is used to estimate the speed of the BLDC motor under a variable and fixed condition of back-emf. Therefore, the correct back-emf estimation senses the position and speed of the BLDC motor. Recently, DC motors have been gradually replaced by BLDC motors as industrial applications require more powerful actuators in small sizes. Elimination of brushes and commutators also solves the problem associated with contacts and gives improved reliability and enhances life. The BLDC motor has low inertia, large power to volume ratio, and low noise when compared to the permanent magnet DC servo motor having the same output rating. Therefore, highperformance BLDC motor drives are widely used for variable speed drive systems of industrial applications. 2. BLDC Motor Drive System 2.1 Four Quadrant Operation There are four possible modes or quadrants of operation using a Brushless DC Motor which is depicted in Fig. 1. When BLDC motor is operating in the first and third quadrant, the supplied voltage is greater than the back emf which is forward motoring and reverse motoring modes respectively, but the direction of current flow differs. When the motor operates in the second and fourth quadrant the value of the back emf generated by the motor should be greater than the supplied voltage which are the forward braking and reverse braking modes of operation respectively, here again the direction of current flow is reversed. The BLDC motor is initially made to rotate in clockwise direction, but when the speed reversal command is obtained, the control goes into the clockwise regeneration mode, which brings the rotor to the standstill position. Instead of waiting for the absolute standstill position, continuous energization of the main phase is attempted. This rapidly slows down the rotor to a standstill position. Therefore, there is the necessity for determining the instant Page 1 of 5

2 when the rotor of the machine is ideally positioned for reversal. approximator that can estimate voluntary non-linear function is applied to the back-emf disturbance model. The structure of the proposed fuzzy back-emf observer is shown in Fig. 4. Fig.3 Back Emf Observer Fig.1 Four quadrant of operation 2.2 Proposed scheme The overall structure of the proposed Sensorless drive system is given in Fig. 2. The fuzzy logic back EMF estimator has two stages: first is the calculation and comparison of the currents, second is estimation of the change in back EMF and the Back EMF. The inputs of the fuzzy function are the line to line current error of the BLDC motor and the differential value of the error. Fig.2 Proposed scheme 2.3 Back EMF estimator The proposed method is based on the fact that the rotor position can be detected by using a trapezoidal back- EMF of BLDC motors. Since a back-emf of the BLDC motor is not measured directly, it is estimated by the unknown input observer. This unknown input observer is constructed by a back-emf regarded as an unknown input and state of the BLDC motor drive system. Since the neutral point of the BLDC motor is not offered, it is difficult to construct the equation for one phase. Therefore, the unknown input observer is considered by the following line-to-line equation: d 2R 1 1 I ab I ab V dt 2L 2L ab 2L eab Iab and Vab can be measured, therefore they are known state variables. On the other hand, since eab cannot be measured, this term is considered as an unknown state. The equation (7) can be rewritten in the following form: dx Ax Bu Ew dt y Cx This disturbance model cannot exactly represent the back-emf of trapezoidal shape, so a fuzzy function Fig.4 Membership Function (a) Error (b) Change in Error (c) Output The fuzzy function includes three stages: fuzzification, inference mechanism and de-fuzzification. Zero: Z, Positive Big: PB, Positive Medium: PM, Positive Small: PS, Negative Big: NB, Negative Medium: NM, Negative Small: NS. Fig. 4. The value of the fuzzy output is determined using a rule base Table 1. The approximation law of the fuzzy function approximator contains 49 rules. Table.1 Fuzzy Rule CE E NB NM NS Z PS PM PB NB NB NB NB NB NM NS Z NM NB NB NB NM NS Z PS NS NB NB NM NS Z PS PM Z NB NM NS Z PS PM PB PS NM NS Z PS PM PB PB PM NS Z PS PM PB PB PB PB Z PS PM PB PB PB PB Page 2 of 5

3 2.4 Speed and Position Estimation Relation between the back-emf and speed in BLDC motor is given by E k e e Where ke is back EMF constant 2.5 Speed Controller The speed controller module adopts discrete sliding mode control (SMC) algorithm. The inputs of the module are ωr* and ωr. ωr * is the reference signal and ωr is the feedback signal of the rotating speed. The output signal has negative saturated limiting value and positive saturated limiting value. The saturated limiting value is the maximum current value. 2.6 The reference current generator The reference current generating module has two inputs. One is the output of the speed control module Is* and the other is the angular displacement signal of the rotor angle. The output of the module is the current of the threephase winding. 2.7 Hysteresis current controller Hysteresis current control is a PWM technique, very simple to implement and taking care directly for the current control. The switching logic is realized by three hysteresis controllers, one for each phase. The hysteresis PWM current control, also known as bang-bang control, is done in the three phases separately. Each controller determines the switching-state of one inverter half-bridge in such a way that the corresponding current is maintained within a hysteresis band. 2.8 Voltage Source Inverter The inverter supplies the input voltage for the three phases of the BLDC motor. It comprises of two power semiconductor devices on each phase leg. Appropriate pairs of MOSFET s (S1 to S6) are driven based on the switching states. Three phases are commutated for every 60 o. 3. Simulation Results With Simulation of the drive model with back EMF estimator is done in MATLAB/ SIMULINK. Runge-Kutta numerical integration method is used to get the solution of the equations. The transient and steady state responses of a 3 phase, 2.0 hp, 2 pole, 1500 rpm, 4 A PMBLDC motor are shown in Figures. The specifications of the PMBLDC motor are given in Table 2. Table.2 Motor Parameters No. of Poles 2 No. of Phases 3 Type of connection Star Rated Speed 1500 rpm Resistance/Ph 1Ω Back EMF Constant 0.41V-Sec/rad Self & Mutual Inductance H/phase Moment of Inertia 0.005kg/m2 Fig.5 Page 3 of 5

4 response of the drive with estimator under speed reversal. The drive takes.34sec to reach the set speed of -1500rpm. The response is smooth and no oscillation in the case of present control scheme. This is due to robust and accurate estimation of Back EMF by estimator. In the motoring mode, the back-emf magnitude increases until the steady state is reached and in braking mode back-emf starts decreasing towards zero. In the motoring mode, the corresponding back-emf and phase current is in phase. In braking mode the back-emf and phase current are out of phase. 4. Conclusions This paper proposed a back-emf observer that continuously estimates a back-emf of trapezoidal shape. A control scheme is proposed for BLDC motor to change the direction from CW to CCW and the speed control is achieved both for servo response and regulator response. The significant advantages of the proposed work are: reliability of the control algorithm, excellent speed control, smooth transition between the quadrants and efficient conservation of energy is achieved with and without load conditions. The technical validity of the proposed algorithm has been shown through simulation using the MATLAB. 5. References Fig.6 At initial conditions, the motor is operated in (Quad-I) Forward motoring mode. Fig. 5 shows the rotor speed, winding current, developed torque, back EMF and rotor position of the PMBLDC drive from standstill to a speed of 1500rpm. The EMF estimator estimates the back EMF of the BLDC drive which exactly matches with the actual back EMF. When a speed reversal command is issued, the motor undergoes braking operation in forward direction, with speed tending to zero and starts rotating in reverse direction as soon as the speed is zero. Fig. 6 shows the speed [1] Tavel, P Modeling and Simulation Design. AK Peters Ltd. [2] T. J. E Miller, Brushless Permanent Magnet and Reluctance Motor Drives, Clarendon Press, Oxford, [3] S. Ogasawara and H. Akagi, "An Approach to position sensorless drive for brushless DC motors," IEEE Trans. Ind. Appl., vol. 27, no. 5, pp , Sep./Oct [4] R. C. Becerra, T. M. Jahns, and M. Ehsani, "Fourquadrant sensorless brushless ECM drive," in Proc. IEEE Appl. Power. Electron. Conf., APEC 91, pp , [5] P. Yedamale, Microchip Technology Inc., Brushless DC (BLDC) motor fundamentals, 2003, AN885. [6] B. Singh and S. Singh, State of the art on permanent magnet brushless DC motor drives, J. Power Electron., vol. 9, no. 1, pp. 1 17, Jan [7] C. S. Joice and Dr. S. R. Paranjothi, Simulation of closed loop control of four quadrant operation in three phase brushless DC motor using MATLAB/simulink, in Proc. ICPCES, 2010, pp [8] L. H. Tsoukalas and R. E. Uhrig, Fuzzy and Neural Approaches in Engineering, John Wiley & Sons, Inc., [9] C. C. Lee, "Fuzzy logic in control systems: fuzzy logic controller-part I & Part II," IEEE Trans. Syst. Man. Cybern., vol. 20, no. 2, pp , Mar./Apr [10] Y. F. Li and C. C. Lau, "Development of fuzzy algorithms for servosystems," IEEE Control System Magazine, vol. 9, no. 2, pp , Apr [11] M. A. Akcayol, A. Cetin, and C. Elmas, "An education tool for fuzzylogic-controlled BDCM," IEEE Trans. on Education, vol. 45, no. 1, pp , Feb Page 4 of 5

5 [12] C. C. Lee, Fuzzy Logic in Control Systems: Fuzzy Logic Controller-Part I & Part II, IEEE Trans. Syst. Man. Cybern., vol. 20, no. 2, pp , March/April [13] V. U, S. Pola, and K. P. Vittal, Simulation of four quadrant operation & speed control of BLDC motor on MATLAB/SIMULINK, in Proc. IEEE Region 10 Conference, 2008, pp [14] C. S. Joice and Dr. S R Paranojothi, Digital control strategy for four quadrant operation of three phase BLDC Motor with Load variations; IEEE Trans. Industrial Informatics, vol. 9, n0. 2, May Page 5 of 5