Priyadarshini College of Engineering Nagpur, India
Priyadarshini College of Engineering Nagpur, India
Brushless DC drive has distinct advantages of high efficiency, high power density, high power factor, high torque, simple control, and minimal maintenance. Modelling, simulation of BLDC drive control schemes is presented in this paper. This paper describes modelling of four switch inverter fed BLDC motor and explained with transfer function model. The simulation of sensor and sensor less control of drive is done in Matlab/Simulink. In sensor Control, the controller is used Fuzzy logic Controller/PI Controller and in sensor less control the method used is terminal voltage method.
Keywords- BLDC Drive; PI Controller; Fuzzy Controller; Inverter.
A brushless DC motor (BLDC) is asynchronous electric motor which is powered by direct current electricity (DC) and has an electronically controlled commutation system, instead of a mechanical commutation system with brushes. It has all the good advantage of DC drives and eliminating the drawbacks using electronic commutation. So in this motor current and torque, voltage and rpm are related linearly. Normally from the Hall Effect sensor, the signal for commutation is generated. But using these sensors the size of the BLDC motor will become larger and when space will be a main constraint, BLDC motor fails to meet the same. BLDC Motors are extensively used in domestic and automobile industries. Cost reduction in BLDC motor drives can be achieved by two methods one topological approach and second control approach. In the topological approach, the number of switches, sensors and associated circuitry used to compose the power converter is minimized. Normally for the BLDC Motor drive six switches inverter topology is used. By reducing the no of switches the cost reduction can be achieved. Moreover switching and conduction losses can be reduced. So here Four Switch VSI (FSVSI) topology is attempted. By using the Sensor less control the cost of the sensors are also eliminated.
Modelling of the BLDC machine and the controller are essential for evaluating their performance. Each of the simulators allows setting of the input parameters. In this work the modelling of BLDCM is explained with transfer function model. The simulation of sensor and sensor less control of drive is done in Matlab/Simulink. Control with sensor, the controller is used by Fuzzy / PI Controller and in sensor less control the method is used terminal voltage sensing.
II. PROPOSED SPEED CONTROL SCHEME OF SENSORLESS BLDC MOTOR DRIVE
The proposed scheme for the Sensor less BLDC motor drive fed by a Zeta based PFC converter operating in DICM mode. The front end Zeta DC-DC converter maintains the DC link voltage to a set reference value. Switch of the Zeta converter is to be operated at high switching frequency for effective control and small size of components like inductors. A sensor less approach is used to detect the rotor position for electronic commutation. A blind startup is used for starting the BLDC motor. A high frequency MOSFET of suitable rating is used in the front end converter for its high frequency operation whereas an IGBT’s (Insulated Gate Bipolar Transistor) are used in the VSI for low frequency operation. The proposed scheme maintains high power factor and low THD of the AC source current while controlling rotor speed equal to the set reference speed. A voltage follower approach is used for the control of Zeta DC-DC converter operating in DICM.
The DC link voltage is controlled by a single voltage sensor. Vdc (sensed DC link voltage) is compared with Vdc* (reference voltage) to generate an error signal which is the difference of Vdc* and Vdc. The error signal is given to a PI (Proportional Integral) controller to give a controlled output. Finally, the controlled output is compared with the high frequency saw tooth signal to generate PWM (Pulse Width Modulation) pulse for the MOSFET of the Zeta converter. A rate limiter is used to limit the stator current during step change in speed.
III. TRANSFER FUNCTION MODEL
The dynamics of the machine are described by a set of differential equations. The electrical and mechanical equations can be obtained from the equivalent circuit. To attain the electrical equations for a BLDC machine, basic circuit analysis was used to find the per-phase voltage as shown below. The equation is only shown for phase-A to neutral since the equations for phase B and C only differ in the subscript notation.
The circuit equation of the motor in phase variable form are given in equation (1) where Van the applied phase voltages, ea is the induced back emf, ia is the phase currents. La, is the sel finductances of the phases and Ra is the resistance of each phase. The mechanical equation that relates the machine’s angular velocity to the developed electromagnetic torque, load torque, and motor parameters is given in equation.
where Tem(t) is developed electro-magnetic torque, TL is load torque, B is viscous friction constant, J is rotor moment of inertia, W is the angular speed of the motor.
But we know that Electromagnetic torque and back emf are given by equations
Taking Laplace transformation of the respective equations and rearranging the terms equations
From the above equations it is possible to draw the model of the BLDC motor. Transfer function of the system is presented
IV. SENSOR LESS CONTROL
A low cost BLDC motor drive with reduced parts that is by reducing the number of switches from six to four is to be developed. The implementation of a low cost, reduced parts BLDC motor is desired with high system reliability. Most of the sensors less methods for a six-switch inverter BLDC motor drive are not directly applicable to the four-switch inverter [6-10]. The main reason is that in the four-switch topology, some methods detect less than six points, and other commutation instants must be interpolated via software. This paper presents a novel sensor less method for four-switch BLDC motor drive based on zero crossing points of stator line voltages.
V. FUZZY LOGIC CONTROLLER
Fuzzy logic controller is used for simulation of BLDC Motor with sensor. Three hall effect sensors are connected the other end of the motor and they are separated by 120 degree mechanically. A Fuzzy Logic Controller (FLC)[11-12] uses fuzzy logic as a design methodology, which can be utilized for developing linear and non-linear systems for embedded control. FLC techniques need less development time, have better performance and are good replacements for conventional control techniques, which require highly complicated mathematical models. A fuzzy logic controller does not require an exact mathematical model. It however requires knowledge-based set of heuristic rules. These rules variables. The steps involved in the design of fuzzy controller are fuzzification, rule definition and defuzzification.
For the fuzzy controller necessary data required for the simulation is given in Table 1. The two inputs given are error and change in error. The output is the reference current for the Hysteresis controller. All three membership functions are Triangular. The input and output membership functions are shown in Figures 10 to 12. The fuzzification rule is entered using the rule editor of the fuzzy toolbox as shown in Figure 13. The simulation diagram is shown in Figure 14. The overall simulation diagram with controller, four-switch inverter and BLDC motor model.
VI. PI CONTROLLER
Two controllers are incorporated: PI controller for speed control and P controller for current control. The feedback measures the actual speed and subtracted from reference speed and error is given as input to the speed PI controller and output of the PI is subjected to current limiter and that acts as current reference from which actual current is subtracted and error is given input to the current P controller. This output of the PI is the dc value that is compared with a continuous triangular pulse of 40 kHz. The output is varying duty cycle that is added with gate pulse to produce a pulse-modulated wave, which triggers the inverter to generate required voltage to maintain the speed at varying load torques and speed reference conditions.
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