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Abstract



Sensorless Control of a Hybrid Stepper Motor


Electrical drives are widely used in today’s society. They can be found in both household products and in the industry. One application where electrical drives are used is in robots for mowing lawns. In the studied robots the motors in the electrical drives used for propulsion are Brush Less Direct Current motors, BLDC- motors. The BLDC-motor has its maximum torque at high speeds and therefore a gearbox is needed. The gearbox is space consuming, add costs and consists of mechanical parts that wear during use. Of interest is therefore to investigate if there are other electrical drives which can be used for propulsion. A motor who has its maximum torque at low speeds is the Stepper motor, and therefore it is of interest to investigate if a stepper motor could replace the BLDC- motor. A drawback with the stepper motor is that it always consumes maximum current and therefore a current controller is beneficial. Together with current control, speed control is needed to make the robot run at desired speed. To be able to perform an accurate current and speed control feedback from the motor is needed. Information about the rotor angle and velocity can be used for the speed control and the load angle can be used for the current control since the current is proportional to the load torque. To estimate the rotor angle and velocity a model has been developed. The model is based on fundamental electrical and mechanical equations and neglects the current and position dependence of the inductance and flux linkage. To com- plete the model three motor parameters, the maximum detent torque Tdm , the maximum flux linkage ψm and the friction constant B was determined. Parameter determination was done by linear regression and by using an Extended Kalman Filter, EKF. The result of the parameter determination were Tdm = 0.2152 Nm, ψm = -0.002854 Vs/rad and B = 0.01186 Nms/rad. The model is used in an EKF to estimate the rotor angle and angular velocity. The result of the implemented EKF seems promising. When making the rotor take a step in velocity from 3.927 rad/s to 7.85 rad/s the EKF estimates the states with only a small bias: 0.02 rad for the angle, 0.3 rad/s for the velocity, 0.005 A for phase a current and 0.0004 A for phase b current. To estimate the load angle the Sliding Discrete Fourier Transform is used. The expected relation between the load torque and load angle is sinusoidal. The load angle is calculated from data where the external load is between 0-2.5 Nm. In that area the load angle shows the expected sinusoidal appearance and the load angle is in the area between 0.1 and 0.45 rad. At 3 Nm the rotor stalls and it is shown that the load angle varies between 0 and 2π rad when the rotor is stalled.

Lina Karlsson

2016

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