In industrial drives market, speed and position estimation are one of the most important subjects for accurate motor drives. Vector controlled drives has the best dynamic performance among AC motor drives. Sensorless vector control is one of the most studied one. However, sensorless drive systems fail at low or zero speeds and may not have enough accuracy. For better accuracy and speed range speed sensors or position encoders are usually essential. However, coupling of sensor and sensor prices introduces extra cost on the drive. Thus in order to reduce the cost of the drive a cheap and easy to mount speed sensor is essential. Throughout this study, a speed and position sensor using an external search coil placed between cooling fins on the frame of an induction machine is proposed. The search coil utilizes the fringing flux outside the frame of induction motor. Using the induced voltage on the external search coil, a new method that estimates the flux and rotor position is proposed. In this study, the induced voltage on the search coils are investigated with different types of search coils placed on various positions. The frequency domain and time domain analysis are performed in order to build a model that can estimate machine flux, rotor speed and rotor position. As a result of this study, a low cost, easy to mount speed and position sensor is designed and implemented. Experiment results are presented.

The organic materials used for stator winding insulation are subject to deterioration from thermal, electrical, and mechanical stresses. Stator winding insulation breakdown due to excessive thermal stress is one of the major causes of electric machine failures; therefore, prevention of such a failure is crucial for increasing machine reliability and minimizing financial loss due to motor failure. This work focuses on the development of an efficient and reliable stator winding temperature estimation scheme for small to medium size mains-fed induction machines. The motivation for the stator winding temperature estimation is to develop a sensorless temperature monitoring scheme and provide an accurate temperature estimate that is capable of responding to the changes in the motors cooling capability. A discussion on the two major types of temperature estimation techniques, thermal model-based and parameter-based temperature techniques, reveals that neither method can protect motors without sacrificing the estimation accuracy or motor performance. Based on the evaluation of the advantages and disadvantages of these two types of temperature estimation techniques, a new online stator winding temperature estimation scheme for small to medium size mains-fed induction machines is proposed in this work. The new stator winding temperature estimation scheme is based on a hybrid thermal model. By correlating the rotor temperature with the stator temperature, the hybrid thermal model unifies the thermal model-based and the parameter-based temperature estimation techniques. Experimental results validate the proposed scheme for stator winding temperature monitoring. The entire algorithm is fast, efficient and reliable, making it suitable for implementation in real time stator winding temperature monitoring.