PERFORMANCE ANALYSIS OF FUZZY BASED FIELD ORIENTED CONTROL OF INDUCTION MOTOR DRIVES FOR HYBRID ELECTRIC VEHICLES

Induction motors (IMs) have widely been regarded as one of the most suitable options in automotive industry for electric propulsion systems of hybrid electric vehicles (HEVs) due to their reliability, ruggedness and low cost. In the past, poor dynamic response of IMs was a key constraint that limited their capability in applications that require speed tracking and fast positioning. However, the development of field oriented control made it possible to decouple the stator current into flux and torque producing components, enabling an independent command on the motor torque for a simpler, more accurate speed control. Design of a field oriented controller requires the knowledge of the phase angle of rotor flux. Indirect field oriented control (IFOC) is a method to determine this phase angle by estimation which eliminates the requirement of additional sensors. However this estimation increases the complexity and the computation time of the control system. Fuzzy logic offers an alternative technique to design such a control system by making decisions based on human expertise, thus avoiding complex calculations. This paper describes the implementation of IFOC using both a conventional PI as well as a fuzzy based controller to compare their performance. Since a fuzzy based control does not depend on machine equations and performs on the basis of linguistic if-else decisions, it produces a faster speed response. Moreover, the torque and speed oscillations were observed to be much lower, as desired in an HEV drive train.