Field Oriented Control (FOC) based induction motor drive is a good choice for electric vehicles especially if we consider its low cost, due to the absence of permanent magnets. The control algorithm needs a good motor state variables estimation, such as a proper flux orientation, to assure full torque and power performances. Usually observers or estimators are adopted, but good results are strongly parameters dependent. In the induction machine control one of the most important parameter is the rotor resistance, that is temperature-dependent and therefore time-varying. The paper shows and compares three different Model Reference Adaptive System (MRAS) rotor resistance estimation methods, based on total active power, reactive power and motor torque. The algorithms have been studied by means of a rotor resistance uncertain of estimation based sensitivity analysis for different load and speed operating conditions. A simulation analysis has been proposed since the algorithm has been defined in order to operate under dynamic conditions, the typical situation during an electric vehicle drive cycle. A simple non linear variable structure MRAS has been adopted for assuring a good rotor resistance estimation convergence. Full theoretical analysis are reported for all the proposed methods.
A rotor resistance MRAS estimator for induction motor traction drive for electrical vehicles
MAPELLI, FERDINANDO LUIGI;BEZZOLATO, ALBERTO;TARSITANO, DAVIDE
2012-01-01
Abstract
Field Oriented Control (FOC) based induction motor drive is a good choice for electric vehicles especially if we consider its low cost, due to the absence of permanent magnets. The control algorithm needs a good motor state variables estimation, such as a proper flux orientation, to assure full torque and power performances. Usually observers or estimators are adopted, but good results are strongly parameters dependent. In the induction machine control one of the most important parameter is the rotor resistance, that is temperature-dependent and therefore time-varying. The paper shows and compares three different Model Reference Adaptive System (MRAS) rotor resistance estimation methods, based on total active power, reactive power and motor torque. The algorithms have been studied by means of a rotor resistance uncertain of estimation based sensitivity analysis for different load and speed operating conditions. A simulation analysis has been proposed since the algorithm has been defined in order to operate under dynamic conditions, the typical situation during an electric vehicle drive cycle. A simple non linear variable structure MRAS has been adopted for assuring a good rotor resistance estimation convergence. Full theoretical analysis are reported for all the proposed methods.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
