Control of SRM of Flywheel Energy Storage Drive

Review of speed estimation algorithms for three- phase induction motor

“…Since linearity is crucial to the KF's derivation and effectiveness as an optimum filter, it is not technically applicable to nonlinear problems. In an attempt to solve this issue, the Extended Kalman Filter (EKF) implements an approximating linearization, where the linearization is implemented around the current state estimate [ [15] , [16] , [17] , 22 , 24 ]. This procedure needs discretization of above equations as in Eqs.…”

“…Using the above mathematical expressions, the motor model reconstructed in discrete form. The following EKF algorithm can be applied in estimating the rotor speed and flux of rotor [ [15] , [16] , [17] , [18] , 21 , 22 ]. Estimated output of state equation is at the instant (k+1/k+1) by a difference among their estimated values and measured value at the instant (k+1) is: …”

“…Stator current, voltage, and back electromotive force (EMF) or flux are typical estimation parameters [ 9 , 10 ]. The first technique depends on machine model comprising the Model Reference Adaptive System (MRAS) [11] , [12] , [13] , [14] , Extended Kalman Filtering approaches (EKF) [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , Speed Estimators (SE) [25] , [26] , [27] , [28] , Sliding Mode Observer (SMO) [ 26 , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] ], reduced order nonlinear observer [ 23 , [36] , [37] , [38] ], Artificial Intelligence methods (AI) [39] , [40] , [41] , [42] , [43] , Direct calculation and Adaptive observers [44] , [45] , [46] , [47] , [48] . These techniques use motor mathematical models that makes use of stator current and voltage measurements and the motor model to estimate rotor speed.…”