An Application of the Extended Kalman Filter for a Sensorless Stepper Motor Drive Working With Long Cables

Estimation of stepping motor current from long distances through cable-length-adaptive piecewise affine virtual sensor

“…The motor-side estimated current obtained with the estimator in [2] in MATLAB double precision is shown in Figure 7 for comparison. The RMS estimation error is 0.0454 A.…”

“…Depending on the application, this extra effort may not be worth the small increase in estimation precision. Figure 8 shows the estimation errors for both estimators, PWAS virtual sensor (blue curve) and estimator in [2] (red curve). Mean value and variance are -0.017 and 0.007, respectively, for the PWAS case and 2.5 10 -3 and 2.1 10 -3 , respectively, for the case in [2].…”

“…A sensorless driver, based on an extended Kalman Filter (EKF), which can work with arbitrarily long power cables between the driver and motor has been developed in [2].…”

“…However, as previously stated, these signals are not directly available in ordinary operation since measurements can only be made on the drive side of the cable. In [2] a cable model is used to obtain a transfer function relating the motor-side current to the driverside current. The current is therefore estimated by means of a digital filter whose coefficients can be easily adapted to the used cable.…”

“…An alternative solution (reduced-complexity virtual sensor) leading to a complexity reduction has been proposed in [6] and [7]. The method used for estimation of the motor-side currents in [2] is based on an approximation of a first principles model of the dynamical system relating the drive-side current to the motorside current. It therefore requires multiple, time intensive steps of modelling, parameter estimation and approximation to produce a real-time implementable, reduced-order estimator.…”