Evaluation of demodulation algorithms for robust self-sensing active magnetic bearings

Abstract

Active magnetic bearings (AMBs) play a key role in various industrial applications. In the ongoing challenge to reduce the number of external sensing devices and manufacturing costs of AMBs, self-sensing techniques have positioned themselves in a dominant role to provide sensorless estimation of rotor displacement. A self-sensing arrangement employs an estimation algorithm that uses the modulated coil voltage and current signals to determine the air gap information. However, filters in the demodulation path of the estimator introduce additional phase-shift that results in lower achievable stability margins. Furthermore, a disadvantage of modulation self-sensing approaches is that the position estimates are nonlinearly dependent on the power amplifier voltage duty cycle. This paper firstly evaluates the static and dynamic performance of different demodulation techniques via an experimentally verified transient simulation model. The direct current measurement (DCM) approach, which comprises a minimum number of filters, is proposed for position estimation of self-sensing AMBs. The DCM algorithm incorporates a novel PA switching method that only uses the bearing coil currents as input. The estimator facilitates duty-cycle invariant position estimates with minimal additional phase-shift. According to simulated as well as experimental results, the sensitivity level of this estimator is the lowest compared to the other examined techniques. A practical implementation of the DCM approach shows that robust estimation can be realized for a 10 A magnetically coupled AMB that lends itself to industrial application