Hybrid Computational Mechanical Sensorless Fuzzified Technique for Speed Estimation of Permanent Magnet Direct Current Brushed Motor

This paper proposes a novel fuzzified mechanical sensorless speed estimation technique for permanent magnet direct current (PMDC) brushed motor operated with pulse width modulation (PWM) based terminal voltage. For replacement of conventional mechanical speed sensors, few mechanical sensorless speed estimation techniques have been reported recently in the field of PMDC brushed motor. In this paper, a novel technique is applied over a recently reported semianalytical dynamic time-domain PMDC brushed motor model incorporating space-domain effects, namely slotting effect and commutation phenomenon to simulate the proposed estimation process. Ripple and back electromotive force based standalone estimation approaches are hybridized in order to eliminate uncertainties in all regions of estimation. In this paper, a discrete fuzzified hybrid speed estimation model has been proposed with adequate dynamic simulation responses. Further the proposed discrete speed estimation model has been applied experimentally over a PWM-driven 24-V, 12-teeth, 100-W PMDC brushed motor and various dynamic real-time responses have been compared with conventionally captured speed samples to validate the proposed model.