Signal processing of the brushed DC motor current was developed in this paper to obtain information about a rotor speed from a measured motor current. The brushed DC motor current contains a signal with a frequency proportional to the rotor speed. This signal is the outcome of a commutation process occurring in the brushed DC motor, and it is called a ripple component. Since the number of ripples in the measured motor current per one rotation is constant, the rotor speed can be estimated. A discrete bandpass filter with a floating bandwidth was developed as the main part of signal processing. This new interpretation of the bandpass filter was used to extract a frequency of the ripple component from the measured motor current. This frequency was used to acquire information about the estimated rotor speed. The estimated speed was set as a feedback value to a cascade control structure to provide sensorless speed control. The advantages and limitations of this approach are presented in this paper. Based on simulations and experimental results, it was confirmed that the proposed sensorless speed control is robust, accurate, and works precisely in a wide range of speeds.

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This paper proposes a novel constant power factor loop in the V/f control strategy with stabilization for a permanent magnet synchronous motor (PMSM). The advantage of such an algorithm is the independence of the machine parameters, which vary under different operational conditions, e.g., with temperature, magnetic core saturation, and skin-effect. Furthermore, it is a low-cost and simple-to-implement sensorless solution. The proposed strategy is compared against traditional sensorless FOC with a Luenberger-type back-electromotive force (EMF) observer, which can be designed based on the machine model. The output of this kind of observer is typically an error signal, which can be specified for position deviation, requiring phase-locked loop (PLL) algorithm implementation. Employing PLL, a rotor speed and position can be estimated from such an error. Therefore, it is a complex sensorless technique with high-performance microcontroller unit (MCU) requirements. Both strategies are deeply analyzed, mathematically described, and compared within the paper. At the end of the paper, these sensorless strategies are supported by experimental verification with a traction PMSM designed for golf cart applications, and the pros and cons of both techniques are discussed.