The high current ripple and torque ripple are the main drawbacks of the switched reluctance motor (SRM) since the nonlinearity and double saliency, which limits its applications. In order to eliminate the current variation and torque ripple, an optimized pulse width modulation (PWM) control is presented in this paper. The voltage ratio duty is able to be predicted precisely according to the information of the motor running parameter. Based on torque sharing functions (TSFs), the current profile is pre-computed and four regions are defined according to the reference current profiles. The three modes, excitation, demagnetization and freewheeling, are flexibly chosen according to the characteristic of the current profile. It is indicated that it is better than that of conventional PWM modulation in terms of current ripple and the current tracing performance is improved without increasing the switching frequency or changing the hysteresis band. The current ripple is defined as the peak-to-peak value dividing the average value and it is reduced by 40%. A comparison in terms of the torque ripple and copper loss is also carried out: the torque ripple is significantly reduced via the proposed scheme under both magnetic linear and saturation conditions. The torque ripple and copper loss are reduced by about 70% and 12%, respectively. The validity and effectiveness of the proposed control strategy is verified by simulation and experimental results.

In this paper, a predictive phase current control (PCC) scheme based on a local linear phase voltage model for a switched reluctance motor is proposed. The current is controlled by regulating the average voltage through PWM, ensuring a fixed switching frequency. A linear model is proposed to approximate the relationship between the voltage and the current slope in a short period. By using the voltage and current slope information in the previous control cycle, the intercept and slope of the model can be identified online. In the previous control cycle, the phase voltage changes from zero to positive or negative DC-link voltage, and then the identified model is used to predict the average voltage required in the next PWM cycle for the actual current so as to accurately track its reference. The effectiveness of the proposed PCC was verified experimentally. The results demonstrate that the proposed control scheme can significantly reduce the current and torque ripples compared to hysteresis control with the same sampling rate. The proposed PCC is easy to implement, does not need to obtain the motor characteristics in advance and is not sensitive to the changes in characteristic parameters caused by motor aging, etc. It is relatively suitable for applications that need to accurately track the given current curve.

The precise estimation of position is an essential concern for the control of a switched reluctance motor (SRM). Given the prominent role of position, the promising sensorless control approach for an SRM drive should be capable of providing accurate position. An inductance-based approach has been widely applied in the position estimation. However, the estimated accuracy suffers from the magnetic saturation effect, resulting in the poor performance of sensorless operation. This paper presents a reversible synchronization of commutation with the corresponding rotor position for SRM. With the consideration of magnetic saturation, the proposed approach is taken as a suitable candidate and plays an essential role in accommodating the requirement of optimal control. The relationship between a typical inductance position and magnetic circuit saturation is investigated. The instant of the intersections is sensed by comparing the instantaneous inductance of adjacent phases. Thus, the predicted position is obtained with the information of the special point and the calculated average speed. Compared with other existing methods, the proposed approach has the certain advantages, such as the ability to update the estimated speed and position six times per electrical period, which guarantees the estimated accuracy. The proposed approach is also valid even when the motor is operated at an acceleration state and heavy load operation. In addition, the requirement of the educated inductance structure is not unnecessary, less memory space is needed in the chip, and the accumulated error is eliminated. The simulation and experimental findings demonstrate the feasibility and practicality of the proposed position estimation approach with carrying out the inertial operation, load mutation, and high-speed test.

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