Online detection of phase resistance of switched reluctance motor by sinusoidal signal injection

Introduction. Switched reluctance motors (SRMs) are widely used in various applications due to their simplicity, robustness, and cost-effectiveness. However, the performance of SRMs can be significantly influenced by variations in their phase resistance, especially under high current and saturated conditions. Accurate knowledge of this parameter is crucial for optimal control and efficient operation. Problem. During operation, SRM parameters, particularly phase resistance, can vary considerably. These variations pose challenges to control strategies that rely on precise parameter values, leading to potential inefficiencies and degraded performance. There is a need for an effective method to monitor and identify these changes in real-time. Goal. This paper aims to develop and validate a method for the online detection and identification of phase resistance in SRMs. The method should work under varying operational conditions without requiring additional hardware, thereby maintaining the system's simplicity and cost-effectiveness. Methodology. The proposed method injects a sinusoidal signal into the inactive phase of the SRM using Sinusoidal Pulse Width Modulation (SPWM) via the main converter. The phasor method is then applied to determine the impedance of the phase circuit, from which the phase resistance can be identified. This approach eliminates the need for extra circuits, making it an efficient solution. Results. Simulations were conducted to evaluate the proposed method. The results demonstrate that the method can accurately track the variation in phase resistance under different operational conditions, validating its effectiveness. Originality. The originality of this work lies in its innovative use of the phasor method combined with SPWM for online phase resistance detection in SRMs, without the need for additional hardware components. Practical value. This method provides a practical solution for real-time phase resistance identification in SRMs, enhancing the reliability and performance of control strategies in various industrial applications. References 17, table 1, figures 6.