Fault Diagnosis Method Based on Temperature Rise Detection for Switched Reluctance Motor Drive Systems in Electrical Transportation

In this paper, a fault diagnosis method based on temperature rise detection is proposed for power converters in switched reluctance motor drive systems used in electrical transportation equipment. First, the total power losses of all power devices are calculated and recorded under different operating conditions in both healthy and faulty states. A finite-element electrothermal model is then established to characterize the relationship between fault-induced power-loss redistribution and variations in the temperature rise of the converter devices. Based on the power-loss analysis, temperature rise is used as a key characteristic, and a corresponding fault diagnosis method is proposed. To account for the influence of operating conditions on the diagnostic criterion, three independent backpropagation neural network (BPNN) models are developed to predict fault-specific temperature-rise thresholds using rotor speed, load torque, and ambient temperature as inputs. During diagnosis, the real-time temperature evolution of the power diodes is compared with the selected thresholds to detect power converter faults. Finally, experimental results demonstrate the validity of the proposed fault diagnosis method.