AI-Based Prediction and Safety Measures for Electromechanical Brake Three-Phase Motor Faults

In the development of future automotive systems, safety and performance are crucial considerations. The reliable operation of Drum-type Electromechanical Brakes (D-EMBs), key components responsible for vehicle braking, is essential. Previous research has predominantly focused on post-fault response strategies, emphasizing fault detection and diagnosis. However, this study aimed to enhance vehicle safety by predicting motor faults in the D-EMB system and developing corresponding measures. Utilizing AI-based FFT (Fast Fourier Transform) analysis, in this research, we successfully developed a technology for the early detection of motor faults, achieving an accuracy of over 80%. This study contributes to improving the safety of future automobiles and the development of innovative safety technologies.