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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/15/12/550 |
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| Summary: | 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. |
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| ISSN: | 2032-6653 |