COMPUTERIZED VIBRATION MONITORING PLATFORM FOR IN-WHEEL ELECTRIC MOTORS

Abstract

The work presents a comprehensive hardware-software platform designed for vibrodiagnostic analysis of rotating mechanisms integrated into the wheel motors of modern electric vehicles. At the core of the hardware platform is an advanced embedded processor based on ARM architecture, ensuring robust and efficient data management for handling the high throughput of data from eight triaxial accelerometers. These accelerometers can be placed to capture vibrational responses from various parts of the in-wheel motor, allowing quasi-simultaneous recording of signals and ensuring minimal latency for accurate diagnostics.

The software component of the system incorporates high-level algorithms designed for extensive data analysis. These algorithms facilitate the processing of vibrational signals in both time and frequency domains, extracting meaningful patterns and characteristics indicative of the health and performance of the rotating mechanisms. This dual-domain analysis provides a comprehensive understanding of the vibrational behaviors, helping identify both periodic and non-periodic anomalies.

To validate the platform's effectiveness, measurements were conducted on an in-wheel motor under two conditions: with and without imbalance. The vibrational signals recorded in both scenarios were subjected to detailed analysis using the platform's software. The results revealed a significant difference in vibration characteristics between the balanced and imbalanced conditions. The platform detected subtle variations in amplitude and frequency indicative of imbalance, confirming its capability to identify and diagnose faults in real-world applications.

The successful deployment of this platform opens new possibilities for predictive maintenance and real-time monitoring of state-of-the-art in-wheel motors widely used in modern electrical transportation. By identifying potential issues before they lead to significant expensive-to-repair failures, the platform helps reduce downtime and maintenance costs, enhancing the overall reliability of electric vehicles.

Key words: vibration diagnostics, software, accelerometer, electric motor, ARM, spectrum, correlation