Adaptability Analysis of Distributed Motor Measurement and Control System Based on Electronic Information Technology

Background: This paper studies the adaptability of distributed motor control system in window motor, aiming at improving the accuracy and efficiency of the system by using electronic information technology. Traditional control and test methods are lacking in accuracy and efficiency, so intelligent, automated systems are needed, combined with high-precision instruments and advanced algorithms, to better simulate real-world conditions and enhance noise analysis. Method: An optimized control system integrating random position control technology and noise analysis mechanism is studied. By simulating various operating conditions of window motors, experiments are carried out, focusing on measuring rotation Angle errors, signal acquisition differences and sound quality changes. Random number generation was added to the setup to increase the variability of the test cycle, and a detailed acoustic assessment was performed to fully analyze the noise characteristics. Result: The experimental results show that the rotation Angle error is significantly reduced, most of the values are less than 2 degrees, and the signal acquisition error is less than 0.8%. Despite the large fluctuation of the sound pressure level, the amplitude error remained below 2%, indicating strong performance of the system in different stages of operation. These improvements not only enhance the comfort of the vehicle, but also help improve the reliability and accuracy of motor performance tests. Conclusion: Integrating modern electronic information technology and intelligent algorithm into distributed motor measurement and control system can significantly improve the adaptability, accuracy and noise evaluation ability of the system, surpassing the traditional methods. This study lays the foundation for the future development of motor test systems, suggesting further exploration of applying advanced machine learning models and real-time data processing techniques to cope with dynamic test conditions. The research results are expected to be widely used in different motor types and systems in the automotive and industrial sectors.