Research On Vibration And Noise Suppression Strategy Of Double Random PWM Motor Based On Markov Chain

As an important part of the electric drive field,the AC speed regulation system has wide application prospects in the fields of industry,electric vehicles and navigation.Permanent magnet synchronous motors are widely used in various transmission occasions due to their advantages of high efficiency,stable speed and simple structure,and have become one of the key research directions of AC speed regulation in recent years.Usually the permanent magnet synchronous motor is driven by the inverter,and the PWM modulation technology of the inverter will cause electromagnetic noise and motor vibration.This poses a great challenge to the concealment of submarines and ships,and is an urgent problem to be solved.To solve this problem,this topic uses random PWM technology to start from changing the frequency spectrum distribution of harmonics,so that the harmonic components output by the inverter are relatively evenly distributed in a wide frequency band,so as to reduce vibration and noise.In addition,the power of traction synchronous motors in ships is usually as high as hundreds of kilowatts or even megawatts.In order to reduce the switching loss of the inverter,it needs to work at low switching frequency,and the motor is easy to appear under low switching frequency,high speed and low carrier ratio.Instability and out of control.In response to this problem,this topic improves the current loop control strategy,adopts an integral feedforward control strategy and considers delay compensation,so that the speed and delay information are compensated in the control strategy to improve the control performance under low carrier ratio and high speed conditions.This paper introduces the Markov process and its related theories,explains the software generation method of random numbers,studies a double random PWM strategy based on Markov chain,and proposes a method to increase the low frequency harmonics caused by the random algorithm.Markov chain double random PWM low frequency optimization strategy.High-power permanent magnet synchronous motors have a low switching frequency.In view of the inherent problems of current loop instability under high-speed and low-carrier-ratio operating conditions,an integral feed-forward current loop control strategy considering angle delay is proposed to suppress system instability oscillations,So that the system can be applied to high-speed low-carrier conditions.An algorithm simulation model was built and an experimental prototype was built to conduct an experimental study on the double random switching frequency PWM technology of Markov chain,and on this basis,the optimization of low frequency harmonics,high speed and low carrier optimization and other programs were experimentally verified.The results show that the low-frequency optimized Markov chain double random PWM strategy has the best vibration and noise reduction effect and the least impact on low-frequency characteristics.The integral feedforward strategy considering delay compensation can control the dq axis current convergence and stability in high-speed low-carrier operating conditions,which solves the problem of instability and out-of-control of permanent magnet synchronous motors under low carrier ratio operating conditions,thereby improving permanent magnet synchronous The adaptability of the motor in high power applications.Simulation and experimental results verify the effectiveness of the algorithm,and are not affected by changes in parameters such as motors and inverters,and can be generalized to other frequency conversion speed control systems.