Research On Torque Ripple Suppression Methods For Brushless DC Motors

With the rapid development of automation,the control accuracy of brushless DC motors in electromechanical equipment has been continuously improved.Torque ripple suppression has always been an important direction of concern for professionals and researchers in the field of motors.Brushless DC motors will produce torque ripple in their body design and commutation process,which will have a certain impact on industrial production efficiency and operation safety.Most existing control systems for brushless DC motors have torque ripple problems.Therefore,researching the technology that can suppress torque ripple in brushless DC motors is a practical requirement to ensure stable operation.Currently,innovation in control methods has gradually become the mainstream research direction.This thesis mainly studies the application of the quasi-Z-source network in torque ripple suppression of brushless DC motors,and makes targeted improvements according to the characteristics of the research object to meet specific requirements.The main research contents are as follows:(1)An analysis was conducted on the operating principles of a brushless DC motor and a mathematical model was established for the motor.At the same time,the mechanical and operating characteristics were analyzed.In order to study the effect of resistance on torque ripple suppression during commutation,this was studied from two aspects: consideration of resistance and neglecting resistance.When neglecting resistance,three torque ripple situations during the transition from phase AB to phase AC were studied,and it was found that there was a four-fold relationship between the DC bus voltage and back electromotive force.Based on theoretical analysis,a simulation system model for brushless DC motors was established.Through simulation,it was found that torque ripple decreases with increasing load and there is a relationship between torque ripple and phase current ripple.(2)To address the issue of traditional quasi-Z-source networks having an unsatisfactory effect on suppressing torque ripple,a new torque ripple suppression method has been proposed and analyzed in both the ON and OFF states.This method can achieve a higher DC bus voltage through a new boosting factor,and the time from the start of boosting to the stabilization of the DC bus voltage is shorter.The core idea is to control the commutation time and the turn-off of two switching devices to ensure that the DC bus voltage is four times the value of the back electromotive force.Finally,a simulation model was established to further verify the torque ripple suppressing effect of this network.Compared with traditional quasi-Z-source networks and switch inductor quasi-Z-source networks,this method has a better torque ripple suppression effect.(3)To address the low control precision issue of traditional PI control methods in torque ripple suppression,a torque ripple suppression method for brushless DC motors based on deep reinforcement learning has been proposed.This method achieves precise tracking of speed and torque by training an agent.Among various reinforcement learning algorithms,this thesis selects the PPO2 algorithm based on its characteristics and applies it to the torque ripple suppression system of brushless DC motors.To improve the DC bus voltage,a new quasi-Z-source network topology is added in front of the inverter.On this basis,the traditional PI controller is replaced by a deep reinforcement learning PPO2 algorithm adaptive controller,and the PPO2 adaptive controller network is constructed for program design.Finally,the agent is trained and the trained agent is inserted into the simulation model for verification,showing that the PPO2 algorithm has a certain effect on torque ripple suppression for brushless DC motors.In summary,this thesis proposes a torque ripple suppression method for brushless DC motors based on an improved quasi-Z-source network and deep reinforcement learning.Through the combination of theoretical analysis and simulation,the feasibility of the proposed methods has been verified.This study is of great significance for ensuring the stable operation of brushless DC motors and improving production efficiency.