Research On Position Sensorless Model Predictive Control Of Permanent Magnet Synchronous In-wheel Motor Considering Dead-time

With the continuous increase of car ownership,the rapid consumption of nonrenewable energy such as petroleum,non-renewable energy such as oil is rapidly being consumed,and automobile emissions have caused serious environmental pollution.Therefore,electric vehicles have become one of the new directions for the future development of automobiles.The permanent magnet synchronous motors have the advantages of small size,light weight,low noise and high power density,and have been widely used as inwheel motors for electric vehicles.As the bottom execution unit of the vehicle,in-wheel motor needs to receive commands from the electric vehicle controller to provide motor torque to meet frequent acceleration and deceleration.Therefore,the control objective of permanent magnet synchronous in-wheel motor control system is to track the desired torque quickly and accurately while ensuring economical efficiency.Field oriented control realizes decoupling control of current by using the rotation coordinate transformation,and the technology of it is relatively mature.However,there are also problems such as slow dynamic response,torque ripple,and switching loss.Moreover,traditional control methods often focus on the motor,but ignore the control of the inverter.There is a dead-time in the actual inverter,which is one of the important factors causing torque ripple.Since field oriented control must use the position information of the motor,traditional method usually uses position sensor to obtain the information.However,position sensors increase the size,weight and cost of the in-wheel motor.In this paper,a position sensorless model predictive control strategy considering dead-time for permanent magnet synchronous motor is designed to solve these problems.In this paper,a mathematical model of the three-phase inverter with dead-time is established,and the model prediction control algorithm is used to eliminate the error caused by the dead-time.The permanent magnet synchronous motor and the threephase inverter are modeled as a whole in order to calculate the PWM to optimize the inverter switch combination directly,which omit the traditional modulation module and can be used for real-time frequency conversion according to the system situation.Model predictive control algorithm can optimize multi-objective comprehensively.By designing an objective function,controller tracks the motor torque and reduces the losses of the motor and inverter under system constraints.An observer is designed to estimate the motor angle so that it can replace the position sensor.Finally,a permanent magnet synchronous motor control system model is built in Matlab/Simulink.The off-line simulation comparison test is performed under different conditions to verify the effectiveness of the designed model predictive control algorithm.The main content and innovation:1.Based on the dead-time of a three-phase inverter,the permanent magnet synchronous motor and the three-phase inverter are modeled as a whole.This will make the prediction model more complete.2.For the limitations of position sensors,a motor angle observer is designed to realize position sensorless control of the motor.3.Based on the principle of field oriented control,a model predictive control algorithm is established,which can optimize multi-objective.The model predictive control algorithm optimizes switch combination of the three-phase inverter directly,without the traditional SVPWM method.The control structure is simple and easy to implement.Due to the establishment of a prediction model considering dead-time,the model predictive control algorithm can eliminate the influence of dead-time and reduce the torque ripple.