| With the rapid increase in the number of cars,the energy shortage and environmental pollution brought by traditional fuel veh icles have become the focus of attention in today's society.In response to these problems,the traditional automotive industry is accelerating the transition to new energy vehicles.Permanent Magnet Synchronous Motor(PMSM)has been widely used in new ene rgy vehicles due to its high operating efficiency,high power density and high torque density.Due to the difficulty in adjusting the size of the main magnetic flux of the PMSM and the obvious decrease in the efficiency of the high-speed flux weakening field,the new energy vehicle has problems such as narrower speed regulation range and lower maximum speed of the flux weakening region.In order to solve these problems,this thesis deeply studies the flux weakening control,the nonlinear factor compensation of the inverter and the “compensation and flux weakening” control strategy combining the two.The main contents are as follows:(1)Voltage difference feedback flux weakening control and hybrid flux weakening control.In order to broaden the speed range of the motor,this paper studies the voltage difference feedback flux weakening control.The control strategy obtains the d-axis demagnetization current by comparing the stator voltage with the maximum supply voltage of the inverter.This current can demagnetize the motor,weaken the main magnetic flux of the rotor and increase the maximum speed of the motor,but the convergence speed of the method is slow.Aiming at this problem,this paper studies the hybrid flux weakening,which adds a feedforward link on the basis of voltage difference feedback flux weakening method.The feedforward link can speed up the response speed of the d-axis current,which can speed up the convergence speed of the control algorithm.(2)The compensation strategy based on time delay and the compensation strategy based on Adaline neural network.In order to compensate the nonlinearity of the inverters,a compensation strategy based on time delay is proposed in this paper.The strategy can realize on-line compensation for nonlinear factors by assuming that the variation of the distortion voltage is approximately zero in one sampling period and using the distortion voltage of the previous period to estimate the distortion voltage of the current period.Since the compensation strategy relies on the motor parameters,the compensation accuracy is limited.Aiming at this problem,this paper derives the mathematical model of the nonlinearity of the inverters in the dq coordinate system.Based on the model,an online identification and compens ation strategy for nonlinear factors equivalent voltage of inverter based on Adaline identifier is studied.This strategy does not depend on the motor parameters,and can accurately compensate the nonlinearity of the inverters.(3)“Compensation and flux weakening” control strategy of combining the compensation method of nonlinearity of the inverters with the control of flux weakening.In order to further improve the maximum speed of the motor,this paper studies a “compensation and flux weakening” control strategy which combines the compensation strategy based on Adaline neural network with the flux weakening control based on voltage feedback.Compared with the traditional flux weakening control based on voltage feedback,the control strategy takes the comp ensated voltage as the feedback voltage.When this voltage reaches the supply voltage of the inverter,it enters the flux weakening control.It can improve the basic speed and the maximum speed of the motor.In summary,the theoretical analysis of five control strategies is carried out in this paper,the core problems that need to be solved by these five control strategies are analyzed and the solution is given.Finally,the experimental verification is carried out on the experimental platform.The control strategy proposed in this paper can be applied to various applications,and has good theoretical significance and application value. |
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