Identification And Control Of On-line Adaptive Parameters Of Permanent Magnet Synchronous Motor For New Energy Vehicles

The Interior Permanent Magnet Synchronous Motor(IPMSM)has many advantages,such as high power density,low moment of inertia,and stable operation,which makes it commonly used as a drive motor for new energy vehicles.Maximum Torque Per Ampere control(MTPA)is widely applied since it can maximize the utilization of magnetic reluctance torque and make full use of stator current to achieve the given output torque for optimal control.However,due to the influences of specific working conditions,electrical parameters such as direct and quadrature axis inductance and resistance may change,causing MTPA working point drift and thus failing to achieve the best control effect.To address this issue,this paper investigates the online adaptive parameter identification method for IPMSM and proposes an MTPA control strategy with high dynamic response for IPMSM,combined with the compensation scheme for inverter dead-zone effect,to improve motor torque current response speed and anti-load disturbance capability.First,the paper introduces the structure classification of permanent magnet synchronous motors,followed by a detailed explanation of the concepts of coordinate systems and the transformation equation between them.Based on coordinate transformation,a mathematical model of IPMSM is established and the basic principle of Space Vector Pulse Width Modulation is analyzed.Next,the paper analyzes the basic logic and theory of Model Reference Adaptive Identification(MRAI),discusses the mainstream methods for the design of adaptive laws,their advantages and disadvantages,and elaborates on the Popov hyperstability theory,pointing out the conditions that linear constant systems and nonlinear time-varying systems need to satisfy.To overcome the issue of rank deficiency,a stepwise identification method is employed.First,the resistance parameters are fixed,and the adaptive laws for direct and quadrature axis inductance parameters are designed,followed by the design of resistance parameter adaptive laws.The parameter identification based on the traditional Recursive Least Squares(RLS)algorithm and MRAI algorithm is compared through simulation experiments,and the influence of different working conditions on parameter identification is analyzed.Subsequently,the paper addresses the nonlinearity and dead-zone effect of inverters by studying two improved dead-zone compensation schemes: static dead-zone compensation and dead-zone voltage compensation.The advantages,disadvantages,and application scopes of both schemes are considered,and simulation experiments are conducted.Finally,by combining adaptive parameter identification and dead-zone compensation,a high dynamic response control strategy for MTPA is proposed to address the problems of traditional MTPA working point drift,PI current controller overshooting,and integral saturation.An automatic segmented solution method based on curve fitting is used to better fit the MTPA trajectory curve.Current predictive control is designed in combination with parameter identification,converting the traditional PI current control in the current loop into a high dynamic response current predictive control.Simulation experiment results confirm that the proposed high dynamic response control strategy retains the high efficiency of MTPA control while achieving high dynamic response control.In this paper,a high-efficiency,high dynamic response control is proposed based on a detailed study of the online adaptive parameter identification of IPMSM and inverter deadzone compensation,which enriches the control methods for permanent magnet synchronous motors and has significant reference value for IPMSM control.