Development And Research On Parameter Self-learning System For Vehicle Motor

Permanent magnet synchronous motor(PMSM)has the advantages of simple structure,strong operation reliability and high power density,and has been widely used in the field of new energy vehicles.To achieve high-performance permanent magnet synchronous motor control,accurate motor parameters need to be obtained.However,due to the influence of temperature changes,magnetic field saturation and other factors,the parameters of the permanent magnet synchronous motor will change during actual operation,which will cause the actual parameter values of the motor to be different from the off-line measurement values.The parameters of magnetic synchronous motors are of great significance for high-performance motor control.In response to this need,this paper has studied the parameter measurement methods of permanent magnet synchronous motors in depth,and developed a set of motor parameter self-learning system based on LabVIEW,which realizes the automatic acquisition of motor parameters during the development of motor control systems.The specific research work in this paper is as follows:The off-line measurement methods of the key parameters of permanent magnet synchronous motors,such as stator resistance,dq inductance,and rotor permanent magnet flux linkage are analyzed,and the shortcomings of off-line measurement of motor parameters are analyzed.An online parameter self-learning method based on recursive least squares was researched and developed to realize the multi-parameter on-line identification of the stator resistance,rotor flux linkage,and dq axis inductance of the permanent magnet synchronous motor.Based on the mathematical model of the permanent magnet synchronous motor in the two-phase synchronous coordinate system,the recursive least square method iterative calculation formula applied to the permanent magnet synchronous motor is derived.Based on the SIMULINK simulation model of the vector control system of the permanent magnet synchronous motor,Preliminary validation was performed.The research analyzes the algorithm’s identification performance and the influence of non-linear factors in the actual system on the performance of the algorithm.An experimental platform for permanent magnet synchronous motor parameter self-learning system was established,and the parameter self-learning software system was designed based on the LabVIEW development platform.The software system can simultaneously acquire and display motor operation and control information by collecting different sensor signals and motor controller signals at the same time.It also integrates permanent magnet synchronous motor parameter analysis and measurement algorithms to realize online self-learning of motor parameters.The parameter selflearning system is used to obtain the motor parameters of a 60 kW permanent magnet synchronous motor for vehicles.The experimental results show that the system can easily obtain the motor parameters during the experiment and effectively improve the development efficiency of the motor control system.