Research On Efficiency Optimization Control Strategy Of Permanent Magnet Synchronous Traction Machines

With the development of industry in the past century,electrical machines have gradually become the main source of power for both manufacturing industry and household appliances,and also played a pivotal role in energy saving and emission reduction.Taking the automobile industry as an example,it is an important national industrial pillar.However,in recent years,due to a series of problems such as the shortage of petrochemical energy and carbon emission,the development of high-efficiency and energy-saving electric vehicles based on machine drive technologies has become the mainstream trend in the market.The traction machine is one of the three core components of new energy electric vehicle.Usually,the efficiency and torque-speed characteristics of electrical machines are directly relevant to the endurance mileage,driving experience,and safety performance of electric vehicles.Compared with the conventional DC and induction machines,the permanent magnet synchronous machine(PMSM)has become the mainstream drive machine in the electric vehicle market thanks to its small size,high reliability and high efficiency.Among all main features of PMSM,its efficiency is one of the most important performance characteristics,which is of great significance to improve the endurance mileage of electric vehicles.In this thesis,based on the machine loss model and the search technology,the efficiency optimization control(EOC)has been deeply investigated.The parameter identification method based on the model reference adaptive system(MRAS)is employed for the improvement of the algorithm adaptability and can effectively improve the machine efficiency.Core contents of this thesis are listed as follows:1)The EOC method based on the machine loss model is investigated in this thesis.The mathematical model of PMSM taking into account iron loss is established,which is then cooperated with the steady state voltage equation for the derivation of controllable losses(mainly includes the copper loss and iron loss).In the end,the constraint condition at which the total loss is minimal is consequently obtained to achieve the optimal efficiency control.2)The EOC method based on the search technology is investigated in this thesis.Under the constant power condition of electrical machine,this method does not rely on the accuracy of electrical machine model,and can achieve the optimal efficiency control of system by the continuous adjustment of controlled state variables.In addition,a comparison between the fixed-step and adaptive variable-step search methods is conducted in this thesis,together with relevant simulation and experimental analysis.3)The EOC method with aiding from MRAS based parameter identification is investigated in this thesis.The EOC based on the machine loss model is easy for implementation,whereas its accuracy is sensitive to the variation of machine parameters.Meanwhile,the PMSM has a strong coupling characteristics and is also a multi-variable-nonlinear system.When there is a load rise or temperature rise,PMSM parameters will vary accordingly,and have a further influence on the control accuracy.Therefore,the EOC method based on machine parameter identification has been proposed in this thesis.According to the identification of stator winding resistance and permanent magnet flux linkage,it will conduct an online adjustment to the loss model parameters to achieve the real time optimum of algorithm.In summary,the EOC method based on the loss model and search technology of PMSM has been deeply investigated in this thesis,of which the effectiveness is verified by simulation and experiment,respectively.Meanwhile,compared with the conventional loss machine based method,the EOC method considering the parameter identification of PMSM can effectively mitigate the issue of being sensitive to the variation of machine parameters,and is of theoretical and engineering significances.