【作者】 张宇；

【导师】 刘侃；

【作者基本信息】 湖南大学 ， 车辆工程（专业学位）， 2019， 硕士

【摘要】 环境保护问题越来越受到当前社会各界的重视,节能减排也已经成为各个行业的关注焦点。传统汽车带来的城市空气污染及其二氧化碳排放问题长期为社会各界所诟病,为此汽车这一国民经济支柱产业正朝着电动化的方向加速转型。内置式永磁同步电机(Interior permanent magnet synchronous motor,IPMSM)因其高启动力矩、高工作效率、高转矩密度、宽调速范围、小体积等优点被广泛用在电动汽车驱动系统中。由于IPMSM的q轴电感值大于d轴电感值,因此在电动汽车基速以下往往采用最大转矩每电流比(Maximum torque per ampere,MTPA)控制以充分利用驱动电机的磁阻转矩,提高驱动电机的转矩输出能力。本文从基于电机参数和不依赖电机参数这两个方向对MTPA控制进行了深入的研究,分析了两种MTPA控制算法所要解决的核心问题,并给出了相应的解决方案:(1)本文研究了基于电机参数的MTPA控制策略。基于电机参数的MTPA控制策略算法简单且易于实现,是目前工程领域应用最广泛的方法。但在负载变化、电机老化、退磁以及温度上升等因素的影响下,电机的参数会随之发生变化,进而会降低MTPA控制器算法的动静态性能与控制精度。本文为此研究了如何通过模型参考自适应算法(Model reference adaptive control,MRAS)来对永磁同步电机的交直轴电感和永磁体磁链进行精确的参数辨识,并进而用于调整MTPA控制器参数以提高控制精度,进而提高电机的转矩输出能力。(2)本文研究了两种典型的不依赖电机参数的MTPA控制策略。本文研究了搜索算法,该控制方案在给定负载且转速恒定的情况下,可在线搜索最优矢量角,并通过比较前后两次的定子电流矢量的大小,来确定搜索方向,最终搜索到MTPA控制对应的电流矢量角。此外,本文还研究了基于高频信号注入法的MTPA控制。通过把高频小幅值电流信号叠加在定子电流上,进而通过信号处理检测输入功率对注入信号的响应,即可锁定MTPA控制矢量角。(3)本文研究了基于最优判断的搜索算法。搜索算法需要对控制系统前后两个时刻的电气信号进行比较来确定搜索方向,因此必然导致搜索算法无法锁定最优值,并在最优值附近震荡。为此,本文进一步研究了基于最优判断的搜索算法,该算法将搜索过程划分为两个区间,不但能准确判断搜索进程是否到达最优值区间,还能够准确的识别并稳定的输出最优矢量角。因此可以减少电机输出的脉动,并提高控制精度。综上所述,本文通过仿真和实验对MTPA控制策略进行了深入的研究,分析了基于电机参数的MTPA控制算法和搜索算法要解决的核心问题,并给出了相应的解决方案。所研究的MTPA控制算法能有效解决传统的基于固定电机参数的MTPA控制算法和传统搜索算法的不足,具有很好的理论意义和工程应用价值。更多还原

【Abstract】 At present,more and more attention has been paid to the environmental protection,and energy-saving and emission-reduction has become the focus of attention in various industries.Air pollution and carbon dioxide emissions in cities caused by traditional automobiles have long been criticized by all social circles,so the automobile industry,the pillar industry of the national economy,is accelerating transformation towards electrification.Interior permanent magnet synchronous motor(IPMSM)has been widely used in electric vehicle drive system thanks to its high efficiency,high torque density,high starting torque,wide speed range and small size.Because the q-axis inductance of IPMSM is greater than to the d-axis inductance,the Maximum Torque Per Ampere(MTPA)control is often adopted below the base speed of the electric vehicle to make full use of the reluctance torque of the driving motor,improve the torque output capability of the driving motor.In this paper,MTPA control is deeply studied from two aspects: relying on motor parameters and independent of motor parameters.The core problems of two control algorithms need to be solved are analyzed,and the corresponding solutions are given.(1)In this paper,MTPA control based on motor parameters is studied.MTPA control strategy based on motor parameters is simple and easy to realize,and is the most widely used scheme in engineering field.However,under the influence of load change,motor aging,demagnetization and temperature rise,the parameters of the motor will change accordingly,which will reduce the dynamic and static performance and control accuracy of the MTPA controller algorithm.How to identify the direct axis and quadrature axis inductances and permanent magnet flux of permanent magnet synchronous motor accurately by model reference adaptive control(MRAS)is studied in this paper,and then the parameters of MTPA controller is adjusted to improve the control accuracy and torque output.(2)In this paper,two typical MTPA control strategies independent of motor parameters are studied.MTPA control based on search algorithm is studied.Under given load and speed,the optimal vector angle is searched online.By comparing the two stator vector currents,the search direction is determined,and the corresponding current vector angle of MTPA control is finally searched.In addition,MTPA control based on high frequency signal injection method is also st udied in this paper.By superimposing high frequency small amplitude current signal on stator current,and then detecting the response of input power to injection signal through signal processing,MTPA control vector angle can be locked.(3)In this paper,the search algorithm based on optimal judgment is further studied.the search algorithm needs to compare the electrical signal of front and back of two moments to determine the search direction,which inevitably leads to the search algorithm can not lock the optimal value,and the current vector angle will oscillate near the optimal value.For this reason,the search algorithm based on optimal judgment is further studied in this paper,which divides the search process into two intervals,not only accurately judges whether the search process reaches the optimal value interval,and can also accurately identify and stably output the optimal vector angle.So it could reduce the torque ripples and improve torque output.In summary,the control strategies of MTPA are deeply studied through simulation and experiment,The core problems of MTPA control algorithm based on motor parameters and search algorithm are analyzed,and the corresponding solutions are given.The MTPA control algorithm studied in this paper c an effectively solve the shortcomings of traditional MTPA control algorithm based on fixed motor parameters and search algorithm,and has good theoretical significance and engineering application value.更多还原