摘 要

近年来电动汽车作为一种节能、清洁的交通工具被广泛使用，对世界经济发展和能源格局产生重大影响。电机驱动的效率和可靠性对电动汽车性能的影响至关重要，多相电机驱动系统与传统三相系统相比具有显著优势，本文以一台七相感应电机为研究对象，对多相电机转速观测和定子电阻的在线辨识进行分析以提升其在无速度传感器场合的性能。

首先，为了获得类似于三相感应电机在dq平面磁链和转矩的解耦特性，本文推导了多相系统的空间变换矩阵，建立了七相感应电机的空间解耦模型。在此基础上讨论了电动汽车中驱动电机设计和控制应用相结合的问题，介绍了多层面优化设计和多领域协同仿真的思想，并以MATLAB/Simulink为例搭建了基于转子磁场定向的七相感应电机矢量控制系统，仿真结果验证了仿真模型和控制器的可行性。

然后，针对多相感应电机的无速度传感器运行控制，本文介绍了一类以模型参考自适应理论为基础的转速辨识方法。分别利用转子磁链模型、反电势模型以及无功功率模型进行转速观测，仿真结果验证了方案的可行性但仍有改进的空间。转子磁链模型以转子磁链的电压模型作为参考模型，由于含有纯积分环节易导致积分饱和，使其动态性能较下降；反电势模型中利用反电势代替转子磁链，动态响应较快但存在静差，受定子电阻影响较大；无功功率模型中不含定子电阻，辨识结果精度高但动态响应较慢。

最后，为克服参考模型中存在的问题，提出一种基于滑模方法的转速观测器。以定子电流和转子磁链为变量推导出状态方程并将滑模面构造在定子电流方程中，将转子磁链的观测结果用于直接磁场定向控制，进一步实现转速和定子电阻的在线辨识。通过搭建仿真模型验证了稳态下转速估计值的误差很小。之后给定阶跃信号和斜坡信号下对系统的动态性能进行测试，仿真结果证明基于滑模方法的转速观测器具有较好的抗扰性能，系统的动稳态性能较好。

关键词：电动汽车，多相电机驱动系统，无速度传感器，模型参考自适应，滑模控制

Abstract

Recently, electric vehicles (EV) have been widely used as an energy-saving and clean vehicle, which has a major impact on the world economic development and energy pattern. The efficiency and reliability of the motor drive deeply decide the performance of the electric vehicles. Multi-phase motor drive system has significant advantages over the traditional three-phase system. Therefore, this paper uses a seven-phase induction motor and focuses on the estimation of motor speed and on-line identification of stator resistance for electric vehicle applications, so as to improve the performance of sensorless control system.

Firstly, in order to obtain the decoupling characteristics of the three-phase induction motor flux linkage and torque in the dq plane, this paper deduces the spatial transformation matrix of the multi-phase system and establishes a spatial decoupling model of the seven-phase induction motor. Based on it, the problems of the combination of the drive motor design and the control application in the electric vehicle are discussed. The ideas of multi-layer optimization design and multi-domain collaborative simulation are introduced. An example is used to build a seven-phase system based on rotor field orientation in Simulink and simulation results verify the feasibility of the simulation model and controller.

Then, for speed-sensorless control of multi-phase induction motors, this paper introduces a kind of speed identification method based on model reference adaptive system (MRAS). The rotor flux model, back electromotive force model and reactive power model were selected to combine the speed adaptive law for speed observation. The rotor flux model, back electromotive force model and reactive power model were selected to combine the speed adaptive law for speed estimation. The simulation results verify the feasibility of the scheme, but there is still room for improvement. The rotor flux model uses the voltage model of the rotor flux as a reference model. Its dynamic performance is poor, and it has a pure integral that can easily lead to integral saturation. The back-EMF model uses a back-EMF signal to replace the flux signal, and the dynamic response is faster at this time. There is a static difference, which is greatly affected by the stator resistance. In the reactive power model, the stator resistance in the reference model is removed. The accuracy of the estimated speed is high but the dynamic response is slow.

Finally, due to the problems existing in the speed estimation based on reference model, a speed observer based on sliding mode is proposed. The equation of state is deduced with the stator current and the rotor flux as variables, and the stator current and rotor flux linkage are observed in the stator current estimation equation to achieve direct magnetic field orientation control. Then on-line identification of the speed and the stator resistance can easily achieved.A steady-state rotational speed is first observed in the simulation model and the result shows that the error of the speed estimation is small. The dynamic performance of the system is tested under the given step signal and ramp signal. The simulation results verify that the speed observer based on sliding mode method has better performance of anti-interference, and the performance of dynamic and steady state of the system is better.

Keywords：Electric Vehciles, multiphase motor drive system, speed sensorless control, MARS, sliding mode control

目录

摘要 I

Abstract II

目录 IV

第1章 绪论 1

1.1 课题背景及研究目的 1

1.2 电动汽车概述 2

1.2.1 国内外发展现状 2

1.2.2 电机驱动系统概述 4

1.3 多相电机无速度传感器运行研究 6

1.4 本文主要研究内容 8

第2章 多相感应电机数学模型分析 9

2.1 多相电机系统及其特点 9

2.2 多相电机模型建立 9

2.3 多相系统空间解耦变换 12

2.4 七相感应电机空间解耦模型 14

2.5 本章小结 16

第3章 多相电机仿真分析 17

3.1 多层面优化设计 17

3.1.1 电机设计与结构仿真 17

3.1.2 电机内多物理场计算 18

3.2 多领域协同仿真 18

3.3 多相电机系统仿真 19

3.3.1 多相电机仿真模型建立 19

3.3.2 转子磁场定向控制策略 22

3.4 仿真结果分析 23

3.5 本章小结 27

第4章 无速度传感器矢量控制系统分析 28

4.1 开环转速观测法 28

4.2 采用模型参考自适应法的转速辨识 29

4.2.1 基于转子磁链模型的转速辨识 31

4.2.2 基于反电势模型的转速辨识 32

4.2.3 基于瞬时无功功率的转速辨识 33

4.3 基于MRAS转速辨识仿真实例 34

4.4 模型参考自适应（MRAS）比较分析 40

4.5 本章小结 40

第5章 滑模转速观测器在多相电机中的应用 42

5.1 滑模控制理论分析 42

5.1.1 滑动模态的数学表达 42

5.1.2 滑模控制的应用实例 44

5.2 基于滑模方法的转速观测器 46

5.2.1 基波平面滑模观测器设计 46

5.2.2 自适应率分析 48

5.3 仿真结果分析 48

5.3.1 转速给定为斜坡信号仿真 49

5.3.2 转速给定为阶跃信号仿真 50

5.4 滑模观测器的电机参数辨识分析 52

5.5 本章小结 53

第6章 总结与展望 54

6.1 总结 54

6.2 展望 55

参考文献 56

致谢 60

绪论

课题背景及研究目的

城市化的快速发展增加了人们对交通工具的需求，导致石油、天然气等资源大量使用。急剧增长的汽车使用量不仅加剧了对化石燃料的依赖，同时排放的汽车尾气使得空气质量恶化。煤炭和石油仍然是我国最主要的消费能源，虽然我国石油、煤炭和天然气的总量较为丰富，据统计我国这几类资源的人均占有量仅为世界人均水平的5.4%、67%和7.5%^[1]，而且因此导致国内部分城市空气污染严重。不管是对世界还是我国的发展，能源利用和环境保护是我们共同的挑战。电动汽车作为一种新型节能环保的交通工具已经被全球汽车工业推广，对世界经济和能源格局的影响非常显著。

与普通燃油汽车相比，电动汽车优势显著 ^[2-5]：电动汽车的主要能量来源是电能，电能作为一种二次能源除了通过火力发电以外，还可以通过水力、风力、太阳能发电等其他形式的能量转化获得，可以减少石油资源的使用，而且不会产生有害气体；电动汽车采用的电驱动系统能够工作在回馈制动状态，易于实现能量回馈，有利于节能；与燃油车发动机相比，电动汽车动力来源于电机驱动，所以其在行驶过程中噪声很小。