【作者】 曹先庆；

【导师】 唐任远；

【作者基本信息】 沈阳工业大学 ， 电机与电器， 2008， 博士

【摘要】 本文围绕混合动力电动汽车用永磁同步电动机驱动系统的开发展开工作,开发出了额定转矩291.5N·m、额定功率55kW、峰值功率90 kW的车用永磁同步电动机驱动系统。在逆变器容量一定的前提下,从提高系统效率、降低电流畸变率、扩大弱磁扩速范围、加快动态响应速度以及增强系统鲁棒性的角度,对所采用的矢量控制策略进行了改进。建立的驱动系统无论在恒转矩区,还是在恒功率区运行均达到了预期的性能指标。在分析永磁同步电动机的恒转矩运行时电流控制策略及弱磁控制策略的基础上,提出了一种基于零电压矢量作用时间T₀的弱磁方法,即通过输入为零电压矢量作用时间T₀与某一定值T₀^*差值的PI控制器得到直轴电流分量i_d。与普通弱磁方法相比,该方法有效地避免了电机参数变化对控制精度的影响,在加快动态响应速度的同时,降低定子电流的幅值。因此,在逆变器容量一定的情况下,可达到拓宽扩速范围的目的。由于功率管的开关时滞及为防止同一桥臂两只功率管直通而设置的死区时间,会使逆变器的实际输出电压产生非线性畸变,进而产生电流波形畸变和转矩波动等。本文在对死区效应产生的误差电压矢量进行详细理论分析的基础上,推导出该误差电压矢量的具体表达式并对其进行动态补偿;在此基础上,对由于电机运行状态及参数变化引起的补偿电压误差进行了二次补偿。这样既可以有效解决现有假设误差电压矢量为定值补偿效果不佳的问题,又能避免运行状态及参数变化对补偿精度的影响。对永磁同步电动机损耗模型进行了深入分析,根据损耗模型求出电机在不同转速和转矩时使电机效率最大的定子电流直轴分量i_d的近似最优值;以该值为初始值,通过梯度算法和黄金分割相结合的方法进行寻优。与目前永磁同步电动机常采用混合寻优中所采用的智能算法相比,本文所提出的效率混合优化算法简单且利于工程实施,寻优速度快,符合电动汽车驱动系统效率优化快速性的要求。与此同时,利用交轴电流i_q的前馈补偿来减小转矩波动。另外,在电机进入动态过程时,采用基于动态快速响应的定子电流分配方法,以缩短动态响应的时间。建立了基于模糊神经网络的速度控制器。利用扰动电压观测器的输出,通过模糊控制器得到对神经网络权值和阈值进行在线调整的误差量,从而避免了其它文献给出的同类速度控制器为得到该误差量而陷入的繁琐计算。相对于定参数的PI控制器,该方法有效地提高了系统的动态响应性能及鲁棒性。与控制策略相结合,深入分析了交、直轴电感及永磁磁链等参数对电机性能,尤其是对弱磁扩速特性的影响。并结合混合动力电动汽车用永磁牵引电机的运行特点和性能要求,给出了它们的设计原则。最后,对所提出的控制策略作了仿真验证,并在样机上进行了相关的实验,实验结果基本满足要求。更多还原

【Abstract】 This dissertation is devoted to the study on permanent magnet synchronous motor （PMSM） drive system for hybrid electric vehicle （HEV） application. A PM traction motor used in HEV is developed, and it’s rated torque is 291.5N·m, rated power is 55kW and peak power is 90kW. In order to improve drive efficiency, reduce the current distortion, expand the scope of field-weaking, speed up the dynamic response rate and enhance the robustness of the drive system, the drive system that improved the vector control strategy has been establishd, in the condition of a certain inverter. Whether in constant torque region, or in constant power region, the proposed drive system can achieve the expected operational performance.The current control strategy in constant torque region and the field weakening control strategy in constant power region are analyzed. An algorithm based on operation times （T₀） of zero voltage space vector is presented. The d-axis current （i_d） can be derived from the PI controller, whose inputs are T₀ and one constant T₀^*. The proposed strategy can achieve fast dynamic control as well as parameter insensitivity in the field-weakening region. Otherwise, it can also reduce the current amplitude of stator compared with the existing method that simply relies on its own ability of the PI controller to reach the final state.In general, Voltage distortion is existed between the reference and the actual output voltages in a pulse-width-modulated voltage-source inverter. This distortion is dead-time effects, which caused by the dead-time setting and non-ideal switching characteristics of power devices. A novel dynamic dead-time compensation for PMSM drive is presented based on the detailed analysis of the error voltage vector; besides, the second compensation is implemented to the voltage vector error caused by the changes of the running conditions and parameters of PM traction motor. Thus, it can improve the perfomance of the drive system effectively.Loss Model is analyzed in detail, sequentially, d-axis component of stator current can be achieved in any constant speed and torque operating point; and optimized through the gradient search technique and the Golden Section technique. In view of the operation characters of PMSM for EV application, this efficiency-optimization control strategy is presented to meet the demand of rapidity after analyzing the defect of efficiency-optimization control strategy of PMSM system with minimum input power in ordinary application. At the same time, the torque current feedforward is used to reduce the torque fluctuations. In addition, rapid response to the dynamic stator current distribution is adopted to get best transient response.The speed controller based on fuzzy neural networks is presented in this paper. Using the output of a fuzzy controller, online training is carried out to update the weights and biases of the artifical neural networks. So it can avoid the fussy calculation. The proposed scheme has the merits of quick dynamic response and robustness.It is studied that the parameters of PM motor affects on the performance of field-weakening combining with control strategy of inverter. The key problems of PM traction motor design are put forward according to the run characteristic and performance of PM traction motor. Analysis of d-axis, q-axis inductance and magnet flux linkage are made to the influence on the performance of the traction motor, and the design principles of PM traction motor are presented.At last, Results of simulation and experiment are done for the proposed driver in the prototype indicate: the presented drive achieves the objectives of the issue.更多还原