感应电机电动助力转向系统电机助力矩控制算法研究
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摘要
电动助力转向系统是继机械液压助力和电液助力转向系统之后所出现的一种新型的助力转向系统，能够更好的协调解决转向系统的轻便性和灵敏性问题。由于电控单元的引入，该系统具有适合模块化生产和配套方便等优点。在乘用车和新能源汽车中，电动助力转向系统正在得到越来越多的应用。
本文以感应助力电机电动助力转向系统为研究对象，研究在EPS应用条件下感应电机控制的相关算法。EPS系统作为力矩伺服系统，其首要要求便是助力电机输出力矩对指令值的快速准确响应，感应电机其结构的特殊性决定了它无法像直流有刷电机和永磁同步电机等永磁体电机那样可以较为简单地实现高性能的力矩控制。为保证感应电机EPS系统的控制性能，本文将研究重点放在了如何提高感应电机的力矩控制性能上面，着重提高助力电机对力矩指令响应的“准”和“快”，而EPS系统的“稳”则通过EPS的上层策略来改善和保证。本文就感应电机的离线参数辨识、转子磁场定向控制条件下感应电机力矩控制准确度的电机参数敏感性、转子磁场定向坐标系中的M/T两轴电流的控制算法、EPS助力特性曲线的优化、EPS硬件在环试验台和软硬件开发进行了详细论述。
本文的具体研究内容如下：
1）感应电机等效电气参数的离线辨识
在感应电机矢量控制算法中，需要通过电机参数对转子磁链位置进行估算。通过对传统感应电机参数离线辨识方法（堵转、空载方法和阶跃电压、电流方法）的辨识原理进行分析，阐述了其辨识结果精度较低的原因。为提高参数辨识精度，需要从减小样本数据受污染程度和参数辨识方法两部分分别进行改善，文中分析了参数辨识过程中的误差引入项，在逆变器供电条件下将功率器件的内阻等效至电机定子内阻，通过误差电压补偿和辨识工况的合理选择对误差进行消除和规避，获取到合理的样本数据；建立了以两相重构电压和转速为输入，两相电流和电磁力矩为输出的感应电机参数辨识模型，以输出电流误差和输出电磁力矩误差的加权值为输入设计了适应度函数，而后通过遗传算法对本文助力感应电机的电气参数进行了辨识。为对辨识得到的参数准确性进行验证，设计了包含静止两相坐标系和转子磁场定向坐标下稳态和暂态实验的参数验证方案，验证实验的结果证明：辨识得到的电机参数能够准确描述逆变器供电条件下感应电机的稳态和暂态响应；将参数应用在转子磁场控制算法中可以使感应电机实现准确的力矩控制。
2）转子磁场定向控制条件下感应电机力矩控制准确度的参数敏感性分析
在感应电机转子磁场定向控制中，力矩控制准确度严重依赖于转子磁场观测的准确程度。虽然通过参数离线辨识算法虽然获取到了较为精确的电机参数，但电机参数随温度和运行工况的变化会发生变化。考虑到感应电机的应用背景，有必要对转子磁场定向条件下应用不同磁链观测器时，感应电机力矩控制效果的参数敏感性进行定量分析，以选取适合EPS应用的观测器类型，文中提出了一种电机参数失准对力矩控制准确度影响的分析方法，对应用静止坐标下的电流-转速模型、电压-电流模型、同步旋转坐标系下的电流-转速模型和全维观测器四种不同的磁链观测模型进行力矩控制时，电机参数失准、力矩指令值大小和转速波动对力矩控制准确度的影响进行了量化分析，结合分析结果并考虑到EPS运行工况中助力电机的转速波动较为频繁，选取电机力矩控制准确度不受转速波动影响的电流-转速模型作为磁链观测模型。考虑到转子电阻对温度变化较为敏感，转子电阻失准直接导致助力电机输出助力矩失准。故采用以无功功率为模型的模型参考自适应算法对的转子电阻进行在线辨识，以提高感应电机输出力矩的控制准确性，同时也对该在线辨识算法的参数敏感性进行了分析。
3）转子磁场定向坐标系中的M/T两轴电流的控制算法
当转子磁链观测准确时，感应电机力矩控制的响应速度取决于电流控制器的调节速度。通过复矢量理论对同步旋转坐标系下常规PI、常规PI+反馈解耦两种控制方法的电流调节性能进行了分析，常规PI的电流调节性能会随同步转速的升高而减弱，而常规PI+反馈解耦的控制方法其调节性能依赖于PI参数与电机参数的匹配程度。在本文的研究中，M轴电流为恒值控制，T轴电流为随动控制，为提高电流调节器的性能，考虑到M/T轴电流指令的差异性，对M轴电流设计了模糊PI+反馈解耦的控制方法，着重消除因T轴电流变化和转速变化对M轴电流所造成的干扰，保证M轴电流的控制精度。对T轴电流设计了自适应前馈+反馈解耦的控制方法，通过减少反馈控制量在总控制量中的比例来提高系统的响应速度；为消除因前馈参数变化而导致的前馈性能减弱，提出了基于最小二乘在线辨识的的自适应前馈控制，对前馈控制性能的鲁棒性进行改善。
4）EPS上层策略中助力特性曲线的优化设计
助力特性决定了在车辆转向过程中驾驶员所施加的转向盘转矩和助力电机输出力矩的分配比例，文中通过对直线、折线和曲线三种助力特性的分析，选择参数化的四段式曲线型助力特性，以理想转向盘手力为设计目标，通过遗传算法对助力特性进行优化设计，使实际转向盘转矩特性接近理想值。
5）搭建了感应电机EPS系统硬件在环试验台，对EPS上层策略和感应电机的控制算法进行验证
为开发和调试感应电机控制算法，开发了感应电机EPS原型控制器，搭建了电机试验台；为模拟实车环境，搭建了EPS系统硬件在环试验台，通过CARSim软件对路面反力求解，并通过力矩电机对EPS系统进行加载。文中介绍了EPS控制器硬件的组成结构和软件流程，对本文的EPS系统控制算法进行了试验台验证。
本文主要得到以下结论：
（1）传统感应电机参数辨识方法存在较多问题，且受误差源的影响较大，通过对参数辨识过程中的误差引入项进行分析，对误差源进行合理补偿和规避，可以获取较为准确的电机参数。
（2）在转子磁场定向控制条件下，应用不同的磁链观测模型时，力矩控制准确度受电机参数失准程度、转速大小、力矩指令大小的影响不甚相同；其中，静止坐标系下的电流-转速模型和同步旋转坐标系下的电流-转速模型的参数敏感性相同，且不受转速波动的影响，电压-电流模型和全维观测器在特定情况下会有力矩方向的情况发生。
（3）当同步转速升高时，同步旋转坐标下的常规PID算法对电流的调节性能逐步减弱。常规PID+反馈解耦较常规PID的电流控制性能有所提高，但其调节性能依赖于通过电机参数对PID参数的整定。
（4）采用前馈算法可以有效提高T轴电流的响应速度，但其性能依赖于前馈参数的准确度，加入基于最小二乘的前馈参数在线辨识算法后可以有效提高T轴电流控制性能的鲁棒性。
本文在以下3个方面有所创新：
（1）提出了磁场定向条件下感应电机力矩控制准确度的分析方法，并对应用电流-转速模型，电压-电流模型、全维观测器进行磁链观测时，感应电机力矩控制准确度的参数敏感性进行了分析，获取了电阻类参数失准、电感类参数失准、电机转速大小、力矩指令大小对力矩控制准确度的量化影响。
（2）针对感应电机转子磁场定向控制下两轴电流指令的差异，提出通过模糊PID+反馈解耦对M轴电流进行调节；以自适应前馈（包含反馈解耦）+PI反馈对T轴电流进行调节的电流控制方法，并对所提出的方法的参数敏感性和电流响应品质进行了实验验证。
（3）提出基于理想转向盘转矩和参数化助力特性曲线的助力特性优化设计，该方法以理想转向盘转矩为优化目标，采用遗传算法对助力特性曲线的描述参数进行优化，使实际转向盘转矩接近于理想值。
Electric power steering system is a new type power steering system developed rapidlyin recent years. This new system can solve the contradiction between handiness andsensitivity, and has many advantages such as energy saving, environmental protection andeasy assemblity. Recently, electric power steering system is gradually replacing the hydraulicand electro-hydraulic power steering system, and becoming automotive technology researchfocus all over the world.
This paper treated the electric power steering system using induction motor as theresearch object, studying on the control algorithm of induction motor under the EPSapplication conditions.EPS system as a servo system, the first requirement is fast andaccurate output torque response of motor. Due to the special nature of the structure ofinduction motor, it can not like the DC brush motors and permanent magnet synchronouspermanent magnet motors that you can more easily achieve high-performance torque control,in order to ensure control performance of induction motor EPS system, this paper focus onthe study of how to improve the performance of the induction motor torque control above. Inthis paper, off-line parameter identification, parameter sensitivity of torque control accuracyunder rotor field oriented control conditions, current control algorithm, EPS hardware in theloop test rig, hardware and software development are discussed in detail.
1) Off-line parameter identification for induction motor
In the induction motor vector control algorithm, the parameters are needed by the motorrotor flux position observer. Through the analysis of conventional off-line induction motorparameter identification method, explained the reasons for the lower accuracy of theidentification results. In order to improve the accuracy of parameter identification,parameter identification can improve from two parts: Keep sample data clean and usingappropriate method, the internal resistance of the power devices is equivalent to the statorresistance of the motor, through the voltage correction and work conditions selecting toeliminate the voltage distortion and error part, getting a reasonable sample data; Treatedtwo-phase reconstruction voltage and speed as input, two-phase current and electromagnetictorque as output. Establish a parameter identification model in Simulink/Matlab. Design thefitness function from the current match and torque match, using a genetic algorithm toidentify the equivalent electrical parameters of induction motor. In order to verify theaccuracy of the identification results, design parameter validation experiment in stationarycoordinates and rotor field oriented coordinates, the validation results showed that: motorparameter identification was able to accurately describe the steady-state and transientresponse of inverter-fed induction motor condition; rotor flux orientation using identificated parameters can achieve precise torque control.
2) Analysis of parameter sensitivity of torque control accuracy under rotor field orientedcontrol conditions.
In the induction motor rotor field oriented control, torque control accuracy is heavilydependent on the accuracy of the rotor field observations. Although off-line parameteridentification algorithm can obtain accurate parameters, but motor parameters will changewith temperature and operating conditions change. This paper presents an analysis of torquecontrol accuracy error caused by parameter mismatch. The impact of motor parametersmismatch in torque control when using different type observer such as stationary coordinatescurrent-speed model, voltage-current models, synchronous coordinates current-speed modeland full-order observer was got. Taking into account the combined results and the continualmotor speed fluctuations in EPS, the current-speed observer model was selected because itstorque control accuracy has no relation with motor speed. In order to eliminate the controlerror, on-line identification algorithms called model reference adaptive system for rotorresistance was introduced, the parameters sensitivity of the algorithm were analyzed.
3) Current regulator in rotor field oriented coordinate
When rotor flux position was estimated correctly, the response speed of torque dependson the performance of the current controller. By the theory of complex vector, two typescontrol method under synchronous rotating coordinate: traditional PI control and PI+feedback decoupling control were analyzed. Conventional PI current regulator’sperformance will weaken with synchronous speed performance increases, while theconventional PI+feedback decoupling current regulator’s performance depends on the PIparameters designing using motor parameters. In this paper, M-axis current is set to aconstant value control, T-axis current is follow-up control, in order to improve the currentregulator performance, taking into account the M/T axis current difference, the M-axiscurrent is regulated by a fuzzy PI+feedback decoupling control method, focusing on theelimination of interference caused by T-axis current changes, ensuring the accuracy of theM-axis current control. The T-axis current is regulated by adaptive feedforward+feedbackdecoupling control method, by reducing the proportion of feedforward amount in the totalamount to improve the response speed of the system; In order to improve feedforwardperformance when motor parameters change, feedforward parameters online identificationalgorithm based on T-axis feedback control was proposed, robustness of feedforward wasimproved.
4) Optimized design of assisted characteristic curve
Assisted characteristics determine the distribution ratio of the steering wheel torqueand power steering motor output torque, the paper through three type assist characteristiccurve analysis. The four-part assist characteristic curve with parameters restricted wasdesigned, treat the ideal torque characteristics as the design target, using genetic algorithm tooptimize the design parameters, so that the actual steering torque characteristics close to theideal value.
5) Hardware system and experimental environment of EPS system used induction motor.
Motor test rig was established for motor control algorithm design and debug. In order tosimulate the automotive environment, the EPS hardware in loop bench was build, CARSimsoftware was used to solve road surface reaction force in real-time and EPS system is loadedby motor. This chapter describes the EPS controller hardware architecture and the softwareprocess. And at last, the EPS system control strategy was validated in EPS hardware in looptest bench.
Through analyse and experiment validation for induction motor used in EPS，the mainconclusions are as follows:
(1) Conventional induction motor parameter identification methods have someproblems, and greatly influenced by error sources. This paper analyze the error terms inparameter identification, through reasonable compensation and avoidance, error term wereeliminated, so more accurate motor parameters can be obtained.
(2) Under the conditions of the rotor field oriented control, When different fluxobserver model was used, the status of torque control accuracy affected by error of the motorparameters、motor speed and torque command is not different.
(3) When the synchronous speed increases, the current regulation performance ofconventional PID algorithm under synchronous rotation coordinates became weakened.Conventional PID+feedback decoupling control’s performance is better than conventionalPID, but its performance is dependent on the PID parameter tuning using motor parameters.
(4) Feedforward algorithm can effectively improve the response speed of T-axiscurrent, but its performance is dependent on the accuracy of the feedforward parameters,adding parameters on-line identification can improve the performance of T-axis currentcontrol robustness.
This paper has been innovative in the following areas:
(1) A analysis method of induction motor torque control accuracy under the conditionsof the rotor field oriented control was proposed. The parameter sensitivity of torque controlaccuracy used different flux observers was analyzed. Quantized affect caused by resistancemismatch、inductance mismatch、motor speed、torque command quantify is obtained.
(2) Consideration of the differences in control goal of M-axis and T-axis, proposedfuzzy PID+feedback decoupling method for the M-axis current regulation, adaptivefeedforward+feedback decoupling method for the T-axis current regulation. Parametersensitivity and current regulation performance of the proposed method was validated throughexperiment.
（3）Proposed assisted characteristic curve optimization based on ideal steering torquecharacteristic. The four-part assist characteristic curve with parameters restricted wasdesigned, treat the ideal torque characteristics as the design target, using genetic algorithm tooptimize the design parameters, so that the actual steering torque characteristics close to theideal value.
本文以感应助力电机电动助力转向系统为研究对象，研究在EPS应用条件下感应电机控制的相关算法。EPS系统作为力矩伺服系统，其首要要求便是助力电机输出力矩对指令值的快速准确响应，感应电机其结构的特殊性决定了它无法像直流有刷电机和永磁同步电机等永磁体电机那样可以较为简单地实现高性能的力矩控制。为保证感应电机EPS系统的控制性能，本文将研究重点放在了如何提高感应电机的力矩控制性能上面，着重提高助力电机对力矩指令响应的“准”和“快”，而EPS系统的“稳”则通过EPS的上层策略来改善和保证。本文就感应电机的离线参数辨识、转子磁场定向控制条件下感应电机力矩控制准确度的电机参数敏感性、转子磁场定向坐标系中的M/T两轴电流的控制算法、EPS助力特性曲线的优化、EPS硬件在环试验台和软硬件开发进行了详细论述。
本文的具体研究内容如下：
1）感应电机等效电气参数的离线辨识
在感应电机矢量控制算法中，需要通过电机参数对转子磁链位置进行估算。通过对传统感应电机参数离线辨识方法（堵转、空载方法和阶跃电压、电流方法）的辨识原理进行分析，阐述了其辨识结果精度较低的原因。为提高参数辨识精度，需要从减小样本数据受污染程度和参数辨识方法两部分分别进行改善，文中分析了参数辨识过程中的误差引入项，在逆变器供电条件下将功率器件的内阻等效至电机定子内阻，通过误差电压补偿和辨识工况的合理选择对误差进行消除和规避，获取到合理的样本数据；建立了以两相重构电压和转速为输入，两相电流和电磁力矩为输出的感应电机参数辨识模型，以输出电流误差和输出电磁力矩误差的加权值为输入设计了适应度函数，而后通过遗传算法对本文助力感应电机的电气参数进行了辨识。为对辨识得到的参数准确性进行验证，设计了包含静止两相坐标系和转子磁场定向坐标下稳态和暂态实验的参数验证方案，验证实验的结果证明：辨识得到的电机参数能够准确描述逆变器供电条件下感应电机的稳态和暂态响应；将参数应用在转子磁场控制算法中可以使感应电机实现准确的力矩控制。
2）转子磁场定向控制条件下感应电机力矩控制准确度的参数敏感性分析
在感应电机转子磁场定向控制中，力矩控制准确度严重依赖于转子磁场观测的准确程度。虽然通过参数离线辨识算法虽然获取到了较为精确的电机参数，但电机参数随温度和运行工况的变化会发生变化。考虑到感应电机的应用背景，有必要对转子磁场定向条件下应用不同磁链观测器时，感应电机力矩控制效果的参数敏感性进行定量分析，以选取适合EPS应用的观测器类型，文中提出了一种电机参数失准对力矩控制准确度影响的分析方法，对应用静止坐标下的电流-转速模型、电压-电流模型、同步旋转坐标系下的电流-转速模型和全维观测器四种不同的磁链观测模型进行力矩控制时，电机参数失准、力矩指令值大小和转速波动对力矩控制准确度的影响进行了量化分析，结合分析结果并考虑到EPS运行工况中助力电机的转速波动较为频繁，选取电机力矩控制准确度不受转速波动影响的电流-转速模型作为磁链观测模型。考虑到转子电阻对温度变化较为敏感，转子电阻失准直接导致助力电机输出助力矩失准。故采用以无功功率为模型的模型参考自适应算法对的转子电阻进行在线辨识，以提高感应电机输出力矩的控制准确性，同时也对该在线辨识算法的参数敏感性进行了分析。
3）转子磁场定向坐标系中的M/T两轴电流的控制算法
当转子磁链观测准确时，感应电机力矩控制的响应速度取决于电流控制器的调节速度。通过复矢量理论对同步旋转坐标系下常规PI、常规PI+反馈解耦两种控制方法的电流调节性能进行了分析，常规PI的电流调节性能会随同步转速的升高而减弱，而常规PI+反馈解耦的控制方法其调节性能依赖于PI参数与电机参数的匹配程度。在本文的研究中，M轴电流为恒值控制，T轴电流为随动控制，为提高电流调节器的性能，考虑到M/T轴电流指令的差异性，对M轴电流设计了模糊PI+反馈解耦的控制方法，着重消除因T轴电流变化和转速变化对M轴电流所造成的干扰，保证M轴电流的控制精度。对T轴电流设计了自适应前馈+反馈解耦的控制方法，通过减少反馈控制量在总控制量中的比例来提高系统的响应速度；为消除因前馈参数变化而导致的前馈性能减弱，提出了基于最小二乘在线辨识的的自适应前馈控制，对前馈控制性能的鲁棒性进行改善。
4）EPS上层策略中助力特性曲线的优化设计
助力特性决定了在车辆转向过程中驾驶员所施加的转向盘转矩和助力电机输出力矩的分配比例，文中通过对直线、折线和曲线三种助力特性的分析，选择参数化的四段式曲线型助力特性，以理想转向盘手力为设计目标，通过遗传算法对助力特性进行优化设计，使实际转向盘转矩特性接近理想值。
5）搭建了感应电机EPS系统硬件在环试验台，对EPS上层策略和感应电机的控制算法进行验证
为开发和调试感应电机控制算法，开发了感应电机EPS原型控制器，搭建了电机试验台；为模拟实车环境，搭建了EPS系统硬件在环试验台，通过CARSim软件对路面反力求解，并通过力矩电机对EPS系统进行加载。文中介绍了EPS控制器硬件的组成结构和软件流程，对本文的EPS系统控制算法进行了试验台验证。
本文主要得到以下结论：
（1）传统感应电机参数辨识方法存在较多问题，且受误差源的影响较大，通过对参数辨识过程中的误差引入项进行分析，对误差源进行合理补偿和规避，可以获取较为准确的电机参数。
（2）在转子磁场定向控制条件下，应用不同的磁链观测模型时，力矩控制准确度受电机参数失准程度、转速大小、力矩指令大小的影响不甚相同；其中，静止坐标系下的电流-转速模型和同步旋转坐标系下的电流-转速模型的参数敏感性相同，且不受转速波动的影响，电压-电流模型和全维观测器在特定情况下会有力矩方向的情况发生。
（3）当同步转速升高时，同步旋转坐标下的常规PID算法对电流的调节性能逐步减弱。常规PID+反馈解耦较常规PID的电流控制性能有所提高，但其调节性能依赖于通过电机参数对PID参数的整定。
（4）采用前馈算法可以有效提高T轴电流的响应速度，但其性能依赖于前馈参数的准确度，加入基于最小二乘的前馈参数在线辨识算法后可以有效提高T轴电流控制性能的鲁棒性。
本文在以下3个方面有所创新：
（1）提出了磁场定向条件下感应电机力矩控制准确度的分析方法，并对应用电流-转速模型，电压-电流模型、全维观测器进行磁链观测时，感应电机力矩控制准确度的参数敏感性进行了分析，获取了电阻类参数失准、电感类参数失准、电机转速大小、力矩指令大小对力矩控制准确度的量化影响。
（2）针对感应电机转子磁场定向控制下两轴电流指令的差异，提出通过模糊PID+反馈解耦对M轴电流进行调节；以自适应前馈（包含反馈解耦）+PI反馈对T轴电流进行调节的电流控制方法，并对所提出的方法的参数敏感性和电流响应品质进行了实验验证。
（3）提出基于理想转向盘转矩和参数化助力特性曲线的助力特性优化设计，该方法以理想转向盘转矩为优化目标，采用遗传算法对助力特性曲线的描述参数进行优化，使实际转向盘转矩接近于理想值。
Electric power steering system is a new type power steering system developed rapidlyin recent years. This new system can solve the contradiction between handiness andsensitivity, and has many advantages such as energy saving, environmental protection andeasy assemblity. Recently, electric power steering system is gradually replacing the hydraulicand electro-hydraulic power steering system, and becoming automotive technology researchfocus all over the world.
This paper treated the electric power steering system using induction motor as theresearch object, studying on the control algorithm of induction motor under the EPSapplication conditions.EPS system as a servo system, the first requirement is fast andaccurate output torque response of motor. Due to the special nature of the structure ofinduction motor, it can not like the DC brush motors and permanent magnet synchronouspermanent magnet motors that you can more easily achieve high-performance torque control,in order to ensure control performance of induction motor EPS system, this paper focus onthe study of how to improve the performance of the induction motor torque control above. Inthis paper, off-line parameter identification, parameter sensitivity of torque control accuracyunder rotor field oriented control conditions, current control algorithm, EPS hardware in theloop test rig, hardware and software development are discussed in detail.
1) Off-line parameter identification for induction motor
In the induction motor vector control algorithm, the parameters are needed by the motorrotor flux position observer. Through the analysis of conventional off-line induction motorparameter identification method, explained the reasons for the lower accuracy of theidentification results. In order to improve the accuracy of parameter identification,parameter identification can improve from two parts: Keep sample data clean and usingappropriate method, the internal resistance of the power devices is equivalent to the statorresistance of the motor, through the voltage correction and work conditions selecting toeliminate the voltage distortion and error part, getting a reasonable sample data; Treatedtwo-phase reconstruction voltage and speed as input, two-phase current and electromagnetictorque as output. Establish a parameter identification model in Simulink/Matlab. Design thefitness function from the current match and torque match, using a genetic algorithm toidentify the equivalent electrical parameters of induction motor. In order to verify theaccuracy of the identification results, design parameter validation experiment in stationarycoordinates and rotor field oriented coordinates, the validation results showed that: motorparameter identification was able to accurately describe the steady-state and transientresponse of inverter-fed induction motor condition; rotor flux orientation using identificated parameters can achieve precise torque control.
2) Analysis of parameter sensitivity of torque control accuracy under rotor field orientedcontrol conditions.
In the induction motor rotor field oriented control, torque control accuracy is heavilydependent on the accuracy of the rotor field observations. Although off-line parameteridentification algorithm can obtain accurate parameters, but motor parameters will changewith temperature and operating conditions change. This paper presents an analysis of torquecontrol accuracy error caused by parameter mismatch. The impact of motor parametersmismatch in torque control when using different type observer such as stationary coordinatescurrent-speed model, voltage-current models, synchronous coordinates current-speed modeland full-order observer was got. Taking into account the combined results and the continualmotor speed fluctuations in EPS, the current-speed observer model was selected because itstorque control accuracy has no relation with motor speed. In order to eliminate the controlerror, on-line identification algorithms called model reference adaptive system for rotorresistance was introduced, the parameters sensitivity of the algorithm were analyzed.
3) Current regulator in rotor field oriented coordinate
When rotor flux position was estimated correctly, the response speed of torque dependson the performance of the current controller. By the theory of complex vector, two typescontrol method under synchronous rotating coordinate: traditional PI control and PI+feedback decoupling control were analyzed. Conventional PI current regulator’sperformance will weaken with synchronous speed performance increases, while theconventional PI+feedback decoupling current regulator’s performance depends on the PIparameters designing using motor parameters. In this paper, M-axis current is set to aconstant value control, T-axis current is follow-up control, in order to improve the currentregulator performance, taking into account the M/T axis current difference, the M-axiscurrent is regulated by a fuzzy PI+feedback decoupling control method, focusing on theelimination of interference caused by T-axis current changes, ensuring the accuracy of theM-axis current control. The T-axis current is regulated by adaptive feedforward+feedbackdecoupling control method, by reducing the proportion of feedforward amount in the totalamount to improve the response speed of the system; In order to improve feedforwardperformance when motor parameters change, feedforward parameters online identificationalgorithm based on T-axis feedback control was proposed, robustness of feedforward wasimproved.
4) Optimized design of assisted characteristic curve
Assisted characteristics determine the distribution ratio of the steering wheel torqueand power steering motor output torque, the paper through three type assist characteristiccurve analysis. The four-part assist characteristic curve with parameters restricted wasdesigned, treat the ideal torque characteristics as the design target, using genetic algorithm tooptimize the design parameters, so that the actual steering torque characteristics close to theideal value.
5) Hardware system and experimental environment of EPS system used induction motor.
Motor test rig was established for motor control algorithm design and debug. In order tosimulate the automotive environment, the EPS hardware in loop bench was build, CARSimsoftware was used to solve road surface reaction force in real-time and EPS system is loadedby motor. This chapter describes the EPS controller hardware architecture and the softwareprocess. And at last, the EPS system control strategy was validated in EPS hardware in looptest bench.
Through analyse and experiment validation for induction motor used in EPS，the mainconclusions are as follows:
(1) Conventional induction motor parameter identification methods have someproblems, and greatly influenced by error sources. This paper analyze the error terms inparameter identification, through reasonable compensation and avoidance, error term wereeliminated, so more accurate motor parameters can be obtained.
(2) Under the conditions of the rotor field oriented control, When different fluxobserver model was used, the status of torque control accuracy affected by error of the motorparameters、motor speed and torque command is not different.
(3) When the synchronous speed increases, the current regulation performance ofconventional PID algorithm under synchronous rotation coordinates became weakened.Conventional PID+feedback decoupling control’s performance is better than conventionalPID, but its performance is dependent on the PID parameter tuning using motor parameters.
(4) Feedforward algorithm can effectively improve the response speed of T-axiscurrent, but its performance is dependent on the accuracy of the feedforward parameters,adding parameters on-line identification can improve the performance of T-axis currentcontrol robustness.
This paper has been innovative in the following areas:
(1) A analysis method of induction motor torque control accuracy under the conditionsof the rotor field oriented control was proposed. The parameter sensitivity of torque controlaccuracy used different flux observers was analyzed. Quantized affect caused by resistancemismatch、inductance mismatch、motor speed、torque command quantify is obtained.
(2) Consideration of the differences in control goal of M-axis and T-axis, proposedfuzzy PID+feedback decoupling method for the M-axis current regulation, adaptivefeedforward+feedback decoupling method for the T-axis current regulation. Parametersensitivity and current regulation performance of the proposed method was validated throughexperiment.
（3）Proposed assisted characteristic curve optimization based on ideal steering torquecharacteristic. The four-part assist characteristic curve with parameters restricted wasdesigned, treat the ideal torque characteristics as the design target, using genetic algorithm tooptimize the design parameters, so that the actual steering torque characteristics close to theideal value.
引文
[1]晋兵营,宁广庆,施国标.汽车电动助力转向系统发展综述[J].拖拉机与农用运输车,2010,37(2):1-2.
[2]余卓平,孟涛,陈慧,等.电动助力转向系统的技术发展趋势[J].汽车技术,2005,(9):1-4.
[3]林逸,施国标.汽车电动助力转向技术的发展现状与趋势[J].公路交通科技,2001,18(3):79-82.
[4]吴锋,杨志家,姚栋伟,等.电动助力转向系统控制策略的研究[J].汽车工程2006,28(7):676-680.
[5]王其东,杨孝剑,陈无畏,等.电动助力转向系统控制的台架试验研究[J].汽车工程,2004,26(5):553-556.
[6]施国标,林逸,邹常丰,等.电动助力转向系统匹配设计的研究[J].公路交通科技,2003,20(5):125-128.
[7] Zhao Liu, Jiajun Yang, Daoxun Liao. The optimization of electric power assistedsteering to improve vehicle performance [J]. Proceedings of the Institution ofMechanical Engineers,Part D: Journal of Automobile Engineering,2003,217(8):639-646.
[8]水木清华研究中心.2011-2012年中国汽车转向系统行业研究报告[R].2012.02.
[9] Hooman Mohammadi, Reza Kazemi. Simulation of Different Types of Electric PowerAssisted Steering (EPS) to Investigate Applied Torque Positions’ Effects[C]. SAETechnical Paper,2003-01-0585,2003.
[10]范心明,程小华.汽车EPS系统用电动机综述[J].防爆电机,2006,41(6):1-5.
[11] M.Abul.Masrur, R.J.Hampo, J.M.Miller. Rotational sensorless scalar control ofthree-phase induction motors and its application to automotive electric power assiststeering[C]. Proceedings of the Institution of Mechanical Engineers,2004,(214):33-44.
[12]吕威.轿车交流电机EPS控制研究与试验台测控系统开发[D].长春:吉林大学,2007.
[13]陈启苗. EPS交流电机变频变压控制与助力策略实现[D].长春:吉林大学,2009.
[14]高尚勇.三相交流异步电机在汽车电动助力转向系统中的应用研究[D].重庆:重庆大学,2009.
[15]张卫冬,晏蔚光,余达太,等.用于转向系统的感应电机转矩伺服系统[J].微电机,2002(5):27-30.
[16]张卫冬,余达太,晏蔚光,等.一种智能汽车电动助力转向系统[J].北京科技大学学报,2003(1):66-68.
[17]张卫冬,余达太,晏蔚光,等.交流转矩伺服系统的H∞鲁棒控制[J].北京科技大学学报,2006(2):185-189.
[18]刘喜东.大客车EPS助动力矩及控制策略研究[D].西安:长安大学,2009.
[19]杜欣慧,刘娇,朱丽娟,王孝.模糊控制器在水泵恒压频比调速系统中的实现[J].节能,2008(3):19-21.
[20]戴先中,刘国,张兴华.恒压频比变频调速系统的神经网络逆控制[J].中国电机工程学报,2005.25(7):109-114.
[21]杜欣慧,刘娇,王孝,朱善俊.模糊控制与恒压频比控制在水泵调速系统中的实现[J].电气技术,2008(1):20-23.
[22]万冬.异步电动机变频调速系统矢量控制的研究[D].南昌:南昌大学,2013.
[23]刘永欢.基于dSPACE的异步电机矢量控制策略研究与实现[D].北京:北京交通大学,2012.
[24]潘景鹏.异步电机的数字化矢量控制[D].大连:大连理工大学,2013.
[25]虞正民.电机矢量控制系统及其节能化研究[D].杭州:浙江大学,2011.
[26]廖桂潘.交流异步电机矢量控制的研究与实现[D].武汉:武汉理工大学,2012.
[27]赵阳.风力发电系统用双馈感应发电机矢量控制技术研究[D].武汉:华中科技大学,2008.
[28]唐广笛.全数字异步电机直接转矩控制系统的仿真与设计方法研究[D].湘潭:湘潭大学,2003.
[29]李辉.改善直接转矩控制低速性能的研究[D].湘潭:湘潭大学,2005.
[30]彭思齐.基于模糊控制和DSP的异步电机直接转矩控制研究[D].湘潭:湘潭大学,2005.
[31]姜伟东.异步电动机直接转矩控制系统的Matlab仿真[D].大连:大连铁道学院,2003.
[32]杨祖泉,姚绪梁,舒小芳.异步电动机直接转矩控制系统的仿真研究[J].电机与控制学报,2004,8(4):329-332.
[33]刘洋,赵金,王庆义.间接矢量控制系统中的异步电动机参数辨识[J].电工技术学报,2009.23(7):21-26.
[34]罗慧,刘军锋,万淑芸.感应电机参数的离线辨识[J].电气传动,2006,6(8):16-21.
[35]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].电工技术学报,2006,21(8):90-96.
[36]张虎,李正熙,童朝南.基于递推最小二乘算法的感应电动机参数离线辨识[J].中国电机工程学报,2011,31(18):79-86.
[37]黄开胜,童怀,郑泰胜.遗传算法在异步电动机动态模型参数识别中的应用[J].中国电机工程学报,2008,20(8):37-41.
[38] Andrew Trentin, Pericle Zanchetta, Patrick Wheeler, Jon Clare. A New Method forInduction Motors Parameter Estimation Using Genetic Algorithms and TransientSpeed measurements[C].41st IAS Annual Meeting,2006.5:2435-2240.
[39] Ebrahim Rahimpour, Vahid Rashtchi, Mahmood Pesaran. Parameter identification ofdeep-bar induction motors using genetic algorithm[J]. ElectricalEngineering,2007,89(7):547-552
[40] Suman Maiti, Chandan Chakraborty. Model Reference Adaptive Controller-BasedRotor Resistance and Speed Estimation Techniques for Vector Controlled InductionMotor Drive Utilizing Reactive Power[J]. IEEE TRANSACTIONS ON INDUSTRIALELECTRONICS,2008,55(2):594-601.
[41]赵歆,王明渝,刘述喜.基于扩展卡尔曼滤波器的异步电机矢量控制系统的转子电阻辨识[J].电机与控制应用,2009,36(3):18-23.
[42]赵歆.感应电动机离线参数辨识方法研究[D].重庆:重庆大学,2008.
[43]刘和平,邓力,郑群英,等.基于矢量控制的电动轿车感应电机驱动控制器[J].电工技术学报,2007,22(11):63-68.
[44]陈硕,迁峰男,山田英二.感应电机无速度传感器矢量控制系统的定子电阻在线辨识[J].中国电机工程学报,2003,23(2):88-92.
[45]罗慧.感应电机全阶磁链观测器和转速估算方法研究[D].武汉:华中科技大学,2009.
[46] Marko Hinkkanen, Jorma Luomi. Parameter Sensitivity of Full-Order Flux Observersfor Induction Motors[J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS,2003,39(4):1127-1134.
[47] Zhenhuan Yuan, Haihui Lu, Russel J. Kerkman, etal. Parameter Sensitivity Analysis ofFluxObservers for Induction Motors[C].42nd IAS Annual Meeting:1015-1022
[48]刁利君,孙大南,陈杰,等.间接矢量控制异步电动机参数敏感性分析[J].电工技术学报,2010,25(6):18-23
[49]杨文强,贾正春.异步电机转子磁链观测器的准确度分析与设计[J].华中科技大学学报,2001,29(2):11-13.
[50]高建华.转子时间常数对异步电机矢量控制的影响[D].北京:中国科学院研究生院,2003.
[51]张代红,王明渝.磁饱和及参数变化对速度观测器精度的影响[J].重庆大学学报(自然科学版),2006,29(3):35-39.
[52] Bu J R, Xu L Y. A new deadbeat fuzzy algorithm for current regulated PWM withoutrotating reference frame transformation transformation[C]. Proceedings of the24thAnnual Conference of the IEEE Industrial Electronics Society,Germany:AachenIECONp98,1998.
[53] Ottersten R, Svensson J. Vector current controlled voltage source converter-deadbeatcontrol and saturation strategies[J]. IEEE Transactions on PowerElectronics,2002,17(2):279-285.
[54] Malesani L, Mattavelli P, Buso S. Robust dead-beat current control for PWM rectifiersand active filters[J]. IEEE Transactions on Industry Applications,1999,35(3):613-620.
[55] Telford D, Dunnigan MW, Williams BW. Adaptive high bandwidth current control forinduction machines[J]. IEEE Transactions on Power Electronics,2003,18(2):527-538.
[56] Nishida K, Nakaoka M. Deadbeat current control with adaptive predictor for three-phase voltage-source active power filter[C]. IEEE35th Annual Conference on PowerElectronics Specialists Conference,Germany Aachen:PESC,2004.
[57] Wang Dazhi, Wang Zhenlei, Gu Shusheng. Identification and control of inductionmotor using artificial neural networks[C]. Proceedings of the Fifth InternationalConference on Electrical Machines and Systems,2001,ICEMS,2(18-20):751-754.
[58]李晓芳.基于神经网络的感应电机定子电阻参数辨识[D].大连:大连交通大学,2007.
[59]孙亚飞,王旭,贾芙蓉.基于人工神经网络的感应电机系统辨识[J].控制工程,2002,9(4):71-72.
[60] Burton B, Harley RG, Diana G, etal. Implementation of a neural network to adaptivelyidentify and control VSI-Fed induction motor stator currents[J]. IEEE Transactions onIndustry Applications,1998,34(3):580-588.
[61] Burton B, Kamran F, Harley R, etal. Identification and control of induction motorstator current using on-line random training of a neural network[J]. IEEE Transactionson Industry Applications,1997,33(3):697-704.
[62] Dell Aquila A, Liserre M, Zanchetta P. A new low cost CC-PWM inverter based onfuzzy logic[C]. The Eighth International Conference on Power Electronics andVariable Speed Drives,2000:466-471.
[63]殷海蒙,高艳霞,朱平平.异步电动机参数离线辨识[J].电气传动和自动控制,2004,26(5):10-11.
[64]刘洋,赵金,王庆义.间接矢量控制系统中的异步电动机参数辨识[J].电工技术学报,2008,23(7):21-26.
[65]王高林,商振,于泳,等.感应电动机参数离线辨识方法实验研究[J].微电机,2009,42(6):4-7.
[66]吴晓新,顾菊平,阮毅.感应电机矢量控制系统参数辨识研究[J].微电机,2010,43(4):20-23.
[67] Ashwin M, Khambadkone, Joachim Holtz. Vector-Controlled Induction Motor Drivewith a self-Commissioning Scheme[J]. IEEE TRANSACTIONS ON INDUSTRIALELECTRONICS,1991,38(5):322-327.
[68]许镇琳,何启莲,李国民,等.异步机矢量控制系统的电机参数自设定[J].电工技术学报,1995,(1):44-47.
[69]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].电工技术学报,2006,21(8):90-96.
[70]谭国俊,朱翀,李广超,等.基于DSP的异步电动机关键参数辨识研究[J].工矿自动化,2009,(9):41-45.
[71]贺晓蓉,刘述喜,雷绍兰,等.基于动态模型的感应电机参数辨识方法[J].重庆理工大学学报(自然科学版),2010,24(7):100-105.
[72]刘述喜,贺晓蓉,雷绍兰,等.基于DSP的感应电机参数辨识[J].微电机,2011,44(1):65-69.
[73]夏超英.交直流传动系统的自适应控制[M].北京:机械工业出版社,1998,5.
[74] WEATHERFORD H, BRICE CW. Estimation of induction motor parameters by agenetic algorithm[C]. Conference Record of the2003Annual Pulp and Paper IndustryTechnical Conference,2003:21-28.
[75] AC Megherbi, H Megherbi, K Benmahamed, etal. Parameter Identification ofInduction Motors using Variable-weighted Cost Function of Genetic Algorithms[J].Journal of Electrical Engineering&Technology,2010,5(4):597-605.
[76]李汉强.矢量控制异步电机等效电路及其参数变化因素分析[J].武汉交通科技大学学报,1999,23(5):469-472.
[77]张文海.损耗对电机参数的影响[J].微电机,2002,35(4):42-43.
[78]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].电工技术学报,2006,21(8):90-96.
[79]张旭,宋文祥,尹赟.一种三电平逆变器输出电压重构方法[J].电气传动,2011,41(10):29-32.
[80]韩利,温旭辉,郭希铮.电压源逆变器输出电压重构技术研究[J].电力电子技术,2007,41(11):94-96.
[81]孙向东,尚媛,钟彦儒,等.三相电压源逆变器输出电压重构技术的研究[J].西安理工大学学报,2005,21(2):122-124.
[82] Alfredo, R Munoz, Thomas A. On-Line Dead-Time Compensation Technique forOpen-Loop PWM-VSI Drives[J]. IEEE Transactions On Power Electronics,1999,14(4):683-689.
[83] Jong-Woo Choi, Seung-Ki Sul. Inverter Output Voltage Synthesis Using Novel DeadTime Compensation[J]. IEEE Transactions On Power Electronics,1996,11(2):221-227.
[84] Seon-Hwan Hwang, Jang-Mok Kim. Dead Time Compensation Method forVoltage-Fed PWM Inverter[J]. IEEE Transactions On Energy Conversion,2010,25(1):1-10
[85]孙向东,钟彦儒,任碧莹,等.一种新颖的死区补偿时间测量方法[J].中国电机工程学报,2003,23(2):103-107.
[86] Jong-Woo Choi, Seung-Ki Sul. Inverter Output Voltage Synthesis Using Novel DeadTime Compensation[J]. IEEE TRANSACTIONS ON POWER ELECTRONICS,1996,11(2):221-227.
[87]朝泽云.无速度传感器矢量控制系统的若干问题研究[D].武汉:华中科技大学,2006.
[88]金舜.交流电动机二极管箝位三电平逆变器PWM控制策略的研究[D].西安:西安理工大学,2006.
[89]汤新舟.永磁同步电机的矢量控制系统[D].杭州:浙江大学,2005.
[90]徐德丰,韩中林,洪雷. PWM控制方式下死区对变频器性能的影响分析[J].低压电器,2004(12):53-57.
[91]郑伟,季筱隆,刘玮,等.一种基于电流矢量的死区时间补偿方案[J].电气传动,2005,35(4):34-36
[92]吴茂刚,赵荣祥,汤新舟.空间矢量PWM逆变器死区效应分析与补偿方法[J].浙江大学学报(工学版),2006,40(3):469-473.
[93]王晓明.电动机的DSP控制[M].北京:北京航空航天大学出版社,2004.7
[94]罗慧.感应电机全阶磁链观测器和转速估算方法研究[D].武汉:华中科技大学,2009.
[95] Zhenhuan Yuan, Haihui Lu, Russel J, etal. Parameter Sensitivity Analysis of FluxObservers for Induction Motors[C].42nd IAS Annual Meeting,2007:1015-1022.
[96]刘豹,唐万生.现代控制理论[M].北京:机械工业出版社,2011.
[97] Novel Rotor-Flux Observer Using Observer Characteristic Function in Complex VectorSpace for Field-Oriented Induction Motor Drive[J]. IEEE Transactions on IndustryApplications,2002,38(5):1334-1343.
[98]张静. Matlab在控制系统中的应用[M].北京:电子工业出版社,2007.
[99] Li Zhen, Long-ya Xu. MRAS Observer for Sensorless Control of Standalone DoublyFed Induction Generators[J]. IEEE TRANSACTIONS ON ENERGYCONVERSION,2005,20(4):710-718.
[100]Ruben Pena, Roberto Cardenas, Jose Proboste, etal. Sensorless Control of Doubly-FedInduction Generators Using a Rotor-Current-Based MRAS Observer[J]. IEEETRANSACTIONS ON INDUSTRIAL ELECTRONICS,2008,55(1):330-339.
[101]周亚丽,李永东,郑泽东.基于MRAS的感应电机无速度传感器矢量控制[J].电气传动,2009,39(4):3-8.
[102]杜圣峰.感应电机参数辨识算法及其FPGA设计研究[D].无锡:江南大学,2008.
[103]陈伯时,杨耕.无速度传感器高性能交流调速控制的三条思路及其发展建议[J].电气传动,2006,36(1):3-8.
[104]Daigo Akamatsu, Akira Chiba. An improved rotor resistance identification forbearing-less induction motors[C]. IEEE International Conference on Electric Machinesand Drives,2005,15(18):1981-1987.
[105]王瑞,赵金,丛喆,等.基于MRAS的转子时间常数辨识方法的参数敏感性分析[J].电气传动,2010,40(1):3-7.
[106]Rehman HU, Derdiyok A, Guven MK, etal. An MRAS scheme for on-line rotorresistance adaptation of an induction machine[C]. Power Electronics SpecialistsConference,2001,2:817-822.
[107]任振华.基于模型参考自适应的异步电机转子电阻辨识[D].北京:北京交通大学,2012.
[108]孙大南,刘志刚,刁利军.牵引电机矢量控制转子磁场准确定向实时校正策略[J].电工技术学报,2011,26(9):116-123
[109]邱阿瑞,尹雁,等.基于DSP的无速度传感器异步电机矢量控制系统[J].清华大学学报(自然科学版),2001,41(3):21-24.
[110]FJ Lin, D.H.Wang, PK Huang. FPGA-based fuzzy sliding-mode control for a linearinduction motor drive, IEEE Proceedings Of Electric Power Applications,2005,52(5):1137-1148.
[111]王文森,李永东,等.基于PI自适应法的无速度传感器异步电动机矢量控制系统[J].电工技术学报,2002,17(1):1-6.
[112]喻寿益,张艳存,高金生,等.基于无功功率模型的异步电机矢量控制系统转子时间常数辨识[J].中南大学学报(自然科学版),2009,40(5):1318-1322.
[113]王高林,杨荣峰,张家皖.一种感应电机转子时间常数MRAS的在线辨识方法[J].电工技术学报,2012,27(4):48-53.
[114]陆海峰,瞿文龙,张磊,等.一种基于无功功率的异步电机矢量控制转子磁场准确定向方法[J].中国电机工程学报,2005,25(16):116-120.
[115]Geng Yang, Tung-Hai Chin. MRAS-based speed sensorless control scheme with statorresistance identification function for vector-controlled induction motor drives[J].Electrical Engineering in Japan,2007,113(1):98-108
[116]Li Zhen, Longya Xu. A mutual MRAS identification scheme for position sensorleefield orientation control of induction machines[C]. Industry ApplicationsConference,1995,1:159-165.
[117]FAIZ J, MOHSENI-ZONOOZI S H. A novel technique for estimation and control ofstator flux of a salient-pole PMSM in DTC method based on MTPF[J]. IEEETransactions on Industrial Electronics,2003,50(2):262-271.
[118]RASHED M, MACCONNELL P, STRONCACH A, etal. Sensorless indirect rotor fieldorientation speed control of permanent magnet synchronous motor using adaptive rotorflux estimator[C]. European Control Conference,2005:647-652.
[119]姜学宝.基于模糊PID控制理论的双微机励磁调节器的研制[D].福州:福州大学,2002.
[120]George Ellis. Control System Design Guide (Third Edition)[M]. BEIJING: PublishingHouse of Electronics Industry,2006:138-139.
[121]余志生.汽车理论(第3版)[M].北京:机械工业出版社,2000.
[122]Berto llini G P, H og an R M. Applying Driving Simulation to Quantify Steering EffortPreference as a Function of Vehicle Speed[J]. SAE Paper,1999-01-0394.
[123]宗长富,麦莉,王德平,李雅娟.基于驾驶模拟器的驾驶员所偏好的转向盘力矩特性研究[J].中国机械工程,2007,18(8):1001-1005.
[124]Ji-Hoon Kim, Jac-Bok Song. Control logic for an Electric Power Steering SystemUsing Assist Motor[J]. Mechatronics,2002,(12):447-459.
[125]陈利利.某轿车EPS系统电机控制策略的仿真研究[D].长春:吉林大学,2008.
[126]刘照.汽车电动助力转向系统动力学分析与控制方法研究[D].武汉:华中科技大学,2004.
[127]赵景波,周冰,李秀莲,贝绍轶.电动汽车EPS曲线型助力特性的设计及试验[J],电机与控制学报,2011,15(12):96-102.
[128]王其东,杨孝剑,陈无畏,等.电动助力转向系统的建模及控制[J].农业机械学报,2004,35(5):1-4.
[129]荆体魁.汽车电动助力转向控制系统的设计[D].大连:大连理工大学,2006.
[130]徐汉斌.电动转向器控制系统研究[D].武汉:武汉理工大学,2007.
[131]徐建平,何仁,苗立东,等.电动助力转向系统回正控制算法研究[J].汽车工程,2004,26(5):557-559.
[132]施国标,林逸,陈万忠,等.汽车电动助力转向试验台测试系统开发[J].测控技术,2005,24(3):23-25.
[133]刘冰,汽车线控转向系统硬件在环试验台研究与开发[D].长春:吉林大学,2008.
[2]余卓平,孟涛,陈慧,等.电动助力转向系统的技术发展趋势[J].汽车技术,2005,(9):1-4.
[3]林逸,施国标.汽车电动助力转向技术的发展现状与趋势[J].公路交通科技,2001,18(3):79-82.
[4]吴锋,杨志家,姚栋伟,等.电动助力转向系统控制策略的研究[J].汽车工程2006,28(7):676-680.
[5]王其东,杨孝剑,陈无畏,等.电动助力转向系统控制的台架试验研究[J].汽车工程,2004,26(5):553-556.
[6]施国标,林逸,邹常丰,等.电动助力转向系统匹配设计的研究[J].公路交通科技,2003,20(5):125-128.
[7] Zhao Liu, Jiajun Yang, Daoxun Liao. The optimization of electric power assistedsteering to improve vehicle performance [J]. Proceedings of the Institution ofMechanical Engineers,Part D: Journal of Automobile Engineering,2003,217(8):639-646.
[8]水木清华研究中心.2011-2012年中国汽车转向系统行业研究报告[R].2012.02.
[9] Hooman Mohammadi, Reza Kazemi. Simulation of Different Types of Electric PowerAssisted Steering (EPS) to Investigate Applied Torque Positions’ Effects[C]. SAETechnical Paper,2003-01-0585,2003.
[10]范心明,程小华.汽车EPS系统用电动机综述[J].防爆电机,2006,41(6):1-5.
[11] M.Abul.Masrur, R.J.Hampo, J.M.Miller. Rotational sensorless scalar control ofthree-phase induction motors and its application to automotive electric power assiststeering[C]. Proceedings of the Institution of Mechanical Engineers,2004,(214):33-44.
[12]吕威.轿车交流电机EPS控制研究与试验台测控系统开发[D].长春:吉林大学,2007.
[13]陈启苗. EPS交流电机变频变压控制与助力策略实现[D].长春:吉林大学,2009.
[14]高尚勇.三相交流异步电机在汽车电动助力转向系统中的应用研究[D].重庆:重庆大学,2009.
[15]张卫冬,晏蔚光,余达太,等.用于转向系统的感应电机转矩伺服系统[J].微电机,2002(5):27-30.
[16]张卫冬,余达太,晏蔚光,等.一种智能汽车电动助力转向系统[J].北京科技大学学报,2003(1):66-68.
[17]张卫冬,余达太,晏蔚光,等.交流转矩伺服系统的H∞鲁棒控制[J].北京科技大学学报,2006(2):185-189.
[18]刘喜东.大客车EPS助动力矩及控制策略研究[D].西安:长安大学,2009.
[19]杜欣慧,刘娇,朱丽娟,王孝.模糊控制器在水泵恒压频比调速系统中的实现[J].节能,2008(3):19-21.
[20]戴先中,刘国,张兴华.恒压频比变频调速系统的神经网络逆控制[J].中国电机工程学报,2005.25(7):109-114.
[21]杜欣慧,刘娇,王孝,朱善俊.模糊控制与恒压频比控制在水泵调速系统中的实现[J].电气技术,2008(1):20-23.
[22]万冬.异步电动机变频调速系统矢量控制的研究[D].南昌:南昌大学,2013.
[23]刘永欢.基于dSPACE的异步电机矢量控制策略研究与实现[D].北京:北京交通大学,2012.
[24]潘景鹏.异步电机的数字化矢量控制[D].大连:大连理工大学,2013.
[25]虞正民.电机矢量控制系统及其节能化研究[D].杭州:浙江大学,2011.
[26]廖桂潘.交流异步电机矢量控制的研究与实现[D].武汉:武汉理工大学,2012.
[27]赵阳.风力发电系统用双馈感应发电机矢量控制技术研究[D].武汉:华中科技大学,2008.
[28]唐广笛.全数字异步电机直接转矩控制系统的仿真与设计方法研究[D].湘潭:湘潭大学,2003.
[29]李辉.改善直接转矩控制低速性能的研究[D].湘潭:湘潭大学,2005.
[30]彭思齐.基于模糊控制和DSP的异步电机直接转矩控制研究[D].湘潭:湘潭大学,2005.
[31]姜伟东.异步电动机直接转矩控制系统的Matlab仿真[D].大连:大连铁道学院,2003.
[32]杨祖泉,姚绪梁,舒小芳.异步电动机直接转矩控制系统的仿真研究[J].电机与控制学报,2004,8(4):329-332.
[33]刘洋,赵金,王庆义.间接矢量控制系统中的异步电动机参数辨识[J].电工技术学报,2009.23(7):21-26.
[34]罗慧,刘军锋,万淑芸.感应电机参数的离线辨识[J].电气传动,2006,6(8):16-21.
[35]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].电工技术学报,2006,21(8):90-96.
[36]张虎,李正熙,童朝南.基于递推最小二乘算法的感应电动机参数离线辨识[J].中国电机工程学报,2011,31(18):79-86.
[37]黄开胜,童怀,郑泰胜.遗传算法在异步电动机动态模型参数识别中的应用[J].中国电机工程学报,2008,20(8):37-41.
[38] Andrew Trentin, Pericle Zanchetta, Patrick Wheeler, Jon Clare. A New Method forInduction Motors Parameter Estimation Using Genetic Algorithms and TransientSpeed measurements[C].41st IAS Annual Meeting,2006.5:2435-2240.
[39] Ebrahim Rahimpour, Vahid Rashtchi, Mahmood Pesaran. Parameter identification ofdeep-bar induction motors using genetic algorithm[J]. ElectricalEngineering,2007,89(7):547-552
[40] Suman Maiti, Chandan Chakraborty. Model Reference Adaptive Controller-BasedRotor Resistance and Speed Estimation Techniques for Vector Controlled InductionMotor Drive Utilizing Reactive Power[J]. IEEE TRANSACTIONS ON INDUSTRIALELECTRONICS,2008,55(2):594-601.
[41]赵歆,王明渝,刘述喜.基于扩展卡尔曼滤波器的异步电机矢量控制系统的转子电阻辨识[J].电机与控制应用,2009,36(3):18-23.
[42]赵歆.感应电动机离线参数辨识方法研究[D].重庆:重庆大学,2008.
[43]刘和平,邓力,郑群英,等.基于矢量控制的电动轿车感应电机驱动控制器[J].电工技术学报,2007,22(11):63-68.
[44]陈硕,迁峰男,山田英二.感应电机无速度传感器矢量控制系统的定子电阻在线辨识[J].中国电机工程学报,2003,23(2):88-92.
[45]罗慧.感应电机全阶磁链观测器和转速估算方法研究[D].武汉:华中科技大学,2009.
[46] Marko Hinkkanen, Jorma Luomi. Parameter Sensitivity of Full-Order Flux Observersfor Induction Motors[J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS,2003,39(4):1127-1134.
[47] Zhenhuan Yuan, Haihui Lu, Russel J. Kerkman, etal. Parameter Sensitivity Analysis ofFluxObservers for Induction Motors[C].42nd IAS Annual Meeting:1015-1022
[48]刁利君,孙大南,陈杰,等.间接矢量控制异步电动机参数敏感性分析[J].电工技术学报,2010,25(6):18-23
[49]杨文强,贾正春.异步电机转子磁链观测器的准确度分析与设计[J].华中科技大学学报,2001,29(2):11-13.
[50]高建华.转子时间常数对异步电机矢量控制的影响[D].北京:中国科学院研究生院,2003.
[51]张代红,王明渝.磁饱和及参数变化对速度观测器精度的影响[J].重庆大学学报(自然科学版),2006,29(3):35-39.
[52] Bu J R, Xu L Y. A new deadbeat fuzzy algorithm for current regulated PWM withoutrotating reference frame transformation transformation[C]. Proceedings of the24thAnnual Conference of the IEEE Industrial Electronics Society,Germany:AachenIECONp98,1998.
[53] Ottersten R, Svensson J. Vector current controlled voltage source converter-deadbeatcontrol and saturation strategies[J]. IEEE Transactions on PowerElectronics,2002,17(2):279-285.
[54] Malesani L, Mattavelli P, Buso S. Robust dead-beat current control for PWM rectifiersand active filters[J]. IEEE Transactions on Industry Applications,1999,35(3):613-620.
[55] Telford D, Dunnigan MW, Williams BW. Adaptive high bandwidth current control forinduction machines[J]. IEEE Transactions on Power Electronics,2003,18(2):527-538.
[56] Nishida K, Nakaoka M. Deadbeat current control with adaptive predictor for three-phase voltage-source active power filter[C]. IEEE35th Annual Conference on PowerElectronics Specialists Conference,Germany Aachen:PESC,2004.
[57] Wang Dazhi, Wang Zhenlei, Gu Shusheng. Identification and control of inductionmotor using artificial neural networks[C]. Proceedings of the Fifth InternationalConference on Electrical Machines and Systems,2001,ICEMS,2(18-20):751-754.
[58]李晓芳.基于神经网络的感应电机定子电阻参数辨识[D].大连:大连交通大学,2007.
[59]孙亚飞,王旭,贾芙蓉.基于人工神经网络的感应电机系统辨识[J].控制工程,2002,9(4):71-72.
[60] Burton B, Harley RG, Diana G, etal. Implementation of a neural network to adaptivelyidentify and control VSI-Fed induction motor stator currents[J]. IEEE Transactions onIndustry Applications,1998,34(3):580-588.
[61] Burton B, Kamran F, Harley R, etal. Identification and control of induction motorstator current using on-line random training of a neural network[J]. IEEE Transactionson Industry Applications,1997,33(3):697-704.
[62] Dell Aquila A, Liserre M, Zanchetta P. A new low cost CC-PWM inverter based onfuzzy logic[C]. The Eighth International Conference on Power Electronics andVariable Speed Drives,2000:466-471.
[63]殷海蒙,高艳霞,朱平平.异步电动机参数离线辨识[J].电气传动和自动控制,2004,26(5):10-11.
[64]刘洋,赵金,王庆义.间接矢量控制系统中的异步电动机参数辨识[J].电工技术学报,2008,23(7):21-26.
[65]王高林,商振,于泳,等.感应电动机参数离线辨识方法实验研究[J].微电机,2009,42(6):4-7.
[66]吴晓新,顾菊平,阮毅.感应电机矢量控制系统参数辨识研究[J].微电机,2010,43(4):20-23.
[67] Ashwin M, Khambadkone, Joachim Holtz. Vector-Controlled Induction Motor Drivewith a self-Commissioning Scheme[J]. IEEE TRANSACTIONS ON INDUSTRIALELECTRONICS,1991,38(5):322-327.
[68]许镇琳,何启莲,李国民,等.异步机矢量控制系统的电机参数自设定[J].电工技术学报,1995,(1):44-47.
[69]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].电工技术学报,2006,21(8):90-96.
[70]谭国俊,朱翀,李广超,等.基于DSP的异步电动机关键参数辨识研究[J].工矿自动化,2009,(9):41-45.
[71]贺晓蓉,刘述喜,雷绍兰,等.基于动态模型的感应电机参数辨识方法[J].重庆理工大学学报(自然科学版),2010,24(7):100-105.
[72]刘述喜,贺晓蓉,雷绍兰,等.基于DSP的感应电机参数辨识[J].微电机,2011,44(1):65-69.
[73]夏超英.交直流传动系统的自适应控制[M].北京:机械工业出版社,1998,5.
[74] WEATHERFORD H, BRICE CW. Estimation of induction motor parameters by agenetic algorithm[C]. Conference Record of the2003Annual Pulp and Paper IndustryTechnical Conference,2003:21-28.
[75] AC Megherbi, H Megherbi, K Benmahamed, etal. Parameter Identification ofInduction Motors using Variable-weighted Cost Function of Genetic Algorithms[J].Journal of Electrical Engineering&Technology,2010,5(4):597-605.
[76]李汉强.矢量控制异步电机等效电路及其参数变化因素分析[J].武汉交通科技大学学报,1999,23(5):469-472.
[77]张文海.损耗对电机参数的影响[J].微电机,2002,35(4):42-43.
[78]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].电工技术学报,2006,21(8):90-96.
[79]张旭,宋文祥,尹赟.一种三电平逆变器输出电压重构方法[J].电气传动,2011,41(10):29-32.
[80]韩利,温旭辉,郭希铮.电压源逆变器输出电压重构技术研究[J].电力电子技术,2007,41(11):94-96.
[81]孙向东,尚媛,钟彦儒,等.三相电压源逆变器输出电压重构技术的研究[J].西安理工大学学报,2005,21(2):122-124.
[82] Alfredo, R Munoz, Thomas A. On-Line Dead-Time Compensation Technique forOpen-Loop PWM-VSI Drives[J]. IEEE Transactions On Power Electronics,1999,14(4):683-689.
[83] Jong-Woo Choi, Seung-Ki Sul. Inverter Output Voltage Synthesis Using Novel DeadTime Compensation[J]. IEEE Transactions On Power Electronics,1996,11(2):221-227.
[84] Seon-Hwan Hwang, Jang-Mok Kim. Dead Time Compensation Method forVoltage-Fed PWM Inverter[J]. IEEE Transactions On Energy Conversion,2010,25(1):1-10
[85]孙向东,钟彦儒,任碧莹,等.一种新颖的死区补偿时间测量方法[J].中国电机工程学报,2003,23(2):103-107.
[86] Jong-Woo Choi, Seung-Ki Sul. Inverter Output Voltage Synthesis Using Novel DeadTime Compensation[J]. IEEE TRANSACTIONS ON POWER ELECTRONICS,1996,11(2):221-227.
[87]朝泽云.无速度传感器矢量控制系统的若干问题研究[D].武汉:华中科技大学,2006.
[88]金舜.交流电动机二极管箝位三电平逆变器PWM控制策略的研究[D].西安:西安理工大学,2006.
[89]汤新舟.永磁同步电机的矢量控制系统[D].杭州:浙江大学,2005.
[90]徐德丰,韩中林,洪雷. PWM控制方式下死区对变频器性能的影响分析[J].低压电器,2004(12):53-57.
[91]郑伟,季筱隆,刘玮,等.一种基于电流矢量的死区时间补偿方案[J].电气传动,2005,35(4):34-36
[92]吴茂刚,赵荣祥,汤新舟.空间矢量PWM逆变器死区效应分析与补偿方法[J].浙江大学学报(工学版),2006,40(3):469-473.
[93]王晓明.电动机的DSP控制[M].北京:北京航空航天大学出版社,2004.7
[94]罗慧.感应电机全阶磁链观测器和转速估算方法研究[D].武汉:华中科技大学,2009.
[95] Zhenhuan Yuan, Haihui Lu, Russel J, etal. Parameter Sensitivity Analysis of FluxObservers for Induction Motors[C].42nd IAS Annual Meeting,2007:1015-1022.
[96]刘豹,唐万生.现代控制理论[M].北京:机械工业出版社,2011.
[97] Novel Rotor-Flux Observer Using Observer Characteristic Function in Complex VectorSpace for Field-Oriented Induction Motor Drive[J]. IEEE Transactions on IndustryApplications,2002,38(5):1334-1343.
[98]张静. Matlab在控制系统中的应用[M].北京:电子工业出版社,2007.
[99] Li Zhen, Long-ya Xu. MRAS Observer for Sensorless Control of Standalone DoublyFed Induction Generators[J]. IEEE TRANSACTIONS ON ENERGYCONVERSION,2005,20(4):710-718.
[100]Ruben Pena, Roberto Cardenas, Jose Proboste, etal. Sensorless Control of Doubly-FedInduction Generators Using a Rotor-Current-Based MRAS Observer[J]. IEEETRANSACTIONS ON INDUSTRIAL ELECTRONICS,2008,55(1):330-339.
[101]周亚丽,李永东,郑泽东.基于MRAS的感应电机无速度传感器矢量控制[J].电气传动,2009,39(4):3-8.
[102]杜圣峰.感应电机参数辨识算法及其FPGA设计研究[D].无锡:江南大学,2008.
[103]陈伯时,杨耕.无速度传感器高性能交流调速控制的三条思路及其发展建议[J].电气传动,2006,36(1):3-8.
[104]Daigo Akamatsu, Akira Chiba. An improved rotor resistance identification forbearing-less induction motors[C]. IEEE International Conference on Electric Machinesand Drives,2005,15(18):1981-1987.
[105]王瑞,赵金,丛喆,等.基于MRAS的转子时间常数辨识方法的参数敏感性分析[J].电气传动,2010,40(1):3-7.
[106]Rehman HU, Derdiyok A, Guven MK, etal. An MRAS scheme for on-line rotorresistance adaptation of an induction machine[C]. Power Electronics SpecialistsConference,2001,2:817-822.
[107]任振华.基于模型参考自适应的异步电机转子电阻辨识[D].北京:北京交通大学,2012.
[108]孙大南,刘志刚,刁利军.牵引电机矢量控制转子磁场准确定向实时校正策略[J].电工技术学报,2011,26(9):116-123
[109]邱阿瑞,尹雁,等.基于DSP的无速度传感器异步电机矢量控制系统[J].清华大学学报(自然科学版),2001,41(3):21-24.
[110]FJ Lin, D.H.Wang, PK Huang. FPGA-based fuzzy sliding-mode control for a linearinduction motor drive, IEEE Proceedings Of Electric Power Applications,2005,52(5):1137-1148.
[111]王文森,李永东,等.基于PI自适应法的无速度传感器异步电动机矢量控制系统[J].电工技术学报,2002,17(1):1-6.
[112]喻寿益,张艳存,高金生,等.基于无功功率模型的异步电机矢量控制系统转子时间常数辨识[J].中南大学学报(自然科学版),2009,40(5):1318-1322.
[113]王高林,杨荣峰,张家皖.一种感应电机转子时间常数MRAS的在线辨识方法[J].电工技术学报,2012,27(4):48-53.
[114]陆海峰,瞿文龙,张磊,等.一种基于无功功率的异步电机矢量控制转子磁场准确定向方法[J].中国电机工程学报,2005,25(16):116-120.
[115]Geng Yang, Tung-Hai Chin. MRAS-based speed sensorless control scheme with statorresistance identification function for vector-controlled induction motor drives[J].Electrical Engineering in Japan,2007,113(1):98-108
[116]Li Zhen, Longya Xu. A mutual MRAS identification scheme for position sensorleefield orientation control of induction machines[C]. Industry ApplicationsConference,1995,1:159-165.
[117]FAIZ J, MOHSENI-ZONOOZI S H. A novel technique for estimation and control ofstator flux of a salient-pole PMSM in DTC method based on MTPF[J]. IEEETransactions on Industrial Electronics,2003,50(2):262-271.
[118]RASHED M, MACCONNELL P, STRONCACH A, etal. Sensorless indirect rotor fieldorientation speed control of permanent magnet synchronous motor using adaptive rotorflux estimator[C]. European Control Conference,2005:647-652.
[119]姜学宝.基于模糊PID控制理论的双微机励磁调节器的研制[D].福州:福州大学,2002.
[120]George Ellis. Control System Design Guide (Third Edition)[M]. BEIJING: PublishingHouse of Electronics Industry,2006:138-139.
[121]余志生.汽车理论(第3版)[M].北京:机械工业出版社,2000.
[122]Berto llini G P, H og an R M. Applying Driving Simulation to Quantify Steering EffortPreference as a Function of Vehicle Speed[J]. SAE Paper,1999-01-0394.
[123]宗长富,麦莉,王德平,李雅娟.基于驾驶模拟器的驾驶员所偏好的转向盘力矩特性研究[J].中国机械工程,2007,18(8):1001-1005.
[124]Ji-Hoon Kim, Jac-Bok Song. Control logic for an Electric Power Steering SystemUsing Assist Motor[J]. Mechatronics,2002,(12):447-459.
[125]陈利利.某轿车EPS系统电机控制策略的仿真研究[D].长春:吉林大学,2008.
[126]刘照.汽车电动助力转向系统动力学分析与控制方法研究[D].武汉:华中科技大学,2004.
[127]赵景波,周冰,李秀莲,贝绍轶.电动汽车EPS曲线型助力特性的设计及试验[J],电机与控制学报,2011,15(12):96-102.
[128]王其东,杨孝剑,陈无畏,等.电动助力转向系统的建模及控制[J].农业机械学报,2004,35(5):1-4.
[129]荆体魁.汽车电动助力转向控制系统的设计[D].大连:大连理工大学,2006.
[130]徐汉斌.电动转向器控制系统研究[D].武汉:武汉理工大学,2007.
[131]徐建平,何仁,苗立东,等.电动助力转向系统回正控制算法研究[J].汽车工程,2004,26(5):557-559.
[132]施国标,林逸,陈万忠,等.汽车电动助力转向试验台测试系统开发[J].测控技术,2005,24(3):23-25.
[133]刘冰,汽车线控转向系统硬件在环试验台研究与开发[D].长春:吉林大学,2008.