永磁同步电机定子槽型对转矩脉动的影响分析

转矩脉动是高性能电机的一个重要指标,转矩脉动的大小,对电机的振动有很大的影响。本文通过研究改变表贴式永磁同步电机定子槽参数来分析转矩脉动的变化,并通过有限元仿真,找出槽参数与转矩脉动的关系,仿真表明,调整槽参数,可以减小转矩脉动,为表贴式永磁电机减小转矩脉动的设计提供参考。     

基于符号回归算法的地铁盾构刀盘扭矩预测研究

为了提高盾构机工作效率、降低施工成本,依托深圳地铁8号线某盾构区间段工程,基于符号回归(Symbolic Regression)算法,对不同掌子面的刀盘扭矩进行了预测。分析了推力、土仓压力以及贯入度变化及换刀对扭矩的影响。结果表明,贯入度增大会导致扭矩增加,但是土仓压力的增加可能会降低扭矩。扭矩模拟数学模型具有较高精度,模型中自变量变动引起因变量变化的趋势与现实情况一致。     

基于Q参数化控制器的无刷直流电机调速系统

提出了一种新的电机调速方法,并将其应用到无刷直流电机的驱动控制中.该驱动系统的所有稳定控制器均可用一个独立的Q参数来描述,由该控制器构成的速度环不仅能消除电机脉动转矩引起的速度波动,同时对其他形式的速度干扰也能进行很好的抑制.仿真结果表明:在系统参数发生变化及存在噪声的情况下,在参考速度和负载转矩发生改变时,本文提出的控制策略都能获得鲁棒稳定性和良好的动态性能.     

永磁同步电动机模糊直接转矩控制的研究

为了提高系统的稳定性和响应速度，将模糊控制技术用于永磁同步电动机控制中，提出了一种新的模糊控制方案．引入零矢量控制，对模糊控制规则进行简化．仿真实验结果表明，与一般直接转距控制相比，模糊直接转距控制的磁链轨迹更接近于圆形；转速能在很短的时间内上升到稳定值；当受到外部干扰时，转距能快速、平稳地变化，达到新的稳态值；电流稳态波形的高频成分大大减少．     

独立轮对耦合转向架导向性能

提出了一种新型的独立轮对转向架方案——独立轮对耦合转向架.理论分析表明,独立轮对耦合转向架不仅在曲线上具有很好的径向调节功能,而且在直线上也具有良好的复位性能,说明独立轮对耦合转向架能解决独立轮对的导向问题.建立了独立轮对耦合转向架的动力学仿真模型,以分析该转向架的动态导向性能.仿真结果与理论分析结果吻合.     

日本地铁用导向转向架的开发

介绍了日本东京地铁公司开发的导向转向架的概况和工作原理。该转向架经过台架试验、公司内部曲线段实车试验和在营业线上试运用,确认了其功能和导向装置零部件的性能及可靠性。     

Vehicle rollover avoidance by application of gain-scheduled LQR controllers using state observers

Many researches have been conducted in the area of control applied to vehicle dynamics, aiming at reducing the possibility of the occurrence of the type of accident known as rollover. In this research, based on a common nonlinear model and its linearisation, a method for properly selecting matrices for solving the Riccati equation considering different speeds was proposed. The method showed in which ways speed really influences the choice of controller gains. By developing the dynamic equations for the yaw- and roll-coupled motions and modelling of controllers and state observers, it is possible to compare the efficacy of this control strategy using both linear and nonlinear simulations using Matlab. Significant results were obtained regarding the reduction of the rollover coefficient for a double-lane change manoeuvre at different speeds, thus indicating advantages of using this controller in practical cases.     

液压助力转向泵模拟加载装置测控系统开发

为了在发动机台架试验中能够按照试验规范控制液压助力转向泵的载荷,研制了转向泵模拟加载装置测控系统.该系统由基于16位微控制器的测控单元、伺服驱动器和工控机组成,利用以太网实现上、下位机通信,实时测量油压、油温和转向阻力等参数,根据获取的发动机台架控制系统试验开始标志来保持时间同步,通过控制机械转向器的转角来调节转向泵的载荷.试验结果表明,测控系统完全满足发动机试验中对转向泵连续加载要求.     

A theoretical model of speed-dependent steering torque for rolling tyres

ABSTRACT

It is well known that the tyre steering torque is highly dependent on the tyre rolling speed. In limited cases, i.e. parking manoeuvre, the steering torque approaches the maximum. With the increasing tyre speed, the steering torque decreased rapidly. Accurate modelling of the speed-dependent behaviour for the tyre steering torque is a key factor to calibrate the electric power steering (EPS) system and tune the handling performance of vehicles. However, no satisfactory theoretical model can be found in the existing literature to explain this phenomenon. This paper proposes a new theoretical framework to model this important tyre behaviour, which includes three key factors: (1) tyre three-dimensional transient rolling kinematics with turn-slip; (2) dynamical force and moment generation; and (3) the mixed Lagrange–Euler method for contact deformation solving. A nonlinear finite-element code has been developed to implement the proposed approach. It can be found that the main mechanism for the speed-dependent steering torque is due to turn-slip-related kinematics. This paper provides a theory to explain the complex mechanism of the tyre steering torque generation, which helps to understand the speed-dependent tyre steering torque, tyre road feeling and EPS calibration.     

Practicability study on the suitability of artificial,neural networks for the approximation of unknown steering torques

For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.