Sensorless interior permanent magnet synchronous motor drive system with a wide adjustable speed range

The authors propose a novel extended flux estimating method for an interior permanent magnet synchronous motor. By using the proposed method, an extended flux can be systematically derived. Then, the shaft position and speed of the motor can be obtained. Starting from a standstill and at a low-speed range control, a current-slope estimating method is used to replace the extended flux method because the estimating extended flux decreases as the motor speed is reduced. By combining the extended flux and the current-slope estimating methods, the interior permanent magnet synchronous motor drive system can be controlled in a wide range with satisfactory performance. The adjustable speed range is from 1 to 2000 r/min. In addition, the system performs fast transient responses and good load-disturbance responses. Moreover, a sensorless position control system has been well developed based on the speed control drive system. A TMS 320LF2407 digital signal processor is used to execute the rotor position estimation, rotor speed estimation, current-loop control, speed-loop control and position-loop control algorithms. The hardware circuit therefore is very simple. Several experimental results are provided to validate the theoretical analysis.     

Incorporating control trajectories with the direct torque control scheme of interior permanent magnet synchronous motor drive

Interior permanent magnet (IPM) synchronous machines have gained increased attention for applications in electric vehicle, variable speed wind turbine, industrial drives, etc., because of their high torque density, wider speed range and compact construction. The authors present a detailed analysis and modelling of control trajectories and incorporate those trajectories in the direct torque control (DTC) scheme of an IPM synchronous motor drive, for constant-torque and constant-power operating regions. The control trajectories are implemented on a real-time digital signal processor. Because the inputs to the inner torque control loop of DTC are the references for the torque and the amplitude of the stator flux linkage (λ_s), they are transformed in the T-λ_s plane, than in the i_d - i_q plane in the indirect control. The modelling and experimental results are presented. Results show very good dynamic and steady-state performances of direct torque controller, incorporating these control trajectories.     

基于电流解耦的表贴式永磁同步电机无源控制研究

为了提高表贴式永磁同步电机的电流环频率响应能力和转速响应性能,针对其无源控制器设计过程中因d轴、q轴电流存在耦合而造成期望互联矩阵未知参数过多的问题,结合电压前馈解耦控制,提出了一种基于电流解耦的无源控制器新型设计方法。首先,根据能量平衡原理和电压前馈解耦控制,构建基于电流解耦的表贴式永磁同步电机端口受控耗散哈密顿系统（port control Hamilton system with dissipation, PCHD）模型。然后,通过互联和阻尼配置的无源控制（interconnection and damping assignment passivity-based control, IDA-PBC）方法,完成表贴式永磁同步电机无源控制器的设计,并在设计过程中引入了电压前馈解耦控制,消除了d轴、q轴电流的耦合关系,使期望互联矩阵的未知参数由3个减少为1个。最后,搭建表贴式永磁同步电机测试平台进行实验验证。实验结果表明,当表贴式永磁同步电机的电流环采用基于电流解耦的无源控制器时,q轴电流响应频率由小于250 Hz增大为大于333 Hz;额定转速下的转速响应时间由0.16 s减小为0.11 s,超调量由2.0%减小为0.6%,稳态误差由5.98 r/min减小为1.15 r/min。研究结果可为永磁同步电机的无源控制器设计提供新思路。     

Single sensor current control of permanent magnet synchronous motor using field programmable gate array

An innovative current control scheme for a permanent magnet synchronous motor using a single current sensor placed at a low potential, in the DC return line of the inverter is proposed. The feedback mechanism employs a digital asymptotic sinusoidal curve-fitting observer implemented in a single field programmable gate array chip. The observer, activated by firing pulses, reconstructs the three-phase feedback signals. The asymptotic observer does not require the parameters of the motor or the load and it is robust under dynamic conditions. The development of the algorithm, implementation and experimental verification of the proposed control scheme are presented in detail     

永磁同步电机故障诊断研究综述

永磁同步电机（permanent magnet synchronous motor,PMSM）具有结构简单、运行稳定、效率高和外形多样等显著优点,广泛应用于不同领域。在永磁同步电机使用过程中,不可避免地会出现各种故障,例如退磁故障、电路故障、转子偏心故障和轴承故障等。基于永磁同步电机的结构和工作原理,对其各类故障的产生原因和诊断方法进行总结,并分析了模型构建和信号处理在故障诊断中的优势。研究结果为永磁同步电机故障诊断提供了一定的理论依据。     

车用永磁同步电机电磁噪声分析研究

以电动汽车驱动用永磁同步电机为研究对象,从作用于电机定子表面的电磁力波和电机定子结构的动态特性两个方面对电动汽车驱动用永磁同步电机空载工况的电磁噪声展开研究.通过研究永磁同步电机产生电磁力波的机理,推导了空载工况电磁力波的解析分析方法,结合电磁仿真的手段,精确计算了电机在空载工况下电磁力波的波次、频率和幅值;通过建立电机定子结构的有限元仿真模型及有限元模态仿真计算,得到了定子结构的模态频率和振型.发现：电机定子结构的前6阶模态频率较低,电机空载工况在调速过程中所激发的电磁力容易引起电机定子结构的共振.该研究为电动汽车驱动用永磁同步电机的减振降噪提供了指导.     

Full speed range permanent magnet synchronous motor control without mechanical sensors

This study presents a control method for permanent magnet (PM) motors based on a combination of a non-linear full-order observer and a signal injection scheme. Stable mechanical-sensorless operating range down to zero speed at full load is obtained using only voltage and current sensors. The signal injection scheme uses the asymmetry of the motor?s d and q-axis inductances to estimate rotor position and speed. Such asymmetry is also taken into account in the motor model used to construct the observer to reduce current estimation error. The performance of the proposed scheme is validated through experimental results.     

Estimation of rotor and load angle of direct-torque-controlled permanent magnet synchronous machine drive

A dynamically well performing rotor and load angle estimation method for direct-torque-controlled (DTC) permanent magnet synchronous machines drives is presented. The rotor or load angle is needed as example in the limitation of the load angle. The method uses the same flux linkage estimate that is used in the core of the DTC and calculates the load and rotor angle directly from the motor equations. The effect of the flux linkage estimation method is analysed through simulation. Both the steady-state and dynamical measurement results are also provided, showing the good performance of the suggested method. The performance is adequate to be used as example in the limitation of the load angle in order to prevent the machine falling from synchronism     

分布式驱动用永磁同步电机电磁转矩的解析计算

针对分布式驱动电动汽车车身阶次振动和车内噪声的主要振源—外转子表贴式永磁同步电机6k阶（ ）转矩波动,提出了一种分布式驱动用永磁同步电机电磁转矩的解析计算方法。基于永磁同步电机磁场畸变,对永磁磁极在均匀气隙中的径向分量进行了傅里叶级数分解,通过磁链、电压的计算,最终得到电磁转矩的解析解,为永磁同步电机的阶次振动与振源识别提供了理论基础。当不考虑电流谐波的影响时,对电磁转矩做了阶次分析,论证了由永磁体磁场谐波引起的电磁转矩波动频率是电源频率的6k倍频。最后,通过有限元计算验证了该解析计算结果。     

浅谈爪极式永磁同步电机关键工序及过程监控

小功率电动机强制性产品认证实施规则(CNCA-01C-013:2007)中<工厂质量保证能力>第4.1条款规定"工厂应对关键生产工序进行识别";第4.3条款规定"可行时,工厂应对适宜的过程参数和产品特性进行监控".     

Adaptive controller design for a synchronous reluctance motor drive system with direct torque control

The design and implementation of adaptive controllers for a sensorless synchronous reluctance drive system with direct torque control is proposed. Two adaptive control algorithms, which include adaptive backstepping control and model-reference adaptive control, are proposed to improve the performance of a sensorless direct torque control synchronous reluctance motor drive system. A digital signal processor, TMS320-C30, is used to execute the rotor position estimating technique and the adaptive control algorithms. The system shows good transient responses, good load disturbance responses and good tracking responses. Several experimental results validate the theoretical analysis. The advanced controller design for a sensorless synchronous reluctance motor drive with direct torque control is proposed.     

内置式永磁同步电机转子初始位置检测方法

内置式永磁同步电机(IPMSM)转子磁极初始位置检测准确度对电机启动性能的影响非常关键。在推导高频旋转电压注入法正序、负序响应电流基础上,提出一种利用两路新型跟踪微分器(NTD)输出信号相位差求解转子磁极初始位置的新方法。该方法无需PI调节器或龙贝格观测器,仅涉及母线电压、高频信号电角度及交、直轴电感4个参数。实验结果表明该方法可使转子磁极初始位置在4 ms内收敛到真实值附近,最大估计误差0.082 rad。     

永磁直线同步电机矢量控制系统建模与实现

针对永磁直线同步电机（PMLSM）的特点，建立PMLSM在dq两相坐标系下的数学模型。介绍了永磁直线同步电机矢量控制系统并给出了硬件和软件的设计思想。通过对控制电流以及电机位置的实验分析，验证了所研究的基于矢量控制的永磁直线同步电机矢量控制方法的有效性。     

A novel synchronous permanent magnet planar motor and its model for control applications

A novel synchronous permanent magnet planar motor (SPMPM) with iron core is proposed. It has higher continuous force compared to the coreless SPMPM. In the novel SPMPM, two sets of windings for generating x-direction thrust and y-direction thrust are perpendicularly fixed in the x-direction slots and y-direction slots of a mover core, respectively. For control system development applications, an electromagnetic model is derived and the analytical method for calculating the model parameters is also reported. The model describes an important characteristic of the novel SPMPM that the x-direction thrust and y-direction thrust are independent of each other. To verify the model and the parameter calculation method, the finite element method (FEM) is used for calculating the phase inductances and electromagnetic forces of an example SPMPM. The results from FEM are in good agreement with the results from the analytical equations. It demonstrates the feasibility and credibility of the proposed model and parameter calculation method to a certain extent.     

Modified Elman neural network controller with improved particle swarm optimisation for linear synchronous motor drive

A modified Elman neural network controller is proposed to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive to track periodic reference trajectories. First, the dynamic model of the PMLSM drive system is derived. Next, a modified Elman neural network is proposed to control the PMLSM. Moreover, the connective weights of the modified Elman neural network are trained online by back-propagation (BP) methodology. However, the learning rates of the online-training weights are usually selected by trial-and- error method, which is time-consuming. Therefore an improved particle swarm optimisation (IPSO) is adopted in this study to adapt the learning rates in the BP process of the modified Elman neural network to improve the learning capability. Finally, the control performance of the proposed modified Elman neural network controller with IPSO is verified by the simulated and experimental results.     

Time and frequency domain identification and analysis of a permanent magnet synchronous servo motor

Abstract

This study employed the approach of non‐linear autoregressive moving average model with exogenous inputs (NARMAX) to analyze the dynamics of a Permanent Magnet Synchronous Motor (PMSM). The non‐linearity in PMSM including cogging force, reluctance force and force ripple is difficult to estimate. By using the NARMAX approach, thrust‐speed relationship and thrust‐position relationship could be analyzed by identifying both time and frequency domain models of the system. The frequency domain analysis is studied by mapping the discrete‐time NARMAX models into generalized frequency response functions (GFRFs) to reveal the non‐linear coupling between the various input spectral components and the energy transfer mechanisms in the system. From the results, the interpretation of the higher‐order GFRFs has been comprehensively studied and non‐linear effects have been related to the physical models of the systems.     

Position sensorless control for interior permanent magnet synchronous motor using adaptive flux observer with inductance identification

A position sensorless control of interior permanent magnet synchronous motors (IPMSMs) is proposed using the adaptive full-order observer with inductance identification. First, mathematical models are discussed for robustness improvement to inductance variation and inductance identification in IPMSMs, the models show that a high-frequency signal needs to be injected to identify the inductance. Next, novel adaptive schemes for inductance identification are proposed here. Finally, identification experiments under IPMSM position sensorless control are carried out with the proposed methods, in which the feasibility and effectiveness of the methods are shown in terms of inductance identification performance and the convergence of position estimation error.     

Design and implementation of an adaptive inverse controller for a micro-permanent magnet synchronous motor control system

An adaptive inverse controller design for a micro-permanent magnet synchronous motor control system is proposed. The adaptive inverse controller is constructed by using an adaptive model and an adaptive controller. The parameters of the adaptive model and adaptive controller are on-line tuned. By using the proposed adaptive inverse controller, the transient responses, load disturbance responses and tracking responses of the control system are improved. To detect the shaft rotor position, a micro-encoder is attached with the micro-permanent magnet synchronous motor. The micro-encoder provides only 100 pulses/revolution because of its space limitation. As a result, the resolution of the position signal and speed signal is not good enough. In order to improve the resolution, a state estimator is proposed here. By using the proposed state estimator, the control system can be operated from 1 to 25 000 r/min. The adaptive inverse control algorithm and the state estimation algorithm are executed by a digital signal processor, TMS320F28335. In addition, the proposed adaptive inverse control algorithm can be applied to the position control for the micro-permanent magnet synchronous motor as well. Several experimental results validate the theoretical analysis. The experimental results show that the proposed system has good performance including transient responses, load disturbance responses, and tracking responses.     

永磁同步电机系统、网络混沌振荡同步中断分析与控制

已有研究表明,电机在某些参数及工作条件下会出现混沌振荡行为。另一方面,现代工业生产过程中,经常需要多台电机协调同步运行。当前,国内外对电机系统、网络的混沌振荡同步分析与控制已有较多研究,但对电机系统、网络由于参数扰动引起同步中断的分析与控制研究尚属少见。为此,在传统的扩散耦合方式基础上,通过引入单向交叉耦合方式,研究了永磁同步电机(PMSM)系统、网络受到参数扰动后的振动特性。分析并证明了单向交叉耦合对PMSM系统、网络的参数扰动具有同步鲁棒性;并以3节点、4节点和一个多节点网络的PMSM系统验证,交叉耦合对多节点电机网络全局稳定同步的重要作用。研究结果表明,通过建立合适的单向交叉耦合方式,能够有效控制电机网络因参数扰动而引发的同步中断,使同步中断得以重新恢复。     

Decomposition-based multi-objective differential evolution particle swarm optimization for the design of a tubular permanent magnet linear synchronous motor

This article proposes a decomposition-based multi-objective differential evolution particle swarm optimization (DMDEPSO) algorithm for the design of a tubular permanent magnet linear synchronous motor (TPMLSM) which takes into account multiple conflicting objectives. In the optimization process, the objectives are evaluated by an artificial neural network response surface (ANNRS), which is trained by the samples of the TPMSLM whose performances are calculated by finite element analysis (FEA). DMDEPSO which hybridizes differential evolution (DE) and particle swarm optimization (PSO) together, first decomposes the multi-objective optimization problem into a number of single-objective optimization subproblems, each of which is associated with a Pareto optimal solution, and then optimizes these subproblems simultaneously. PSO updates the position of each particle (solution) according to the best information about itself and its neighbourhood. If any particle stagnates continuously, DE relocates its position by using two different particles randomly selected from the whole swarm. Finally, based on the DMDEPSO, optimization is gradually carried out to maximize the thrust of TPMLSM and minimize the ripple, permanent magnet volume, and winding volume simultaneously. The result shows that the optimized TPMLSM meets or exceeds the performance requirements. In addition, comparisons with chosen algorithms illustrate the effectiveness of DMDEPSO to find the Pareto optimal solutions for the TPMLSM optimization problem.