Torque Ripple Of Switched Reluctance Motor Research Articles

An Offline Torque Sharing Function for Torque Ripple Reduction in Switched Reluctance Motor Drives

In this paper, an offline torque sharing function (TSF) for torque ripple reduction in switched reluctance motor (SRM) drives over a wide speed range is proposed. The objective function of an offline TSF is composed of two secondary objectives with a Tikhonov factor to minimize the square of the phase current (copper loss) and derivatives of current references (rate of change of flux linkage). The proposed TSFs with different Tikhonov factors are compared with the conventional TSFs including linear, cubic, and exponential TSFs in terms of efficiency and torque-speed performance while operating in both magnetic linear and saturation regions. Then, the Tikhonov factor is selected based on a tradeoff between the copper loss and torque-speed performance. The maximum torque-ripple-free speed of the selected offline TSF is validated to be seven times as high as the best case in these conventional TSFs. The performance of the offline TSF is verified by simulations and experiments with a 2.3-kW, three-phase 12/8 SRM. Results show that the proposed offline TSF can significantly reduce the torque ripple of SRM without increasing copper loss over a wide speed range.

Torque Ripple Suppression of Switched Reluctance Motor Based on Torque Sharing Strategy

The torque ripple is the main disadvantage of switched reluctance motor (SRM). In order to reduce the torque ripple of SRM, and improve the performance of the system, the torque sharing strategy was combined with RBF neural network for the purpose of torque ripple suppression by controlling the winding current of each phase. In consideration of the possible error of network, the real-time current compensation was taken to compensate the loss of torque which could suppress the torque ripple of the system in further. The results show that he torque ripple of SRM was suppressed effectively.

Sensitivity Analysis of Geometrical Parameters of a Switched Reluctance Motor with Modified Pole Shapes

A major problem in Switched Reluctance Motor (SRM) is torque ripple, which causes undesirable acoustic noise and vibration. This work focuses on reducing the undesirable torque ripple in SRM by modifying stator and rotor geometry. This paper presents a comparative study on torque ripple minimization in SRM with modified pole shapes such as stator pole taper, stator pole face with non-uniform air gap and pole shoe attached to rotor pole. Further this paper presents a detailed sensitivity analysis of the effect of different geometrical parameters that alter the pole face shapes on the performance of SRM. The analysis is performed using finite-element method considering average torque and torque ripple as performance parameters. Based on the analysis, a design combining stator pole taper with non-uniform air gap is proposed to improve the torque characteristics of SRM. The dynamic characteristics of the proposed design are simulated and the results show satisfactory reduction in torque ripple.

Neural fuzzy control to minimise torque ripple of SRM

The switched reluctance motor (SRM) exhibits high non-linear characteristics, so it is difficult to employ conventional control algorithms to achieve the desired dynamic performances for non-linear SRMs. It is proposed, in this paper, a new kind of neural fuzzy controller to tackle the problem of torque ripple reduction in switched reluctance motor drive, which does not require the precise mathematical model of the system and offers an obvious advantage over traditional PID control system. The simulation results show that the neural fuzzy control strategy possesses superior performance in reducing low frequency torque ripple and torque dip, and demonstrate the effectiveness and feasibility of the proposed scheme.

Torque Ripple Reduction in Switched Reluctance Motor Drives Using B-Spline Neural Networks

A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented in this paper. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weights updating algorithm of the BSNN, the appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not required high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme.

New Rotor Shape Design for Minimum Torque Ripple of SRM Using FEM

A major problem of switched reluctance motors (SRMs) is torque ripple, which causes undesirable acoustic noise and vibration. It is caused by the saliency of the stator and rotor. In this paper, the geometry for low torque ripple is researched and a motor having notched teeth is proposed. Its characteristics are simulated by finite-element method (FEM) analysis and compared with SRMs having conventional shape.

Minimization of torque ripple in SRM drives

The torque pulsations in switched reluctance motors (SRMs) are relatively higher compared to sinusoidal machines due to the doubly salient structure of the motor. The magnetization pattern of the individual phases together with the T-i-/spl theta/ characteristics of the motor dictate the amount of torque ripple during operation. Both machine design and electronic control approaches have been used to minimize the torque ripple in SRMs. This paper presents an extensive review of the origin of torque ripple and the approaches adopted over the past decade to minimize the torque ripple. A hybrid torque-ripple-minimizing controller that incorporates the attractive features of some of the techniques developed in the past decade is presented along with simulation and experimental results.

Control of switched reluctance motor torque for force control applications

The paper presents a method for controlling switched reluctance motor (SRM) torque for force control applications. SRMs are used in AdeptOne robots, and the authors perform experiments with two robots, controlled in coordination, in grasping and manipulation of various objects. The object and robot parameters are not exactly known, and adaptive methods are used to control the overall system. These methods are model-based control techniques which require high bandwidth torque control. This requirement is typical for high precision mechanisms. SRM characteristics are very nonlinear. In particular the torque ripple, friction, and the torque versus position and current relationships were analyzed in the context mentioned above, and specifically, for force control applications. The proposed method is based on a new commutation algorithm and a measured torque versus position and current relationship, used to smooth the SRM's torque ripple, hence generating a torque output nearly independent of position. Furthermore, the internal friction is estimated on-line, and compensated for. This renders a high accuracy torque tracking. The torque control method is based on feedback from the motor angular velocity, motor angle, armature current, and feedforward for friction compensation and cancellation of nonlinear effects. The method has been tested experimentally on Adept motors and the results were very encouraging. The method has been also used for adaptive control of two coordinated Adept robots.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>