Control of variable reluctance machine (8/6) by artificiel intelligence techniques

The non-linearity of variable-Reluctance Machine (8/6) and the dependence of machine inductance on rotor position and applied current complicate the development of the control strategies of drives using variable-Reluctance Machine variable-Reluctance Machine (VRM). The classical-control algorithms for example of derived full proportional action may prove sufficient if the requirements on the accuracy and performance of systems are not too strict. In the opposite case and particularly when the controlled part is submitted to strong nonlinearity and to temporal variations, control techniques must be designed which ensure the robustness of the process with respect to the uncertainties on the parameters and their variations. These techniques include artificial-intelligence-based techniques constituted of neural networks and fuzzy logic. This technique has the ability to replace PID regulators by nonlinear ones using the human brain’s reasoning and functioning and is simulated by using MATLAB/Simulink software. Finally, by using obtained waveforms, these results will be compared

Torque Control

This book is the result of inspirations and contributions from many researchers, a collection of 9 works, which are, in majority, focalised around the Direct Torque Control and may be comprised of three sections: different techniques for the control of asynchronous motors and double feed or double star induction machines, oriented approach of recent developments relating to the control of the Permanent Magnet Synchronous Motors, and special controller design and torque control of switched reluctance machine

Fuzzy Controller Based DTC of SRM Drive Fed by Common High Side Asymmetric Switch Converter

The switched reluctance motor (SRM) is recently gaining huge popularity in electric vehicle (EV) applications due to its control flexibility, simple structure, lower cost and high efficiency than the synchronous and induction motors. Among all the controllers, the direct torque control (DTC) is the most preferred due to its higher efficiency, lower losses and superior control characteristics. In this paper, a 6/4 pole SRM with fuzzy logic based DTC has been proposed for the EV application along with a converter with reduced switch counts to reduce the torque ripples and enhance the performance of the system under steady and transient state conditions. The proposed system is tested and validated under various scenarios that include load torque and speed variations and compared with the vector control method. From, the investigation it has been found that the proposed technique reduces ripples from the system during all the scenarios with a resultant flux of less than 0.5pu

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

Torque Ripple Minimization of a Switched Reluctance Motor using Fuzzy Logic Control

Switched Reluctance Motors (SRMs) are attractive for industrial applications because of their simple construction and low cost, ruggedness, the capability to cover a wide speed range and relatively high torque-to-mass ratio. The primary disadvantage of an SRM is the higher torque ripple compared with conventional machines, which contributes to acoustic noise & vibration. The origin of torque pulsations in an SRM is due to the highly nonlinear & discrete nature of torque production mechanism. The total torque in an SRM is the sum of torques generated by each of the stator phases, which are controlled independently. Torque-ripple reduction in switched reluctance motors (SRM) has become a major research theme. In servo control applications or when smooth control is required at low speeds, reduction of the torque ripple becomes the main issue in an acceptable control strategy. In this paper intelligent controller such as Fuzzy Logic Controller current compensating technique is employed for minimizing the torque ripples in switched reluctance motor. For the purpose of comparison, the performance of conventional Proportional- Integral (PI) controller and PID controller are also considered. The statistical parameters like minimum, maximum, mean of total torque and torque ripple coefficient are reported. DOI: 10.17762/ijritcc2321-8169.15070

An Adaptive PID Speed Controller for an 8/6 Switched Reluctance Machine

This paper presents a classical controller with parameters adaptation capability, in an automatic way. This controller is based on a PID where a parameters adaptation algorithm is used and applied to the switched reluctance motor (SRM) speed control. This PID design do not require any kind of adjustment or calibration from the operator. The parameters adaptation algorithm implemented is based on one fuzzy system with a Takagi-Sugeno inference mechanism with some simplifications. These simplifications had the goal to select the parameters adaptation algorithm contributing for a fast controller response. The developed adaptive PID algorithm was modelled and simulated

Chattering-Free Robust Adaptive Sliding Mode Speed Control for Switched Reluctance Motor

This study describes an adaptive sliding mode control (ASMC) for the control of switched reluctance motor (SRM). The main objective is to minimize torque ripples with controller effort smoothness while the system is under perturbation by structured uncertainties, unknown parameters, and external disturbances. The control algorithm employs an adaptive approach to remove the need for prior knowledge within the bound of perturbations. This is suitable for tackling the chattering problem in the sliding motion of ASMC. In order to achieve control effort smoothness and more effective elimination of chattering, the algorithm then incorporates proper modifications in order to build a chattering-free robust adaptive sliding mode control (RASMC) using Lyapunov stability theory. A final advantage of the algorithm is that system stability and error convergence are guaranteed. The effectiveness of the proposed controller in improving robustness and minimizing ripples is demonstrated by numerical simulation. Experimental validation is used to demonstrate the efficiency of the proposed scheme. The results indicate that RASMC provides a superior performance with respect to speed tracking and disturbance rejection over the conventional sliding mode control (CASMC) in the face of uncertainties in model and dynamic loads

PV Array Driven Adjustable Speed Drive for a Lunar Base Heat Pump

A study of various aspects of Adjustable Speed Drives (ASD) is presented. A summary of the relative merits of different ASD systems presently in vogue is discussed. The advantages of using microcomputer based ASDs is now widely understood and accepted. Of the three most popular drive systems, namely the Induction Motor Drive, Switched Reluctance Motor Drive and Brushless DC Motor Drive, any one may be chosen. The choice would depend on the nature of the application and its requirements. The suitability of the above mentioned drive systems for a photovoltaic array driven ASD for an aerospace application are discussed. The discussion is based on the experience of the authors, various researchers and industry. In chapter 2 a PV array power supply scheme has been proposed, this scheme will have an enhanced reliability in addition to the other known advantages of the case where a stand alone PV array is feeding the heat pump. In chapter 3 the results of computer simulation of PV array driven induction motor drive system have been included. A discussion on these preliminary simulation results have also been included in this chapter. Chapter 4 includes a brief discussion on various control techniques for three phase induction motors. A discussion on different power devices and their various performance characteristics is given in Chapter 5

Intelligent Control of Switched Reluctance Motor Using Fuzzy Logic and SMC Controller for EV Applications

Switched Reluctance Motors have expanded their field of application in recent years, from a control system stepping motor to high torque e-vehicle applications. High-speed operation and a light-weight driving motor are critical elements for an effective electric vehicle design. SRM's low torque-to-weight ratio and magnetless rotor design make it ideal for use in electric vehicles with less weight and low cost. The only limitation with switched reluctance motors is torque ripple and vibrations. There have been a variety of techniques to reducing torque pulsations in the SRM, by which vibration and noise can be reduced. In this paper, an optimization technique is used in switching controllers in and a comparison is done between a sliding mode controller (SMC) with a modified reaching law and by using  Fuzzy Logic Controller (FLC). By using matlab Simulink the magnitude of torque ripple is simulated and compared for 8/6 pole  SRM. The results shows that the torque ripple is reduced in fuzzy compared to SMC  significantly