Fuzzy Logic Control of Switched Reluctance Motor Drives

In this chapter, the electromechanical behavior of switched reluctance motor (SRM) is first modeled by analyzing the related nonlinear differential equations. In the model, the estimation of rotor speed is also considered. After modeling, the effects of torque ripple, radial force, and acoustic noise are investigated. As we know, torque ripple and acoustic noise are two of the main disadvantages of a switched reluctance motor. Thus, a fuzzy logic current compensator is proposed both for reducing the peak of radial force and for decreasing acoustic noise effects. In the parts that torque reduces, the fuzzy logic current compensator injects additional current for each phase current to overcome the torque ripple. Also, the fuzzy logic current compensator reduces speed estimation error. The speed estimation is carried out using a hybrid sliding mode observer which estimates the rotor position and speed for a wide speed range. These new approaches have been simulated using MATLAB/SIMULINK for a nonlinear model of switched reluctance motor. The simulation results indicate that proposed methods decrease the maximum radial force and the torque ripple while the maximum torque is preserved. Also, these results show that proposed methods will estimate the rotor position and speed with high precision for all speeds from near zero speeds up to rated speed. These procedures have the advantages of simple implementation on the every switched reluctance motor drive without extra hardware, low cost, high reliability, low vibration, and excellent performance at long term

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

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

A New Phase Current Profiling with FLC f or Torque Optimization of 12/8 SRM

The switched reluctance machine against its several merits such as simplicity, robustness, less cost manufacturing and large speed still suffers from its undesirable torque ripple and acoustic noise. Compared to different candidates of hybrid and electric vehicle engine, the frequency of use of SRM in traction drives is improved with the different optimizing torque oscillation solutions. Most of studies used the generic or specific model of switched reluctance machine in the Simulink library (6/4,8/6 and 10/8). Despite, a new non linear model simply implemented in Simulink tool usinga static finite element analysis a previous study is used in this work. Hence, a 12/8 non linear SRM drive system is simulated using MATLAB toolbox tested with an intelligent controller (FLC) in order to minimize the torque ripple of an oriented starter –alternator application of a hybrid vehicle

Novel Design and Simulation of Fuzzy Controller for Turn-On & Turn-Off Angle in Coordination with SRM Speed Control for Electric Vehicles

In current scenario the Switch Reluctance Motor (SRM) are powerful alternative for Electric vehicles applications, due to its simple and rugged structure, high speed, its fault tolerance ability and Magnet free design these attributes make SRM superior to other conventional machines. This motor is a reluctance torque-driven stepper motor that can be used for bi-directional control and self-starting applications. In This paper novel control strategy proposed is to minimizing the Multiobjective function for accurate speed control of SRM by using Mamdani based two input two output fuzzy controller for optimal evaluation of α and β angle by designing closed loop system for accurate speed control of SRM and the corresponding error indices ITAE, IAE, ISE for with and without controller is analysed and compared modelling and simulation is done using MATLAB 2020a

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

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

Multiple Objective Co-Optimization of Switched Reluctance Machine Design and Control

This dissertation includes a review of various motor types, a motivation for selecting the switched reluctance motor (SRM) as a focus of this work, a review of SRM design and control optimization methods in literature, a proposed co-optimization approach, and empirical evaluations to validate the models and proposed co-optimization methods. The switched reluctance motor (SRM) was chosen as a focus of research based on its low cost, easy manufacturability, moderate performance and efficiency, and its potential for improvement through advanced design and control optimization. After a review of SRM design and control optimization methods in the literature, it was found that co-optimization of both SRM design and controls is not common, and key areas for improvement in methods for optimizing SRM design and control were identified. Among many things, this includes the need for computationally efficient transient models with the accuracy of FEA simulations and the need for co-optimization of both machine geometry and control methods throughout the entire operation range with multiple objectives such as torque ripple, efficiency, etc. A modeling and optimization framework with multiple stages is proposed that includes robust transient simulators that use mappings from FEA in order to optimize SRM geometry, windings, and control conditions throughout the entire operation region with multiple objectives. These unique methods include the use of particle swarm optimization to determine current profiles for low to moderate speeds and other optimization methods to determine optimal control conditions throughout the entire operation range with consideration of various characteristics and boundary conditions such as voltage and current constraints. This multi-stage optimization process includes down-selections in two previous stages based on performance and operational characteristics at zero and maximum speed. Co-optimization of SRM design and control conditions is demonstrated as a final design is selected based on a fitness function evaluating various operational characteristics including torque ripple and efficiency throughout the torque-speed operation range. The final design was scaled, fabricated, and tested to demonstrate the viability of the proposed framework and co-optimization method. Accuracy of the models was confirmed by comparing simulated and empirical results. Test results from operation at various torques and speeds demonstrates the effectiveness of the optimization approach throughout the entire operating range. Furthermore, test results confirm the feasibility of the proposed torque ripple minimization and efficiency maximization control schemes. A key benefit of the overall proposed approach is that a wide range of machine design parameters and control conditions can be swept, and based on the needs of an application, the designer can select the appropriate geometry, winding, and control approach based on various performance functions that consider torque ripple, efficiency, and other metrics