Intelligent Control of Switched Reluctance Motor for Electrical Vehicle Applications with Different Controller

تستخدم محركات المعاوقي المفتاحي لإنتاج الكثير من  عزم الدوران والتي تعمل عند التشبع المغناطيسي العالي. وبالنظر إلى التشبع المغناطيسي العالي، فإن العلاقة بين تيار الطور، وموقع الدوار هي علاقة غير خطية. لذلك فان  الضجيج، الاضطرابات، وعزم القصور الذاتي  عند  التحميل يمكن أن يكون لها جميعا تأثير سلبي على أداء المحرك المعاوقي المفتاحي. في هذه الدراسة تم تطوير وحدة التحكم الانزلاقي. وقد استخدم وحدة التحكم الانزلاقي في تنظيم السرع على مدى واسع  بما في ذلك المحرك المعاوقي المفتاحي في السرع العالية والسرع الواطئة وتقارن هذه الدراسة وحدة التحكم الانزلاقي مع وحدة التحكم التناسبي المتكامل التفاضلي في المحرك المعاوقي المفتاحي ذو 4/6 اقطاب باستعمال  الطرق الامثل للتحكم . ومقارنة  سرعة الجزء الدوار مع السرعة المضبوطة .فان وحدة التحكم الانزلاقي المتسارع هو الافضل من حيث الاداء والمتانة في  تطبيق السيارات الكهربائية  تبعا لنظام السيمولنك المستخدم Switched reluctance motors (SRM) are used to produce a lot of torque when they are operating at high magnetic saturation. Due to the high magnetic saturation, the relationship between phase current, rotor position, and the flux linkage of SRM is nonlinear. Noise, disturbances, and inertia of load torque can all have a negative impact on the SRM driver system's speed controller performance. In this study, the SRM driver system's sliding mode controller was developed .The sliding mode controller( SMC) speed controller was used to regulate speeds of the SRM throughout a wide range speeds, including high and low speeds. This study compares (SMC) with a modified reaching law and a Proportional Integral Divertive Control (PID) controller for a 6/4 pole SRM using an optimization technique for switching controllers. Furthermore, the rotor speed was simulated and compared to the reference speed. The Exponential Sliding Mode Controller (ExpSMC) is the best in terms of performance and robustness for an electric vehicle application, depending on a simulation of an established test bench using the two controllers

Stability analysis of fuzzy sliding mode controlled switched reluctance motor drives

This paper presents a small deviant dynamic-state model and the system transfer functions for SRM drive system under different control modes with fuzzy sliding mode controller. With the help of the system open-loop and dosed-loop transfer functions, the operation performances of SRM drive system are discussed. From the characteristics of the transfer functions, it is concluded that the FSMC speed regulator can be regarded as an adaptive PI regulator. The proposed scheme is applied to a 4 kW SRM drive and the system performance is verified by computer simulation results.published_or_final_versio

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

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

Comparison of Average Current Controlled PFC SEPIC and CUK Converter Feeding Current Controlled SRM

In this paper, current control of 6/4 switched reluctance motor (SRM) fed by both power factor correction (PFC) SEPIC and CUK converter is realised and asymmetric bridge converter is used to drive SRM. Furthermore, SEPIC and CUK DC-DC converters are connected in series to diode bridge rectifier in order to build PFC converters. Average current control of PFC converters is carried out by PI algorithm and both converters are operated at continuous conduction mode (CCM). Besides, switching frequency of PFC and asymmetric bridge converters is 62, 9 kHz with 5750 W power. Studies are conducted by using MATLAB/Simulink software. Total harmonic distortions (THD)s of grid current, grid power factor (PF) and output voltages of the converters are compared. Also, THDs of grid current of each converter are compared by IEEE 519-2014 standard. In addition, current waveform and flux of SRM phases are shown. It is validated by simulations that PFC CUK converter gives better result with 9.08% THD, 0.998 PF than PFC SEPIC converter having 9.61% THD and 0.997 PF. Furthermore, both converters provide the limit defined by standards

Control Theory in Engineering

The subject matter of this book ranges from new control design methods to control theory applications in electrical and mechanical engineering and computers. The book covers certain aspects of control theory, including new methodologies, techniques, and applications. It promotes control theory in practical applications of these engineering domains and shows the way to disseminate researchers’ contributions in the field. This project presents applications that improve the properties and performance of control systems in analysis and design using a higher technical level of scientific attainment. The authors have included worked examples and case studies resulting from their research in the field. Readers will benefit from new solutions and answers to questions related to the emerging realm of control theory in engineering applications and its implementation

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

Active suspension control of electric vehicle with in-wheel motors

In-wheel motor (IWM) technology has attracted increasing research interests in recent years due to the numerous advantages it offers. However, the direct attachment of IWMs to the wheels can result in an increase in the vehicle unsprung mass and a significant drop in the suspension ride comfort performance and road holding stability. Other issues such as motor bearing wear motor vibration, air-gap eccentricity and residual unbalanced radial force can adversely influence the motor vibration, passenger comfort and vehicle rollover stability. Active suspension and optimized passive suspension are possible methods deployed to improve the ride comfort and safety of electric vehicles equipped with inwheel motor. The trade-off between ride comfort and handling stability is a major challenge in active suspension design. This thesis investigates the development of novel active suspension systems for successful implementation of IWM technology in electric cars. Towards such aim, several active suspension methods based on robust H∞ control methods are developed to achieve enhanced suspension performance by overcoming the conflicting requirement between ride comfort, suspension deflection and road holding. A novel fault-tolerant H∞ controller based on friction compensation is in the presence of system parameter uncertainties, actuator faults, as well as actuator time delay and system friction is proposed. A friction observer-based Takagi-Sugeno (T-S) fuzzy H∞ controller is developed for active suspension with sprung mass variation and system friction. This method is validated experimentally on a quarter car test rig. The experimental results demonstrate the effectiveness of proposed control methods in improving vehicle ride performance and road holding capability under different road profiles. Quarter car suspension model with suspended shaft-less direct-drive motors has the potential to improve the road holding capability and ride performance. Based on the quarter car suspension with dynamic vibration absorber (DVA) model, a multi-objective parameter optimization for active suspension of IWM mounted electric vehicle based on genetic algorithm (GA) is proposed to suppress the sprung mass vibration, motor vibration, motor bearing wear as well as improving ride comfort, suspension deflection and road holding stability. Then a fault-tolerant fuzzy H∞ control design approach for active suspension of IWM driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The T-S fuzzy suspension model is used to cope with the possible sprung mass variation. The output feedback control problem for active suspension system of IWM driven electric vehicles with actuator faults and time delay is further investigated. The suspended motor parameters and vehicle suspension parameters are optimized based on the particle swarm optimization. A robust output feedback H∞ controller is designed to guarantee the system’s asymptotic stability and simultaneously satisfying the performance constraints. The proposed output feedback controller reveals much better performance than previous work when different actuator thrust losses and time delay occurs. The road surface roughness is coupled with in-wheel switched reluctance motor air-gap eccentricity and the unbalanced residual vertical force. Coupling effects between road excitation and in wheel switched reluctance motor (SRM) on electric vehicle ride comfort are also analysed in this thesis. A hybrid control method including output feedback controller and SRM controller are designed to suppress SRM vibration and to prolong the SRM lifespan, while at the same time improving vehicle ride comfort. Then a state feedback H∞ controller combined with SRM controller is designed for in-wheel SRM driven electric vehicle with DVA structure to enhance vehicle and SRM performance. Simulation results demonstrate the effectiveness of DVA structure based active suspension system with proposed control method its ability to significantly improve the road holding capability and ride performance, as well as motor performance

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area