The suspension system is classified into three types passive suspension, semi-active, and active suspension.The term a quarter car model originated in the early part of the 20th century.It is considered the best way for studying the effectiveness of vehicle stability.This paper presents the modelling and control of a nonlinear active suspension system for a quarter car, the mathematical model represents a spring-mass (Quarter of the chassis) and unsprung mass (the wheel), with two degrees of freedom (2-DOF) system characterized by a pair of the differential equations.The objective of this work is to determine control strategy to deliver better performance with respect sprung displacement; sprung mass velocity; suspension deflection; peak overshoot; setting time.The active control of the suspension system is achieved using fractional-order PID (FOPID) tuned by particle swarm optimization algorithms (PSO algorithms) because the ordinary FOPID did not give good results, and linear quadratic regulator (LQR) control actions.The results are developed and simulated in MATLAB/Simulink.It is observed that the LQR controller gives better ride comfort by reducing the RMS error and the vibration of various types of road conditions as compared to an intelligent FOPID controller.
In this particular study, an artificial neural network (ANN) was utilized to effectively extract the maximum power from a photovoltaic (PV) installation.The primary objective was to assess the performance of the ANN in comparison to the commonly used perturb and observe (P&O) technique, especially when faced with varying climatic conditions.The results of the study unequivocally demonstrated the superiority of artificial intelligence, specifically the ANN, in enhancing the optimization of PV power.When compared to the traditional P&O technique, the ANN consistently outperformed it in terms of accurately tracking the maximum power point under different climatic conditions.This highlights the remarkable capabilities of artificial intelligence in improving the efficiency and performance of PV systems.
The study presented in this paper consists in the modeling and optimization of the performance of the control of an induction motor (IM) by the application of the sensorless field oriented control (SFOC), using the strategy of the discontinuous pulse width modulation (DPWM) to switch the transistors which form the three-phase voltage source inverter (3Ph_VSI).The latter gives a reduction in the number and the switching losses compared to the space vector modulation (SVPWM).This leads to improve the performance of the IM.The proposed system has many advantages; provides for the decrease in noise, presents an increase in reliability and makes the material less expensive.The study of this control is done in order to show the efficiency and robustness of the method during variations in speed and torque.
This study describes how to regulate the frequency and terminal voltage of a freestanding wind energy conversion system using an Enhanced Phase Locked Loop (EPLL)-based strategy to supply power to varied loads regardless of wind speed. In a standalone wind turbine energy conversion system, the EPLL control scheme extracts the reference source currents (SWECS). The control algorithm employs two proportional-integral (PI) controllers to create the active and reactive power components of the consumers' load currents, estimate reference source currents, and connect the zigzag transformer to PCC with VSC for neutral current compensation. To obtain optimal PI controller gains and most-suited settings to apply to SWECS, optimization approaches are used. The control algorithm is the most significant aspect of the system, and the speed with which it calculates, evaluates, and guesstimates determines the generation of source currents based on the algorithm's ideal controller PI gains. By properly estimating source currents, the EPLL control method improves dynamics and power quality issues, and the optimization technique is employed to acquire the gains of PI controllers. The proposed system employs the EPLL algorithm on a three-phase, four-wire system with changing loads to achieve ideal total harmonic distortion of source currents and voltages on the PCC, as defined by IEEE-519 standards. A battery energy storage device coupled to the VSC dc link keeps the load's necessary power constant. If the generator output exceeds the consumer demand, the excess power is delivered to BESS for temporary storage. When consumer demand exceeds generated power, a BESS delivers deficit power to the load, which adjusts and the frequency under various load conditions. The suggested system simulated results were tested with 3-phase 4-wire for harmonics reduction, load balancing, neutral wire current compensation, frequency and voltage control using MATLAB / Simulink.
Induction machine health monitoring is considered a developing technology for the online detection of faults that occur even at the initial stage. The objective of this study is to present an artificial intelligence (AI) technique for the detection and localization of adjacent and distant broken bar faults in the induction machine, through a multi-winding model for the simulation of these cases. In this work, it was found that the application of Artificial Neural Networks (ANN) based on Mean Squared Error (MSE) and Random Forest (decision tree) plays an important role in detecting and locating defaults. The stator current signal Ias of a motor in the dynamic state was acquired from a healthy and faulty motor with a broken rotor bar fault. 9 statistical features and 8 wavelet packet parameters are extracted from the stator current signal. These features were employed as an input vector to train and test the ANN and random fores29t and determine whether the motor was running under normal conditions or defective. For optimizing the rotor bar defect classification procedure, feature selection algorithms are adopted, such as BBAT and BPSO. For feature reduction, we used the principal component analysis (PCA) algorithm, to reduce the number of features. The results showed that the random forest classifier based on statistical parameters and wavelet packet parameters followed by PCA can detect the defective with high accuracy (98.3333%) compared to other methods.
Bioinspired control system strategies have received considerable attention in recent years, demonstrating their effectiveness to control various classes of systems. This paper presents a new robust LQR-based fuzzy-immune PID controller synthesis method, the particularity of this structure is the combination of the features granted by the linear quadratic regulator LQR and the fuzzy-immune PID controller as: robustness, optimization and self-adapting. The proposed approach is applied to the temperature control of a greenhouse system over Ethernet network. Such control loop is bound to be affected by several uncertainties such as communication delays, packet dropout... etc., it is therefore necessary to adopt a robust control strategy that can handle these problems. MATLAB/Simulink is used to simulate the proposed controller structure under several perturbations/uncertainties scenarios. The results show better time domain performance and greater robustness against uncertainties, in comparison with other PID structures (classic and fuzzy immune PID).
This paper presents a novel external secondary self-excitation capacitance and chopper resistance across the diode bridge rectifier in the rotor circuit to control the voltage and frequency of 3-phase, wound-rotor, slip-ring, induction generator (WRSRIG). The problem related to the excitation- capacitance from the rotor side is the required large excitation capacitance to enhance the generator performance in a wide - range. In the present proposed method, a dynamic excitation capacitance is used in the H-Bridge inverter circuit connected in series with a chopper resistance across a 3-phase diode bridge rectifier in the rotor circuit. The duty ratios of the H-bridge thyristor elements and the thyristor chopper element are varied to emulate the excitation-capacitance as well as external-rotor resistance values dynamically, and to be used as terminal voltage and its frequency control. The dynamic excitation-capacitance is used to control the terminal voltage, while the dynamic external rotor resistance is used to control the generator speed (frequency). To study the performance of the WRSRIG a dynamic model is presented in this paper in D-Q axes rotating synchronously in a reference frame. The dynamic model takes into account all the machine parameters, such as stator and rotor - iron core losses, stator and rotor - stray load losses, dynamic saturation of the magnetizing inductance, rotor harmonic losses generated due to switching action of the bridge rectifier, reduction voltage in the rotor circuit due to the over-lap phenomenon and rotor external resistance losses. The new proposed equivalent circuit of the WRSRIG will become an efficient method for studying the performance characteristics of the generator and to be used as a suitable tool for an algorithm of the vector control analysis.
Based on a theorem giving the maximum available active power with constant transmission losses valid for arbitrary waveforms it is possible rigorously generalize the definitions of power factor based on the definition of apparent power as the maximum power available. Then it could be applied to systems with non-symmetric, non-sinusoidal, and eventually time-varying (ie non-periodic) waveforms or DC grids. By this way, the application may be extended to hybrid multi-wire systems with asymmetrical phases, with different voltages, frequencies or waveforms (i.e. non-sinusoidal waves, such as rectangular or PWM) and even DC, which can be combined eventually sharing the neutral conductor.
In this paper, we proposed, modelled, and then simulated a standalone photovoltaic system with storage composed of conventional batteries and a Supercapacitor was added to the storage unit in order to create hybrid storage sources (batteries and Supercapacitor), and to better relieve the batteries during peak power. And reduce stress on the batteries by avoiding deep discharges. This study includes, on the one hand, a MPPT (Maximum Power Point Tracking) algorithm integrated to the control of this converter allowing the photovoltaic panels to operate according to their optimal nominal voltage, thus providing the maximum power. On the other hand, efficient global management allows the system to offer optimal performance.
One of the main issues on high voltage direct current (HVDC) cable is the electric field distribution on the insulation induced by space charges accumulation. Indeed, the space charges can cause a local increase of the electric field, which will accelerate ageing and may lead to dielectric breakdown. The TSM is one of the techniques that allow space charge measurements. The principle of the TSM consists in disturbing the electrostatic balance of the cable insulation system using a short thermal stimulus. For this study, the thermal pulse is created by Joule effect. This paper describes the structural optimization of a multi-cell DC-DC converter and its use in a high-current application to produce thermal stimulus. The design of the converter is first presented, then a multi-objective optimization is proposed for minimizing volume and losses. Finally, experimental results using a converter prototype which confirmed the space charge measurement principle are presented.
This study of modifying the frame forces of an electric vehicle offers benefits for controlling stability. We used a two-wheeled self-driving electric vehicle in this study. Taking into account important parameters such as vehicle speed, the vehicle's stability criterion is determined based on the torque level and lateral slip angle. It is equipped with a traction control system that integrates its dynamic system with a sporty design. This level of control improves the vehicle's stability and safety. A conventional regulator has been developed and trained to apply motor control to a sophisticated power supply system. The stability of the EVs was controlled by a simulation model. We validated the proposed stability criterion, and the wheel torque control algorithm. Stability control for two-wheeled autonomous vehicles can be developed on the basis of related research. We would like to stress that the controller can be used in a variety of modern electric vehicles because it is so easy to use. An overview of the modeling and simulation results for this system in the MATLAB-Simulink environment will be presented.
In this article, the meta-heuristic algorithm PSO with PI fuzzy logic controller is proposed to develop a new control strategy of bidirectional converter (CSBC), in order to improve the stability and increase the efficiency of energy flow exchange in grid-connected photovoltaic generator (PVG) Battery hybrid system. The proposed command aims to satisfy the DC Motor load demand, manages the power flows from different parts, injects surplus energy into the grid as and when need, ensure charge-discharge battery operation even under the fluctuating condition of power generation, and stabilize the DC bus voltage. This new control has been placed in the network topology, which consists of a PVG Photovoltaic Generator, grid-connected DC/AC converter, storage battery and DC motor load. A bidirectional buck-boost converter is used for optimum exploit of power from PVG along with battery charging/discharging control, and for feeding DC motor load. The effectiveness of the proposed control scheme is demonstrated by using MATLAB / Simulink program. The results obtained, show that the proposed control provided the system with the stability of Vdc voltage, and contributed to improving the speed produced by the DC motor load. The results have been compared with the conventional control.
DC circuit breaker is the core equipment for the safe and stable operation of DC transmission system. In order to design a DC circuit breaker with low cost and current limiting function, a capacitor converter DC circuit breaker with current limiting function is proposed in this paper. The topology uses capacitance to replace IGBT to realize the switching of circuit state, which greatly reduces the number of IGBT, moreover, through the use of current limiting branch, the peak value and rate of current are restrained, the requirements of energy absorption capacity of lightning arrester are reduced, the fault cut-off time is shortened, and the cost and technical difficulty are greatly reduced. In this paper, the working principle of the extracted topology is studied and analyzed in stages, and then the parameters are designed. Finally, the system simulation model is built by using PSCAD software to verify the simulation model. Compared with the typical circuit breaker design scheme, the rationality and superiority of the proposed scheme are proved.
A photovoltaic (PV) panel produces energy that is influenced by external factors including temperature, irradiation, and the fluctuations in the load related to it. The PV system should perform at maximum power point (MPP) in order to adjust towards the rapidly increasing interest in energy. Because of the changing climatic conditions, it becomes has a limited efficiency. In order to maximize the PV system's efficiency, a maximum power point technique is necessary. In the present paper a maximum power point (MPP) of photovoltaic (PV) panel is designed and simulated to optimize system performance, accurate synthesis model based on the hybrid neural fuzzy systems is proposed to directly obtain the MPP. So, photovoltaic panel (PV) is analyzed with the mathematical model to obtain the training data. Three cases were used to test the identification of the structure proposed. The results show neuro-fuzzy (Sugeno Model) used were efficient in modeling the MPP of our PV panel. The Mean square error (MSE) is used as the fitness function to guarantee that the MSE is small, the algorithm synthesis model is validated by the MPP PV Panel analysis, simulation, and measurements. Neuro-fuzzy models is presented throughout this paper to demonstrate the effectiveness of the method of training suggested.
Because water extraction from wells accounts for the bulk of energy consumption in irrigation operations globally, the sustainability and profitability of irrigation are strongly reliant on the energy efficiency of the pumping system.A technique that studies and improves the performance of motors used in well pumping systems is reported in this body of research as having been undertaken.In a similar manner, an experimental investigation of the energy efficiency of two modern systems of induction motor control has been carried out.According to the results, proper control performance is critical to achieving improvements in energy and efficiency.Using DTC-SVM for IM, the purpose of this study is to demonstrate a prototype of a pumping system that is powered by solar energy in the presence of changing radiation levels.Real-time MATLAB/Simulink simulations are used in conjunction with a dSpace 1104 board to carry out the hardware implementation.
The dielectric barrier discharge (DBD) is a more efficient medium of ozone production, which requires voltages of the order of several kV and frequencies of a few tens of kHz. The principal objective of this study is to model and optimize a cylindrical-shaped ozone generator with a surface DBD that will be used in a water treatment plant. By playing on the electrical parameters (voltage, oxygen flow) and geometric parameters (the nature and diameter of the dielectric, the length of the electrode), to achieve high ozone efficiency and minimum energy consumption. It is recommended to use cylindrical surface discharge reactors with reduced diameter and electrode length and with the smallest possible oxygen circulation interval to achieve satisfactory ozone concentrations, with reduced power consumption.
In this paper, a new approach to control active and reactive powers for DFIG wind power system is proposed. Where parameters of the RST controller are tuned by the Particle Swarm Optimization (PSO) algorithm. First the calculation of conventional RST polynomial is presented. The main goal of this study is to apply and compare the performances of two kinds of regulators (conventional RST and PSO-RST) for DFIG wind turbine system. A vector control of the DFIG is also presented in order to accomplish the control of active and reactive powers. The obtained results show the effectiveness and good performances of PSO-RST controller compared to the conventional RST in terms of reference tracking and disturbances rejection.
The exploitation of solar energy and the universal interest in photovoltaic systems have increased nowadays due to galloping energy consumption and current geopolitical and economic issues. This has led to high technical and economic requirements. The PV system still faces major obstacles such as high cost and low efficiency compared to other renewable technologies. In addition, the photovoltaic system suffers from the rate of undesirable harmonics of the generated power which could alter the quality of energy and the performance requested by users. In order to remedy this problem, the use of the multi-level inverter is in these cases one of the most promising solutions. Indeed, the multi-level technology seems to be well suited to photovoltaic applications to help fill the need for several sources on the DC side of the converter. The technical performance and reliability of the multi-level inverter used to connect the PV modules to the electrical power distribution networks can improve and make profitable the power produced. In this work, we compare two multi-level inverter topologies for PV systems: H-Bridge (HB) and Neutral Point Clamped (NPC). The comparison between these inverters is based on the criteria of spectral quality of the output voltage and the complexity of the power circuits.
Due to the high efficiency, high power density and low EMI provided by the LLc resonant converter, it has been widely used by researchers in many fields such as induction heating (IH). This converter is based on a resonant circuit consisting of a capacitor (Cr) and two inductors Lr, Lm operating in wide output load regulating ranges for the purpose of achieving good efficiency for very high power systems using a high operating frequency. This paper aims to present a half-bridge LLC resonant converter based on power supplies for IH applications. The analysis contains five components: half bridge inverter, resonant tank, high frequency transformer, rectifier and coil. The switching bridge generates a square waveform to excite the LLC resonant tank, which will produce a resonant sinusoidal current which is transferred to the secondary of the converter through a high-frequency transformer. as it scales the voltage up or down according to the output requirements. The load represented by the equivalent circuit of the coil and work-piece is fed by the current transformed by the rectifiers. This paper provides an improved knowledge of the control of the output power for high-temperature applications through numerical simulation Considering that the load parameters and resonant frequency vary substantially throughout the system operation. The results of testing demonstrated that the proposed scheme and assembly has good efficiency, and it is well suited for magnetic induction heating systems.
Wirebonds ageing in power modules used in electric vehicles is a main concern for the development of reliable inverters. The development of a specific test bench to study the evolution of their properties over time has allowed conclusions to be drawn on the possibility of accelerating or not accelerating ageing tests without distorting the mechanisms actually involved in ageing. Through the use of specifically developed test bench in terms of electrical and thermal properties the studied wirebonds samples are more easily thermally controllable, equipped with measuring devices and the energy consumption at a given cycle is divided by ten compared to a classical bench. The entire process of designing and producing the specific samples and the associated test bench and a description of the first results obtained to demonstrate the relevance of the approach is given.
