Predictive torque control of electric vehicle

The following article represents the development of a traction system of an electrical vehicle (EV) that consist of two Three-phase squirel-cage induction motors (IM) that permit the drive of the two front driving wheels. The two motors are controlled  using the Predictive Torque Control (PTC) method; A technique based on the next step prediction and evaluation of the electromagnetic torque and stator flux In a cost function in order to determinate the inverter switching vector that minimize the error between references and predicted values. PTC is what we tried to underline in this paper, so we explain below the principle of the method; and the system mathematical description is provided. An electronic differential is applied on the system to control independently the speed of the two wheels at different operating conditions in order to characterize the driving wheel system behavior, the robustness in steady state and in transient state

Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Induction Machine Control

In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations.

Two wheel speed robust sliding mode control for electric vehicle drive

Nowadays the uses of electrical power resources are integrated in the modern vehicle motion traction chain so new technologies allow the development of electric vehicles (EV) by means of static converters-related electric motors. All mechanical transmission devices are eliminated and vehicle wheel motion can be controlled by means of power electronics. The proposed propulsing system consists of two induction motors (IM) that ensure the drive of the two back driving wheels. The proposed control structure-called independent machines- for speed control permit the achievement of an electronic differential. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling independently, every driving wheel to turn at different speeds in any curve. This paper presents the study and the sliding mode control strategy of the electric vehicle driving wheels

A Novel and Robust Model of the GUPFC Controller System Based on Adaptive Fuzzy Logic- PI Controller to Enhance the Control System Performance in Following Reference Active and Reactive Power

The optimal electrical power transmission problem in electrical energy transmission lines has led to increased attention to the use of flexible alternating current transmission systems (FACTS) and the design of double- and multi-circuit lines. Hence, recently, multi-converter FACTS devices have been utilized in the literature to control voltage and power of multi-circuit transmission lines. A generalized unified power flow controller (GUPFC) is one of such emerging FACTS devices that can manage voltage and power control crisis in multi-circuit lines. The GUPFC is the most advanced generation of FACTS, which will be able to control active and reactive power in at least two circuits and voltage in one circuit with the best quality possible and satisfy the operator’s all requests. This paper, for the first time, presents the use of an adaptive control system design based on the proportional-integral (PI) controller and fuzzy system to enhance the fast and dynamic responsiveness of the system. PI systems alone cannot control the GUPFC under different operation conditions such as when the default reference values of active and reactive power are changed, or transient faults occur, or a transmission line experience outage. Thus, the use of a fuzzy controller, as a powerful tool, is very efficient in solving the mentioned problems. To analyze the proposed algorithm’s results, a test system and a GUPFC based on a 48-pulse voltage source converter (VSC) are implemented in the MATLAB/Simulink environment. The satisfactory results obtained in the simulation section verify the correct performance of the suggested method

Photovoltaic System with SEPIC Converter Controlled by the Fuzzy Logic

In this work, a fuzzy logic controller is used to control the output voltage of a photovoltaic system with a DC-DC converter; type Single Ended Primary Inductor Converter (SEPIC). The system is designed for 210 W solar PV (SCHOTT 210) panel and to feed an average demand of 78 W. This system includes solar panels, SEPIC converter and fuzzy logic controller. The SEPIC converter provides a constant DC bus voltage and its duty cycle controlled by the fuzzy logic controller which is needed to improve PV panel’s utilization efficiency. A fuzzy logic controller (FLC) is also used to generate the PWM signal for the SEPIC converter.

Self-Tuning Fuzzy Based PI Controller for DFIM Powered by Two Matrix Converters

This paper presents a study of the Doubly Fed Induction Machine (DFIM) powered by two matrix converters; one connected to the stator windings and the other connected to the rotor windings. First, the mathematical model of DFIM and those of the matrix converters are developed. Then, the vector control technique is applied to the DFIM. Fuzzy logic is used in order to automatically adjust the parameters of the PI controller. The performance of this structure under different operating conditions is studied. Particular interest is given to the robustness of the fuzzy logic based control. The operation of the DFIM under overload conditions is also examined.  Simulation results obtained in MATLAB/Simulink environment are presented and discussed

Speed Synchronization of Multi Induction Motors with Fuzzy Sliding Mode Control

A continuous web winding system is a large-scale, complex interconnected dynamic system with numerous tension zones to transport the web while processing it. There are two control schemes for large-scale system control: the centralized scheme and the decentralized scheme. Centralized control is the traditional control method, which considers all the information about the system to be a single dynamic model and design a control system for this model. Aspeed synchronization control strategy for multiple induction motors, based on adjacent cross-coupling control structure, is developed by employing total sliding mode control method. The proposed controlstrategy is to stabilize speed tracking of each induction motor while synchronizing its speed with the speed of the other motors so as to make speed synchronization error amongst induction motors converge to zero. The global stability and the convergence of the designedcontroller are proved by using Lyapunov method. Simulation results demonstrate the effectiveness of the proposed method