Multi-input multi-output fuzzy logic controller for utility electric vehicle

2011 ◽  
Vol 60 (3) ◽  
pp. 239-256 ◽  
Author(s):  
Brahim Gasbaoui ◽  
Chaker Abdelkader ◽  
Laoufi Adellah
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Direct Torque Control ◽  
Torque Control ◽  
Control Technique ◽  
Single Input Single Output ◽  
Driving Wheel ◽  
On The Road

Multi-input multi-output fuzzy logic controller for utility electric vehicle Currently commercialization of electric vehicle (EV) is based to minimize the time of starting and acceleration. To undergo this problem multi-input multi-output fuzzy logic controller (MIMO-FLC) affect on propelled traction system forming MMS process was proposed. This paper introduces a MIMO-FLC applied on speeds of electric vehicle, the electric drive consists of two directing wheels and two rear propulsion wheels equipped with two light weight induction motors. The EV is powered by two motors of 37 kilowatts each one, delivering a 476 Nm total torque. Its high torque (476Nm) is instantly available to ensure responsive acceleration performance in built-up areas. Acceleration and steering are ensured by an electronic differential system which maintains robust control for all cases of vehicle behavior on the road. It also allows controlling independently every driving wheel to turn at different speeds in any curve. Direct torque control based on space vector modulation (DTC-SVM) is proposed to achieve the tow rear driving wheel control. The MIMO-FLC control technique is simulated in MATLAB SIMULINK environment. The simulation results have proved that the MIMO-FLC method decreases the transient oscillations and assure efficiency comportment in all type of road constraints, straight, slope, descent and curved road compared to the single input single output fuzzy controller (SISO-FLC).

Hybrid Anti-Windup Fuzzy PI Controller Based Direct Torque Control of Three Phase Induction Motor

2014 ◽  
Vol 573 ◽  
pp. 155-160
Author(s):  
A. Pandian ◽  
R. Dhanasekaran
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Direct Torque Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Constant Speed ◽  
Three Phase

This paper presents improved Fuzzy Logic Controller (FLC) of the Direct Torque Control (DTC) of Three-Phase Induction Motor (IM) for high performance and torque control industrial drive applications. The performance of the IM using PI Controllers and general fuzzy controllers are meager level under load disturbances and transient conditions. The FLC is extended to have a less computational burden which makes it suitable for real time implementation particularly at constant speed and torque disturbance operating conditions. Hybrid control has advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of DTC based IM drive with fuzzy logic controller becomes significant. To improve the performance of the system, a new control method, Hybrid fuzzy PI control is proposed. The effectiveness of proposed method is verified by simulation based on MATLAB. The proposed Hybrid fuzzy controller has adaptive control over load toque variation and can maintain constant speed.

scholarly journals Improved DTC strategy of an electric vehicle with four in-wheels induction motor drive 4WDEV using fuzzy logic control

2021 ◽  
Vol 12 (2) ◽  
pp. 650
Author(s):  
Nair Nouria ◽  
Gasbaoui Brahim Ghazouni Abdelkader ◽  
Benoudjafer Cherif
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Induction Motors ◽  
Control Strategies ◽  
Direct Torque Control ◽  
Torque Control ◽  
The Road ◽  
Time Simulation ◽  
Wheel Drive ◽  
Four Wheel Drive

In this paper, we will study a four-wheel drive electric vehicle (4WDEV)with two control strategies: conventional direct torque control CDTC and DTC based on fuzzy logic (DTFC). Our overall idea in this work is to show that the 4WDEV equipped with four induction motors providing the drive of the driving wheels controlled by the direct fuzzy torque control ensures good stability of the 4WDEV in the different topologies of the road, bends and slopes. and increases the range of the electric vehicle. Numerical simulations were performed on an electric vehicle powered by four 15 kW induction motors integrated into the wheels using the MATLAB / Simulink environment, where the reference speeds of each wheel (front and rear) are obtained using an electronic speed differential (ESD). This can eventually cause it to synchronize the wheel speeds in any curve. The speed of each wheel is controlled by two types of PI and FLC controllers to improve stability and speed response (in terms of setpoint tracking, disturbance rejection and climb time). Simulation results show that the proposed FLC control strategy reduces torque, flux and stator current ripple. While the4WDEV range was improved throughout the driving cycle and battery power consumption was reduced.

scholarly journals 24 Sectors DTC Control with Fuzzy Hysteresis Comparators for DFIM Fed by the Three-level NPC Inverter

2022 ◽  
Vol 12 ◽  
pp. 141-154
Author(s):  
Abderrahmane Moussaoui ◽  
Habib Benbouhenni ◽  
Djilani Ben Attous
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Direct Torque Control ◽  
Control Process ◽  
Torque Control ◽  
Electromagnetic Torque ◽  
External Disturbances ◽  
Parameter Variations ◽  
Doubly Fed

This article presents 24 sectors direct torque control (DTC) with fuzzy hysteresis comparators for the doubly-fed induction motor (DFIM) using a three-level neutral point clamped (NPC) inverter. The designed DTC technique of the DFIM combines the advantages of the DTC strategy and fuzzy logic controller. The reaching conditions, stability, and robustness of the DFIM with the designed DTC technique are guaranteed. The designed DTC technique is insensitive to uncertainties, including parameter variations and external disturbances in the whole control process. Finally, the designed DTC technique with fuzzy hysteresis comparators is used to regulate the electromagnetic torque and the flux of the DFIM fed by the three-level NPC inverter and confirms the validity of the designed DTC technique. Results of simulations containing tests of robustness and tracking tests are presented.

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