An Efficiency PI Speed Controller for Future Electric Vehicle in Several Topology. (2016)

• Record Type: Journal Article
• Authors: Gasbaoui, Brahim; Nasri, Abdelfatah; Abdelkhalek, Othmane
• Is Part Of: Procedia technology. Volume 22(2016)
• Page Start: 501
• Page End: 508
• Publication Date: 2016
• Subjects: Neural Networks -- PI speed control -- DTC -- Electric vehicle -- SOC; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.01.109
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: In this paper a four-Wheels-Drive (4WD) Electric Vehicle (EV) controlled by Direct Torque Control (DTC) is presented, where neural network PI speed controller is proposed to tune the PI controller gains to ensure optimal performance of 4WD Electric Vehicle. The electrical traction chain was well analyzed and studied from the Lithium Ion (Li-Ion) battery, the buck boost to the mechanical load behavior. The speed of the four wheels is calculated independently during the turning with the electronic differential system computations which distributes torque and power to each in-wheel motor according to the requirements, adapts the speed of each motor to the driving conditions. The basic idea of this work is to maintain the initial battery state of charge (SOC) equal to 60% and the prototype was tested in several topology conditions and under speed. Our electric vehicle direct torque control is simulated in MATLAB SIMULINK environment. 4WD Electric vehicle (EV) has demonstrated satisfactory results in all kind of roads constraints: straight, ramp, curved road and downhill. The analysis and simulations lead to the conclusion that the proposed system is feasible. Results also indicate that this strategy can be successfully implemented into the traction drive of the modern 4WD electric vehicles.