Implementation of the ACO algorithm in an electrical vehicle system powered by five-level NPC inverter

• Published in: Electrical engineering Vol. 103; no. 3; pp. 1335 - 1345
• Main Authors: Rtibi, Waad, M’barki, Lotfi, Yaich, Mohamed, Ayadi, Moez
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021; Springer Nature B.V
• Subjects: Algorithms; Ant colony optimization; Dynamic loads; Economics and Management; Electric vehicles; Electrical Engineering; Electrical Machines and Networks; Energy Policy; Engineering; Harmonic distortion; Induction motors; Inverters; Original Paper; Power Electronics; Pulse duration modulation; Shafts (machine elements); PDC-PWM; PI-ACO regulator; Electric vehicle; NPC inverter
• ISSN: 0948-7921; 1432-0487
• DOI: 10.1007/s00202-020-01162-9

The ant colony optimization (ACO) algorithm is generally used to create an optimal PI regulator added to the pulse width modulation (PWM) strategy for a five-level neutral-point-clamped (NPC) inverter implemented in electric vehicle (EV). As heavy transportation is our main focus, the proposed system was formed by two induction motors (IMs); each of which was fed by one NPC inverter. The two IMs were fixed to the front axle and the rear axle, respectively. The PDC-PWM (Phases Disposition Carrier-PWM) strategies for the three-phase five-level NPC inverter was employed in the rotor-flux-oriented control (FOC) of the induction motor (IM). Special interest was given to the analysis of the total harmonic distortion (THD%). Considering the dynamic loading conditions of an EV driven by an IM, the proposed ACO algorithm effectively calculated the required PI parameter to find the best PI regulator gains values. These optimizations were applied to the PDC-PWM strategy in order to obtain the minimum THD% in both current and voltage outputs. The effectiveness of the introduced system for a wide range of torque/speed variations was proven through simulation by developing a model of an IM traction inverter drive with the FOC strategy for closed-loop control. As the experimental test realization of the designed system was not possible because it is very expensive, the ACO optimization performance was confirmed by means of MATLAB/SimPower Systems simulations.