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Keywords = dSPACE DS1202 real-time control (RTC) card

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23 pages, 28161 KB  
Article
Development and Experimental Implementation of Optimized PI-ANFIS Controller for Speed Control of a Brushless DC Motor in Fuel Cell Electric Vehicles
by Abdessamad Intidam, Hassan El Fadil, Halima Housny, Zakariae El Idrissi, Abdellah Lassioui, Soukaina Nady and Abdeslam Jabal Laafou
Energies 2023, 16(11), 4395; https://doi.org/10.3390/en16114395 - 29 May 2023
Cited by 34 | Viewed by 4483
Abstract
This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive neuro-fuzzy inference [...] Read more.
This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive neuro-fuzzy inference system (PI-ANFIS) and particle swarm optimization-proportional integral-adaptive neuro-fuzzy inference system (PSO-PI-ANFIS)). The control objective is to regulate the rotor speed to its desired reference value in the presence of load torque disturbance and parameter variations. The proposed controller uses a dSPACE platform (MicroLabBox controller board). The experimental prototype comprises a PEMFC system (the Nexa Ballard FC power generator: 1.2 kW, 52 A) and a brushless DC motor BLDC of 1 kW 1000 rpm. The PSO-PI-ANFIS controller presents better performance than the PI-ANFIS and classical PI controllers due to its ability to optimize the PI-ANFIS controller’s parameters using the particle swarm optimization (PSO) algorithm. This optimization results in improved tracking accuracy and reduced overshoot and settling time. Full article
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14 pages, 5458 KB  
Article
Theoretical Design and Experimental Validation of a Nonlinear Controller for Energy Storage System Used in HEV
by Zakariae El Idrissi, Hassan El Fadil, Fatima Zahra Belhaj, Abdellah Lassioui, Mostapha Oulcaid and Khawla Gaouzi
World Electr. Veh. J. 2020, 11(3), 49; https://doi.org/10.3390/wevj11030049 - 21 Jul 2020
Cited by 8 | Viewed by 3810
Abstract
This work presented a nonlinear control for a reversible power buck–boost converter (BBC) in order to control energy storage in a supercapacitor (SC) used in hybrid electric vehicles (HEV). The aim was to control a power converter in order to satisfy the following [...] Read more.
This work presented a nonlinear control for a reversible power buck–boost converter (BBC) in order to control energy storage in a supercapacitor (SC) used in hybrid electric vehicles (HEV). The aim was to control a power converter in order to satisfy the following two requirements: (i) perfect tracking of SC current to its reference signal and (ii) asymptotic stability of the closed-loop system. The two objectives were achieved using an integral sliding mode control. In order to validate the proposed approach, an experimental prototype was built. The controller was integrated into dSPACE prototyping systems using the DS1202 card. It was clearly shown, using formal analysis, simulation, and experimental results, that the designed controller metall the objectives, namely, the stability of the system and the control of the current at its reference. Full article
(This article belongs to the Special Issue Control and Optimization of Hybrid-electric Vehicle Powertrains)
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