Exploitation of vehicle's kinetic energy in power management of tow -wheel drive electric vehicles based on ANFIS DTC-SVM comparative study

Benhammou, Aissa; Hamza, Tedjini; Guettaf, Yacine; Soumeur, Mohammed Amine; Hartani, Mohammed Amine; Hafsi, Oussama; Benabdelkader, A.

doi:10.1016/j.ijhydene.2021.06.023

Cited by 18 publications

(13 citation statements)

References 52 publications

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“…where d [N m s 2 ] is the drag coefficient and l [m] is the distance between the center of the quadcopter and the center of a propeller. From Equation (7) and Equation ( 9), the equations motion of the quadcopter are given as follows:…”

Section: Mathematical Modelmentioning

confidence: 99%

A Particle Swarm Optimization Based Fuzzy Flcpi-Pso Controller for Quadcopter System

Baba,

Bounaama,

Bennaceur

et al. 2024

Communications

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The quadcopter persist as important roles across diverse applications, and the enhancement of their control efficacy has been the subject of extensive research. In this work, the authors proposed optimal Proportional Integral (PI) controller based Fuzzy Logic Control (FLC) for the roll, pitch, altitude, and yaw motions of the quadcopter system. The proposed technique uses the Particle Swarm Optimization (PSO) algorithm to tune the parameters of the FLC and enhance the quadcopter performance. The simulation results show that the proposed technique achieves smoothness of control and significant improvement over classical techniques, as the rise time and the settling time are reduced by 61 % and 66 %, respectively. These times are important for stabilizing the system's response speed and avoiding overshooting or oscillating. This indicates that the FLCPI-PSO can achieve the desired roll and altitude angles more rapidly and effectively.

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Section: Mathematical Modelmentioning

confidence: 99%

A Particle Swarm Optimization Based Fuzzy Flcpi-Pso Controller for Quadcopter System

Baba,

Bounaama,

Bennaceur

et al. 2024

Communications

Self Cite

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“…Whereas Gao et al utilize logic threshold EMS to train ANFIS for a parallel hybrid EV with a DC-motor traction motor, achieving improved performance in simulation tests [112]. Authors in [113] propose a unique HESS EV configuration to increase kinetic energy utilization with ANFIS EMS. The ESS used are FC, battery, and SC.…”

Section: ) Flc and Frequency Decouplingmentioning

confidence: 99%

Energy Management in Hybrid Electric and Hybrid Energy Storage System Vehicles: A Fuzzy Logic Controller Review

Maghfiroh,

Wahyunggoro,

Cahyadi

2024

IEEE Access

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The transportation sector, a significant contributor to carbon dioxide emissions as of 2020, confronts a pressing challenge in mitigating pollution. Electric Vehicles (EVs) present a promising solution, offering a cleaner alternative; however, their limited travel range poses a constraint. Hybrid Electric Vehicles (HEVs) and Hybrid Energy Storage System Electric Vehicles (HESS EVs) emerge as economically feasible compromises. Nonetheless, the effective management of energy and the optimization of power source size remain crucial challenges for both HEVs and HESS EVs. Among various Energy Management Strategies (EMS), the Fuzzy Logic Controller (FLC) stands out for its performance, simplicity, and real-time applicability. This article comprehensively explores the diverse applications of FLC as an EMS in both HEVs and HESS EVs, providing a comparative analysis with other EMS methods and delving into the advantages and challenges associated with each approach. A detailed examination of various FLC types employed as EMS has been conducted, drawing insights from a multitude of references. Each class of FLC EMS is scrutinized, presenting a broad overview of proposed methodologies within each category. By providing this comprehensive information, the article equips readers with foundational knowledge and insights for the continued development of FLC EMS in hybrid electric and hybrid energy storage system electric vehicles.INDEX TERMS energy management, hybrid vehicle, electric vehicle, fuzzy logic controller, review I. INTRODUCTION

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“…This control technique actually combines the processes of fuzzy as well as ANN [25]. ANFIS is used to create the torque standard from speed error variations, each time.…”

Section: Anfismentioning

confidence: 99%

Direct torque control of electric vehicle drives using hybrid techniques

Marulasiddappa¹,

Pushparajesh²

2023

IJECE

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Permanent magnet synchronous motors (PMSM) have the capability of delivering a high torque-to-current ratio, better efficiency and low noise. Because of the above-mentioned factors, PMSMs are commonly employed in variable speed drives, especially in electric vehicle (EV) applications. Without the usage of electromechanical devices, the conventional direct torque control (DTC) can control the speed and torque of PMSM. DTC is highly efficient, fast-tracking and provides smooth torque while limiting its ripple during transient periods. There are many benefits to using a DTC-controlled PMSM drive, including quick and reliable torque reaction, high-performance control speed, and enhanced performance. This research examines the use of the DTC approach to enhance the speed and torque behavior of PMSM. The jellyfish search optimizer (JSO) is used to adjust the DTC's responsiveness and tailor the controller's best gains. In order to train the adaptive neuro-fuzzy inference system (ANFIS) controller, JSO data are utilized. The simulation outcomes demonstrate that the proposed JSO-ANFIS controller achieves a minimal torque ripple of 0.26 Nm and preserves the speed with a harmonic error of 1.21% while contrasted to existing methods.

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Exploitation of vehicle's kinetic energy in power management of tow -wheel drive electric vehicles based on ANFIS DTC-SVM comparative study

Cited by 18 publications

References 52 publications

A Particle Swarm Optimization Based Fuzzy Flcpi-Pso Controller for Quadcopter System

A Particle Swarm Optimization Based Fuzzy Flcpi-Pso Controller for Quadcopter System

Energy Management in Hybrid Electric and Hybrid Energy Storage System Vehicles: A Fuzzy Logic Controller Review

Direct torque control of electric vehicle drives using hybrid techniques

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