Analysis, control and design of speed control of electric vehicles delayed model: multi‐objective fuzzy fractional‐order  controller

Khooban, Mohammad Hassan; Shasadeghi, Mokhtar; Niknam, Taher; Blaabjerg, Frede

doi:10.1049/iet-smt.2016.0277

Cited by 44 publications

(22 citation statements)

References 31 publications

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“…Most attention over the past few years has focused on electric vehicles (EVs). EVs can decrease the fossil fuel consumptions but increase the demand in power sector [1,2]. EVs can be summarised into two categories: battery EV and hybrid EV [3,4].…”

Section: Motivationmentioning

confidence: 99%

Cost‐based optimal siting and sizing of electric vehicle charging stations considering demand response programmes

Simorgh¹,

Doagou‐Mojarrad

Razmi

et al. 2018

IET Generation, Transmission & Distribution

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Section: Motivationmentioning

confidence: 99%

Cost‐based optimal siting and sizing of electric vehicle charging stations considering demand response programmes

Simorgh¹,

Doagou‐Mojarrad

Razmi

et al. 2018

IET Generation, Transmission & Distribution

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“…Recently, the integration of fractional-order (FO) calculus into traditional controller appreciable improves the conventional controllers' tracking and disturbance rejection ability. Because of having better dynamic performance in uncertain situations, FO-based controllers (FOC) have been predominantly observed in the LFC study of power systems [22][23][24][25]. In ref.…”

Section: Introductionmentioning

confidence: 99%

Disturbance observer aided optimised fractional‐order three‐degree‐of‐freedom tilt‐integral‐derivative controller for load frequency control of power systems

Guha

Roy

Banerjee

2020

IET Generation Trans & Dist

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This work demonstrates a maiden application of a fractional-order based three-degreeof-freedom tilt-integral-derivative controller for escalating the load frequency control performance of power system having wind power generator integrated. The disturbance observer is housed with the proposed fractional-order-three-degree-of-freedom-tiltintegral-derivative controller to efficiently estimate the wind velocity's uncertain profile and subsequently enrich the control law. The mastery of the proposed control algorithm has been tested on multi-area interconnected power systems by performing an extensive comparative study with other prevalent techniques reported in the state-of-art. Harris' Hawks optimisation is applied to explore the proposed controllers' optimum gains, exercising an integral error-based criterion. Time response measurements of the studied test systems in the wake of load fluctuation and intermittent output of wind power generator explicitly establish the efficacy of the proposed Harris' Hawks optimisation tuned disturbance observer-based fractional-order-three-degree-of-freedom-tilt-integral-derivative controller over its other counterparts concerning damping of system oscillations. Furthermore, the developed control system's robust stability is affirmed using Kharitonov's stability theorem, considering ±25% variation in system parameters. wileyonlinelibrary.com/iet-gtd

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“…Electric vehicle (EV) systems are basically time variant that makes the operation of controlling an EV difficult. For the vehicle speed control design, there is a class of approaches [4–7] published recently to deal with the issue by considering the exterior disturbances and uncertainties in which fuzzy logic control and model predictive control were attempted. Comparatively, few other studies have focused on the braking system design.…”

Section: Introductionmentioning

confidence: 99%

Integrated electromagnetic braking/driving control of electric vehicles using fuzzy inference

Chen

Lin

2019

IET Electric Power Applications

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Although the antilock braking system (ABS) has been commonly used in electric vehicles (EVs), most of the vehicles still use the traditional hydraulic-based disc brake in which the driving and the braking systems are two individual modules. A novel integrated driving and braking control system with an ABS for EVs was developed, and an electric scooter was used as the experimental object. While braking, the motor acts as a generator. The autonomously generated inertial energy was used to generate a reverse magnetic braking torque and realise an antilock braking control with fast response. Compared with the existing regenerative and short-circuit braking methods, the proposed method uses back electromotive force to yield a reverse magnetic braking torque in a sophisticated manner. In the proposed method, a capacitor-aided regenerative braking strategy was used in an antilock braking controller. For the ABS control design, the slip ratio was maintained within an optimal range for obtaining the best tyre-road surface adhesion using a fuzzy slip ratio controller to prevent the wheel from skidding during emergency braking. For real-world verification, the electric scooter was subjected to various on-road tests to examine the performance of the proposed method.

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Analysis, control and design of speed control of electric vehicles delayed model: multi‐objective fuzzy fractional‐order controller

Cited by 44 publications

References 31 publications

Cost‐based optimal siting and sizing of electric vehicle charging stations considering demand response programmes

Cost‐based optimal siting and sizing of electric vehicle charging stations considering demand response programmes

Disturbance observer aided optimised fractional‐order three‐degree‐of‐freedom tilt‐integral‐derivative controller for load frequency control of power systems

Integrated electromagnetic braking/driving control of electric vehicles using fuzzy inference

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