Real‐time extremum seeking controller for brushless DC hub motors in electric vehicles

Ramaraj, Ramachandran; Dharmaraj, Ganeshaperumal; Srinivasan, Seshadhri; Balasubramanian, Subathra; Periyasamy, Muthuvel; Bekiroğlu, Korkut

doi:10.1049/iet-epa.2020.0117

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…The EST considers the position error gain (Kxerr), velocity error gain (Kverr), and relative velocity gain (Kvrel) as the gains for the EST controller [24]. These gains are specified initially with values 1, 1, and 0.5, respectively for the ACC.…”

Section: Applying Extremum Seeking Technique With Adaptive Cruise Con...mentioning

confidence: 99%

Controlling a vehicle braking and longitudinal acceleration using a seeking control approach

Salman,

Shallal,

Sabry

2024

Bulletin EEI

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Traditional methods for tracking the paths of driverless vehicles use plant models to determine the corresponding control laws. Due to the intricate interactions between the road and the tires, time-varying characteristics, and unidentified disturbances. It is challenging to create an accurate vehicle model. As a result, data-driven controllers, which are independent of a predetermined plant model are becoming more and more well-liked. This work implements adaptive cruise control (ACC) by employing a control approach called extremum seeking technique (EST), which is a model-free control (MFC), to control a vehicle braking and longitudinal acceleration. The main aim here is to create an ego vehicle that travels at a specific speed with maintaining a secure space with respect to a guide vehicle. A car including an ACC technique called ego car, exploits radar to determine relative velocity and relative space relating to the guiding car. The ACC technique is considered to keep maintain a relatively secure space or a preferred cruising velocity concerning the guiding vehicle. The developed model succeeded to determine the relative velocity and relative space according for the ego car to another guiding car with acceleration not more than ±2 m/s2 and spacing error less than 6 m.

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Section: Applying Extremum Seeking Technique With Adaptive Cruise Con...mentioning

confidence: 99%

Controlling a vehicle braking and longitudinal acceleration using a seeking control approach

Salman,

Shallal,

Sabry

2024

Bulletin EEI

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“…In the study by Killingsworth and Krstic (2005), ESC has been applied to tune PID gains such that the performance is optimized. In the study by Ramaraj et al (2020), ESC method has been applied to find optimum value of a PID controller gains. It has been shown that the ESC-PID controller provides disturbance rejection, less torque ripple and better tracking compared with conventional PID and optimal PID controllers.…”

Section: Introductionmentioning

confidence: 99%

Perturbation observer design based on extremum seeking control: An analytical insight

Taleshian

Noei

Sadati

et al. 2023

Transactions of the Institute of Measurement and Control

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In this paper, an optimal extended state observer (ESO) is designed for nonlinear integral chain system. For the first time, in this paper, proportional–integral (PI) extremum seeking control (ESC; PIESC) approach is applied to design a perturbation observer by minimizing the estimation error. The PI type structure of the ESC provides fast transient response for the closed-loop system to attain optimum equilibrium point. A mathematical proof is presented to show that the average error dynamic asymptotically converges to zero while the estimation error is minimized. The simulation results verify that the estimation error achieved by the proposed PIESC-based ESO (PIESC-ESO) is found significantly less than that achieved by the classic ESO and PSO-based ESO. Moreover, if slow changes occur within the system or external to it, the PIESC-ESO is still able to modify the observer gains such that the estimation error is minimized again. Therefore, this may help PIESC-ESO to be used in practical applications.

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“…If things stay as they are, mobility issues will get worse as population and GDP growth lead to more people owning cars and driving more miles. As a result, the mobility sector is launching a dizzying array of technologies specifically suited for urban roadways, including mobility-as-a-service, cutting-edge parking and traffic management systems, freight-sharing options, and novel twoor three-wheeled transportation concepts [2]. Electric vehicles are the major focus of the industry as they have become the need of the hour due to the rising fuel prices and increasing problems of greenhouse gases.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study on Different Motors used in Electric Vehicles

Ahmed¹,

Zaidi²,

Khan³

2022

JISR-C

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Motors are the main part of the drivetrain of electric vehicles (EVs) as they transfer the power of batteries to the axle and tires. Therefore, the performance of batteries is a great concern as loss of energy, or lower torque/speed can cause a negative impact on the performance of EVs. In this regard, this study aimed to study different motors that are used in EVs. These motors include DC motors (brushed and brushless), permanent magnet motor motors(BLDCs), switched reluctance motors (SRMs), induction motors(IMs), and outer rotor motors. This study has performed a rigorous review of past literature to examine different factors (speed, torque, efficiency, flux linkage) that affect the performance of motors in EVs. The results of the study have found that SRMs are the most efficient and reliable motors for use in EVs as they can perform in different conditions and offer benefits of low cost and high efficiency. The study has noted the performance rating of SRM to be the highest (87), while BLDCs, PMSMs, and IMs, showed a performance rating of 75, 85, and 82 out of 100. However, more research is needed in this area to enhance the performance of the motors through the development of a novel motor design to enhance efficiency and reduce cost.

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Real‐time extremum seeking controller for brushless DC hub motors in electric vehicles

Cited by 5 publications

References 28 publications

Controlling a vehicle braking and longitudinal acceleration using a seeking control approach

Controlling a vehicle braking and longitudinal acceleration using a seeking control approach

Perturbation observer design based on extremum seeking control: An analytical insight

A Comparative Study on Different Motors used in Electric Vehicles

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