Torque ripple minimization of bridgeless CUK converter-based BLDC motor using Improved Jellyfish Search Algorithm

Rajesh, A.; Saravanan, A. Gnana

doi:10.1016/j.isatra.2022.11.025

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…According to this analysis, the minor signals produced by the electromechanical system have an average value model of PMSM. This model may be obtained by using the non-sinusoidal back EMF in the same way as BLDC utilizes the trapezoidal back EMF [21]- [23]. The electrical parameters of BLDC motor are shown in Table 1.…”

Section: Mathematical Modellingmentioning

confidence: 99%

Controlling the significance of BLDC motor internal faults using dual examine algorithm in electric vehicle applications

Gaurav,

Nakka,

Obulesu

et al. 2023

IJPEDS

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<span lang="EN-US">This paper presents dual examine algorithm (DEA) to reduce residual error as well as to provide accurate phase currents without any distortion for a closed loop brushless direct current (BLDC) motor of an electric vehicle (EV). The underlying technology of DEA is a hybrid of the tabu search optimization (TSO) method and the genetic algorithm (GA). During closed loop operation of BLDC motor residual error is introduced by the discrepancy between the actual and reference speed, and the phase current distortion lowers the efficiency of the machine as a result machine performance is degraded. To address these issues, GA algorithm calculates the necessary parameters for the controller to produce precise current without distortion based on stator phase currents, and the suggested TSO algorithm limits the repeated operations in the PID controller to reduce the residual error to the greatest degree feasible. After primary examining, dual examine process initiate the transposing operation such as TSO is used to prove and calculate the phase current controller parameters, and GA is used to correct for remaining inaccuracy. To validate the proposed DEA algorithm is compared with advanced particle swarm optimization (APSO). The results verified the superiority of proposed DEA algorithm using MATLAB/Simulink platform.</span>

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Section: Mathematical Modellingmentioning

confidence: 99%

Controlling the significance of BLDC motor internal faults using dual examine algorithm in electric vehicle applications

Gaurav,

Nakka,

Obulesu

et al. 2023

IJPEDS

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“…The suggested regulation technique estimates EMF, stator current, torque, and speed. Another technique [ 16 ] proposes the Improved Jellyfish Search (ImpJS) technique is presented for minimizing torque ripple on a BLDC motor with a CUK converter. Crossover and mutation operators enhance the JS algorithm and improve the speed and torque control strategy.…”

Section: Introductionmentioning

confidence: 99%

Selection/control concurrent optimization of BLDC motors for industrial robots

Padilla-García¹,

Cervantes-Culebro

Rodríguez-Ángeles

et al. 2023

PLoS ONE

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This paper aims to concurrently select and control off-the-shelf BLDC motors of industrial robots by using a synergistic model-based approach. The BLDC motors are considered with trapezoidal back-emf, where the three-phase (a,b,c) dynamics of motors are modeled in a mechatronic powertrain model of the robot for the selection and control problem, defining it as a multi-objective dynamic optimization problem with static and dynamic constraints. Since the mechanical and electrical actuators’ parameters modify the robot’s performance, the selection process considers the actuators’ parameters, their control input, operational limits, and the mechanical output to the transmission of the robot joints. Then, three objective functions are to be minimized, the motor’s energy consumption, the tracking error, and the total weight of installed motors on the robot mechanism. The control parameterization approach via a cascade controller with PI controllers for actuators’ voltage and a PID controller for actuators’ torque is used to solve the multi-objective dynamic optimization problem. Based on simulations of the closed-loop system, a Pareto front is obtained to examine trade-offs among the objective functions before implementing any actuators in the existing robotic system. The proposed method is tested on an experimental platform to verify its effectiveness. The performance of an industrial robot with the actuators originally installed is compared with the results obtained by the synergic approach. The results of this comparison show that 10.85% of electrical power can be saved, and the trajectory tracking error improved up to 57.41% using the proposed methodology.

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Optimizing brushless direct current motor design: An application of the multi-objective generalized normal distribution optimization

Pandya,

Jangir,

Mahdal

et al. 2024

Heliyon

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Torque ripple minimization of bridgeless CUK converter-based BLDC motor using Improved Jellyfish Search Algorithm

Cited by 4 publications

References 39 publications

Controlling the significance of BLDC motor internal faults using dual examine algorithm in electric vehicle applications

Controlling the significance of BLDC motor internal faults using dual examine algorithm in electric vehicle applications

Selection/control concurrent optimization of BLDC motors for industrial robots

Optimizing brushless direct current motor design: An application of the multi-objective generalized normal distribution optimization

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