Efficiency Optimization of Induction Motor Using a Fuzzy Logic Based Optimum Flux Search Controller

Ramesh, L.; Chowdhury, S.P.; Chowdhury, Shajjad; Saha, Akshay Kumar; Song, Yonghua

doi:10.1109/pedes.2006.344354

Cited by 16 publications

(8 citation statements)

References 7 publications

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“…then these numerical variables are converted into the Linguistic variables. Five fuzzy sets are seen in table.1 as NL(Negative large), NS(Negative small), Z(Zero), PS (Positive small) and PL( Positive large) [11][12][13][14][15]. Fuzzy control structure is defined as follow: 1.…”

Section: Parameter Pso In Induction Motormentioning

confidence: 99%

A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive

Aryza

Irwanto

Lubis

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract.The induction motor has in the industry . More attention has been a focus to develop and design of induction motor drive. With the method of vector control novelty prove the efficiency of induction motor over their entire speed range. In this paper desirable to design a loss minimization controller which can improve the efficiency. Also, this research described Modeling of an induction motor with core loss included. Realization of methods vector control for an induction motor drive with loss element included. The case of the loss minimization condition. The procedure was successful to calculate the gains of a PI controller. Though the problem of obtaining a robust and sensorless induction motor drive is by no means completely solved, the results obtained as part of this work point in a promising direction. Introduction.IM are critical components in industrial processes. A motor failure may yield an unexpected interruption at the industrial plant, with consequences in costs, product quality, commonly used in adjustable speed drive systems. Induction motors have been widely employed in various industries as actuators or drivers to produce mechanical motions and forces. Since it is estimated that more than 50% of the world electric energy is generated and consumed by electric machines, to improve an efficiency of electric drives are important [1.2]. Induction motors require both full operating range of speed and fast torque response in operational conditions, regardless of load variations. Namely, induction motors have a high efficiency at rated speed and torque.Its efficient control requires a suitable model with accurate parameters, the minimization of the objective function is carried out using the Particle Swarm Optimization. Particle Swarm Optimization (PSO) is an evolutionary algorithm inspired by social interaction. PSO is an evolutionary once technique (a search method based on a natural system) developed by Kennedy and Eberhart. The basic concept of the PSO technique 'lies in accelerating each particle towards its p best and g best locations, with a random weighted acceleration at each time step. PSO has many parameters, and these are described as follow: V max is the maximum allowable velocity of the particles (i.e. in the case where the velocity of the particle exceeds Vmax, then it is limited to Vmax). Particle swarm optimization (PSO) is one of the modern heuristic algorithms [16], [17]. PSO has attracted great attention due to its features of easy implementation, robustness to control parameters and computation efficiency compared with other existing heuristic algorithms, and has been successful. Particle swarm

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Section: Parameter Pso In Induction Motormentioning

confidence: 99%

A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive

Aryza

Irwanto

Lubis

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Fuzzy logic control is used in [42] to set the optimum direct-axis stator current (i ds ), which in turn minimizes the input power P in . Membership functions are built based on derivative estimates ΔP in /Δids.…”

Section: Definitionmentioning

confidence: 99%

A survey of real-time power-loss minimizers for induction motors

Bazzi

Krein

2009

2009 IEEE Electric Ship Technologies Symposium

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This paper presents a survey of available techniques for minimizing power losses and input power of induction motors. The presented techniques serve different induction motor applications, including electric ship propulsion systems. Realtime techniques presented here are divided into three main categories: model-based methods that use the induction motor model, physics-based methods that search for the minimum power loss regardless of the motor model or parameters, and hybrid methods that combine both approaches. Definitions, comparisons, and details about these methods are presented. To compare model-based and physics-based methods in a propulsion application, simulations of a model-based technique and another physics-based technique are also presented.

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“…This effectively minimises the machine core losses. The most popular industry practices to find out the optimum flux level for IM drive operation can broadly be categorised as: (i) loss model‐based control (LMC) [3–5]; and (ii) search control (SC) [6–11]. The LMC estimates losses by using the machine model and sets the optimum flux level that subsequently reduces the machine losses.…”

Section: Introductionmentioning

confidence: 99%

“…Perturb and observe technique is the most popular technique and has been widely used in loss minimisation problems in industrial drives. A conventional fuzzy logic‐based SC technique is used in [6] to set the optimum flux component of current, which in turn minimises the input power requirement. Simulation results depict a 50% reduction in the input power to meet certain load demand.…”

Section: Introductionmentioning

confidence: 99%

Search controller‐based online efficiency optimisation strategy for induction motor drives using modified adaptive quadratic interpolation

Pal

Das

2020

IET power electron.

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A search control‐based new efficiency optimisation strategy for indirect vector controlled induction motor (IM) drive is proposed in this work. The online optimisation method considered in this regard is based on modified adaptive quadratic interpolation. The proposed strategy is employed in the flux loop of the speed control technique to decide the optimum flux component of stator current necessary to meet a particular drive operating condition. The selection of the optimum flux in this way, in fact, minimises the core loss of IM drive, thereby improving the overall efficiency of the drive depending upon the motor loading condition. Like the conventional search controllers, the algorithm is simple, immune to the machine parameter variation and does not require any additional circuitry for its implementation. The algorithm offers faster convergence, thereby preserving the dynamic response of the speed control loop. Analytical studies are done in MATLAB/Simulink and the results are validated experimentally in a 2.2 kW IM drive laboratory prototype.

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Efficiency Optimization of Induction Motor Using a Fuzzy Logic Based Optimum Flux Search Controller

Cited by 16 publications

References 7 publications

A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive

A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive

A survey of real-time power-loss minimizers for induction motors

Search controller‐based online efficiency optimisation strategy for induction motor drives using modified adaptive quadratic interpolation

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