Solar PV fed non-isolated DC-DC converter for BLDC motor drive with speed control

RajaSekhar, G. G; Banakar, Basavaraja

doi:10.11591/ijeecs.v13.i1.pp313-323

Cited by 20 publications

(11 citation statements)

References 12 publications

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“…Both these issue contribute to the waste of power and hence shrink of the power tracking efficiency of solar PV. To overcome this issue a modified P&O is designed in [22], in which, the perturbation step voltage size K is reduced as the operating PV output voltage reaches near its MPP [23,24].…”

Section: Conventional Perturb and Observe (P And O)mentioning

confidence: 99%

A Literature review on industrially accepted MPPT techniques for solar PV system

Yadav

Maurya

Gupta

2020

IJECE

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Solar energy is a clean renewable energy and it is available around 89,000 TW on the earth surface. To get maximum power from a solar PV system with minimum power transfer loss is one of the main design objectives of an energy transferring network. Power electronic devices perform a very important character for an efficient PV power tracking system control and either incorporates to transfer the generated power to the ac/dc grid or battery storage system. In this case the duty of the power electronics devices used in PV system is to track maximum power point under different operating conditions of environment, so that power tracking efficiency of solar PV system can be improved. This paper encapsulates based the on performance comparisions on the behavior of MPP under uniform and nonuniform operating conditions and selects the optimum duty cycle for industrially accepted MPPT techniques with their algorithm.

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Section: Conventional Perturb and Observe (P And O)mentioning

confidence: 99%

A Literature review on industrially accepted MPPT techniques for solar PV system

Yadav

Maurya

Gupta

2020

IJECE

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“…, and are the self-inductances of the stator windings; , , , , and are the mutual inductances amongst the stator windings and , and are the back EMFs of the three phase stators [3,12]. Given the symmetric structure and equal resistances of the three stator windings, we derive (4) (5) where is the self-inductance of the stator and M is the mutual inductance. L and M are independent of the rotor position.…”

Section: Dynamic Model Of a Bldc Motormentioning

confidence: 99%

“…Compared with brushed DC motors and induction machines, BLDC motors have lower inertia that enables faster dynamic response to reference commands. In addition, they are more efficient due to the permanent magnets that can perform with virtually zero rotor losses [3][4][5].BLDC motors have a complex and nonlinear model. To overcome the control problem, a nonlinear fuzzy logic controller (FLC) is used to control the speed of a BLDC motor.…”

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confidence: 99%

Type 1 versus type 2 fuzzy logic speed controllers for brushless dc motors

Abed

Humod

Humaidi

2020

IJECE

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This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC. INTRODUCTIONBrushless DC (BLDC) motors can be used in several fields and applications, such as industrial automated electric vehicles and aerospace computers. BLDC motors exhibit several advantages over brushed DC motors. They are characterised by low maintenance due to commutator disposal, long operating life due to lack of friction and electrical losses and high power density [1,2]. The BLDC motors have no brushes, which prolongs the life time of motor and avoids their maintenance. Additionally, these motors are characterized by high electromagnetic torque-to-weight ratio, which make them suitable for most application [2,3]. Compared with brushed DC motors and induction machines, BLDC motors have lower inertia that enables faster dynamic response to reference commands. In addition, they are more efficient due to the permanent magnets that can perform with virtually zero rotor losses [3][4][5].BLDC motors have a complex and nonlinear model. To overcome the control problem, a nonlinear fuzzy logic controller (FLC) is used to control the speed of a BLDC motor. This intelligent controller has a simple structure and is relatively easy to implement due to its modest fuzzy rule in the rule base [6,7]. Recently, the intelligent control of BLDC motors has elicited the attention of many researchers. A review of the most relevant studies is presented in this paper. R. Arulmozhiyal and R. Kandiban compared a conventional proportional-integral-derivative (PID) controller and a fuzzy PID controller in terms of the speed control of BLDC motors. The results were obtained using MATLAB/SIMULINK and then experimentally verified.The simulated and practical results showed that the fuzzy PID.Controller outperformed the conventional PID controller [8]. E. Blessy and M. Murugan analysed a BLDC motor model and designed an FLC to improve the dynamic performance of speed control. They compared the fuzzy logic (FL), proportional, proportional-integral and PID controllers to evaluate the impact of each controller on speed dynamic performance [9].

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“…Such applications include, for example robotic manipulators, steel rolling mills, electric trains, cranes, electric cars, etc [1][2]. Even the Brushless DC (BLDC) motor has been developed with higher efficiency in operation than classic DC motor [3]. The most flexible control is obtained by means of Separately Excited DC Motor (SEDM).…”

Section: Introductionmentioning

confidence: 99%

Speed control of DC motor using conventional and adaptive PID controllers

Al-Bargothi

Qaryouti

Jaber

2019

IJEECS

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<p>Proportional Integral Derivative (PID) controllers are <a href="http://www.thesaurus.com/browse/extensively">extensively</a> used in practical industries to control the speed of DC Motors. The single weakness of PID controllers is their sensitivity to variation in parameters and operating conditions; thus, tuning the controller gains to adapt with these variations presents a practical challenge. In this paper, an adaptive mechanism that utilizes a Recursive Least Square (RLS) algorithm, with rate limiters, is implemented to perform an online self-adjusting of each of the PID gains in order to achieve Adaptive PID (APID) controller that will accommodate to system variations. MATLAB/ Simulink software is used to implement and simulate APID control of a Chopper-Fed DC motor. A conventional PID control system is also designed and simulated to obtain results that can be used to judge the performance of the APID controller. Results proved that the APID controller forced the motor speed to track the reference input with <a href="http://www.thesaurus.com/browse/insignificant">insignificant</a> tracking error, and also managed to attain the motor speed at its desired value, regardless of the load changes inflected on the motor. This enhances both transient and steady-state speed responses.</p>

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Solar PV fed non-isolated DC-DC converter for BLDC motor drive with speed control

Cited by 20 publications

References 12 publications

A Literature review on industrially accepted MPPT techniques for solar PV system

A Literature review on industrially accepted MPPT techniques for solar PV system

Type 1 versus type 2 fuzzy logic speed controllers for brushless dc motors

Speed control of DC motor using conventional and adaptive PID controllers

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