DC Motor Pump Research Articles

Maximum Power Point Tracker Control Design of a Photovoltaic-Generator Powered DC Motor-Pump System Based on Artificial Neural Networks

This paper presents the optimisation of a photovoltaic (PV) water pumping system using maximum power point tracker (MPPT) technique. The optimisation is suspended to reference optimal power. This optimisation technique is developed to assure the optimum chopping ratio of buck-boost converter. The presented MPPT technique is used in PV water pumping system in order to optimise its efficiency. An adaptive controller with emphasis on non-linear autoregressive moving average (NARMA) based on artificial neural networks approach is applied in order to optimise the duty ratio for PV maximum power at any irradiation level. In this application, an indirect data-based technique is taken, where a model of the plant is identified on the basis of input-output data and then used in the model-based design of a neural network controller. The proposed controller has the advantages of robustness, fast response and good performance. The PV generator DC motor pump system with the proposed controller has been tested through a step change in irradiation level. Simulation results show that accurate MPPT tracking performance of the proposed system has been achieved. Further, the performance of the proposed artificial neural network (ANN) controller is compared with a proportional-integral-derivative controller through simulation studies. Obtained results demonstrate the effectiveness and superiority of the proposed approach.

Modeling, analysis and neural MPPT control design of a PV-generator powered dc motor-pump system

This paper presents the optimization of a photovoltaic (PV) water pumping system using maximum power point tracking technique (MPPT). The optimization is suspended to reference optimal power. This optimization technique is developed to assure the optimum chopping ratio of buck-boost converter. The presented MPPT technique is used in photovoltaic water pumping system in order to optimize its efficiency. An adaptive controller with emphasis on Nonlinear Autoregressive Moving Average (NARMA) based on artificial neural networks approach is applied in order to optimize the duty ratio for PV maximum power at any irradiation level. In this application, an indirect data-based technique is taken, where a model of the plant is identified on the basis of input-output data and then used in the model-based design of a neural network controller. The proposed controller has the advantages of robustness, fast response and good performance. The PV generator DC motor pump system with the proposed controller has been tested through a step change in irradiation level. Simulation results show that accurate MPPT tracking performance of the proposed system has been achieved. Further, the performance of the proposed artificial neural network (ANN) controller is compared with a PID controller through simulation studies. Obtained results demonstrate the effectiveness and superiority of the proposed approach.

PERFORMANCE IMPROVEMENT OF A PHOTOVOLTAIC GENERATOR POWERED DC MOTOR-PUMP SYSTEM BASED ON ARTIFICIAL NEURAL NETWORKS

This paper presents the optimization of a photovoltaic (PV) waterpumping system using maximum power point tracking technique(MPPT). The optimization is suspended to reference optimal power. Thisoptimization technique is developed to assure the optimum choppingratio of buck-boost converter. The presented MPPT technique is used inphotovoltaic water pumping system in order to optimize its efficiency. Anadaptive controller with emphasis on Nonlinear Autoregressive MovingAverage (NARMA) based on artificial neural networks approach isapplied in order to optimize the duty ratio for PV maximum power at anyirradiation level. In this application, an indirect data-based technique istaken, where a model of the plant is identified on the basis of inputoutputdata and then used in the model-based design of a neural networkcontroller. The proposed controller has the advantages of robustness,fast response and good performance. The PV generator DC motor pump system with the proposed controller has been tested through a step change in irradiation level. Simulation results show that accurate MPPTtracking performance of the proposed system has been achieved.Further, the performance of the proposed artificial neural network(ANN) controller is compared with a PID controller through simulationstudies. Obtained results demonstrate the effectiveness and superiority ofthe proposed approach.

Integrated solar pump design incorporating a brushless DC motor for use in a solar heating system

Most solar thermal hot water heating systems utilize a pump for circulation of the working fluid. An elegant approach to powering the pump is via solar energy. A “solar pump” employs a photovoltaic module, electric motor, and pump to collect and convert solar energy to circulate the working fluid. This article presents an experimental investigation of a new integrated solar pump design that employs the stator of a brushless DC motor and a magnetically coupled pump that has no dynamic seal. This design significantly reduces total volume and mass, and eliminates redundant components. The integrated design meets a hydraulic load of 1.7 bar and 1.4 litres per minute, equal to 4.0 watts, at a rotational speed of 500 revolutions per minute. The brushless DC motor and positive displacement pump achieve efficiencies of 62% and 52%, respectively, resulting in an electric to hydraulic efficiency of 32%. Thus, a readily available photovoltaic module rated 15 watts output is suitable to power the system. A variety of design variations were tested to determine the impact of the armature winding, pump size, pulse width modulation frequency, seal can material, etcetera. The physical and magnetic design was found to dominate efficiency. The efficiency characteristics of a photovoltaic module are such that over-sizing is wasteful. The integrated design presents a robust, efficient package for use as a solar pump. Although focus has been placed on application to a solar thermal collector system, variations of the design are suitable for a wide variety of applications such as remote location water pumping.

GPS 기반의 초소형 무인선박을 위한 자율항법 알고리즘 개발

최근 항공기, 자동차, 선박을 포함하여 다양한 분야에서 무인시스템에 관한 연구 개발이 이루어지고 있다. 우리나라에서도 IT 기술의 발달과 함께 무인시스템에 관한 연구가 활발히 진행되고 있지만 아직 개발 실적은 미미한 수준이다. 이 연구에서는 바지(barge)선형의 초소형자율 무인선박(USV)을 개발하고자 하였다. 자율항법 알고리즘 개발에 GPS센서의 위치 정보를 기반으로 대권항법 계산식을 적용하였으며, 프로그래밍은 NI사의 LabVIEW 8.2를 이용하였다. 조타제어는 펄스진폭변조 방식으로 하였다. 또한, 엔진시스템은 전동모터 및 전자 변속기로 구성하였고, 엔진시스템 냉각방식으로 DC모터펌프를 이용한 해수 직접냉각방식을 채용하였다. 무인선박을 자체 설계 제작하고, 해상실험을 통해 자율운항 알고리즘의 유효성을 검증하였다. Recently, unmanned systems have been studied and developed in various areas including aircrafts, automobiles and vessels. In addition, many researches about unmanned systems in Korea have been studying actively with the advancement of IT However, it is not satisfied with the result of the researches and developments. Bemuse of the reason we've here tried to make a very small USV which is a barge type. We applied the Great circle navigation calculation based on GPS to the autonomous navigation algorithm and used the LabVIEW 8.2 developed by NI corp. for programming The engine and rudder were controlled by pulse width modulation method. The engine system was composed of the DC motor and ESC(Electronic Speed Controller). It was also applied by the direct cooling system using DC motor pump. A very small USV was designed and made by ourself and it was verified the effectiveness of autonomous navigation algorithm through the tests at the sea.