Cakar ayam shaping machine

Cakar ayam (Figure 7.1) is one of the Malay traditional cookies that are made from sliced sweet potatoes deep-fried in the coconut candy. In current practice of moulding the cookies, the fried sweet potatoes are molded using traditional manual tools, which are inefficient and less productive for the mass production purposes. “Kuih cakar ayam” associated with the meaning of the idiom means less messy handwriting has a somewhat negative connotation .This cookies may just seem less attractive in shape but still likeable . In fact, this cookie is considered a popular snack even outside the holiday season. The choice of the name of this cookie is more to shape actually resembles former chicken scratches made by the paw the ground while foraging. The value of wisdom, beauty and creativity of the Malays is clearly evident through the Malay cookie. Although it is attacked by the invention of modern cakes that look far more interesting, these cakes will be able to survive a long time until now

Evolution engine technology in exhaust gas recirculation for heavy-duty diesel engine

In this present year, engineers have been researching and inventing to get the optimum of less emission in every vehicle for a better environmental friendly. Diesel engines are known reusing of the exhaust gas in order to reduce the exhaust emissions such as NOx that contribute high factors in the pollution. In this paper, we have conducted a study that EGR instalment in the vehicle can be good as it helps to prevent highly amount of toxic gas formation, which NOx level can be lowered. But applying the EGR it can lead to more cooling and more space which will affect in terms of the costing. Throughout the research, fuelling in the engine affects the EGR producing less emission. Other than that, it contributes to the less of performance efficiency when vehicle load is less

A Sliding Mode Multimodel Control for a Sensorless Photovoltaic System

In this work we will talk about a new control test using the sliding mode control with a nonlinear sliding mode observer, which are very solicited in tracking problems, for a sensorless photovoltaic panel. In this case, the panel system will has as a set point the sun position at every second during the day for a period of five years; then the tracker, using sliding mode multimodel controller and a sliding mode observer, will track these positions to make the sunrays orthogonal to the photovoltaic cell that produces more energy. After sunset, the tracker goes back to the initial position (which of sunrise). Experimental measurements show that this autonomic dual axis Sun Tracker increases the power production by over 40%

A Sliding Mode Control for a Sensorless Tracker: Application on a Photovoltaic System

The photovoltaic sun tracker allows us to increase the energy production. The sun tracker considered in this study has two degrees of freedom (2-DOF) and especially specified by the lack of sensors. In this way, the tracker will have as a set point the sun position at every second during the day for a period of five years. After sunset, the tracker goes back to the initial position (which of sunrise). The sliding mode control (SMC) will be applied to ensure at best the tracking mechanism and, in another hand, the sliding mode observer will replace the velocity sensor which suffers from a lot of measurement disturbances. Experimental measurements show that this autonomic dual axis Sun Tracker increases the power production by over 40%

Solar Tracking System based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

Fotovoltaik panellerin güç toplama verimliliğini artırmak için genellikle güneş takip sistemleri (GTS) ile entegre edilmelidir. Bu çalışmada, uyarlamalı sinirsel bulanık çıkarım uygulaması ile GTS sunulmuştur. GTS, zenit ve azimut açılarını kontrol eden iki motora sahip çift eksenli olarak tasarlanmıştır. Bu motorların hızının kontrol edilmesi için ANFIS’in tasarlanmasından sonra bulanık mantık kontrolörünün giriş-çıkış ilişkisini öğrenmek için yapay sinir ağı eğitilmiştir. Pozisyon hatası ve hatanın değişimi modellerin girişi olarak alınmıştır. Motora uygulanan gerilim modellerin çıkışı olarak alınmıştır. ANFIS modelde, deneysel verilerden doğrudan üretilen kurallar kümesine sahip yapay sinir ağının öğrenme yeteneği ile bulanık çıkarım modeli birleştirilir. Sonuç olarak, elde edilen sonuçlar GTS için amaçlanan kontrol yaklaşımının doğru cevap ve takip etme etkinliğini doğrular.Solar tracking systems (STS) should usually be integrated with photovoltaic (PV) panel so that the photovoltaic panels can increase power collection efficiency. In this paper, STS with implementation of adaptive neuro-fuzzy inference system (ANFIS) is presented. STS designed as dual axis has two motors that control azimuth angle and zenith angle. After designing an ANFIS for controlling these motors' speed, a Neural Network is trained to learn the input–output relationship of fuzzy logic controller. Position error and error variation were taken as model’s inputs. Applied voltage to the motor was taken as model's output. The ANFIS model is combined modeling function of fuzzy inference with the learning ability of artificial neural network that has set of rules generated directly from the experimental data. Finally, the obtained results confirm the tracking efficiency and correct response of the proposed control approach for STS

Comparison Between Different Algorithms for Maximum PPT in Photovoltaic Systems and its Implementation on Microcontroller

This paper presents the practical implementation of fuzzy logic control algorithm for maximum power point tracking (MPPT) in photovoltaic (PV) systems. A prototyping PV system is implemented with a boost DC-DC converter using Microchip® PIC18F452 microcontroller to execute the MPPT algorithms. The common algorithms like perturbation and observation (P&O) and incremental conductance (IncCon.) as well as the proposed fuzzy logic control algorithm are implemented and tested under different conditions, and the test results are analyzed and compared. The results show that the proposed fuzzy logic control algorithm can give better performance than perturbation and observation and incremental conductance algorithms. Keywords: Photovoltaic, Maximum power point tracking, Fuzzy logic control, Microcontrollers

A modified particle swarm optimization based maximum power point tracking for photovoltaic converter system

This thesis presents a modified Particle Swarm Optimization based Maximum Power Point Tracking for Photovoltaic Converter system. All over the world, many governments are striving to exploit the vast potential of renewable energy to meet the growing energy requirements mainly when the price of oil is high. Maximum Power Point Tracking (MPPT) is a method that ensures power generated in Photovoltaic (PV) systems is optimized under various conditions. Due to partial shading or change in irradiance and temperature conditions in PV, the power-voltage characteristics exhibit multiple local peaks; one such phenomenon is the global peak. These conditions make it very challenging for MPPT to locate the global maximum power point. Many MPPT algorithms have been proposed for this purpose. In this thesis, a modified Particle Swarm Optimisation (PSO)-based MPPT method for PV systems is proposed. Unlike the conventional PSO-based MPPT methods, the proposed method accelerates convergence of the PSO algorithm by consistently decreasing weighting factor, cognitive and social parameters thus reducing the steps of iterations and improved the tracking response time. The advantage of the proposed method is that it requires fewer search steps (converges to the desired solution in a reasonable time) compared to other MPPT methods. It requires only the idea of series cells; thus, it is system independent. The control scheme was first created in MATLAB/Simulink and compared with other MPPT methods and then validated using hardware implementation. The TMS320F28335 eZDSP board was used for implementing the developed control algorithm. The results show good performance in terms of speed of convergence and also guaranteed convergence to global MPP with faster time response compared to the other MPPT methods under typical conditions (partial shading, change in irradiance and temperature, load profile). This demonstrates the effectiveness of the proposed method

Research on MPPT methods for photovoltaic system based on microgrid

This thesis introduces some basic concepts about a microgrid. Then it discusses the structure of photovoltaic system (PVS) which contains a solar panel and simplified PV models. Next, it discusses and compares different methods for Maximum Power Point Tracking (MPPT) with PVS. It presents three types of DC-DC converters -- Buck, Boost and Buck-Boost converter. This work proposes to apply a DC-DC converter of Buck-Boost type to make PVS controllable because this type of converter has the largest range for operational region so that it can get the best result on MPPT. Finally, this thesis presents a kind of new MPPT method based on fuzzy logic theory. It concludes that the proposed method is effective in achieving MPPT in comparison with the prior arts

Literature Survey On Standalone Pumping Station For Agriculture Purpose Using Solar PV

The concept of the project is to utilize the abundant solar energy available, harness it for effective work output. Here we are trying to use solar energy to run the centrifugal pump for lifting the water from the well. This can be utilized for different purpose like irrigation for agriculture & nurseries, etc. Here we are collecting all information about which kind of constraints required for planning of standalone pumping station for agriculture purpose. In this paper we are finding out which are power electronics applications in renewable energy sources. This document will help all researcher to start work on Solar PV’s, irrigation using renewable energy , as well as for finding the power electronics application in renewable energy sources. DOI: 10.17762/ijritcc2321-8169.15036

Identification and Simulation of Dc-Dc Boost Converter for Charging Up PV Voltage for 24-Volts Battery

This manuscript is a piece of report on the identification of a DC-DC Boost switched mode converter for charging up Photovoltaic (PV) voltage for 24-volts battery. A DC-DC Boost converter with unknown mathematical characteristic is identified using Auto-Regressive with Exogenous Input (ARX) model. The identification of such DC-DC converter, on the basis of recorded data from PV is conducted to obtain the mathematical model of the converter. The knowledge about the converter is then beneficial for the design process of a PV’s maximum power point tracking (MPPT) system. The identification process that exploits the advantage of linear parametric ARX gives beneficial information such as correlation, best fit and poles-zeros location. The purpose of identification is to obtain the best model of the converter and hence, beneficial the simulation and controller design phase which include the MPPT