Ahmad Fudholi

Drying of Malaysian Capsicum annuum L. (Red Chili) Dried by Open and Solar Drying

This study evaluated the performance of solar drying in the Malaysian red chili (Capsicum annuum L.). Red chilies were dried down from approximately 80% (wb) to 10% (wb) moisture content within 33 h. The drying process was conducted during the day, and it was compared with 65 h of open sun drying. Solar drying yielded a 49% saving in drying time compared with open sun drying. At the average solar radiation of 420 W/m2 and air flow rate of 0.07 kg/s, the collector, drying system, and pickup demonstrated efficiency rates of approximately 28%, 13%, and 45%, respectively. Evaporative capacity ranged from 0.13 to 2.36 kg/h, with an average of 0.97 kg/h. The specific moisture extraction rate (SMER) of 0.19 kg/kWh was obtained. Moreover, the drying kinetics of C. annuum L. were investigated. A nonlinear regression procedure was used to fit three drying models. These models were compared with experimental data on red chilies dried by open sun drying and those dried by solar drying. The fit quality of the models was evaluated using their coefficient of determination (), mean bias error, and root-mean-square error values. The Page model resulted in the highest and the lowest mean bias and root-mean-square errors.

Drying of salted silver jewfish in a hybrid solar drying system and under open sun: Modeling and performance analyses

ABSTRACT This study investigated the thin-layer drying kinetics of salted silver jewfish in a hybrid solar drying system and under open sun. Ten drying models were compared with experimental data of salted silver jewfish drying. A new model was introduced, which is an offset linear logarithmic (offset modified Page model). The fit quality of the models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), and sum of squared absolute error (SSAE). The result showed that Midilli et al. model and new model were comparable with two or three-term exponential drying models. This study also analyzed energy and exergy during solar drying of salted silver jewfish. Energy analysis throughout the solar drying process was estimated on the basis of the first law of thermodynamics, whereas exergy analysis during solar drying was determined on the basis of the second law of thermodynamics. At an average solar radiation of 540 W/m2 and a mass flow rate of 0.0778 kg/sec, the collector efficiency and drying system efficiency were about 41% and 23%, respectively. Specific energy consumption was 2.92 kWh/kg. Moreover, the exergy efficiency during solar drying process ranged from 17% to 44%, with an average value of 31%. The values of improvement potential varied between 106 and 436 W, with an average of 236 W.

Comparison of Selected Metals Content in Cambodian Striped Snakehead Fish (Channa striata) Using Solar Drying System and Open Sun Drying

The content of 12 elements in Cambodian dried striped snakehead fish was determined using inductively coupled plasma mass spectrometry. The present study compares the level of the trace toxic metals and nutritional trace elements in the fish processed using solar drying system (SDS) and open sun drying (OSD). The skin of SDS fish has lower level of As, Pb, and Cd compared to the OSD sample. As such, the flesh of the fish accumulated higher amount of toxic metals during OSD compared to SDS. However, arsenic was detected in both samples within the safe limit. The nutritional elements (Fe, Mn, Mg, Se, Mo, Cu, Ni, and Cr) were higher in the skin sample SDS fish compared to OSD fish. These beneficial metals were not accumulated in the flesh sample SDS fish demonstrating lower level compared to drying under conventional system. The reddish coloration of the SDS fish was due to the presence of high Cu content in both the skin and flesh samples which possibly account for no mold formation 5 days after packaging. As conclusion, drying of Cambodian C. striata using solar-assisted system has proven higher content of the nutritious elements compared to using the conventional system despite only slight difference in the toxic metals level between the two systems.

Entropy Generation Analysis of Power-Law Non-Newtonian Fluid Flow Caused by Micropatterned Moving Surface

In the present study, the first and second law analyses of power-law non-Newtonian flow over embedded open parallel microchannels within micropatterned permeable continuous moving surface are examined at prescribed surface temperature. A similarity transformation is used to reduce the governing equations to a set of nonlinear ordinary differential equations. The dimensionless entropy generation number is formulated by an integral of the local rate of entropy generation along the width of the surface based on an equal number of microchannels and no-slip gaps interspersed between those microchannels. The velocity, the temperature, the velocity gradient, and the temperature gradient adjacent to the wall are substituted into this equation resulting from the momentum and energy equations obtained numerically by Dormand-Prince pair and shooting method. Finally, the entropy generation numbers, as well as the Bejan number, are evaluated. It is noted that the presence of the shear thinning (pseudoplastic) fluids creates entropy along the surface, with an opposite effect resulting from shear thickening (dilatant) fluids.

Development of a Solar Assisted Drying System Using Double-Pass Solar Collector with Finned Absorber

The Solar Energy Research Group, Universiti Kebangsaan Malaysia, International Islamic University Malaysia and Yayasan FELDA has designed and constructed a solar assisted drying system at OPF FELDA Factory, Felda Bukit Sagu 2, Kuantan, Pahang. The drying system has a total of six double-pass solar collectors. Each collector has a length of 480 cm and a width of 120 cm. The first channel depth is 3.5 cm and the second channel depth is 7 cm. Longitudinal fins made of angle aluminium, 0.8 mm thickness were attached to the bottom surface of the absorber plate. The solar collectors are arranged as two banks of three collectors each in series. Internal manifold are used to connect the collectors. Air enters through the first channel and then through the second channel of the collector. An auxiliary heater source is installed to supply heat under unfavourable solar radiation condition. An on/off controller is used to control the startup and shutdown of the auxiliary heater. An outlet temperature of 70–75 °C can be achieved at solar radiation range of 800–900 W/m2 and flow rate of 0.12 kg/s. The average thermal efficiency of a solar collector is approximately 37%.

Overview of Photovoltaic Thermal (PVT) Water Collector

Received May 21, 2018 Revised Aug 30, 2018 Accepted Sep 13, 2018 This paper presents a novel Stator Current based Model Reference Adaptive System (SC_MRAS) speed observer for high-performance Six Phases Induction Motor (SPIM) drives using linear neural network. The article aim is intended to improve performance of an SC_MRAS observer, which were presented in the literature. In this proposed scheme, the measured stator current components are used as the reference model of the MRAS observer to avoid the use of a pure integrator and reduce the influence of motor parameter variation. The adaptive model uses a two-layer Neural Network (NN) to estimate the stator current, which has been trained online by means of a Least Squares (LS) algorithm instead of uses a nonlinear Back Propagation Network (BPN) algorithm to reduce the complexity and computational burden, it also help to improve some disadvantages cause by the inherent nonlinearity of the BPN algorithm as local minima, two heuristically chosen parameters, initialization, and convergence problems, paralysis of the neural network. The adaptive model of the proposed scheme is employed in prediction mode, not in simulation mode as is usually the case in the literature, this made the proposed observer operate better accuracy and stability. In the proposed observer, stator and rotor resistance values are estimated online, these values thereafter were updated for the current observer and rotor flux identifier to enhance the accuracy, robustness and insensitivity to parameters variation for the proposed observer. The proposed LS SC_MRAS observer has been verified thought the simulation and compared with the BPN MRAS observer. The simulation results have proven that the speed is estimated a consequent quicker convergence, do not need the estimated speed filter, lower estimation errors both in transient and steady state operation, better behavior in low and zero speed operation. Keyword:Received Jun 7, 2018 Revised Jul 8, 2018 Accepted Sep 13, 2018 Experiments confirmed that Transformerless Inverters (TIs) deliver more reliability and higher energy efficiency. Nonetheless, one of the shortcomings of TIs is the leakage current that occurs between the photovoltaic (PV) string terminals and the ground. Such a drawback is justified by the non-galvanic isolation caused by the transformer being omitted. As such, this study is intended to develop a novel TI inverter topology for solar PV systems. The latter is meant to remove the leakage current and enhance the operating system of the entire PV conversion as well. Added to its null zero-crossing distortion and capability regarding energy efficiency, the developed TI, being validated by simulation and experiment, eradicated the leakage current. Keyword:Now a day’s renewable energy sources became an interesting area of research of which fuel cells are emerged as an alternative source for producing electricity to meet the energy crisis. This led to a research on power conditioning systems through which fuel cell is interfaced to the utility. Of the different converter topologies Isolated full bridge boost converter (IFBC) topology is most suitable for fuel cell applications. In this paper a Predictive Switching Modulator (PSM) Control is proposed for the converter topology and its performance is compared with Linear Peak Current Mode control (LPCM), Non-Linear Carrier Control (NLC).Received May 2, 2018 Revised Aug 23, 2018 Accepted Sep 14, 2018 Recently of the main topic of research is the sensorless vector control of induction motor drive, In this paper presents the predictive model reference adaptive system (PMRAS) rotor speed observer, This observer developed from the classical MRAS rotor flux scheme associated with predictive adaptation mechanism designed from the Finite Control Set Model Predictive Control (FCS–MPC) by using a search optimization algorithm for calculate the rotor position which guarantee a minimum speed tuning error signal at each sampling period. The effectiveness of the proposed observer proved with the simulation results, show high dynamic performance speed and position observed in sensorless vector control process at low and zero speed as well robustness against motor parameter variation with different loading conditions. Keyword:

Outdoor Performance Evaluation of Building Integrated Photovoltaic Thermal (BIPVT) Solar Collector with Spiral Flow Absorber Configurations

Received May 21, 2018 Revised Aug 30, 2018 Accepted Sep 13, 2018 This paper presents a novel Stator Current based Model Reference Adaptive System (SC_MRAS) speed observer for high-performance Six Phases Induction Motor (SPIM) drives using linear neural network. The article aim is intended to improve performance of an SC_MRAS observer, which were presented in the literature. In this proposed scheme, the measured stator current components are used as the reference model of the MRAS observer to avoid the use of a pure integrator and reduce the influence of motor parameter variation. The adaptive model uses a two-layer Neural Network (NN) to estimate the stator current, which has been trained online by means of a Least Squares (LS) algorithm instead of uses a nonlinear Back Propagation Network (BPN) algorithm to reduce the complexity and computational burden, it also help to improve some disadvantages cause by the inherent nonlinearity of the BPN algorithm as local minima, two heuristically chosen parameters, initialization, and convergence problems, paralysis of the neural network. The adaptive model of the proposed scheme is employed in prediction mode, not in simulation mode as is usually the case in the literature, this made the proposed observer operate better accuracy and stability. In the proposed observer, stator and rotor resistance values are estimated online, these values thereafter were updated for the current observer and rotor flux identifier to enhance the accuracy, robustness and insensitivity to parameters variation for the proposed observer. The proposed LS SC_MRAS observer has been verified thought the simulation and compared with the BPN MRAS observer. The simulation results have proven that the speed is estimated a consequent quicker convergence, do not need the estimated speed filter, lower estimation errors both in transient and steady state operation, better behavior in low and zero speed operation. Keyword:Received Jun 7, 2018 Revised Jul 8, 2018 Accepted Sep 13, 2018 Experiments confirmed that Transformerless Inverters (TIs) deliver more reliability and higher energy efficiency. Nonetheless, one of the shortcomings of TIs is the leakage current that occurs between the photovoltaic (PV) string terminals and the ground. Such a drawback is justified by the non-galvanic isolation caused by the transformer being omitted. As such, this study is intended to develop a novel TI inverter topology for solar PV systems. The latter is meant to remove the leakage current and enhance the operating system of the entire PV conversion as well. Added to its null zero-crossing distortion and capability regarding energy efficiency, the developed TI, being validated by simulation and experiment, eradicated the leakage current. Keyword:Now a day’s renewable energy sources became an interesting area of research of which fuel cells are emerged as an alternative source for producing electricity to meet the energy crisis. This led to a research on power conditioning systems through which fuel cell is interfaced to the utility. Of the different converter topologies Isolated full bridge boost converter (IFBC) topology is most suitable for fuel cell applications. In this paper a Predictive Switching Modulator (PSM) Control is proposed for the converter topology and its performance is compared with Linear Peak Current Mode control (LPCM), Non-Linear Carrier Control (NLC).Received May 2, 2018 Revised Aug 23, 2018 Accepted Sep 14, 2018 Recently of the main topic of research is the sensorless vector control of induction motor drive, In this paper presents the predictive model reference adaptive system (PMRAS) rotor speed observer, This observer developed from the classical MRAS rotor flux scheme associated with predictive adaptation mechanism designed from the Finite Control Set Model Predictive Control (FCS–MPC) by using a search optimization algorithm for calculate the rotor position which guarantee a minimum speed tuning error signal at each sampling period. The effectiveness of the proposed observer proved with the simulation results, show high dynamic performance speed and position observed in sensorless vector control process at low and zero speed as well robustness against motor parameter variation with different loading conditions. Keyword:

Overview of Bifluid-based Photovoltaic Thermal (PVT) Systems

Received May 21, 2018 Revised Aug 30, 2018 Accepted Sep 13, 2018 This paper presents a novel Stator Current based Model Reference Adaptive System (SC_MRAS) speed observer for high-performance Six Phases Induction Motor (SPIM) drives using linear neural network. The article aim is intended to improve performance of an SC_MRAS observer, which were presented in the literature. In this proposed scheme, the measured stator current components are used as the reference model of the MRAS observer to avoid the use of a pure integrator and reduce the influence of motor parameter variation. The adaptive model uses a two-layer Neural Network (NN) to estimate the stator current, which has been trained online by means of a Least Squares (LS) algorithm instead of uses a nonlinear Back Propagation Network (BPN) algorithm to reduce the complexity and computational burden, it also help to improve some disadvantages cause by the inherent nonlinearity of the BPN algorithm as local minima, two heuristically chosen parameters, initialization, and convergence problems, paralysis of the neural network. The adaptive model of the proposed scheme is employed in prediction mode, not in simulation mode as is usually the case in the literature, this made the proposed observer operate better accuracy and stability. In the proposed observer, stator and rotor resistance values are estimated online, these values thereafter were updated for the current observer and rotor flux identifier to enhance the accuracy, robustness and insensitivity to parameters variation for the proposed observer. The proposed LS SC_MRAS observer has been verified thought the simulation and compared with the BPN MRAS observer. The simulation results have proven that the speed is estimated a consequent quicker convergence, do not need the estimated speed filter, lower estimation errors both in transient and steady state operation, better behavior in low and zero speed operation. Keyword:Received Jun 7, 2018 Revised Jul 8, 2018 Accepted Sep 13, 2018 Experiments confirmed that Transformerless Inverters (TIs) deliver more reliability and higher energy efficiency. Nonetheless, one of the shortcomings of TIs is the leakage current that occurs between the photovoltaic (PV) string terminals and the ground. Such a drawback is justified by the non-galvanic isolation caused by the transformer being omitted. As such, this study is intended to develop a novel TI inverter topology for solar PV systems. The latter is meant to remove the leakage current and enhance the operating system of the entire PV conversion as well. Added to its null zero-crossing distortion and capability regarding energy efficiency, the developed TI, being validated by simulation and experiment, eradicated the leakage current. Keyword:Now a day’s renewable energy sources became an interesting area of research of which fuel cells are emerged as an alternative source for producing electricity to meet the energy crisis. This led to a research on power conditioning systems through which fuel cell is interfaced to the utility. Of the different converter topologies Isolated full bridge boost converter (IFBC) topology is most suitable for fuel cell applications. In this paper a Predictive Switching Modulator (PSM) Control is proposed for the converter topology and its performance is compared with Linear Peak Current Mode control (LPCM), Non-Linear Carrier Control (NLC).Received May 2, 2018 Revised Aug 23, 2018 Accepted Sep 14, 2018 Recently of the main topic of research is the sensorless vector control of induction motor drive, In this paper presents the predictive model reference adaptive system (PMRAS) rotor speed observer, This observer developed from the classical MRAS rotor flux scheme associated with predictive adaptation mechanism designed from the Finite Control Set Model Predictive Control (FCS–MPC) by using a search optimization algorithm for calculate the rotor position which guarantee a minimum speed tuning error signal at each sampling period. The effectiveness of the proposed observer proved with the simulation results, show high dynamic performance speed and position observed in sensorless vector control process at low and zero speed as well robustness against motor parameter variation with different loading conditions. Keyword:

Improvement Potential and Exergy Analyses of Photovoltaic Thermal with and without ∇-Collector

Received May 21, 2018 Revised Aug 30, 2018 Accepted Sep 13, 2018 This paper presents a novel Stator Current based Model Reference Adaptive System (SC_MRAS) speed observer for high-performance Six Phases Induction Motor (SPIM) drives using linear neural network. The article aim is intended to improve performance of an SC_MRAS observer, which were presented in the literature. In this proposed scheme, the measured stator current components are used as the reference model of the MRAS observer to avoid the use of a pure integrator and reduce the influence of motor parameter variation. The adaptive model uses a two-layer Neural Network (NN) to estimate the stator current, which has been trained online by means of a Least Squares (LS) algorithm instead of uses a nonlinear Back Propagation Network (BPN) algorithm to reduce the complexity and computational burden, it also help to improve some disadvantages cause by the inherent nonlinearity of the BPN algorithm as local minima, two heuristically chosen parameters, initialization, and convergence problems, paralysis of the neural network. The adaptive model of the proposed scheme is employed in prediction mode, not in simulation mode as is usually the case in the literature, this made the proposed observer operate better accuracy and stability. In the proposed observer, stator and rotor resistance values are estimated online, these values thereafter were updated for the current observer and rotor flux identifier to enhance the accuracy, robustness and insensitivity to parameters variation for the proposed observer. The proposed LS SC_MRAS observer has been verified thought the simulation and compared with the BPN MRAS observer. The simulation results have proven that the speed is estimated a consequent quicker convergence, do not need the estimated speed filter, lower estimation errors both in transient and steady state operation, better behavior in low and zero speed operation. Keyword:Received Jun 7, 2018 Revised Jul 8, 2018 Accepted Sep 13, 2018 Experiments confirmed that Transformerless Inverters (TIs) deliver more reliability and higher energy efficiency. Nonetheless, one of the shortcomings of TIs is the leakage current that occurs between the photovoltaic (PV) string terminals and the ground. Such a drawback is justified by the non-galvanic isolation caused by the transformer being omitted. As such, this study is intended to develop a novel TI inverter topology for solar PV systems. The latter is meant to remove the leakage current and enhance the operating system of the entire PV conversion as well. Added to its null zero-crossing distortion and capability regarding energy efficiency, the developed TI, being validated by simulation and experiment, eradicated the leakage current. Keyword:Now a day’s renewable energy sources became an interesting area of research of which fuel cells are emerged as an alternative source for producing electricity to meet the energy crisis. This led to a research on power conditioning systems through which fuel cell is interfaced to the utility. Of the different converter topologies Isolated full bridge boost converter (IFBC) topology is most suitable for fuel cell applications. In this paper a Predictive Switching Modulator (PSM) Control is proposed for the converter topology and its performance is compared with Linear Peak Current Mode control (LPCM), Non-Linear Carrier Control (NLC).Received May 2, 2018 Revised Aug 23, 2018 Accepted Sep 14, 2018 Recently of the main topic of research is the sensorless vector control of induction motor drive, In this paper presents the predictive model reference adaptive system (PMRAS) rotor speed observer, This observer developed from the classical MRAS rotor flux scheme associated with predictive adaptation mechanism designed from the Finite Control Set Model Predictive Control (FCS–MPC) by using a search optimization algorithm for calculate the rotor position which guarantee a minimum speed tuning error signal at each sampling period. The effectiveness of the proposed observer proved with the simulation results, show high dynamic performance speed and position observed in sensorless vector control process at low and zero speed as well robustness against motor parameter variation with different loading conditions. Keyword:

Implications of drying temperature and humidity on the drying kinetics of seaweed

A Low Temperature and Humidity Chamber Test tested in the Solar Energy Laboratory, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Selangor, Malaysia. Experiments are attempted to study the effect of drying air temperature and humidity on the drying kinetics of seaweed Kappaphycus species Striatum besides to develop a model to estimate the drying curves. Simple method using a excel software is used in the analysis of raw data obtained from the drying experiment. The values of the parameters a, n and the constant k for the models are determined using a plot of curve drying models. Three different drying models are compared with experiment data seaweed drying at 30, 40, 50 and 60°C and relative humidity 20, 30 and 40% for seaweed. The higher drying temperatures and low relative humidity effects the moisture content that will be rapidly reduced. The most suitable model is selected to best describe the drying behavior of seaweed. The values of the coefficient of determination (R2), mean bias error (MBE) and root mean square error (RMSE) are used to determine the goodness or the quality of the fit. The Page model is showed a better fit to drying seaweed. The results from this study crucial for solar dryer development on pilot scale in Malaysia.