Switching Time Optimization via Time Optimal Control for Natural Gas Vehicle Refueling

The implementation of Natural Gas Vehicle (NGV) refueling system using multipressure storage source requires a suitable controller to be developed. In this thesis, a refueling algorithm using Time Optimal Control (TOC) technique is proposed as a basis for determining the optimal switching time in NGV refueling using the mass and mass flowrate as the state variables, measured using Coriolis flowmeter. In order to implement TOC in actual NGV refueling process, a fully instrumented NGV laboratory test facility was designed and commissioned which includes three main parts: the NGV test rig, the Data Acquisition (DAQ) & Control System using FieldPoint, and the LabVIEW programming model. Performance measurements for experiments conducted at NGV test rig are based on two criteria, i. e., the refueling time and the total mass of natural gas stored. These become the performance measurements used to evaluate the performance of TOC and other NGV controller currently applied in the commercial NGV dispenser i. e., Kraus refueling algorithm. The performance of the refueling algorithms are evaluated based on three experiments: the first experiment is the performance of valves switching and refueling time transitions; the second experiment is the performance of refueling when the storage pressures are set to 3600 psig while the receiver tank is varied from 20 to 2000 psig; and the third experiment is the performance of refueling when the storage pressures are set to different pressures while the receiver tank is maintained at 20 psig. In conclusion, the results from the third experiment verifies the viability of TOC refueling compared to Kraus refueling to be used in NGV refueling using multi-pressure storage source, which average difference for refueling time and total mass loss are 25.33 seconds and 0.95 kg, respectively. By implementing the refueling algorithm in actual NGV refueling stations, it is expected to provide saving in term of the energy consumed by the compressor and contributing to the reduction in the NGV station congestion problem in the country

SYSTEM IDENTIFICATION AND PARAMETRIC ESTIMATION OF INFERENTIAL CORIOLIS

Metering technology offers a number of possible options for the measurement of compressible natural gas (CNG). However, the accuracy of these measurements is dependent on various dynamic factors and fluid parameters. To avoid flow measurement from such dynamic errors, a new technique or novel concept of flowmeter is needed for measuring CNG. One of the options is to use natural force phenomenon that could be derived from fundamental physics, a force known as coriolis. It is used in mass flowmeter design that uses vibration tubes to guide and measure fluid or gas based on coriolis force. The motivation behind the research is to develop and apply coriolis in an embedded FieldPoint controller proclaimed as an inferential coriolis. The major challenge is to find a suitable algorithm for coriolis in the form of a mathematical model that could measure mass and mass flowrate of CNG with maximum permissible error. To define such system, an experimental approach known as System Identification (SYSID) theory is used. Performance of inferential coriolis is tested on experimental natural gas test rig which could be summarized into three areas: single pressure flow; continuous pressure flow; multi pressure flow with disturbances. When experiment was conducted, mass flowrate was measured using inferential coriolis and a commercial flowmeter from a manufacturer i.e., Micro Motion. To validate both methods, a load cell was used as the reference. Details evaluations of three pressure flow scenarios namely the single pressure flow, the continuous pressure flow, and the multi pressure flow for a CNG refueling system are presented. From percentage error analyses, it shows that in all measurements the inferential coriolis have less error compares to commercial coriolis manufactured by Micro Motion. The findings demonstrate the viability of the SYSID approach to provide a solution to the modeling of an inferential coriolis, and confirm the qualitative behavior of the inferential coriolis in response to the different flow measurements

Switching Time Optimization via Time Optimal Control for Natural Gas Vehicle Refueling

The implementation of Natural Gas Vehicle (NGV) refueling system using multipressure storage source requires a suitable controller to be developed. In this thesis, a refueling algorithm using Time Optimal Control (TOC) technique is proposed as a basis for determining the optimal switching time in NGV refueling using the mass and mass flowrate as the state variables, measured using Coriolis flowmeter. In order to implement TOC in actual NGV refueling process, a fully instrumented NGV laboratory test facility was designed and commissioned which includes three main parts: the NGV test rig, the Data Acquisition (DAQ) & Control System using FieldPoint, and the LabVIEW programming model. Performance measurements for experiments conducted at NGV test rig are based on two criteria, i. e., the refueling time and the total mass of natural gas stored. These become the performance measurements used to evaluate the performance of TOC and other NGV controller currently applied in the commercial NGV dispenser i. e., Kraus refueling algorithm. The performance of the refueling algorithms are evaluated based on three experiments: the first experiment is the performance of valves switching and refueling time transitions; the second experiment is the performance of refueling when the storage pressures are set to 3600 psig while the receiver tank is varied from 20 to 2000 psig; and the third experiment is the performance of refueling when the storage pressures are set to different pressures while the receiver tank is maintained at 20 psig. In conclusion, the results from the third experiment verifies the viability of TOC refueling compared to Kraus refueling to be used in NGV refueling using multi-pressure storage source, which average difference for refueling time and total mass loss are 25.33 seconds and 0.95 kg, respectively. By implementing the refueling algorithm in actual NGV refueling stations, it is expected to provide saving in term of the energy consumed by the compressor and contributing to the reduction in the NGV station congestion problem in the country

SYSTEM IDENTIFICATION AND PARAMETRIC ESTIMATION OF INFERENTIAL CORIOLIS

Metering technology offers a number of possible options for the measurement of compressible natural gas (CNG). However, the accuracy of these measurements is dependent on various dynamic factors and fluid parameters. To avoid flow measurement from such dynamic errors, a new technique or novel concept of flowmeter is needed for measuring CNG. One of the options is to use natural force phenomenon that could be derived from fundamental physics, a force known as coriolis. It is used in mass flowmeter design that uses vibration tubes to guide and measure fluid or gas based on coriolis force. The motivation behind the research is to develop and apply coriolis in an embedded FieldPoint controller proclaimed as an inferential coriolis. The major challenge is to find a suitable algorithm for coriolis in the form of a mathematical model that could measure mass and mass flowrate of CNG with maximum permissible error. To define such system, an experimental approach known as System Identification (SYSID) theory is used. Performance of inferential coriolis is tested on experimental natural gas test rig which could be summarized into three areas: single pressure flow; continuous pressure flow; multi pressure flow with disturbances. When experiment was conducted, mass flowrate was measured using inferential coriolis and a commercial flowmeter from a manufacturer i.e., Micro Motion. To validate both methods, a load cell was used as the reference. Details evaluations of three pressure flow scenarios namely the single pressure flow, the continuous pressure flow, and the multi pressure flow for a CNG refueling system are presented. From percentage error analyses, it shows that in all measurements the inferential coriolis have less error compares to commercial coriolis manufactured by Micro Motion. The findings demonstrate the viability of the SYSID approach to provide a solution to the modeling of an inferential coriolis, and confirm the qualitative behavior of the inferential coriolis in response to the different flow measurements

Performance Evaluation of Nanofluids in an Inclined Ribbed Microchannel for Electronic Cooling Applications

Nanofluids are liquid/solid suspensions with higher thermal conductivity, compared to common working fluids. In recent years, the application of these fluids in electronic cooling systems seems prospective. In the present study, the laminar mixed convection heat transfer of different water–copper nanofluids through an inclined ribbed microchannel––as a common electronic cooling system in industry––was investigated numerically, using a finite volume method. The middle section of microchannel’s right wall was ribbed, and at a higher temperature compared to entrance fluid. The modeling was carried out for Reynolds number of 50, Richardson numbers from 0.1 to 10, inclination angles ranging from 0° to 90°, and nanoparticles’ volume fractions of 0.0–0.04. The influences of nanoparticle volume concentration, inclination angle, buoyancy and shear forces, and rib’s shape on the hydraulics and thermal behavior of nanofluid flow were studied. The results were portrayed in terms of pressure, temperature, coefficient of friction, and Nusselt number profiles as well as streamlines and isotherm contours. The model validation was found to be in excellent accords with experimental and numerical results from other previous studies

Mathematical Modeling for Nanofluids Simulation: A Review of the Latest Works

Exploiting nanofluids in thermal systems is growing day by day. Nanofluids having ultrafine solid particles promise new working fluids for application in energy devices. Many studies have been conducted on thermophysical properties as well as heat and fluid flow characteristics of nanofluids in various systems to discover their advantages compared to conventional working fluids. The main aim of this study is to present the latest developments and progress in the mathematical modeling of nanofluids flow. For this purpose, a comprehensive review of different nanofluid computational fluid dynamics (CFD) approaches is carried out. This study provides detailed information about the commonly used formulations as well as techniques for mathematical modeling of nanofluids. In addition, advantages and disadvantages of each method are rendered to find the most appropriate approach, which can give valid results

MHD natural convection nanofluid flow in a heat exchanger: effects of brownian motion and thermophoresis for nanoparticles distribution

The free convection of Cu-water nanofluid is simulated and investigated inside a square heat exchanger chamber in the presence of MHD magnetic field. The Buongiorno model with the effects of Brownian and thermophoresis motion is considered to nanoparticles distribution inside the chamber. The geometry consists of a square chamber with two cylinders on the right and left sides as heater and cooler in order to create the buoyancy force, respectively. These cylinders represent hot and cold pipes, and the walls of the chamber are heat and mass insulation. the FVM with SIMPLE algorithm are used for velocity and pressure coupling. In current two-phase simulation, the effects of Rayleigh number, Hartmann number, inclination angle of chamber and volume fraction on streamline contours, isothermal lines, Lorentz force lines, nanoparticle distribution and Nusselt number are investigated. By modeling the motion of nanoparticles and evaluating it, a nanoparticle transport zone was observed. The diffusion effects of thermophoresis were significant in this zone. The nanoparticles were thrown from the hot cylinder to the cold cylinder. The application of a magnetic field enlarged the nanoparticle transport zone. However, increasing the Rayleigh number and decreasing the inclination angle of the enclosure caused the nanoparticles to disperse evenly