The electrification of passenger vehicles has been a step towards the reduction of greenhouse gas emissions by automobiles; however, in the United States many plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) must still be plugged in to a grid that is heavily reliant on the burning of fossil fuels to charge. The goal of this thesis is to investigate how to develop a system capable of fully charging a PHEV using only alternative and/or regenerative energy sources. In developing such a system, various alternative and regenerative energy sources were investigated with the intent of reaching a specified daily energy goal; sufficient to charge a PHEV. These energy sources were evaluated based upon criteria such as novelty, ability to reach desired daily energy goal, applicability to BEV/PHEV, etc. The primary technological categories considered include but are not limited to regenerative and solar technologies. The evaluation of technologies indicated that a major opportunity lies in solar technologies, and in particular concentrated photovoltaics. Design alternatives for a concentrated photovoltaic system capable of reaching the desired energy goal are described. The design alternatives utilize Fresnel lenses as a means of concentrating a large area of sunlight onto an array of photovoltaics affixed to a vehicle. Various tracking mechanisms for the concentrating systems have been outlined to meet given design criteria. 3-D ray tracing algorithms have been developed to determine the path of the tracking mechanisms depending upon the time of year and on the geographic location. The same algorithms have been used in conjunction with typical meteorological year data to determine the expected output of the concentrating systems based upon the solar resource and solar angles at a specific place and time. The findings suggest that a concentrated photovoltaic system designed specifically for charging an electrified vehicle may generate sufficient energy over the course of a day to power a typical driver’s trips. However, for such a concentrating system to be commercially feasible there are still many design challenges to be overcome. Design limitations and implications for further research are discussed.

<p>Photovoltaic (PV) cells have become an increasingly ubiquitous technology; however, concentrating photovoltaics (CPV), despite their higher theoretical efficiencies and lower costs, have seen much more limited adoption. Recent literature indicates that thermal management is a key challenge in CPV systems. If not addressed, it can negatively impact efficiency and reliability (lifetime). Traditional cooling methods for CPV use heat sinks, forced air convection or liquid cooling, which can induce an extremely large convection area, or parasite electric consumption. In addition, the moving parts in cooling system usually result in a shorter life time and higher expense for maintenance. Therefore, there is a need for an improved cooling technology that enables significant improvement in CPV systems. As a passive and compact cooling mechanism, radiative cooling utilizes the transparency window of the atmosphere in the long wavelength infrared. It enables direct heat exchange between objects on earth’s surface with outer space. Since radiated power is proportional to the difference of the fourth powers of the temperatures of PV and ambient, significantly greater cooling powers can be realized at high temperatures, compared with convection and conduction. These qualities make radiative cooling a promising method for thermal management of CPV. In this work, experiments show that a temperature drop of 36 degree C have been achieved by radiative cooling, which results in an increase of 0.8 V for open-circuit voltage of GaSb solar cell. The corresponding simulations also reveal the physics behind radiative cooling and give a thorough analysis of the cooling performance.</p>

Global economic trends suggest that there is a need to generate sustainable renewable energy to meet growing global energy demands. Solar energy harnessed by concentrated photovoltaic (CPV) systems has a potential for strong contributions to future energy supplies. However, as a relatively new technology, there is still a need for considerable research into the relationship between the technology and the solar resource. Research into CPV systems was carried out at the University of Ottawa’s Solar Cells and Nanostructured Device Laboratory (SUNLAB), focusing on the acquisition and assessment of meteorological and local solar resource datasets as inputs to more complex system (cell) models for energy yield assessment. An algorithm aimed at estimating the spectral profile of direct normal irradiance (DNI) was created. The algorithm was designed to use easily sourced low resolution meteorological datasets, temporal band pass filter measurement and an atmospheric radiative transfer model to determine a location specific solar spectrum. Its core design involved the use of an optical depth parameterization algorithm based on a published objective regression algorithm. Initial results showed a spectral agreement that corresponds to 0.56% photo-current difference in a modeled CPV cell when compared to measured spectrum. The common procedures and datasets used for long term CPV energy yield assessment was investigated. The aim was to quantitatively de-convolute various factors, especially meteorological factors responsible for error bias in CPV energy yield evaluation. Over the time period from June 2011 to August 2012, the analysis found that neglecting spectral variations resulted in a ~2% overestimation of energy yields. It was shown that clouds have the dominant impact on CPV energy yields, at the 60% level.

Global economic trends suggest that there is a need to generate sustainable renewable energy to meet growing global energy demands. Solar energy harnessed by concentrated photovoltaic (CPV) systems has a potential for strong contributions to future energy supplies. However, as a relatively new technology, there is still a need for considerable research into the relationship between the technology and the solar resource. Research into CPV systems was carried out at the University of Ottawa’s Solar Cells and Nanostructured Device Laboratory (SUNLAB), focusing on the acquisition and assessment of meteorological and local solar resource datasets as inputs to more complex system (cell) models for energy yield assessment. An algorithm aimed at estimating the spectral profile of direct normal irradiance (DNI) was created. The algorithm was designed to use easily sourced low resolution meteorological datasets, temporal band pass filter measurement and an atmospheric radiative transfer model to determine a location specific solar spectrum. Its core design involved the use of an optical depth parameterization algorithm based on a published objective regression algorithm. Initial results showed a spectral agreement that corresponds to 0.56% photo-current difference in a modeled CPV cell when compared to measured spectrum. The common procedures and datasets used for long term CPV energy yield assessment was investigated. The aim was to quantitatively de-convolute various factors, especially meteorological factors responsible for error bias in CPV energy yield evaluation. Over the time period from June 2011 to August 2012, the analysis found that neglecting spectral variations resulted in a ~2% overestimation of energy yields. It was shown that clouds have the dominant impact on CPV energy yields, at the 60% level.

This work investigates the Fresnel-lens-based solar concentrator-receiver system in a multi-perspective manner to design, test and fabricate this concentrator with high-efficiency photon and heat outputs and a minimized effect of chromatic aberrations. First, a MATLAB®-incorporated algorithm optimizes both the flat-spot and the curved lens designs via a statistical ray-tracing methodology of the incident light, considering all of its incidence parameters. The target is to maximize the solar ray intensity on the receiver's aperture, and therefore, achieve the highest possible focal flux. The algorithm outputs prismatic and dimensional geometries of the Fresnel-lens concentrator, which are simulated by COMSOL® Multiphysics to validate the design. For the second part, a novel genetically-themed hierarchical algorithm (GTHA) has been investigated to design Fresnel-lens solar concentrators that match with the distinct energy input and spatial geometry of various thermal applications. Basic heat transfer analysis of each application decides its solar energy requirement. The GTHA incorporated in MATLAB® optimizes the concentrator characteristics to secure this energy demand, balancing a minimized geometry and a maximized efficiency. Two experimental applications were selected from literature to validate the optimization process, a solar welding system for H13 steel plates and a solar Stirling engine with an aluminum-cavity receiver attached to the heater section. In each case, a flat Fresnel-lens with a spot focus was algorithmically designed to supply the desired solar heat, and then a computer simulation of the optimized lens was conducted showing great comparability to the original experimental results. Thirdly, the prismatic geometry of the Fresnel lens was further optimized through a statistical approach that incorporates laws of light refraction and trigonometry. The proposed design produces high focal irradiance that is more suitable for thermal applications. The motivation was to enhance the tolerability of a flat Fresnel-lens concentrator to tracking errors, without the use of secondary optics or sophisticated, and normally costly, meticulous tracking equipment. A comparative simulation analysis was conducted for two case studies from literature, each with a different design method. Fresnel lenses optimized by this work enhanced the concentration acceptance product (CAP) significantly, compared to that in literature. Then, this work introduced an innovative code-based, detailed, and deterministic geometrical approach, which couples the optimization of the Fresnel lens primary optical element (POE) and the dome-shaped secondary optical element (SOE). The objective was to maximize the concentration acceptance product, while using the minimum SOE and receiver geometries at a given f-number and incidence angle (also referred to as the tracking error angle). The laws of polychromatic light refraction along with trigonometry and spherical geometry were utilized to optimize the POE grooves, SOE radius, receiver size, and SOE–receiver spacing. Two literature case studies were analyzed to verify this work's optimization, and the equivalent POEs designed by this work, with optimized SOEs, showed a significant enhancement in the CAP values compared to that of literature. Lastly, four methods for prototyping the Fresnel lens were discussed and experimentally tested; 3D printing, acrylic resin casting, direct CNC machining in acrylic and hot embossing. Once tested, the methods of CNC machining and hot embossing of acrylic proved to be the most promising in terms of cost, fabrication time, and concentration effectiveness. Future work will focus on enhancing the algorithmic design and improving the quality of lens fabrication.