World's Most Advanced Supercapacitors
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19.3 Batteries
19. Components of PV Systems 305 Efficiency of power converters For planning a PV system it is very important to know the efficiency of the power convert- ers. This efficiency of DC-DC and DC-AC converters is defined as P η = o , (19.20) Po + Pd i.e. the fraction of the output power Po to the sum of Po with the dissipated power Pd. For estimating the efficiency we thus must estimate the dissipated (lost) power, which can be seen as a sum of several components, Pd = PL + Pswitch + Pother, (19.21) i.e. the power lost in the inductor PL, the power lost in the switch, and other losses. PL is given as 2 PL = IL, rms RL, (19.22) where IL, rms is the mean current flowing through the inductor. The losses in the switch strongly depend on the type of switch that is used. Other losses are for example resistive losses in the circuitry in-between the switches. For a complete inverter unit it is convenient to define the efficiency as PAC ηinv = , (19.23) PDC which is the ratio of the output AC power to the DC input power. Figure 19.18 shows the efficiency of a commercially available inverter for different input voltages. As we can see, in general the lower the output power, the less efficient the inverter. This is due to the power consumed by the inverter (self-consumption) and the power to control the vari- ous semiconductor devices which is relatively high at low output power. This efficiency characteristic must be taken into account when planning a PV system. -
Hierarchically Porous Carbon Materials and Limn2o 4 Electrodes for Electrochemical Supercapacitors
Graduate Theses, Dissertations, and Problem Reports 2015 Hierarchically Porous Carbon Materials and LiMn2O 4 Electrodes for Electrochemical Supercapacitors Shimeng Hao Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Hao, Shimeng, "Hierarchically Porous Carbon Materials and LiMn2O 4 Electrodes for Electrochemical Supercapacitors" (2015). Graduate Theses, Dissertations, and Problem Reports. 5760. https://researchrepository.wvu.edu/etd/5760 This Thesis is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact [email protected]. Hierarchically Porous Carbon Materials and LiMn2O4 Electrodes for Electrochemical Supercapacitors Shimeng Hao Thesis submitted to the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University in partial fulfillment of the requirements for the degree of Master of Science In Mechanical Engineering -
A Biomimetic, Energy-Harvesting, Obstacle-Avoiding, Path-Planning Algorithm for Uavs" (2016)
Dissertations and Theses 2016 A Biomimetic, Energy-Harvesting, Obstacle-Avoiding, Path- Planning Algorithm for UAVs Snorri Gudmundsson Follow this and additional works at: https://commons.erau.edu/edt Part of the Automotive Engineering Commons, and the Mechanical Engineering Commons Scholarly Commons Citation Gudmundsson, Snorri, "A Biomimetic, Energy-Harvesting, Obstacle-Avoiding, Path-Planning Algorithm for UAVs" (2016). Dissertations and Theses. 306. https://commons.erau.edu/edt/306 This Dissertation - Open Access is brought to you for free and open access by Scholarly Commons. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of Scholarly Commons. For more information, please contact [email protected]. A BIOMIMETIC, ENERGY-HARVESTING, OBSTACLE-AVOIDING, PATH-PLANNING ALGORITHM FOR UAVs A DISSERTATION SUBMITTED TO THE DEPARTMENT OF MECHANICAL ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF EMBRY-RIDDLE AERONAUTICAL UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Snorri Gudmundsson 2016 © Copyright by Snorri Gudmundsson, 2016 All Rights Reserved ii THIS PAGE INTENTIONALLY LEFT BLANK iv ABSTRACT This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. -
Battery/Supercapacitor Hybrid Via Non-Covalent Functionalization of Graphene Macro-Assemblies
Electronic Supplementary Material (ESI) for Journal of Materials Chemistry A. This journal is © The Royal Society of Chemistry 2014 Supporting Information For: Battery/Supercapacitor Hybrid via Non-Covalent Functionalization of Graphene Macro-Assemblies Patrick G. Campbell*, Matthew D. Merrill, Brandon C. Wood, Elizabeth Montalvo, Marcus A. Worsley, Theodore F. Baumann, Juergen Biener Contents: GMA synthesis details.......................................................................................................S2 Experimental details for Figure 4 (Ragone plot) ...............................................................S2 Theoretical calculation details ...........................................................................................S3 Figure S1............................................................................................................................S4 Figure S2............................................................................................................................S5 Figure S3............................................................................................................................S6 Figure S4............................................................................................................................S7 Figure S5............................................................................................................................S8 References..........................................................................................................................S9