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Fuel cell hybrid electric vehicle sizing using ordinal optimization -

Show simple item record Dinnawi, Rafica Khaled, 2014 2015-02-03T10:35:03Z 2015-02-03T10:35:03Z 2014 2014
dc.identifier.other b18263021
dc.description Thesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2014. ET:6022
dc.description Advisor : Dr. Sami Karaki, Professor, Electrical and Computer Engineering ; Members of Committee: Dr. Riad Chedid, Professor, Electrical and Computer Engineering ; Dr. Rabih Jabr, Associate Professor, Electrical and Computer Engineering.
dc.description Includes bibliographical references (leaves 46-48)
dc.description.abstract This thesis will develop an optimal design methodology for fuel cell hybrid electric vehicle (FCHEV) based on ordinal optimization (OO) technique and dynamic programming; the optimal design aims to determine the appropriate sizes of the different units – hydrogen tank, fuel cell, and battery – for the purpose of minimizing the investment and operational cost given some specification of the car range, the road type and its gradeability. The dynamic programming simulates the operation of the vehicle for a set of specified sizes on given driving cycles and provides the total vehicle cost per year. The OO method offers an efficient approach for simulation optimization by focusing on ranking and selecting a finite set of good alternatives through two models: the simple model and the accurate model. The OO program sets the sizes of the components to sample the search space using the simple but fast model. In the simple model the operation of components is simplified by taking small samples of the mixed driving cycles with appropriate scaling for the energy utilized. Moreover, the number of discrete states used in the dynamic programming is made relatively low. The OO theory is then applied to determine the numbers of top-S of selected design solutions. The method that is used to determine the best good enough solutions of this selected set S is the blind pick. Then, the top-S designs are examined using an “accurate model”, which is implemented by taking the whole mixed driving cycles and an increased number of states in dynamic programming. Five different test runs were carried out based on different situations. First, three tests were conducted: one based on gradeability with the variation of the fuel cell and hydrogen costs, another without gradeability, and a third without separate gradeability but with 5percent slope on the HWFET driving cycle. Another test run was performed to study the effect of road range. The fifth test run used an OO selection method other than the blind pick. The results
dc.format.extent xii, 48 leaves : illustrations ; 30 cm
dc.language.iso eng
dc.relation.ispartof Theses, Dissertations, and Projects
dc.subject.classification ET:006022 AUBNO
dc.subject.lcsh Renewable energy sources.
dc.subject.lcsh Fuel cells.
dc.subject.lcsh Electric vehicles -- Power supply.
dc.subject.lcsh Hybrid electric vehicles.
dc.subject.lcsh Fuel cell vehicles.
dc.subject.lcsh Mathematical optimization.
dc.title Fuel cell hybrid electric vehicle sizing using ordinal optimization -
dc.type Thesis
dc.contributor.department American University of Beirut. Faculty of Engineering and Architecture. Department of Electrical and Computer Engineering, degree granting institution.

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