No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

<p> This thesis focuses on the static optimization of a fuel cell plug-in hybrid electric vehicle. The vehicle is been powered by three (3) sources of electrical energy. These sources of electrical energy are: fuel cell, supercapacitor, and lithium-ion battery. </p><p> The main target of this thesis is to make good the performance of a fuel cell plug-in hybrid electric vehicle. This will be achieved by applying static optimization method on the dynamic equations of a moving hybrid vehicle. </p><p> The optimization model of this plug-in hybrid electric vehicle (PHEV) was formulated bases on multiple objectives. The objective parameters are: cost, volume, and mass. We were able to apply static optimization algorithm to find optimal solutions for both the objective values and decision variables of the multiple energy sources. </p><p> The optimization model formulated from the dynamic equations, objective specifications, and design constrains were found to be feasible, bounded, and optimizable by subjecting the primal optimization model to its equivalent dual optimization test. </p><p> Advanced vehicle simulator (ADVISOR) was used to stimulate vehicle performance of our design on a standard driving cycle. The results provide a better outcome than that of standard driving cycles.</p><p>

<p> This research presents cyber-physical systems (CPS) modeling of the smart charging process to both identify and analyze potential vulnerabilities that may exist during the interaction and integration between an Electric Vehicle (EV) and the Electric Vehicle Service Equipment (EVSE). As EVSEs are increasingly being integrated into building energy management systems and interfaced with electric vehicles, safe and secure integration of these systems is of paramount importance for the safety and security of the nation's critical infrastructure and people. Both the charging station and electric vehicles have electro-mechanical components built from 3rd party providers, and there is no mechanism to check for safe and secure integration of EVs and EVSEs. The overall goal of the proposed research is to apply formal methods to verify and validate the cyber-physical interactions between the EV and EVSE to gain insight into vulnerable system states and their impacts. To that end, each component (EV and EVSE) was considered its own cyber-physical system and then separately broken down into individual states of operation. The states of each system were compared to determine how the EV and EVSE interacted on a fundamental level, with one system's state becoming the catalyst for change within the other system. These individual models were completed and subsequently integrated using the open-source software Ptolemy II. Upon successfully completing the interactions, the model was scrutinized using linear temporal logic (LTL) operators to test its veracity and projectability. The initial EV/EVSE model was then altered to emphasize previously determined vulnerabilities within the integrated system in order to verify their existence and potential for harming the system. Two such vulnerabilities were demonstrated in this research to confirm integrity of the model, which will be a valuable asset going forward to ensure the future safety of both operators and consumers regarding EV and EVSE interaction.</p><p>