As electric vehicles (EVs) become more popular, the utility companies are forced to increase power generations in the grid. However, these EVs are capable of providing power to the grid to deliver different grid ancillary services in a concept known as vehicle-to-grid (V2G) and grid-to-vehicle (G2V), in which the EV can serve as a load or source at the same time. These services can provide more benefits when they are integrated with Photovoltaic (PV) generation. The proper modeling, design and control for the power conversion systems that provide the optimum integration among the EVs, PV generations and grid are investigated in this thesis.
The coupling between the PV generation and integration bus is accomplished through a unidirectional converter. Precise dynamic and small-signal models for the grid-connected PV power system are developed and utilized to predict the system’s performance during the different operating conditions. An advanced intelligent maximum power point tracker based on fuzzy logic control is developed and designed using a mix between the analytical model and genetic algorithm optimization.
The EV is connected to the integration bus through a bidirectional inductive wireless power transfer system (BIWPTS), which allows the EV to be charged and discharged wirelessly during the long-term parking, transient stops and movement. Accurate analytical and physics-based models for the BIWPTS are developed and utilized to forecast its performance, and novel practical limitations for the active and reactive power-flow during G2V and V2G operations are stated. A comparative and assessment analysis for the different compensation topologies in the symmetrical BIWPTS was performed based on analytical, simulation and experimental data. Also, a magnetic design optimization for the double-D power pad based on finite-element analysis is achieved. The nonlinearities in the BIWPTS due to the magnetic material and the high-frequency components are investigated rely on a physics-based co-simulation platform. Also, a novel two-layer predictive power-flow controller that manages the bidirectional power-flow between the EV and grid is developed, implemented and tested. In addition, the feasibility of deploying the quasi-dynamic wireless power transfer technology on the road to charge the EV during the transient stops at the traffic signals is proven.
| Identifer | oai:union.ndltd.org:fiu.edu/oai:digitalcommons.fiu.edu:etd-4605 |
| Date | 09 November 2017 |
| Creators | Mohamed, Ahmed A S, Mr |
| Publisher | FIU Digital Commons |
| Source Sets | Florida International University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | FIU Electronic Theses and Dissertations |
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