Digital geometric-sequence control technique for bidirectional dual active bridge DC-DC converters used in future electric vehicles

Bidirectional DC-DC converters are widely used in different applications such as energy storage systems, Electric Vehicles (EVs), UPS, etc. In particular, future EVs require bidirectional power flow in order to integrate energy storage units into smart grids. These bidirectional power converters provide Grid to Vehicle (V2G)/ Vehicle to Grid (G2V) power flow capability for future EVs. Generally, there are two control loops used for bidirectional DC-DC converters: The inner current loop and The outer loop. The control of DAB converters used in EVs are proved to be challenging due to the wide range of operating conditions and non-linear behavior of the converter. In this thesis, the precise mathematical model of the converter is derived and non-linear control schemes are proposed for the control system of bidirectional DC-DC converters based on the derived model. The proposed inner current control technique is developed based on a novel Geometric-Sequence Control (GSC) approach. The proposed control technique offers significantly improved performance as compared to one for conventional control approaches. The proposed technique utilizes a simple control algorithm which saves on the computational resources. Therefore, it has higher reliability, which is essential in this application. Although, the proposed control technique is based on the mathematical model of the converter, its robustness against parameter uncertainties is proven. Three different control modes for charging the traction batteries in EVs are investigated in this thesis: the voltage mode control, the current mode control, and the power mode control. The outer loop control is determined by each of the three control modes. The structure of the outer control loop provides the current reference for the inner current loop. Comprehensive computer simulations have been conducted in order to evaluate the performance of the proposed control methods. In addition, the proposed control have been verified on a 3.3 kW experimental prototype. Simulation and experimental results show the superior performance of the proposed control techniques over the conventional ones.

The Open Data Smart City: A Case Study of Smart City Progress through Open Data Initiatives

Smart cities, cities that are supported by an extensive digital infrastructure of sensors, databases and intelligent applications, have become a major area of academic, governmental and public interest. Simultaneously, there has been a growing interest in open data, the unrestricted use of organizational data for public viewing and use. Drawing on Science and Technology Studies (STS), Urban Studies and Political Economy, this thesis examines how digital processes, open data and the physical world can be combined in smart city development, through the qualitative interview-based case study of a Southern Ontario Municipality, Anytown. The thesis asks what are the challenges associated with smart city development and open data proliferation, is open data complimentary to smart urban development; and how is expertise constructed in these fields? The thesis concludes that smart city development in Anytown is a complex process, involving a variety of visions, programs and components. Although smart city and open data initiatives exist in Anytown, and some are even overlapping and complementary, smart city development is in its infancy. However, expert informants remained optimistic, faithful to a technologically sublime vision of what a smart city would bring. The thesis also questions the notion of expertise within the context of smart city and open data projects, concluding that assertions of expertise need to be treated with caution and scepticism when considering how knowledge is received, generated, interpreted and circulates, within organizations.