BIDIRECTIONAL AC-DC CONVERTERS USING ONE CYCLE CONTROL (OCC) FOR ELECTRIC VEHICLES

The electric vehicle (EV) market has seen a rapid growth in the recent past. With an increase in the number of electric vehicles on road, there is an increase in the number of high capacity battery banks interfacing the grid. The battery bank of an EV, besides being the fuel tank, is also a huge energy storage unit. Presently, it is used only when the vehicle is being driven and remains idle for rest of the time, rendering it underutilized. Whereas on the other hand, there is a need of large energy storage units in the grid to filter out the fluctuations of supply and demand during a day. EVs can help bridge this gap. The EV battery bank can be used to store the excess energy from the grid to vehicle (G2V) or supply stored energy from the vehicle to grid (V2G ), when required. To let power flow happen, in both directions, a bidirectional AC-DC converter is required. This thesis concentrates on the bidirectional AC-DC converters which have a control on power flow in all four quadrants for the application of EV battery interfacing with the grid. This thesis presents a bidirectional interleaved full bridge converter topology. This helps in increasing the power processing and current handling capability of the converter which makes it suitable for the purpose of EVs. Further, the benefit of using the interleaved topology is that it increases the power density of the converter. This ensures optimization of space usage with the same power handling capacity. The proposed interleaved converter consists of two full bridges. The corresponding gate pulses of each switch, in one cell, are phase shifted by 180 degrees from those of the other cell. The proposed converter control is based on the one-cycle controller. To meet the challenge of new requirements of reactive power handling capabilities for grid connected converters, posed by the utilities, the controller is modified to make it suitable to process the reactive power. A fictitious current derived from the grid voltage is introduced in the controller, which controls the converter performance. The current references are generated using the second order generalized integrators (SOGI) and phase locked loop (PLL). A digital implementation of the proposed control ii scheme is developed and implemented using DSP hardware. The simulated and experimental results, based on the converter topology and control technique discussed here, are presented to show the performance of the proposed theory.

Numerical Modelling of Eddy Current Probes for CANDU® Fuel Channel Inspection

Multi-frequency Eddy Current (EC) inspection with a transmit-receive probe (two horizontally offset coils) is used to monitor the Pressure Tube (PT) to Calandria Tube (CT) gap of CANDU® fuel channels. Accurate gap measurements are crucial to ensure fitness of service; however, variations in probe liftoff, PT electrical resistivity, and PT wall thickness can generate systematic measurement errors. Validated mathematical models of the EC probe are very useful for data interpretation, and may improve the gap measurement under inspection conditions where these parameters vary. As a first step, exact solutions for the electromagnetic response of a transmit-receive coil pair situated above two parallel plates separated by an air gap were developed. This model was validated against experimental data with flat-plate samples. Finite element method models revealed that this geometrical approximation could not accurately match experimental data with real tubes, so analytical solutions for the probe in a double-walled pipe (the CANDU® fuel channel geometry) were generated using the Second-Order Vector Potential (SOVP) formalism. All electromagnetic coupling coefficients arising from the probe, and the layered conductors were determined and substituted into Kirchhoff’s circuit equations for the calculation of the pickup coil signal. The flat-plate model was used as a basis for an Inverse Algorithm (IA) to simultaneously extract the relevant experimental parameters from EC data. The IA was validated over a large range of second layer plate resistivities (1.7 to 174 µΩ∙cm), plate wall thickness (~1 to 4.9 mm), probe liftoff (~2 mm to 8 mm), and plate-to plate gap (~0 mm to 13 mm). The IA achieved a relative error of less than 6% for the extracted FP resistivity and an accuracy of ±0.1 mm for the LO measurement. The IA was able to achieve a plate gap measurement with an accuracy of less than ±0.7 mm error over a ~2.4 mm to 7.5 mm probe liftoff and ±0.3 mm at nominal liftoff (2.42±0.05 mm), providing confidence in the general validity of the algorithm. This demonstrates the potential of using an analytical model to extract variable parameters that may affect the gap measurement accuracy.