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A multi-objective design procedure is applied to the design of a close-coupled inductor for a three-phase interleaved 140kW DC-DC converter. For the multi-objective optimization, a genetic algorithm is used in combination with a detailed physical model of the inductive component. From the solution of the optimization, important conclusions about the advantages and disadvantages of using close-coupled inductors compared to separate inductors can be drawn.

The growing number of distributed energy resources, DC loads and energy storage systems drive the adoption of DC distribution networks. This paper in particular addresses three-wire bipolar DC distribution networks (b-DCDN), that provide two voltage levels to connect low-and high-power loads, while transferring twice the amount of power with less conduction losses as compared to the two-wire unipolar network configuration. To stabilize and control these two voltage levels, converters with voltage balancing capability are essential. Although dedicated voltage balancing converters that transfer power between both poles exist, this paper shows the extent to which certain three-level DC-DC converters can both interface DC devices such as battery energy storage systems and balance the pole-toneutral voltages in the presence of unbalanced currents. More in particular, this paper identifies and analyzes the members of the non-isolated three-level converter family that feature a bipolar DC front-end in different unbalanced conditions, thereby explicitly deriving the operating area of these converters, based upon a decomposition in balanced and unbalanced components. Furthermore, the paper demonstrates the influence of the modulation scheme in unbalanced conditions on the current ripple and required inductance.

A method for solving the full equations of Maxwell for circuits with discrete non-linear, non-ideal elements is presented. To this end the method of moments is used in combination with a classical circuit simulator. Both operate in the frequency domain. A few methods to greatly accelerate the calculations are also presented. The methods are implemented and tested in Matlab®.

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