A line loss approximation via parametrization is developed to improve performance of the simplified Baran and Wu DistFlow method, while maintaining a linear set of equations. The approach is evaluated on thousands of training feeders that are created to determine a numerically optimal setting for the parameterization. Feeders are generated using recent advances in synthetic network test case generation. The problem is formulated with the same structure as the simplified DistFlow, yet is more accurate given that line losses are explicitly expressed and quantified. The single-phase methodology is extended to multiphase systems by formulating matrix-vector equations that maintain an analogy to their single-phase counterpart. Results with approximated line losses are shown to also improve the accuracy of multiphase distribution system calculations.

Dual active bridge (DAB) DC-DC converters are used widely in electric vehicle (EV) charging systems with the advantage of high-power density, bidirectional power flow, and possibility of soft-switching. The Maximum converter efficiency of DAB-based EV chargers happens at unity voltage gain, while it degrades at the start of the charging cycle where the gain is lower. This paper presents a novel gate signal modulation method called asymmetric half-frequency modulation (AHFM) that modifies the duty ratio and switching frequency of the source bridge switches to achieve the higher converter efficiency at low gain operation. Generalized harmonic approximation (GHA) method is utilized to analyze the circuit operation with applied AHFM, and evaluation of zero voltage switching (ZVS) requirements is explained. Then, a loss optimization problem is developed with an objective to select the optimal set of phase shift control variables depending on the modulation method to minimize the sum of conduction and switching losses. Five modulation methods based on conventional modulation and proposed AHFM are compared in terms of resultant switching network efficiency at a wide gain/power range that gives an understanding of optimal method at a specific operating point. The proposed AHFM and loss optimization are applied to the EV battery charging profile to improve the converter efficiency during the whole charging cycle. A 1.1 kW-rated proof-of-concept DAB DC-DC converter has been developed to validate the performance of the proposed method.