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T-type primary bridge-based resonant converters employed in unfolding-based single-stage ac–dc conversion systems commonly adopt a leading-edge aligned modulation strategy, as it facilitates zero-voltage switching (ZVS) throughout the grid cycle. However, the application of this modulation strategy can result in partial ZVS of the common-source mosfets within the T-type bridge. In this letter, we investigate the underlying reasoning of such partial ZVS, quantify the severity of the problem, and propose a mitigation solution. Specifically, an optimized leading-edge aligned modulation strategy is introduced, incorporating an intentional staggered time delay for the turn-off of the common-source mosfets during the leading edge. The proposed modulation strategy is validated through hardware testing on a 20-kW unfolding-based ac–dc conversion system. 

Unfolder-based quasi-single-stage ac-dc power converter has been widely used for high-power electric vehicle (EV) charging systems for its high efficiency and power density. However, the resonance between the grid inductance (impedance) and the capacitors on the soft-dc-link of the converter impacts the system stability and significantly limits the system control bandwidth and dynamic response performance. A quasi-single-stage ac-dc converter with unfolder plus T-bridge series resonant converter (T-SRC) is studied in this work. The small-signal modeling and plant transfer function derivation of the T-SRC is presented in this paper. A damping filter design using the extra element theorem (EET) is then proposed to achieve high- bandwidth and stable operation of the quasi-single-stage ac-dc converter. Simulation and hardware results from an 18 kW module for high-power EV charging are provided to validate the proposed modeling and damping filter design. 

To optimize the utilization of a T-type bridge structure in resonant converters, one must thoroughly examine the soft-switching criteria specific to the T-type configuration. This work proposes an energy-based method to determine the softs-witching requirements of a T-type bridge during its various switching transitions. The study estimates the minimum required zero voltage switching (ZVS) current while considering the nonlinearity and voltage dependence associated with the output capacitance of MOSFETs. Moreover, this paper demonstrates that existing studies on ZVS analysis for T-type bridge-based resonant dc-dc converters, which rely only on capacitive energy considerations, significantly underestimate the necessary ZVS current values, with errors as high as 50%. Simulation and hardware results on a T-type primary bridge circuit validate the accuracy of the proposed minimum ZVS current calculation. Hardware tests are conducted on a T-type bridge in a 20 kW electric vehicle charger. 

This paper examines an application of a two-lane microscopic Traffic Flow (TF) simulation to comprehend the impact of the complex behavior of Dynamic Wireless Power Transfer (DWPT) charging systems onto electric power distribution grids. The proposed approach utilizes real-world data to determine a more accurate TF density at each time interval. The simulation is carried out considering all vehicles, whether electric vehicles (EVs) or non-electric, and they have a randomized lane changing behavior and fluctuating velocities following a leading car model. Three different scenarios are conducted for 5 mile, 10 mile, and 15 mile DWPT networks that are proportionally connected to an IEEE 33-bus distribution grid. Our findings indicate that EVs' average State-of-Charge (SOC) increases proportionally and significantly at each DWPT network length. Furthermore, the load demand generated from the DWPT network also increases proportionally with its length; and this increment in load demand causes adverse impacts on distribution grid voltage magnitudes exceeding operational standards that leads to equipment failure or blackout events. 

Due to environmental concerns, electric vehicles (EVs) have become increasingly popular in recent decades. While EV s offer several benefits, they also present challenges such as prolonged charging times and range anxiety. To address these issues and enhance EV market participation, dynamic wireless power transfer (DWPT) is gaining a great attention in electrified-transportation sector, leading to an emergence of DWPT for EVs. DWPT offers advantages like charging while in-motion. However, DWPT roadways also impose additional demands on the power system, potentially increasing operational costs. The main objective of this paper is to manage effectively the additional load caused by DWPT roadways, and this paper presents the utilization of distributed energy resources (DERs), such as photovoltaic (PV) systems and battery storage system (BSS), to minimize the system costs. The importance of our proposed load management strategy becomes even more critical during extreme events. Therefore, this paper further examines two scenarios, i.e., normal operations and under extreme conditions considering line outages, to compare the costs associated with DWPT systems. The efficiency of the proposed method is validated using IEEE 33-bus distribution systems through a mixed integer linear programming (MILP) optimization problem. Test results demonstrate that integrating DWPT system increases the system costs under both normal and extreme conditions, however, the DER-based mechanism is capable of mitigating these costs optimally. 

This paper presents a novel direct duty-to-current control strategy to mitigate the dc bias and eliminate the need for a dc blocking capacitor in Dual Active Bridge (DAB) converters. The proposed control mechanism directly controls the duty cycle of each leg in the primary H-bridge to regulate the average (over one switching period) volt-seconds applied to the transformer primary winding to be zero without a dc blocking capacitor, under both steady-state and transient operations. This strategy is particularly relevant for electric vehicle (EV) applications, where variations in power demand and charging protocols can introduce dc bias, and the proposed control strategy work seamlessly with the output voltage control loop, during both steady-state operation and transients. The analysis, presented in detail, includes simulation results validating the effectiveness of the proposed control strategy under various steady-state and transient conditions, demonstrating its robustness and applicability in EV systems. 

Large-scale in-motion inductive wireless charging infrastructure could be a key enabler for widespread adoption of electric vehicles (EVs) leading to net-zero carbon emissions for the transportation sector. However, the challenge of distributing power to the numerous transmitters in such large-scale systems has not been adequately investigated. This paper presents further development of a patented novel power distribution architecture that provides improved system efficiency, reliability, and cost in large-scale EV in-motion wireless charging systems. This paper provides details on operation and analysis of the proposed current-fed wireless charging transmitter. The proposed transmitter achieves load-independent transmitter coil current and high tolerance to mistuning. Simulation results from a 1 kW current-fed transmitter design validate the proposed design and analysis. 

Unfolding-based single-stage ac-dc converters offer benefits in terms of efficiency and power density due to the low-frequency operation of the Unfolder, resulting in negligible switching losses. However, the operation of the Unfolder results in time-varying dc voltages at the input of the subsequent dc-dc converter, complicating its soft-switching analysis. The complication is further enhanced due to the nonlinear nature of the output capacitance ( Coss ) of MOSFETs employed in the dc-dc converter. Furthermore, unlike two-stage topologies with a constant dc-link voltage, as seen in high-frequency grid-tied converters, grid voltage fluctuations also impact the dc input voltages of the dc-dc converter in unfolding-based systems. This work comprehensively analyzes the soft-switching phenomenon in the T-type primary bridge-based dc-dc converter used in unfolding-based topologies, considering all the aforementioned challenges. An energy-based methodology is proposed to determine the minimum zero-voltage switching (ZVS) current and ZVS time during various switching transitions of the T-type bridge. It is shown that the existing literature on the ZVS analysis of the T-type bridge-based resonant dc-dc converter, relying solely on capacitive energy considerations, substantially underestimates the required ZVS current values, with errors reaching up to 50%. The proposed analysis is verified through both simulation and hardware testing. The hardware testing is conducted on a 20-kW 3- ϕ unfolding-based ac-dc converter designed for high-power electric vehicle battery charging applications. The ZVS analysis is verified at various grid angles with the proposed analysis ensuring a complete ZVS operation of the ac-dc system throughout the grid cycle. 

As electric vehicles (EVs) become increasingly common in transportation infrastructures, the need to strengthen and diversify the EV charging systems becomes more necessary. Dynamic Wireless Power Transfer (DWPT) roadways allow EVs to be recharged while in-motion, thus allowing to improve the driving ranges and facilitating the widespread adoption of EVs. One major challenge to adopt large-scale DWPT networks is to efficiently and accurately develop load demand models to comprehend the complex behavior on power distribution grid due to difficulty in developing power electronic simulations for charging systems consisting of either numerous transmitter pads or high traffic volumes. This paper proposes a novel modified Toeplitz convolution method for efficient large-scale DWPT load demand modeling. The proposed method achieves more accurate modeling of DWPT systems from a few transmitter pads to tens of miles in real-world traffic scenarios with light computational load. Test results for a small-scale DWPT system are first generated to validate the accuracy of the proposed method before scaling to large-scale load demand modeling where real-world traffic flow data is utilized in DWPT networks ranging from 2–10 miles. A comparative analysis is further performed for the scenarios under consideration to demonstrate the efficiency and accuracy of the proposed method.