This article presents a novel active compensation-based harmonic reduction (ACHR) technique in order to mitigate the existing third harmonic component in the input current of the power factor corrector (PFC) circuit in electric vehicle (EV) charging systems. Traditional PFC control scheme includes an outer voltage loop to control the output dc voltage and an inner current loop to ensure that the grid current is sinusoidal. The work shows how third and other high-order harmonic components are created, while the signal is transmitting through the voltage control loop, and then, an analytical model is developed to calculate the dominant third harmonic magnitude according to the circuit specifications and control parameters. The ACHR approach takes advantage of multilevel filter design to prevent the presence of high-order odd harmonics in addition to mitigating the existing third harmonic component created by the voltage control loop before it is passed through the current control loop. ACHR is designed optimally, and its performance is analyzed in detail to have a robust and stable closed-loop system while keeping the characteristics of fundamental harmonic. A totem-pole boost PFC proof-of-concept is built to verify the proposed ACHR technique. The results show that the third harmonic magnitude is reduced from 244 mA in conventional control scheme to 130 mA in the proposed ACHR technique. Moreover, total harmonic distortion (THD) in input current is decreased from 4.88% to 4.03%.

Bidirectional onboard chargers introduce electric vehicles (EVs) as flexible actors in the power grids that can operate in grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes. Despite the benefits of the bidirectional EVs in the event of grid contingencies, they may have adverse impacts on the normal operation of the power systems. This article investigates the impacts of bidirectional EVs on power quality, voltage profile, and frequency stability of the power grid. For this purpose, a detailed model of practical bidirectional onboard charger is presented to measure the total harmonic distortion (THD) in the grid current caused by the EVs. The proposed study accounts for various EV power levels, grid voltage levels, and EV modes of operation. Furthermore, an optimal frequency support strategy is developed that takes advantage of available EVs in V2G mode to improve the frequency stability of the grid in the event of frequency fluctuations. The effects of bidirectional EVs on the voltage profile is also explored by implementing current summation method (CSM)-derived power flow analysis for IEEE 33-Bus radial distribution system. The results show that with an optimal planning of EVs, it is possible to improve voltage profile and frequency stability of the grid while the power quality of the grid is maintained in the allowed range according to the IEEE 519-2014 standard.

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.

Electric vehicle (EV) charging station (CS) congestion is highly dependent on the EV owner’s behavior and their selected CS as charging choice. A fixed pricing strategy causes some CSs to be congested with EVs waiting in line to charge, while there are some other CSs with available electric plugs, which adversely affects both charging station operator (CSO) revenue and EV users’ welfare. To solve this problem, this paper presents a dynamic pricing strategy aimed at conducting EVs from congested CSs to the uncongested ones through controlling the charging prices of CSs at different times. The problem is formulated as a scenario-based stochastic optimization with the objective of maximizing overall revenue of the CSO. Moreover, an attraction function model is developed to quantify the charging choice of the EV owners by considering the effective parameters of CSs in EV charging choice decisions. QGIS software is used in this work to formulate a realistic modeling for CS locations and EV routes to calculate the distances from EVs to CSs. Three scenarios are designed to evaluate the performance of the proposed framework and to compare the results with the fixed pricing approach. The results indicate that the proposed dynamic pricing strategy mitigates the congestion of CSs while facilitating an increased number of charged EVs up to 48% as well as increasing the overall revenue of the CSO.