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The demand for renewable energy-based Electric Vehicle (EV) charging infrastructure is increasing in recent years. Solar PV based EV charging method is preferred as it has simple energy harvesting technique. The PV system is an uncertain power source, where the power generation is varied with respect to the availability of sunlight. So, that the charging station requires a backup power supply for the uninterrupted charging. For the integrated power sources, the charging station requires a simple and efficient conversion unit for the DC/AC/DC conversion. In this work, a modified Z-source inverter (MZSI) is developed for the multiport EV charger using PV and grid. The proposed MZSI is connected between the input and output sides to boost the voltage as per the demand at the battery side. In order to connect many battery units with the charger, the capacitors used in the MZSI are split as per the required number of charging ports. This developed converter topology operates the systems in four different modes like PV-Grid, PV-battery, grid-battery, and battery-grid. The performance of this proposed work has been validated in MATLAB/Simulink® and in the experimental setup. The experimental setup has been developed with two charging ports for obtaining 250W at each charger end which cumulatively produces 500W output across both chargers with an efficiency of 90.18%. [ABSTRACT FROM AUTHOR]

The Electric Vehicle (EV) landscape has witnessed unprecedented growth in recent years. The integration of EVs into the grid has increased the demand for power while maintaining the grid's balance and efficiency. Demand Side Management (DSM) plays a pivotal role in this system, ensuring that the grid can accommodate the additional load demand without compromising stability or necessitating costly infrastructure upgrades. In this work, a DSM algorithm has been developed with appropriate objective functions and necessary constraints, including the EV load, distributed generation from Solar Photo Voltaic (PV), and Battery Energy Storage Systems. The objective functions are constructed using various optimization strategies, such as the Bat Optimization Algorithm (BOA), African Vulture Optimization (AVOA), Cuckoo Search Algorithm, Chaotic Harris Hawk Optimization (CHHO), Chaotic-based Interactive Autodidact School (CIAS) algorithm, and Slime Mould Algorithm (SMA). This algorithm-based DSM method is simulated using MATLAB/Simulink in different cases and loads, such as residential and Information Technology (IT) sector loads. The results show that the peak load has been reduced from 4.5 MW to 2.6 MW, and the minimum load has been raised from 0.5 MW to 1.2 MW, successfully reducing the gap between peak and low points. Additionally, the performance of each algorithm was compared in terms of the difference between peak and valley points, computation time, and convergence rate to achieve the best fitness value. [ABSTRACT FROM AUTHOR]

To reduce the burden of electric vehicle (EV) charging power requirements, photovoltaic (PV) infrastructure EV charging has grown in recent years. The Z-Source Inverter (ZSI) allows tapping the boosted DC and AC by adjusting the switching shoot-through. However, it has only one DC tapping, thus limiting multiport charging options. This can be overcome by splitting the boosting capacitors used at the load terminal, which supports multiple charging ports, enabling simultaneous charging of multiple EVs, thereby increasing capacity and improving overall system efficiency. This paper presents a novel PV-tied Adaptable Z-Source Inverter (AZSI) for multiport EV charging. The modified split capacitor Z-source impedance networks ensure power availability at the charging station by regulating PV generation and grid supply. The performance of the AZSI was evaluated with experimentations that achieved an efficiency of 93.8% with three charging ports. This work contributes to developing sustainable and efficient charging infrastructure to meet the growing demands of the electric vehicle market. [ABSTRACT FROM AUTHOR]

The demand for electric vehicles (EVs) has increased dramatically in recent years, making it increasingly challenging to keep up with the demand for charging infrastructure. However, conventional power converters (DC–DC converters) have drawbacks such as a high component count, low voltage gain, low efficiency, and high cost. A new DC–DC multiport converter has been proposed to address these challenges by hybridizing a Super-lift Luo and Boost Converter (SLBC) with Photovoltaic (PV) and battery sources as dual inputs. The proposed Dual-Input Dual-Output (DIDO) converter offers significant advantages by super-lifting the input voltage while producing two step-up voltages, one by the Luo converter and another by the Boost converter. The SLBC uses simple structures without any additional electric circuits or transformers to generate high voltage gain and high power efficiency. To evaluate the performance of the proposed SLBC, the converter operation has been analyzed under steady-state and Continuous Current Mode conditions, and a comparison with other similar configurations has been conducted to demonstrate its benefits. Simulation and experimental results have shown that the proposed SLBC offers a considerable reduction in conduction losses compared to other SLBC converters in similar situations. Furthermore, the SLBC system provides 1.2 kW output at the charger side with 94.8% efficiency, making it a viable option for powering various EV components, including the charger, motor, lighting, and audio system, with variable voltages. [ABSTRACT FROM AUTHOR]

To reduce the pollution to a large extent in the transportation sector, it is important to charge the Electrical Vehicles (EV) from sustainable sources of electricity, such as solar or wind energy. Building integrated photovoltaic (BIPV) systems have gained popularity over the past 10 years and have been demonstrated to be a practical method of generating renewable energy that can be used to partially power buildings. One of the emerging technologies in EV charging systems is wireless charging technology; we realize that using this technology, fully automatic charging is simple. Compared to a plug-in charging system, wireless charging is free from rust, rain, and other environmental impacts like vandalization and visual pollution. By integrating wireless EV charging with BIPV shading systems, it offers a green and cutting-edge charging option. Building integrated solar panels are affected by different scenarios and causes due to their positioning. The direction of the solar panel, tilted position, and reflected irradiation, these all factors are to be considered in design of BIPV system. In this article, a system designed in way to analyze the effect of white and black color reflectors effect on solar panels (shading system) in different directions. In this work, a 256-W wireless charging system developed for E-bikes utilizing BIPV system. The proposed BIPV-fed resonant inductive charging system achieved efficiency of 95% for simulation and 91.6 for experimental analysis. The experimental analysis is verified by simulation and experimental results. [ABSTRACT FROM AUTHOR]

The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate user's "range anxiety". The existing charging stations fail to adopt power provision, allocation and scheduling management. To improve the existing charging infrastructure, data based on real-time information and availability of reserves at charging stations could be uploaded to the users to help them locate the nearest charging station for an EV. This research article focuses on an a interactive user application developed through SQL and PHP platform to allocate the charging slots based on estimated battery parameters, which uses data communication with charging stations to receive the slot availability information. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on the road due to battery drain out. The proposed model is implemented using a low-cost microcontroller and the system etiquette tested. [ABSTRACT FROM AUTHOR]