Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/6583
Title: Design and Development of Solar Powered EV Charging Station
Authors: Pattnaik, Manasi
Supervisor: Badoni, Manoj
Tatte, Yogesh
Keywords: Electric Vehicle;SOC;Solar PV;Adaptive control
Issue Date: 6-Sep-2023
Abstract: In this research work, the design and development of solar-powered electric vehicle (EV) charging station is presented. It aims to develop a grid-integrated solar-PV system to provide an uninterruptable power supply to charge EV batteries and surplus power can be fed into the grid and local load. The motivation of the work is to maximum utilization of renewable energy sources (RESs) for EV charging, and household load demands to reduce the carbon footprints. A single-phase grid-integrated solar PV system is considered for the study, which can be useful for home/office/building EV charging station. The work started with designing of single-phase grid-integrated solar PV system for real power transfer along with power quality enhancement. Different control techniques are developed to enhance performance of the system in terms of dynamic response, complexity and harmonic compensation capability. Thereafter, the system is modified to develop EV charging station, which can be fed with PV and Grid. The system is controlled in such a manner to maximize the utilization of PV for EV charging based on availability. An efficient energy management system is developed for optimal utilization of resources and to achieve various modes of operation. Eventually, some work is presented on accurate estimation of the state of charge (SOC) of EV battery used in the developed system. The proposed system is simulated in MATLAB/Simulink and validated using a developed hardware setup in the laboratory. In the begning a single-phase grid-integrated solar photovoltaic (GISPV) system is developed using a projected Kernel least mean p-power (PKLMP) control technique for gating pulse generation. This technique is based on the vector projection (VP) method with a criterion of mean p-power error (MPE). The proposed controller extracts fundamental current components from nonlinear load current at different conditions and generates reference grid currents. It offers superior filtering accuracy and a faster convergence rate. The system using PKLMP control technique can feed load power demand and improve power quality, like power factor correction, harmonic elimination, and dynamic behavior under load disconnection and reconnection. The grid side is connected with PV array through a double-stage power conversion system. The first stage consists of a DC-DC boost converter with maximum power point tracking (MPPT) control technique to control the duty ratio of DC-DC boost converter. The second stage consists of a voltage source converter (VS) to convert the DC from the PV array into the AC. A DC-link capacitor is used to decouple the DC-DC converter stage to DC-AC inverter stage. Afterwards, an adaptive VSC controller is developed for an efficient PV-based residential EV charging purposes. The design of the proposed control technique is implemented to control the solar-based home charging station with power quality improvement features, such as real power transfer, power factor correction and harmonic suppression, which follows the limitation specified in the IEEE-519. To connect EV battery with DC-link capacitor DC-DC bidirectional buck-boost converter is used. It analyses the charge-discharge operation of the battery. In this work, an improved third-order sinusoidal signal integrator (TOSSI) based character of triangular function (CTF) controller is proposed, for the control of grid side converter. The TOSSI-based CTF is used, to extract fundamental active components by eliminating harmonic distortions from the load currents. This control structure has the unique capability of active current separation technique with the help of simple mathematical operations. Moreover, the response is refined with the help of optimized gains parameters This work also aims to develop an energy management system, which is designed so that the EV is charged efficiently either by the solar PV or distribution grid. The converter in the proposed system has a stable closed-loop controller capable of executing 4-mode of power flows viz. PV to EV, PV to Grid, Grid to EV, EV to Grid. The vehicle-to-grid (V2G) technology effectively turns EV batteries into an energy storage resource. Besides converters control and operation in PV-based EV charging, it is also imperative to analyze the state of charge (SOC) of EV battery for its best and most efficient use. Therefore, in this work, the accurate estimation of battery SOC is proposed using the Gaussian-sequential-probabilistic-inference concept (GSPIC) based Kalman filter (KF). It represents battery characteristics of its state of charge, voltage, and current response according to load demand. A real-time experimental parametric analysis of 48V and 40Ah battery to monitor and observe a graphical representation of results for different functionalities, like performance characteristics of its SOC, voltage and current response is presented in this work. The proposed system is simulated in MATLAB/Simulink and validated using a developed hardware setup in the laboratory.
URI: http://hdl.handle.net/10266/6583
Appears in Collections:Doctoral Theses@EIED

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