In this paper, improved control strategies of a smart topology of EVs charging station (CS) based on grid tied PV/Battery system are designed and analyzed. The proposed strategies consist of three operating modes i.e. Pv2B; charging a battery storage buffer (BSB) of the CS from solar energy, V2G; discharging an EV battery via grid, and Pv2G; injecting the produced power from PV system into the energy distribution system. However, the BSB is connected to the PV system through a single ended primary inductor converter, the V2G operating mode is emulated by an EV lithium-ion battery tied to the grid via a high frequency full bridge inverter and a bidirectional dc/dc converter. The aim of this work is to improve the energy efficiency of the CS by using a hybrid energy system. Simulation studies are performed in Matlab/Simulink in order to operate the proposed solar CS with multiple control strategies of each case scenario based on a CS management algorithm (CSMA). To provide credible findings of this research, a low power prototype is developed in order to validate the proposed CSMA and its associated controls.

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This paper proposes optimal control strategies of a standalone Hybrid Power System (HPS) to supply sustainable and optimal energy to an isolated site with improved quality of electrical energy. A topology of Isolated Hybrid Power System (IHPS) is proposed, consists of: a Photovoltaic System (PVS), a Wind Energy Conversion System (WECS), electronic power devices controlled to maximize energy production from renewable sources and to maintain the constant DC-link voltage, a Battery Energy Storage System (BESS), Diesel Generator (DG), and a Pulse Width Modulation (PWM) Voltage Source Inverter (VSI) located at the load-side end. In addition, a novel control strategy has been proposed, in this work, to maximize the power from the PVS. This presented strategy, based on the combination between Perturb and Observe (P&O) algorithm and the Fuzzy PI Controller (FPIC), presents a good performance, especially in the dynamic state compared to the classical algorithm P&O. A supervisory control algorithm has been elaborated to manage the energy flows between the devices of the hybrid system to make the decision of the optimal operating mode in order to ensure a continuous supply of the load with minimum usage of batteries and DG. The simulation results developed in the Matlab/Simulink environment are applied to show the efficiency and performance of the proposed control strategies in terms of power optimization and energy management. Doi: 10.28991/esj-2021-01262 Full Text: PDF

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In this paper, an implementation of a DC/DC buck converter for electric vehicles charging station and a DSP based closed-loop digital controller design are presented and analyzed. The aim of this work is to achieve an improved control strategy for a Li-ion battery charger implemented on a Real-time test platform. The test platform consists of a popular power pole board (MPCA75136) dedicated to studying the DC/DC converters, and a DSP development kit (TMS320F28379D) that is used to drive the DC/DC buck converter. The control strategy is based on a digital control system containing the closed-loop current controller followed by a pulse width modulation block, and on a real time state of charge estimation technique for a Li-ion battery. However, the overall control design is modeled on Simulink via block diagrams, and automatically generated code that is targeted into the DSP processor. Simulation and experimental results have shown the effectiveness of the proposed test bench and its external digital control strategy via a charging scenario for electric vehicles batteries.

The current paper aims at presenting and examining an implementation on a digital signal processor (DSP) of the conventional space vector pulse width modulation (CSVPWM) so as to control the dual three phase permanent magnet synchronous motors (DTP-PMSM) drives applied on electric ship propulsion. It is also an attempt to accomplish a developed control of this technique based on vector space decomposition (VSD) strategy. By this strategy, the analysis and the control of the machine are achieved in three two-dimensional orthogonal subspaces. Among the 12 voltage vectors having maximum, the conventional technique namely the adjacent two-vectors (12SA2V) is chosen. Thereby, the test platform allows the implementation of the chosen vectors which are modeled on MATLAB/Simulink using block diagrams and the automatically generated code which is targeted in the DSP card processor. Simulation and experimental results have exposed the efficiency of the proposed test bench of 5 KW prototype machine by using a low-cost TMS32F28379D.

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