Critical Review of Key DC-DC Converters for Maximum Power Extraction in Solar-Powered Electric Vehicle Charging Stations

Sugunakar Mamidala, Pavan Kumar Y. V.

Abstract


Integrating solar photovoltaic (PV) systems into charging stations of electric vehicles (EVs) presents a viable option for improving energy efficiency and decreasing dependence on traditional grid sources. However, the effectiveness of the PV system rely on the selection of a suitable DC-DC converter along with the maximum power point tracking (MPPT) methodology. Generally, there are five key DC-DC converters (namely buck-boost, Cuk, SEPIC, zeta, and flyback converters) and two MPPT methods (namely perturb and observe (P&O) and incremental conductance (INC) methods) have been developed in the literature for different renewable energy applications in different scenarios. However, an effective combination of the converter and MPPT method for PV-based EV charging station application was not identified in the literature. Thus, this paper performs a critical review of all the key DC-DC converters and MPPT methods that are given above and identifies their best combination that optimally extracts maximum power from solar PV panels. For the performance comparison, various parameters namely solar power extraction, converter output voltage, and converter efficiency are computed under diverse test conditions including irradiance, temperature, and the electric vehicle’s battery state of charge (SOC). The system design has been carried out in MATLAB/Simulink software. The outcomes of this research work explore the flyback converter as superior to other converters when it is combined with P&O-based MPPT. Thus, this work provides valuable insights into the investigation of an efficient DC-DC for solar-powered electric vehicles, fostering advancements in renewable energy utilization for automotive applications.

Keywords


Charging station; DC-DC converters; Electric vehicles; EV battery; MPPT algorithm; PV system

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v16i1.15237.g9162

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