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@article{143235,
        author = {Deepthy Thomas and Aparna Thampi},
        title = {Boost Half Bridge Converter with ANN Based MPPT},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {2},
        number = {8},
        pages = {15-19},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143235},
        abstract = {This paper deals with the design and implementation of the boost half-bridge photovoltaic (PV) system with ANN based MPPT. In order to achieve low cost, easy control and high efficiency, a boost-half-bridge dc-dc converter is introduced to interface the low-voltage PV module. An ANN based maximum power point tracking (MPPT) generates the PV voltage reference. ANN is adopted such that fast tracking speed and high MPPT efficiency are obtained. It also improves the robustness of the MPPT system against temperature and irradiance. The performance of the system will be investigated with MATLAB/Simulink .},
        keywords = {Artificial neural network (ANN) Boost half bridge converter (BHB),   Maximum power point tracking (MPPT), Photovoltaic (PV),},
        month = {},
        }