Faculty Publications

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Author: search.filters.author.Goud, J.S.Subject: search.filters.subject.Charging (batteries)

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    A Global Maximum Power Point Tracking Technique of Partially Shaded Photovoltaic Systems for Constant Voltage Applications
    (Institute of Electrical and Electronics Engineers Inc., 2019) Goud, J.S.; Kalpana, R.; Singh, B.; Kumar, S.
    The P-V characteristics of photovoltaic (PV) array exhibit several maximum power points (MPP) during non-uniform insolation (i.e., during partial shading) conditions; there exists only one global MPP (GMPP), whereas others are referred to local MPP. This paper presents a technique to track the GMPP for the constant voltage or battery loads during partial shading conditions using a single sensor connected to the battery terminals. The proposed method introduces fast and efficient scanning based method, i.e., scanning Ibatt-D curve of power electronic interface at selective duty cycles to recognize the kind of the solar shading pattern (i.e., kind of P-V curve) on PV array and to find the GMPP neighborhood. Moreover, the proposed method overcomes the drawbacks of existing methods such as low convergence speed, increased number of sensors, and heavy computational complexity. The proposed GMPPT method is simulated in MATLAB/Simulink and validated through test results on a prototype for various non-uniform insolation conditions. The results have shown that this paper tracks the GMPP with best tracking efficiency and fast tracking speed. Further, the proposed method is compared with two P-V curve scanning based GMPPT methods and one global optimization based artificial bee colony method. © 2018 IEEE.
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    An Online Method of Estimating State of Health of a Li-Ion Battery
    (Institute of Electrical and Electronics Engineers Inc., 2021) Goud, J.S.; Kalpana, R.; Singh, B.
    Li-ion batteries are playing a crucial role in the fields of renewable energy systems and electric vehicles. The reliability of these systems depends on a battery management system (BMS) which monitors the state of charge (SoC) and state of health (SoH) effectively. Knowing the SoH of a battery in advance enhances the system reliability. This article proposes an accurate online estimation of SoH of a Li-ion battery integrated in solar photovoltaic system (SPV) applications. The proposed method uses the modified coulomb counting method to estimate the SoH of a battery. The proposed SoH estimation method is simulated in MATLAB/Simulink by considering the aging factors such as temperature, charge/discharge rates and depth of discharge. Moreover, the proposed method is validated using an experimental prototype and the results are found to be satisfactory. © 1986-2012 IEEE.