Yazar "Erdogan, Birand" seçeneğine göre listele

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    A Fast Simulation Model for Large Scale Battery Packs Used in Heavy Electric Vehicles
    (Institute of Electrical and Electronics Engineers Inc., 2019) Erdogan, Birand; Savrun, Murat Mustafa; Koroglu, Tahsin; Cuma, Mehmet Ugras; Tumay, Mehmet
    Voltage imbalance occurs in a battery pack due to the differences of internal resistance, temperature, self discharge rate, leakage current etc. reduce the usable energy over time. To overcome voltage imbalances in the battery pack, cell balancing methodologies are used. Although passive balancing methods provide cheap solutions for equalizing imbalances, active balancing methods make it possible to balance faster. This paper presents an active balancing topology for large scale battery packs in a heavy electric vehicle. In order to investigate the performance of the system, a battery pack and bidirectional flyback converter (BiFLC) based active balancing circuit equipped with switch matrix (SwM) has been simulated by using MATLAB/Simulink. A charge transfer bus, which is supplied by the first cell of the battery pack, is used to transfer energy between the source/ destination cells. Thus, the need for the auxiliary circuit/battery is eliminated. A large scale battery pack consist of 176 series cells and 22 BiFLCs is used in the simulation model. Because of using switching models of BiFLCs requires high run time and more complexity, a simple model of BiFLC using current sources is presented. © 2019 IEEE.
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    Öğe
    A NARMA-L2 ANN-controlled hybrid storage-based energy management framework for enhanced microgrid operation
    (Elsevier, 2025) Erdogan, Birand; Tumay, Mehmet; Savrun, Murat Mustafa; Cuma, Mehmet Ugras
    This paper presents an advanced energy management system (EMS) for a hybrid microgrid comprising photovoltaic (PV), Fuel cell (FC), battery, supercapacitor (SC), and AC grid sources. The proposed architecture ensures efficient power distribution and system stability through intelligent coordination of multiple energy resources under varying irradiance and load conditions. Two multiport converter topologies are adopted: one connects the PV and FC to a common DC link, and the other integrates battery and SC storage units, enabling flexible and optimized power flow. A NARMA-L2 Artificial Neural Network (ANN)-based controller is implemented to manage power exchange intelligently by predicting and adapting to real-time variations in demand and supply. The EMS operates efficiently in both power surplus and deficit modes, dynamically engaging sources and storage units to ensure continuous load support. Simulation results demonstrate that the system maintains a constant load power of 6 kW despite fluctuations in PV and FC outputs, with the battery and SC compensating during transitions. The coordinated control ensures voltage stability, minimizes conversion stages, and enables quick response to transients. This integrated and intelligent control approach offers a robust and sustainable solution for microgrids and renewable-based EV charging infrastructures.
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    Öğe
    An improved and fast balancing algorithm for electric heavy commercial vehicles
    (Elsevier, 2021) Erdogan, Birand; Savrun, Murat Mustafa; Koroglu, Tahsin; Cuma, Mehmet Ugras; Tumay, Mehmet
    Nowadays, the tendency towards electric vehicles is increasing and various studies are being carried out in order to eliminate the shortage of battery life. One way to improve battery life is to overcome imbalances between cells in battery packs. The imbalances due to structural differences arising from production and changing operating conditions reduce the utilization of available energy. Passive and active balancing methods are used in order to eliminate these imbalances. Due to the slow equalization speed and energy inefficiency of passive balancing circuits, the trend towards active balancing is increasing. In this paper, an active balancing system with a new balancing algorithm that features fast balancing, multiple charge transfers, and suitable for large battery packs used in electric heavy commercial vehicles is proposed to increase usable energy. To test the algorithm, battery module and bidirectional dc-dc converter based active balancing system simulation study has been performed in Matlab-Simulink. The performance of proposed algorithm is compared with other algorithms and simulation results show that the proposed algorithm has better balancing performance.