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Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery
Ohirul Qays1, Yonis Buswig2, Martin Anyi3

1Ohirul Qays, Electrical and Electronic Engineering, Universiti Malaysia Sarawak, Samarahan, Malaysia.
2Yonis Buswig, Electrical and Electronic Engineering, Universiti Malaysia Sarawak, Samarahan, Malaysia.
3Martin Anyi, Electrical and Electronic Engineering, Universiti Malaysia Sarawak, Samarahan, Malaysia.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 2424-2430 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8905078919/19©BEIESP | DOI: 10.35940/ijitee.I8905.078919
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Power conveyance potentiality for series and parallel allied battery-packages are constrained by the wickedest cell of the string. Every cell contains marginally dissimilar capability and terminal voltage because of industrialized acceptances and functional situations. During charging or discharging progression, the charge status of the cell strings become imbalanced and incline to loss equalization. Therefore, the enthusiasm of this paper is to design an active charge balancing system for Lithium-ion battery pack with the help of online state of charge (SOC) estimation technique. A Battery Management System (BMS) is modeled by means of controlling the SOC of the cells to upsurge the efficacy of rechargeable batteries. The capacity of each cell is calculated by dint of SOC function estimated as a result of Backpropagation Neural Network (BPNN) algorithm through four switched DC/DC Buck-Boost converter. The simulation results confirm that the designed BMS can synchronize the cell equalization via curtailing the SOC estimation error (RMSE 1.20%) productively.
keyword: Active Cell balancing, Battery Management System, Battery modeling, SOC estimation.

Scope of the Article: Probabilistic Models and Methods