Minimization of Battery Pack Imbalance of Electric Vehicles Using Optimized Balancing Parameters

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dc.contributor.authorSavrun, Murat Mustafa
dc.contributor.authorKöro?lu, Tahsin
dc.contributor.authorÜnal, Erdem
dc.contributor.authorOnur, Burak
dc.contributor.authorCuma, Mehmet U?raş
dc.date.accessioned2025-01-06T17:29:43Z
dc.date.available2025-01-06T17:29:43Z
dc.date.issued2019
dc.description2019 Electric Vehicles International Conference, EV 2019 -- 3 October 2019 through 4 October 2019 -- Bucharest -- 154291
dc.description.abstractBattery, one of the key components of developing electric vehicle (EV) technology, has a great significance in the adoption of EVs. The battery packs consist of several cells connected in series and parallel according to the operating voltage and required capacity. Imbalances between serially connected cells are frequently encountered, although cell balancing between parallel connected cells is not a common concern. Batteries are often equipped with balancing systems to prevent the imbalances, which reduces the available capacity and lifetime of the battery. This paper presents a comparative analysis for passive balancing method by considering Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to acquire the optimal timing of enabling/disabling the balancing current to minimize imbalance of cells of the EV battery. In order to perform the balancing operation, the cell voltages are continuously monitored by the controller unit. Cells with lower voltages are detected evaluating the average voltage of the cells, balancing resistor switches of the rest are operated. In the optimal timing of enabling/disabling the balancing current, the minimum imbalance is determined as the cost function for PSO and GA. In the proposed study, a battery pack consisting of 16 series cells is modeled by using MATLAB/Simulink. The nominal capacity and voltage of each cell are 108 Ah and 3.7 V, respectively. The performance of the proposed system is validated. © 2019 IEEE.
dc.identifier.doi10.1109/EV.2019.8893011
dc.identifier.isbn978-172810791-2
dc.identifier.scopus2-s2.0-85075639380
dc.identifier.urihttps://doi.org/10.1109/EV.2019.8893011
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1314
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2019 Electric Vehicles International Conference, EV 2019
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectelectric vehicle
dc.subjectgenetic algorithm
dc.subjectparticle swarm optimization
dc.subjectpassive balance
dc.titleMinimization of Battery Pack Imbalance of Electric Vehicles Using Optimized Balancing Parameters
dc.typeConference Object

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