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Title: | Battery state-of-charge estimation based on open-circuit voltage measurement | Authors: | Li, Yixuan | Keywords: | Engineering::Electrical and electronic engineering | Issue Date: | 2023 | Publisher: | Nanyang Technological University | Source: | Li, Y. (2023). Battery state-of-charge estimation based on open-circuit voltage measurement. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166245 | Abstract: | The ever-increasing number of fossil fuel powered vehicles has led to the production of large amount of carbon dioxide, which results in environmental issues like global warming. The automotive industry is one of the primary contributors to the carbon footprint caused by automobile exhaust, which contains up to 100 different compounds. To combat these issues, electric vehicles (EVs) have been emerged as a solution due to their low pollution, energy-saving, and reduced exhaust emissions. The battery is the most crucial component of EVs, and the positive electrode material, which accounts for the highest proportion of the battery's cost, has become a focus in reducing battery cost. Among all the materials, the LiFePO4 battery (LFP) has been found to be the most suitable material because of its low cost, as well as large capacitance, long life-cycle, high-temperature stability, and high discharge capacity. The accurate estimation of the battery's state of charge (SOC) is essential for maintaining safe operation of the battery and maximizing its efficiency. However, the battery's nonlinear behavior during operation makes determining its SOC challenging. In this dissertation, the open-circuit voltage (OCV) of the battery will be explored as a parameter to estimate the SOC accurately with the objective to examine the suitability of OCV for the estimation of the SOC of the LFP battery. | URI: | https://hdl.handle.net/10356/166245 | Schools: | School of Electrical and Electronic Engineering | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Theses |
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LI YIXUAN.pdf Restricted Access | 1.52 MB | Adobe PDF | View/Open |
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