Lithium-ion batteries are the most are widely used as electrical storage device in various applications such as portable electronics, electric vehicles, Photovoltaic application, telecommunication etc due to the characteristics of the batterie such as high-power density, long cycling and high-power efficiency. Extensive condition monitoring of the battery should be implemented due to the usage of the battery so that there will be an increase in all the overall performance and expectancy. This research is focused on implementing an online condition monitoring on the Li-ion battery using a signal injection through a power converter. The implemented technique in this research is known as the Electrochemical Impedance Spectroscopy (EIS). The EIS is a widely known technique used in determining the internal impedance of a battery cell. The estimated impedance can be used to determine the state of charge (Soc) and State of health (SoH) of a battery. The EIS is used to characterize the electrochemical behaviour thereby monitoring the change in the impedance of the cell of the battery. The EIS technique is accomplished by sinusoidally injecting current at different frequencies and measuring the voltage response. A standard Frequency Response Analyser (FRA) is used as an offline test while the battery is disconnected from the Load. The limitation of this standard FRA analyser is that it is bulky and Expensive. Attempts have been made to migrate the techniques to online operations, each having their own challenges. For an online Implementation, the interfacing power converter is used for Signal injection to measure the impedance of the battery. This work explores the low current ripple advantage of a threelevel boost converter to implement EIS on lithium ion battery.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/32664 |
| Date | 25 January 2021 |
| Creators | Mosunmola, Faloye Omolola |
| Contributors | Barendse, Paul |
| Publisher | Faculty of Engineering and the Built Environment, Department of Electrical Engineering |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MSc |
| Format | application/pdf |
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