Design And Analysis Of Li-Ion Battery Fuel Gauge Algorithm For Mobile Systems
Personal battery-powered devices like mobile phones, smart watches and smart glasses have become part of necessity in our daily life. Apart from sophisticated features, the battery lifetime or standby time is also one of the attractiveness of the devices. Most of these mobile or wearable devices us...
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| 主要作者: | |
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2016
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| 主题: | |
| 在线阅读: | http://eprints.usm.my/41326/1/WONG_TECK_SING_24_Pages.pdf |
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| 总结: | Personal battery-powered devices like mobile phones, smart watches and smart glasses have become part of necessity in our daily life. Apart from sophisticated
features, the battery lifetime or standby time is also one of the attractiveness of the devices. Most of these mobile or wearable devices use Lithium-Ion(Li-Ion)-type
batteries as they offer a variety of advantages such as the capability of holding the charge longer, the ability to be recharged numerous times, and most importantly, being lightweight. Many people tend to purchase those with longer battery standby time so
that they do not have to recharge the devices very often or carry a backup power supply
when they are on a travel. However, in many cases, the battery indicators of the devices
do not exactly represent the remaining charge of the battery. This does not only lead
to inaccurate description of the devices, but also leaves negative impressions to the
users or buyers, which consequently affects the sales of the products. Hence a solution to accurately estimate available battery charge for remaining activities and
optimization of battery usage based on device activities is important to give users a high quality user experience. In this thesis, a fuel gauge algorithm design is proposed to increase estimation accuracy of the state of charge (SOC) of the Li-ion battery. The design is based on the integration of coulomb counting and open-circuit-voltage methods. It is shown in this work that this technique is able to reduce the error to ±3%, which is a standard industry specification requirement. |
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