48V battery management unit
Zhang, Peng (2014)
2014
Master's Degree Programme in Radio Frequency Electronics
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
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Hyväksymispäivämäärä
2014-01-15
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201401041008
https://urn.fi/URN:NBN:fi:tty-201401041008
Tiivistelmä
Battery management system design and application are the most important issues in power application unit. In dynamic system, a set of battery pack comprised with multi-ple cells are used to provide a required output voltage, where the performance and relia-bility of batteries are seriously concerned. A smart and adaptive battery management system is able to monitor battery cells in real-time, also to control the power operation on batteries. Therefore, with the help of battery management system, not only the batteries could be working under control, the safety issue of batteries is guaranteed as well.
This thesis aims to design a 48V power unit with 12 cells of lithium-ion batteries. A battery management system with LTC 6803-2 is applied to give a real-time monitor on each cell’s voltage, state of charge and operation status. Besides, a graphic user interface is designed in software to implement all function in the aspect of users. Based on all the measurement results displayed on screen in real-time, a user is able to make a decision on batteries performance and then put forward controlling on batteries. This study is one part of an intelligent adaptive battery management system, some thoughts are proposed from this thesis, which are contributed to the future intensive research.
This thesis aims to design a 48V power unit with 12 cells of lithium-ion batteries. A battery management system with LTC 6803-2 is applied to give a real-time monitor on each cell’s voltage, state of charge and operation status. Besides, a graphic user interface is designed in software to implement all function in the aspect of users. Based on all the measurement results displayed on screen in real-time, a user is able to make a decision on batteries performance and then put forward controlling on batteries. This study is one part of an intelligent adaptive battery management system, some thoughts are proposed from this thesis, which are contributed to the future intensive research.