Battery Management and Component Optimization
- Title
- Battery Management and Component Optimization
- Author
- 최호준
- Advisor(s)
- 이영문
- Issue Date
- 2023. 8
- Publisher
- 한양대학교
- Degree
- Master
- Abstract
- With the advent of the electric vehicle era, batteries have become a crucial
technology in many industries. They are applied not only in mobility such
as electric cars, scooters, and UAMs but also in high-capacity energy
storage systems such as ESS, enhancing quality of life. However, batteries
are affected by environmental factors like temperature and electric shock,
leading to performance degradation. Increased internal resistance and
reduced lifespan due to battery aging render continuous operation
impossible and can result in sudden accidents. Therefore, research on
battery management systems and reducing internal resistance in the initial
battery manufacturing stages is crucial. This thesis addresses these two
problems one in each chapter. In Chapter 1, the impact of heat generation
in drone systems on batteries is examined, and an improved battery
estimation algorithm is developed for the BMS system of drone batteries.
To achieve this, a framework consisting of offline and online states is
proposed. In the offline state, battery capacity estimation is performed
using current pulses while, in the online state, an adaptive algorithm is
used for State-of-Charge estimation. Validation is conducted on two
batteries with different cycles, demonstrating more reliable SoC
estimation results compared to the existing BMS. In Chapter 2, research
is conducted to optimize the ionic conductivity of battery electrolytes in
the initial battery synthesis stage. Bayesian optimization is employed as
the iterative design methodology and a total of six design iterations are
performed. The experimental results show that optimized mole fraction
yields an increased conductivity by 9% compared to initial maximum value
and thus reducing the battery resistance in synthesis stage.
- URI
- http://hanyang.dcollection.net/common/orgView/200000684827https://repository.hanyang.ac.kr/handle/20.500.11754/186952
- Appears in Collections:
- GRADUATE SCHOOL[S](대학원) > DEPARTMENT OF SMART CITY ENGINEERING(스마트시티공학과) > Theses (Master)
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