리튬이온배터리와 슈퍼커패시터를 하이브리드한 에너지 팩을 위한 LSTM 기반 SOC 예측 연구LSTM-Based SOC Estimation for Hybrid Energy Pack Combining Li-ion Battery and Supercapacitor
- Other Titles
- LSTM-Based SOC Estimation for Hybrid Energy Pack Combining Li-ion Battery and Supercapacitor
- Authors
- 박진석; 임완수
- Issue Date
- Aug-2024
- Publisher
- 한국자동차공학회
- Keywords
- Lithium-ion battery; Electric vehicle; State of charge; Supercapacitor; Hybrid energy pack; LSTM; 리튬이온배터리; 전기자동차; 충전상태; 슈퍼커패시터; 하이브리드 에너지 팩; 장단기 기억 신경망
- Citation
- 한국자동차공학회 논문집, v.32, no.8, pp 681 - 688
- Pages
- 8
- Journal Title
- 한국자동차공학회 논문집
- Volume
- 32
- Number
- 8
- Start Page
- 681
- End Page
- 688
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/28872
- ISSN
- 1225-6382
2234-0149
- Abstract
- A hybrid energy pack combines lithium-ion batteries and supercapacitors to meet high-energy and high-power demands simultaneously, providing various benefits such as improved energy efficiency and extended battery life, which is crucial in the field of energy storage and management. This study proposed a Long Short-Term Memory(LSTM)-based algorithm for State of Charge(SOC) estimation in hybrid energy packs. Data generated from FTP72, FTP75, UDDS, WLTP Class 1, WLTP Class 2, and WLTP Class 3 drive cycles, each discharged 100 times, were used to train and test the model.
Compared to a GRU-based model that uses the Root Mean Square Error(RMSE) metric, our proposed model demonstrated a 50 % improvement in performance, showing superior SOC estimation accuracy.
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