Concept of a cloud state modeling system for lead-acid batteries: Theory and prototyping
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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2021 International Conference on Electronics, Information, and Communication (ICEIC). Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., 2021. 9369785 (International Conference on Electronics, Information, and Communication, ICEIC ; Vol. 2021).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Concept of a cloud state modeling system for lead-acid batteries
T2 - 20th International Conference on Electronics, Information, and Communication, ICEIC 2021
AU - Kortmann, Felix
AU - Brieske, Daniel
AU - Piekarek, Pia
AU - Eckstein, Julian
AU - Warnecke, Alexander
AU - Drews, Paul
AU - Sauer, Dirk Uwe
N1 - Conference code: 20
PY - 2021/1/31
Y1 - 2021/1/31
N2 - Lead-acid batteries are still the cash cow in the market of energy storage systems. Use in vehicles will continue in the next years due to several advantages over competing products. Despite the high level of maturity of Lead-Acid Batteries (LABs), the Lead-Acid Battery (LAB) is with 40% by far the largest cause of short-term vehicle breakdowns. This is primarily not due to defective products, but rather to over-aged or deeply discharged batteries. The complex aging characteristics of lead-acid batteries do not allow the health status of a battery to be easily detected, which increases the probability of short-term failures. Our paper presents a solution of monitoring the current health status of a battery and discusses modeling opportunities in a cloud as a digital twin to predict breakdowns in the future. We present both, a Low Power Wide Area Network (LPWAN) based monitoring prototype and theory for state modeling and prediction.
AB - Lead-acid batteries are still the cash cow in the market of energy storage systems. Use in vehicles will continue in the next years due to several advantages over competing products. Despite the high level of maturity of Lead-Acid Batteries (LABs), the Lead-Acid Battery (LAB) is with 40% by far the largest cause of short-term vehicle breakdowns. This is primarily not due to defective products, but rather to over-aged or deeply discharged batteries. The complex aging characteristics of lead-acid batteries do not allow the health status of a battery to be easily detected, which increases the probability of short-term failures. Our paper presents a solution of monitoring the current health status of a battery and discusses modeling opportunities in a cloud as a digital twin to predict breakdowns in the future. We present both, a Low Power Wide Area Network (LPWAN) based monitoring prototype and theory for state modeling and prediction.
KW - Battery Management System
KW - Electrochemical Impedance Spectroscopy
KW - Intelligent Battery Sensor
KW - Monitoring
KW - Informatics
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=85102967650&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/41230524-c565-3d38-8937-6b96e5febf7c/
U2 - 10.1109/ICEIC51217.2021.9369785
DO - 10.1109/ICEIC51217.2021.9369785
M3 - Article in conference proceedings
AN - SCOPUS:85102967650
SN - 978-1-7281-9162-1
T3 - International Conference on Electronics, Information, and Communication, ICEIC
BT - 2021 International Conference on Electronics, Information, and Communication (ICEIC)
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
CY - Piscataway
Y2 - 31 January 2021 through 3 February 2021
ER -