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Multiple-Model-Based Overheating Detection in a Supercapacitors String
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AI
DOI：10.1109/TEC.2016.2578320.png)
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摘要
En 中文
The need for continuous temperature monitoring and thermal management is unquestionable as operating temperature is a critical factor affecting many electrical/electronic components and devices, including energy storage such as batteries and supercapacitors (SCs). On the other hand, many applications require the battery or SC cells to be stacked up to meet the required voltage or power level which introduces uneven temperature distribution among the cells. Hence, thermal-model-based temperature monitoring and management has been widely utilized, using state estimation to allow the use of minimum number of temperature sensors. This paper explores the performance of multiple-model-based abnormal overheating detection in a SCs string with minimum number of sensors based on simulation and experimental results. The performance of the estimator/detector system is evaluated for the case of an abnormally overheating cell as well as for different values of the estimator parameters. Preliminary indication from the experimental results shows satisfying performance of the estimator/detector system.
Keyword:
Kalman filters
monitoring
state estimation
supercapacitors
temperature
期刊
IF:
5.4
论文数:
6.9K
被引数:
1.5W
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