Volume 13: Proceedings Applied Energy Symposium: CUE2020, Part 2, Japan/Virtual, 2020

AN H-∞ AND ANN JOINT METHOD FOR ONLINE SUPERCAPACITOR TEMPERATURE ESTIMATION Li Wei,Xintong Bai, Ming Wu

Abstract

The supercapacitor thermal management system is of great significance to the safe operation and aging moni-toring of the supercapacitor. This article provides a solu-tion for estimating the internal temperature through the surface temperature, instead of directly measurement. By adopting a suitable electrothermal coupling model of supercapacitor, the internal temperature can be estimat-ed online via an H-infinity filter. Besides, in order to re-duce error caused by model inaccuracy and noise chang-ing, this paper uses the neural network to correct the result of the H-infinite filter. To verify the effectiveness method proposed in this paper, a series of experiments are designed and conducted. The results shows that the H-∞-ANN joint filter has less error than H-∞ filter alone.

Keywords Temperature observation, Supercapacitor, Online implementation

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