Volume 13: Low Carbon Cities and Urban Energy Systems: Part II

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

https://doi.org/10.46855/energy-proceedings-7497

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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