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  4. Vol 7, Issue 3, 2023

Model-based health state estimation method for proton exchange membrane fuel cells

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DOI: 10.23977/acss.2023.070306 | Downloads: 27 | Views: 500

Author(s)

Zhou Su 1,2, Sun Qi 1, Zhao Peng 2

Affiliation(s)

1 School of Automotive Studies, Tongji University, Shanghai, China
2 Sino-German College, Tongji University, Shanghai, China

Corresponding Author

Sun Qi

ABSTRACT

In order to control the output power of proton exchange membrane fuel cell (PEMFC) more accurately during the aging process, the power-current curve was selected as the state of health (SOH) index. Aiming at the estimation of health status indicators, the mapping relationship between the fuel cell power and the aging of internal components was established. Based on the polarization curve, the semi mechanism power attenuation model was derived. The least square algorithm is used to fit the initialization parameters. The particle filter algorithm was employed to estimate the fuel cell SOH based on the semi mechanism power attenuation model. The experimental results show that the model estimation method based on regularized particle filter algorithm adopted in this paper can attribute to estimating the performance attenuation trend of PEMFC.

KEYWORDS

Fuel cell vehicle, State of health estimation, Particle filter

CITE THIS PAPER

Zhou Su, Sun Qi, Zhao Peng. Model-based health state estimation method for proton exchange membrane fuel cells. Advances in Computer, Signals and Systems (2023) Vol. 7: 39-47. DOI: http://dx.doi.org/10.23977/acss.2023.070306.

REFERENCES

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