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  4. Vol 5, Issue 1, 2024

Control Method of Temperature for Multi-stack Fuel Cell System

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DOI: 10.23977/autml.2024.050102 | Downloads: 10 | Views: 204

Author(s)

Zhou Su 1, Yang Ning 1, Chen Chunguang 1

Affiliation(s)

1 College of Automotive Studies, Tongji University, Shanghai, 201804, China

Corresponding Author

Yang Ning

ABSTRACT

In order to control each stack temperature in a multi-stack fuel cell system (MFCS), a model prediction control algorithm based on back propagation neural network (BPNN) is proposed. Firstly, a parallel multi-stack fuel cell thermal management subsystem model was established and a BP neural network system prediction model was trained by applying the system model simulation data; then, the step response matrix of the system prediction model was obtained at typical operating conditions and a dynamic matrix controller was designed; finally, a test operating condition was designed for simulation analysis. The results show that the dynamic matrix controller (DCM) based on BPNN can quickly and accurately control the temperature of the multi-stack fuel cell system, while having the characteristics of small overshoot and short regulation time.

KEYWORDS

Multi-stack fuel cell system, thermal management subsystem, model predictive control, BP neural network, dynamic matrix control

CITE THIS PAPER

Zhou Su, Yang Ning, Chen Chunguang, Control Method of Temperature for Multi-stack Fuel Cell System. Automation and Machine Learning (2024) Vol. 5: 7-16. DOI: http://dx.doi.org/10.23977/autml.2024.050102.

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