Hydrogen production characteristic prediction method for electrolytic water hydrogen production system based on data support
By optimizing the BiLSTM-GAM model through data preprocessing and the CPO algorithm, the problem of inaccurate prediction of hydrogen production characteristics in water electrolysis hydrogen production systems was solved, achieving high-precision prediction of hydrogen production characteristics and adapting to the dynamic electrochemical losses of electrolyzers under different operating conditions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING UNIV
- Filing Date
- 2024-02-29
- Publication Date
- 2026-07-24
AI Technical Summary
Existing electrochemical models cannot accurately characterize the hydrogen production characteristics of electrolytic hydrogen production systems, nor can they adapt to the dynamic electrochemical losses of electrolyzers under different working conditions and operating states, resulting in inaccurate predictions of hydrogen production characteristics.
A data-supported approach was adopted, using the Pauta criterion and Z-Score method for data preprocessing, and combining the CPO algorithm to optimize the BiLSTM-GAM model. A CPO-BiLSTM-GAM model was then established to predict hydrogen production characteristics, and the BiLSTM-GAM model was used to extract the characteristic values of the water electrolysis hydrogen production system.
It achieves high-precision prediction of hydrogen production characteristics under different operating conditions of water electrolysis hydrogen production system, solves the problem that existing models cannot adapt to fluctuating operating conditions, and improves the accuracy and efficiency of prediction.
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Figure CN118098439B_ABST