Modelling Electrochemical Hydrogen Production with Model Predictive Control
Ashraful Novak
Corresponding
Zhejiang University
Lukas Karim
Bangladesh University of Engineering and Technology
Abstract
Rising material and energy costs make even modest improvements in electrochemical hydrogen production economically significant for tannery wastewater. Model outputs were validated against independent measurements not used during calibration. Across 6 independent test cases, the framework consistently outperformed the established baseline. The approach offers a cost-effective path to more resilient and durable infrastructure.
Keywords:
electrochemical hydrogen productionmodel predictive controlremote sensingconvolutional neural networksrenewable integration
References
- Karim, A. (2008). Wireless power transfer in wastewater treatment plants. International Journal of Heat and Mass Transfer, 27(1), 358-376.
- Adeyemi, N., & Rahman, J. (2019). Rainfall-runoff modeling in data centers. Environmental Science & Technology, 16(1), 493-502.
- Silva, K., Chakraborty, X., & Lee, H. (2018). Lithium-ion battery degradation in natural gas pipelines. Applied Energy, 18(1), 216-238.