Optimization of Photo-fermentative Hydrogen Production Process Based on the ADM1 Kinetic Model

REN Changpeng; JIANG Qiushi; LIU Xin; CAO Wen; GUO Liejin

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Optimization of Photo-fermentative Hydrogen Production Process Based on the ADM1 Kinetic Model

更新时间：2026-08-31

- Optimization of Photo-fermentative Hydrogen Production Process Based on the ADM1 Kinetic Model
- JOURNAL OF XI’AN JIAOTONG UNIVERSITY (2026)
- 作者机构：
  
  西安交通大学动力工程多相流国家重点实验室，710049，西安
- 作者简介：
- 基金信息：
- DOI：
  CLC： TQ116.2+9
- Received：10 November 2025，
  
  Revised：2026-02-05，
  
  Accepted：15 February 2026，
- 稿件说明：
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REN Changpeng, JIANG Qiushi, LIU Xin, et al. Optimization of Photo-fermentative Hydrogen Production Process Based on the ADM1 Kinetic Model[J]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY,2026.
DOI：

REN Changpeng, JIANG Qiushi, LIU Xin, et al. Optimization of Photo-fermentative Hydrogen Production Process Based on the ADM1 Kinetic Model[J]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY,2026. DOI：

摘要

为了系统阐明光发酵制氢过程中各主要代谢路径的动力学特征，本研究建立并优化了一种基于厌氧消化一号模型ADM1的光发酵制氢模型，以葡萄糖为标准底物进行描述与分析。模型以物质守恒为基础，将底物按照一定比例分配给细胞生长、产物合成和细胞代谢消耗三个途径。充分考虑了光发酵制氢过程中发生的12个关键代谢反应，保持化学计量比不变，通过调整反应速率反映不同代谢路径的变化。基于微生物糖酵解的反应顺序，采用“两步法”快速确定动力学参数。模型利用不同初始浓度葡萄糖的光发酵实验数据进行了参数校准与验证。同时改进了模型，将乳酸和乙醇纳入中间代谢产物中，并引入pH与光照强度对底物转化、生物量积累及产氢性能的影响，并考虑了pH对于碳代谢流影响。结果表明，改进后的光发酵制氢动力学模型成功提高了预测的准确性，在预测不同浓度葡萄糖运行条件下氢气生产、光合细菌生长、有机酸的生产以及光强和pH的变化时，拟合系数均超过0.96。利用模型结合曲面响应法，快速确定了光发酵最佳的初始pH为8，最佳的光照强度为5000 lx。该研究可为制氢反应器开发与制氢过程控制提供重要的理论依据与建模方法支持。

Abstract

To comprehensively elucidate the kinetic characteristics of major metabolic pathways involved in photo-fermentative hydrogen production

this study developed and optimized an (Anaerobic Digestion Model No. 1) ADM1-based photo-fermentation model with glucose as the reference substrate. The model is grounded in mass conservation principles and allocates the substrate to three key pathways: cell growth

product synthesis

and cellular maintenance. Twelve critical metabolic reactions were incorporated

maintaining stoichiometric consistency

and variations in metabolic fluxes were represented by adjusting reaction rates. A "two-step" approach was used to efficiently determine the kinetic parameters based on microbial glycolysis. Experimental data from photo-fermentation with varying initial glucose concentrations were used for model calibration and validation. The model was further refined by including lactate and ethanol as intermediate metabolites and by considering the effects of pH and light intensity on substrate conversion

biomass accumulation

and hydrogen production. Additionally

the impact of pH on carbon metabolic flux was accounted for. Results showed that the improved model significantly enhanced predictive accuracy

with correlation coefficients exceeding 0.96 for hydrogen production

bacterial growth

organic acid production

and the variation of light intensity and pH under different glucose concentrations. Utilizing response surface methodology

optimal conditions for photo-fermentation were determined

with an initial pH of 8 and light intensity of 5000 lx. This work provides important theoretical support and a modeling framework for the development and control of hydrogen production reactors.

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references

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