Hydrogen Production System through Dimethyl Ether Autothermal Reforming, Based on Model Predictive Control

Abstract

In this study, a thermodynamic analysis of the low temperature autothermal reforming (ATR) of dimethyl ether (DME) for hydrogen production was conducted. The Pd/Zn/γ-Al2O3 catalyst coated on the honeycomb cordierite ceramic was applied to catalyze the reaction, and the optimum activity temperature of this catalyst was demonstrated experimentally and through simulations to be 400 °C. Furthermore, an optimal model predictive control (MPC) strategy was designed to control the hydrogen production rate and the catalyst temperature. Experimental and simulation results indicated that the controller was automated and continuously reliable in the hydrogen production system. By establishing the state-space equations of the autothermal reformer, it can precisely control the feed rates of DME, high-purity air and deionized water. Ultimately, the hydrogen production rate can be precisely controlled when the demand curve changed from 0.09 to 0.23 mol/min, while the catalyst temperature was maintained at 400 °C, with a temporary fluctuation of 4 °C during variations of the hydrogen production rate. Therefore, the tracking performance of the hydrogen production and the anti-disturbance were satisfactory.

Evaluation of hydrogen production via steam reforming and partial oxidation of dimethyl ether using response surface methodology and artificial neural network

“…This study involves a thermodynamic assessment of hydrogen production through low-temperature auto-thermal reforming (ATR) of DME. The experimental and simulated demonstrations of the Pd/Zn/γ-Al 2 O 3 catalyst, which is applied to honeycomb cordierite ceramic, revealed its effectiveness at 400 °C 20 . Chen et al conducted a study where they utilized ANN to forecast methanol conversion and H 2 yield by incorporating input variables such as the steam-to-carbon (S/C) ratio, gas hourly space velocity (GHSV), and reaction temperature 21 .…”