Simulation of Two-stage Automotive Shredder Residue Pyrolysis and Gasification Process Using the Aspen Plus Model

The disposal of automotive shredder residue (ASR) directly affects China's goal of achieving a 95% recycling rate for end-of-life vehicles. Pyrolysis and gasification have gradually become the most commonly used thermochemical technologies for ASR recycling. To obtain more hydrogen-rich syngas, it is necessary to determine the optimal process parameters of the ASR pyrolysis and gasification process. The main process parameters of the two-stage ASR pyrolysis and gasification process were studied using the established Aspen Plus model. Through analyzing the effects of process parameters, such as the temperature, equivalence ratio, and mass ratio of steam to ASR feedstock, on the product distribution and product characteristics of ASR pyrolysis and gasification, the optimal process parameters were determined. A series of comparative experiments under different conditions were conducted. The experimental results verified the accuracy and reliability of the Aspen Plus simulation model for the ASR pyrolysis and gasification processes and verified the practical feasibility of the process parameters obtained from the simulation analysis.

Automated summary

The proper disposal of automotive shredder residue (ASR) is crucial for China's goal of achieving a 95% recycling rate for end-of-life vehicles. Pyrolysis and gasification are the most commonly used thermochemical technologies for ASR recycling, and determining the optimal process parameters is essential for obtaining more hydrogen-rich syngas. By studying the main process parameters of the two-stage ASR pyrolysis and gasification process, the optimal parameters were determined through analyzing the effects of factors like temperature, equivalence ratio, and mass ratio of steam to ASR feedstock on product distribution and characteristics. Moreover, experimental results confirmed the accuracy and reliability of the Aspen Plus simulation model and the practical feasibility of the process parameters obtained from the analysis.