An experimental-computational study of DPF soot capture and heat regeneration. Issue 4 (15th March 2020)

• Record Type: Journal Article
• Authors: Liu, Bingxia; Sun, Ping; Aggarwal, Suresh K.; Zhao, Sibo; Huang, Biao
• Is Part Of: International journal of green energy. Volume 17:Issue 4(2020)
• Page Start: 301
• Page End: 308
• Publication Date: 2020-03-15
• Subjects: Soot capture -- DPF thermal regeneration -- experiments -- simulations -- parametric study; Power resources -- Research -- Periodicals; Energy industries -- Periodicals; Energy development -- Periodicals; 333.79
• DOI: 10.1080/15435075.2020.1727481
• Languages: English
• ISSNs: 1543-5075

Abstract

ABSTRACT: A diesel particulate filter (DPF) can effectively reduce the exhaust emissions of particulate matter (PM) and meet emission regulations. We report herein an experimental-numerical study to investigate the soot capture and regeneration behavior in a commonly used DPF. Simulations are performed using the AVL FIRE software that considers a fairly detailed DPF model. The model is validated using measured pressure drop history during soot capture, and temperature history during regeneration from a parallel experimental study using a diesel engine equipped with a DPF. Then, a detailed numerical study is performed to examine the soot capture and heat regeneration processes, and characterize the effects of various parameters on these processes and on DPF performance. Results indicate that the pressure drop during soot loading can be reduced by increasing the CPSI (channels per square inch), minimizing the amount of residual soot in each regeneration cycle, and using moderate gas flow rates. The DPF regeneration performance is characterized in terms of the rates of temperature rise and soot oxidation. Results indicate that these rates are enhanced, as the oxygen content in the exhaust stream is increased to about 12%, the rate of thermal heating is moderately increased, and as the exhaust gas flow rate is increased. Thus, the regeneration efficiency can be significantly improving by optimizing these parameters.