Calibration of a Mass Balance Based Soot Load Estimation Model for Diesel Particulate Filter. Issue 31 (2018)

• Record Type: Journal Article
• Authors: Huang, Tiexiong; Zhu, Yuanxian; Ran, Yong; Zhang, Mingchao; Jing, Si
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 31(2018)
• Page Start: 362
• Page End: 365
• Publication Date: 2018
• Subjects: Diesel particulate filter -- Soot load estimation -- Passive regeneration -- Calibration mapping -- Modeling; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.10.074
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: To accurately estimate the amount of soot in the diesel particulate filters (DPFs) is critical to maintain DPF integrity while minimizing the fuel penalty. A mass balance based soot load estimation model is developed by use of the engine-out soot emission and DPF passive regeneration characteristics. Calibration mapping and the mapping result are described and discussed. Experimental validation is carried out in both engine test cell and vehicle road tests. Results show that after calibration mapping in a systematic way, the proposed mass balance based model has achieved an accuracy of +/-1g/L, which indicates a considerable potential to contribute to the DPF applications and management.