Research on dynamic modeling and carbon load estimation of diesel particulate filter

References

• Bai, S., J. Tang, G. Wang, and G. Li. 2016a. Soot loading estimation model and passive regeneration characteristics of DPF system for heavy-duty engine. Applied Thermal Engineering 100:1001292–98. doi:10.1016/j.applthermaleng.2016.02.055.
   Web of Science ®Google Scholar
• Bai, S., J. Tang, G. Wang, and G. Li. 2016b. Soot loading estimation model and passive regeneration characteristics of DPF system for heavy-duty engine. Applied Thermal Engineering 100:1292–98. doi:10.1016/j.applthermaleng.2016.02.055.
   Web of Science ®Google Scholar
• Bin, G., Z. Reggie, L. He, and H. Zhen. 2015. Review of the state-of-the-art of exhaust particulate filter technology in internal combustion engines. Journal of Environmental Management 154:225–58. doi:10.1016/j.jenvman.2015.02.027.
   PubMed Web of Science ®Google Scholar
• Chiavola, O., G. Chiatti, D. M. Cavallo, et al. Modeling of soot deposition and active regeneration in wall-flow DPF and experimental Validation[R]. SAE Technical Paper, 2020.
   Google Scholar
• Chiavola, O., G. Chiatti, and N. Sirhan. 2019. Impact of particulate size during deep loading on DPF management. Applied Sciences 9 (15):3075. doi:10.3390/app9153075.
   Google Scholar
• Depcik, C., C. Langness, J. Mattson Development of a simplified diesel particulate filter model intended for an engine control unit[R]. SAE Technical Paper, 2014.
   Google Scholar
• Di Sarli, V., and A. Di Benedetto. 2015. Modeling and simulation of soot combustion dynamics in a catalytic diesel particulate filter. Chemical Engineering Science 137:69–78. doi:10.1016/j.ces.2015.06.011.
   Web of Science ®Google Scholar
• Di Sarli, V., and A. Di Benedetto. 2016. Operating map for regeneration of a catalytic diesel particulate filter. Industrial & Engineering Chemistry Research 55 (42):11052–61. doi:10.1021/acs.iecr.6b02521.
   Web of Science ®Google Scholar
• Di Sarli, V., and A. Di Benedetto. 2018. Combined effects of soot load and catalyst activity on the regeneration dynamics of catalytic diesel particulate filters. AIChE Journal 64 (5):1714–22. doi:10.1002/aic.16047.
   Web of Science ®Google Scholar
• Di Sarli, V., and A. Di Benedetto. 2019. Using CFD simulation as a tool to identify optimal operating conditions for regeneration of a catalytic diesel particulate filter. Applied Sciences 9 (17):3453. doi:10.3390/app9173453.
   Google Scholar
• Du, Y., G. Hu, S. Xiang, K. Zhang, H. Liu, and F. Guo. 2018. Estimation of the diesel particulate filter soot load based on an equivalent circuit model. Energies 11 (2):472. doi:10.3390/en11020472.
   Web of Science ®Google Scholar
• Feulner, M., F. Seufert, A. Müller, G. Hagen, and R. Moos. 2017. Influencing parameters on the microwave-based soot load determination of diesel particulate filters. Topics in Catalysis 60 (3–5):374–80. doi:10.1007/s11244-016-0626-7.
   Web of Science ®Google Scholar
• Huang, T., G. Hu, F. Guo, and Y. Zhu. 2019. Investigation of a model-based approach to estimating soot loading amount in catalyzed diesel particulate filters. SAE International Journal of Engines 12 (5):567–78. doi:10.4271/03-12-05-0036.
   Web of Science ®Google Scholar
• Jin, M., L. Tian, and J. Tong. 2016. A meta-analysis of the effect of atmospheric PM10 pollution on population mortality in China. Journal of Environment and Health. 33 (008):725–729. doi:10.16241/j.cnki.1001-5914.2016.08.018.
   Google Scholar
• Kort, A., F. X. Ouf, T. Gelain, J. Malet, R. Lakhmi, P. Breuil, and J.-P. Viricelle. 2021. Quantification of soot deposit on a resistive sensor: Proposal of an experimental calibration protocol. Journal of Aerosol Science 156:105783. doi:10.1016/j.jaerosci.2021.105783.
   Web of Science ®Google Scholar
• Landi, G., V. Di Sarli, and L. Lisi. 2021. A numerical investigation of the combined effects of initial temperature and catalyst activity on the dynamics of soot combustion in a catalytic diesel particulate filter. Topics in Catalysis 64 (3–4):270–87. doi:10.1007/s11244-020-01386-w.
   Web of Science ®Google Scholar
• Lao, C., J. Akroyd, N. Eaves, A. Smith, N. Morgan, A. Bhave, and M. Kraft. 2019. Modelling particle mass and particle number emissions during the active regeneration of diesel particulate filters. Proceedings of the Combustion Institute 37 (4):4831–38. doi:10.1016/j.proci.2018.07.079.
   Web of Science ®Google Scholar
• Ran, Y., T. Huang, M. Zhang, S. Jing, and Y. Zhu. 2018. DPF soot loading estimation strategy based on pressure difference. IFAC-Papersonline 51 (31):366–68. doi:10.1016/j.ifacol.2018.10.075.
   Google Scholar
• Reşitoğlu, İ. A., K. Altinişik, and A. Keskin. 2015. The pollutant emissions from diesel-engine vehicles and exhaust aftertreatment systems. Clean Technologies and Environmental Policy 17 (1):15–27. doi:10.1007/s10098-014-0793-9.
   Web of Science ®Google Scholar
• Rossomando, B., I. Arsie, E. Meloni, et al. Experimental test on the feasibility of passive regeneration in a catalytic DPF at the exhaust of a light-duty diesel engine[R]. SAE Technical Paper, 2019.
   Google Scholar
• Shi, Y., Y. Cai, X. Li, X. PU, N. ZHAO, and W. WANG. 2019. Effect of the amount of trapped particulate matter on diesel particulate filter regeneration performance using non-thermal plasma assisted by exhaust waste heat. Plasma Science and Technology 22 (1):015504. doi:10.1088/2058-6272/ab4d3c.
   Web of Science ®Google Scholar
• Shi, X., D. Jiang, Y. Liang, and P. Liang. 2020. Research on carbon load prediction model of DPF based on circulation resistance. Automotive Engineering 42 (9):1183–88.
   Google Scholar
• Sun, Y., T. Cai, and D. Zhao. 2021. Thermal performance and NOx emission characteristics studies on a premixed methane-ammonia-fueled micro-planar combustor. Fuel 291:120190. doi:10.1016/j.fuel.2021.120190.
   Web of Science ®Google Scholar
• Tang J., G. Li, and Z. Wang. 2015. Construction and experiment of DPF soot loading model. Transactions of Csice 33 (1):51–57. doi:10.16236/j.cnki.nrjxb.201501008.
   Google Scholar
• Tan, P., D. Wang, C. Yao, L. Zhu, Y.-H. Wang, M.-H. Wang, Z.-Y. Hu, and D.-M. Lou. 2020. Extended filtration model for diesel particulate filter based on diesel particulate matter morphology characteristics. Fuel 277:118150. doi:10.1016/j.fuel.2020.118150.
   Web of Science ®Google Scholar
• Wang, D. 2013. Research on diesel particle trap and its regeneration Technology. Jilin University. https://kns.cnki.net/kcms2/article/abstract?v=O9dCEmDP74LANvTEr7KNGOuFRumcCvjHXTE1XJ0RnIKVdGmkeTPmK2U73mB7Qj-6nYvhYAfmF2GjUwcZs3ZroUuNynSG3dYiR745-aGXviKqDi0UTNxAM6KzMp8-K-AnV9ozwGFd7YMm27qqLZmH5Q==&uniplatform=NZKPT&language=CHS
   Google Scholar
• Wang, D., P. Tan, L. Zhu, Y.-H. Wang, Z.-Y. Hu, and D.-M. Lou. 2021. Novel soot loading prediction model of diesel particulate filter based on collection mechanism and equivalent permeability. Fuel 286:119409. doi:10.1016/j.fuel.2020.119409.
   Web of Science ®Google Scholar
• Wu, F., B. Zhang, D. Yao, and Y. Yang. 2019. Modeling and order reduction for the thermodynamics of a diesel oxidation catalyst with hydrocarbon dosing. Catalysts 9 (4):369. doi:10.3390/catal9040369.
   Web of Science ®Google Scholar
• Zhang, B., H. Zuo, Z. Huang, J. Tan, and Q. Zuo. 2020. Endpoint forecast of different diesel-biodiesel soot filtration process in diesel particulate filters considering ash deposition. Fuel 272:117678. doi:10.1016/j.fuel.2020.117678.
   Web of Science ®Google Scholar
• Zhong, C., J. Liang, Y. Zhu, H. Zuo, S. Wang, B. Chen, X. Wu, and C. Wu. 2022. Effects analysis on soot oxidation performance in the diesel particulate filter based on synergetic passive-active composite regeneration methods. Chemical Engineering Science 262:118013. doi:10.1016/j.ces.2022.118013.
   Web of Science ®Google Scholar