Publication
Exhaust aftertreatment systems for light-duty diesel vehicles - OBD data analysis for DPF malfunction avoidance
| datacite.subject.fos | Engenharia e Tecnologia::Outras Engenharias e Tecnologias | pt_PT |
| dc.contributor.advisor | Ferreira, Lino Miguel Moreira | |
| dc.contributor.advisor | Santos, Helder Manuel Ferreira dos | |
| dc.contributor.author | Lopes, António Pedro Correia | |
| dc.date.accessioned | 2024-09-06T12:56:04Z | |
| dc.date.embargo | 2027-06-21 | |
| dc.date.issued | 2024-06-21 | |
| dc.description.abstract | This research investigates modern automotive exhaust gas treatment systems, vital for curbing air pollution from vehicles. It explores the complexity of emission control regulations, emphasizing the convergence of challenging criteria such as air pollutants, greenhouse gases, and fuel efficiency. The research analyses the evolution of diesel engines exhaust aftertreatment systems alongside EURO standards, discussing novel solutions and their role in achieving compliance with real-world driving emission standards. The current emission regulations require the integration of exhaust gas aftertreatment systems that are increasingly intricate and effective in diesel-powered vehicles. Among these systems, the Diesel Particulate Filter (DPF) assumes a crucial role in particulate matter capture and conversion. To enhance the longevity of this system, a series of precautionary measures becomes imperative for drivers. Central to these measures is the avoidance of disrupting regeneration cycles—an essential process during which captured particles are transformed into inert residues, preventing the filter from becoming obstructed. This Thesis presents an innovative framework that uses a proprietary algorithm capable of adapting to vehicle data acquired from vehicle On-Board Diagnostics (OBD). In cases where specific DPF information is unavailable, due to the manufacturer’s decision to make such information accessible only with specialized tools for the effect, the system employs Fuzzy Logic to process alternative data sources, effectively identifying regeneration events and offering drivers tailored guidance to optimize DPF lifespan extension. The system features include communication of key insights, including ongoing regeneration activity, DPF health status, and predictions regarding the timing of subsequent regenerations, all delivered through an integrated display mechanism. Overall, the methods investigated in this Thesis and the performance results obtained from road tests, demonstrate that relevant contributions were achieved and the main objective of the developed tool as a preventive measure to optimize the DPF lifespan was successfully accomplished. | pt_PT |
| dc.description.sponsorship | This work was financially supported by Project SMARTool: Sistema Modular Multi-Protocolar para a Manutenção Preventiva e Preditiva de Máquinas, Equipamentos e Ferramentas Industriais e Outras, (SI I&DT – empresas em copromoção, CENTRO-01-0247-FEDER-047116) in the scope of Portugal 2020, co-funded by FEDER (Fundo Europeu de Desenvolvimento Regional) under the framework of PO CENTRO (Programa Operacional da Região Centro). | pt_PT |
| dc.identifier.tid | 203690850 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.8/10016 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | On-board diagnostics | pt_PT |
| dc.subject | Diesel particulate filter | pt_PT |
| dc.subject | Regeneration | pt_PT |
| dc.subject | Controller Area network | pt_PT |
| dc.subject | Engine control unit and fuzzy logic | pt_PT |
| dc.title | Exhaust aftertreatment systems for light-duty diesel vehicles - OBD data analysis for DPF malfunction avoidance | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | restrictedAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Engenharia Automóvel | pt_PT |
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