1. Αποθετήριο Παραδοτέων Υποτρόφων Δράσεων ΕΣΠΑ Τριτοβάθμιας Εκπαίδευσης 2017-2023
2. Όλο το Αποθετήριο
3. Υποψήφιοι διδάκτορες

Τύπος:	Διδακτορική διατριβή
Τίτλος:	Development of algorithms for estimation of particle emissions using soot sensor for on-board diagnostic systems
Εναλλακτικός τίτλος:	-
Συγγραφέας:	[EL] Κοντσές, Δημήτριος[EN] Kontses, Dimitrios
Επιβλέπων διατριβής:	[EL] Σαμαράς, Ζήσης[EN] Samaras, Zissis
Συμβουλευτική επιτροπή:	[EL] Ντζιαχρήστος, Λεωνίδας[EN] Ntziachristos, Leonidas [EL] Γκεϊβανίδης, Σάββας[EN] Geivanidis, Savas
Μέλος εξεταστικής επιτροπής:	[EL] Κολτσάκης, Γρηγόριος[EN] Koltsakis, Grigorios [EL] Τομπουλίδης, Ανανίας[EN] Tomboulides, Ananias [EL] Μουσιόπουλος, Νικόλαος[EN] Moussiopoulos, Nicolas [EL] Βλάχος, Δημήτριος[EN] Vlachos, Dimitrios
Ημερομηνία:	10/09/2019
Περίληψη:	he current thesis developed and optimised an OBD system for DPF diagnosis using a resistive soot sensor and the necessary OBD models. Following the introduction in chapter 1, chapter 2 describes the methodology. Two engine dynamometers, three test vehicles, various artificially failed DPFs and the Micro Soot Sensor (MSS) as reference equipment were used. Chapter 3 presents the development of the OBD model. The model is based on the comparison between the measured response time of a resistive soot sensor and the modelled sensor response time for a DPF failed at the OBD limit (12 mg/km on the NEDC). The modelled response time was predicted using the soot model to estimate engine-out emissions, the DPF model to calculate the filtration efficiency of the threshold DPF and the sensor model to convert the calculated emissions to sensor response time. The results show that the error associated with the soot model for the estimation of the engine-out soot emissions compared to the measured emission by the reference equipment (MSS) was calculated to be 25% and 2% for the base and the advanced model, respectively. The accuracy of the DPF model was 9% for the non-optimal scenario of constant filtration efficiency. The corresponding error for the advanced filtration efficiency, which accounts for the DPF loading and the exhaust volume flow was significantly lower (5%). The sensor model, which implements the empirical function and estimates the sensor response time, was associated with a 7% error attributed to measurement inaccuracies effects on the sensor model. The sensor inaccuracy was estimated to be about 18% and is attributed to the stochastic construction of soot dendrites which leads to variability of the response time for a specific particle flux. The overall OBD index error was estimated to be 28% and 19% for the base and the advanced approaches, respectively. The challenges and the limitations related to the sensor model and the resistive soot sensor that came up during the realisation of the OBD model on a vehicle application are analysed in chapter 4. Cross sensitivities were found to be the most serious concern for resistive sensors. Experiments for sulphur, methane, carbon monoxide, hydrogen and sodium showed no significant effect (either direct or remaining) on sensor behaviour (<10% effect on response time). Urea and NH3 slightly affects sensor behaviour. On the other hand, ash accumulation significantly increased the response time (up to 250% for the single tip sensor at the end of the useful life of the vehicle). The latest tip design and the use of a repelling voltage (software solution) could retain the increase in response time at approximately 43%. Chapter 5 presents the requirements and the methods for PN/PM estimation for advanced on-board applications. Lower mass limits, additional number limit, on-board and fleet monitoring with smart systems and more sensitive and effective in-service conformity checks, require advanced sensors able to be set-up and be ready for measurement in a short period. Optical and electrical charge-based principles were presented and evaluated as candidate sensor solutions.
Γλώσσα:	Αγγλικά
Τόπος δημοσίευσης:	Thessaloniki, Greece
Σελίδες:	213
Θεματική κατηγορία:	[EL] Μηχανολογια οχημάτων[EN] Automotive Engineering
Κάτοχος πνευματικών δικαιωμάτων:	© Dimitrios Kontses
Διατίθεται ανοιχτά στην τοποθεσία:	https://www.didaktorika.gr/eadd/handle/10442/46567
Σημειώσεις:	“This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the project “Scholarships programme for post-graduate studies - 2nd Study Cycle” (MIS-5003404), implemented by the State Scholarships Foundation (ΙΚΥ).”
Εμφανίζεται στις συλλογές:	Υποψήφιοι διδάκτορες