{"id":{"repo_id":"bradford","oai_identifier":"oai:bradscholars.brad.ac.uk:10454/17450"},"canonical_url":"https://search.dev.ndltd.org/etd/bradford/oai:bradscholars.brad.ac.uk:10454/17450","repository":{"repo_id":"bradford","name":"University of Bradford","base_url":"https://bradscholars.brad.ac.uk/oai/request"},"display":{"title":"Virtual sensor for air mass flow measurement in an SI engine: Application of distributed lumped modelling in prediction of air mass flow into the cylinder of SI combustion engines","abstract":"After undergoing an extensive study about engine air mass flow measurement approaches as well as engine modelling for air mass flow prediction, a major problem found to exist is that engineers have still not found a suitable technique to accurately measure the air mass flow entering the cylinder of an internal combustion engine. The engine air mass flow is the most important parameter needed during engine development so the fuel control can be accurately calibrated and as a result increase performance and reduce emission output of an engine. The current methods used to determine the air mass flow lead to inaccuracies due to the large amount of mathematical assumptions and also sensor errors and as a result the mapping and calibration process of a new engine family takes approximately 2 years due to extensive modelling and testing required overcoming the above drawbacks. To improve this, the distributed lumped modelling technique (D-L) of the inlet manifold was chosen, where the intake system is separated into very small sections which are distributed continuously throughout the volume of the intake until entering the cylinder. This technique is validated against a CFD model of the engine’s intake system and real engine data as well as a 1D engine model.","abstract_html":"After undergoing an extensive study about engine air mass flow measurement approaches as well as engine modelling for air mass flow prediction, a major problem found to exist is that engineers have still not found a suitable technique to accurately measure the air mass flow entering the cylinder of an internal combustion engine. The engine air mass flow is the most important parameter needed during engine development so the fuel control can be accurately calibrated and as a result increase performance and reduce emission output of an engine. The current methods used to determine the air mass flow lead to inaccuracies due to the large amount of mathematical assumptions and also sensor errors and as a result the mapping and calibration process of a new engine family takes approximately 2 years due to extensive modelling and testing required overcoming the above drawbacks. To improve this, the distributed lumped modelling technique (D-L) of the inlet manifold was chosen, where the intake system is separated into very small sections which are distributed continuously throughout the volume of the intake until entering the cylinder. This technique is validated against a CFD model of the engine’s intake system and real engine data as well as a 1D engine model.","abstract_has_math":false,"creators":["Filippou, Sotirios"],"institution":"University of Bradford","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Qi, Hong Sheng","Ebrahimi, Kambiz M."],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:13:22Z","subjects":["Engine air mass flow","D-L modelling","Transient engine testing"],"languages":["en"],"rights":["\"Creative
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The University of Bradford theses are licenced under a Creative Commons Licence."],"dc:subject":["Engine air mass flow","D-L modelling","Transient engine testing"],"dc:title":["Virtual sensor for air mass flow measurement in an SI engine: Application of distributed lumped modelling in prediction of air mass flow into the cylinder of SI combustion engines"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["PhD"]},"updated_at":"2026-07-24T01:13:22Z"}