Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.738155
Title: Application of multidisciplinary design optimisation frameworks for engine mapping and calibration
Author: Kianifar, Mohammed R.
ISNI:       0000 0004 7227 1336
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 2014
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Abstract:
With ever-increasing numbers of engine actuators to calibrate within increasingly stringent emissions legislation, the engine mapping and calibration task of identifying optimal actuator settings is much more difficult. The aim of this research is to evaluate the feasibility and effectiveness of the Multidisciplinary Design Optimisation (MDO) frameworks to optimise the multi-attribute steady state engine calibration optimisation problems. Accordingly, this research is concentrated on two aspects of the steady state engine calibration optimisation: 1) development of a sequential Design of Experiment (DoE) strategy to enhance the steady state engine mapping process, and 2) application of different MDO architectures to optimally calibrate the complex engine applications. The validation of this research is based on two case studies, the mapping and calibration optimisation of a JLR AJ133 Jaguar GDI engine; and calibration optimisation of an EU6 Jaguar passenger car diesel engine. These case studies illustrated that: -The proposed sequential DoE strategy offers a coherent framework for the engine mapping process including Screening, Model Building, and Model Validation sequences. Applying the DoE strategy for the GDI engine case study, the number of required engine test points was reduced by 30 – 50 %. - The MDO optimisation frameworks offer an effective approach for the steady state engine calibration, delivering a considerable fuel economy benefits. For instance, the MDO/ATC calibration solution reduced the fuel consumption over NEDC drive cycle for the GDI engine case study (i.e. with single injection strategy) by 7.11%, and for the diesel engine case study by 2.5%, compared to the benchmark solutions.
Supervisor: Not available Sponsor: UK Technology Strategy Board (TSB)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.738155  DOI: Not available
Keywords: Multidisciplinary Design Optimisation (MDO) ; Model based calibration ; Design of experiments ; Engine mapping
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