Tim Beattie

This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the ‘Global’ level,
associated… Show more

This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the ‘Global’ level,
associated with performance over a drive cycle, and ‘Local’ level, relating to engine operation at each speed / load point. The case study of a diesel engine was considered to study the
application of the ATC framework to a calibration optimisation problem. The paper describes the analysis and mathematical formulation of the diesel engine calibration optimisation as an
ATC framework, and its Matlab implementation with gradient based and evolutionary optimisation algorithms. The results and performance of the ATC are discussed comparatively with
the benchmark steady state solution for the engineering calibration of the diesel engine. The main conclusion from this research is that ATC optimisation framework offers an effective
approach for engine calibration, with a potential to deliver significant fuel economy benefits. Further advantages of the ATC framework is that it is flexible and scalable to the
complexity of the calibration problem, and enables calibrator preference to be incorporated a priori in the optimisation problem formulation, delivering important time saving for the overall calibration development process. Show less

A generic framework of testing and development efficiency has
been presented, covering two distinct methods, namely the four
lever approach and the system optimisation approach.
• The 4 lever approach has been applied multiple times and has been
proven to provide significant gains in test field effectiveness.
• System optimisation – Achieving the optimal balance between the
engineering test requirement and testing capability is a powerful
concept which can be used to… Show more

A generic framework of testing and development efficiency has
been presented, covering two distinct methods, namely the four
lever approach and the system optimisation approach.
• The 4 lever approach has been applied multiple times and has been
proven to provide significant gains in test field effectiveness.
• System optimisation – Achieving the optimal balance between the
engineering test requirement and testing capability is a powerful
concept which can be used to improve test field effectiveness.
• A circular work flow phenomenon has been presented which originates
from a mismatch between engineering requirements and test
capabilities. This mismatch is often explored in an iterative timeconsuming
way. System optimisation is proposed to be a suitable
remedy.
• The full potential of investment in facility cannot be realised
without commensurate attention to development process, organisational
change, training and communication between test and
engineering.
• The philosophies presented can be used to justify expenditure on
test facility upgrades with a specifically targeted benefit to the
development process. Show less

The paper documents some of the findings from a joint JLR and AVL project which was conducted at the JLR Gaydon test facility in the UK. A testing and development efficiency concept is presented and test data quality is identified as a key factor. In support of this methods are proposed to correctly measure and set targets for data quality with high confidence. An illustrative example is presented involving a Diesel passenger car calibration process which requires response surface models (RSMs)… Show more

The paper documents some of the findings from a joint JLR and AVL project which was conducted at the JLR Gaydon test facility in the UK. A testing and development efficiency concept is presented and test data quality is identified as a key factor. In support of this methods are proposed to correctly measure and set targets for data quality with high confidence. An illustrative example is presented involving a Diesel passenger car calibration process which requires response surface models (RSMs) of key engine measured quantities e.g. engine-out emissions and fuel consumption. Methods are proposed that attempt to quantify the relationships between RSM statistical model quality metrics, test data variability measures and design of experiment
(DOE) formulation. The methods are tested using simulated and real test data. Show less