Search Results

This paper presents a calibration optimization study for a Gasoline Direct Injection engine based on a multidisciplinary design optimization (MDO) framework. The paper presents the experimental framework used for the GDI engine mapping, followed by an analysis of the calibration optimization problem. The merits of the MDO approach to calibration optimization are discussed in comparison with a conventional two-stage approach based on local trade-off optimization analysis, focused on a representative emissions drive cycle (NEDC) and limited part load engine operation. The benefits from using the MDO optimisation framework are further illustrated with a study of relative effectiveness of different camshaft timing control strategies (twin independent Versus fixed timing, exhaust only, inlet only and fixed overlap / dual equal) for the reference GDI engine based on the part load test data.

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 effective deployment of FMEAs within complex automotive applications faces a number of challenges, including the complexity of the system being analysed, the need to develop a series of coherently linked FMEAs at different levels within the systems hierarchy and across intrinsically interlinked engineering disciplines, and the need for coherent linkage between critical design characteristics cascaded through the systems levels with their counterparts in manufacturing. The approach presented in this paper to address these challenges is based on a structured Failure Mode Avoidance (FMA) framework which promotes the development of FMEAs within an integrated Systems Engineering approach. The effectiveness of the framework is illustrated through a case study, centred on the development of a diesel exhaust aftertreatment system.

The complexity of powertrain calibration has increased significantly with the development and introduction of new technologies to improve fuel economy and performance while meeting increasingly stringent emissions legislation with given time and cost constraints. This paper presents research to improve the model-based engine calibration optimization using an integrated sequential Design of Experiments (DoE) strategy for engine mapping experiments. This DoE strategy is based on a coherent framework for a model building - model validation sequence underpinned by Optimal Latin Hypercube (OLH) space filling DoEs. The paper describes the algorithm development and implementation for generating the OLH space filling DoEs based on a Permutation Genetic Algorithm (PermGA), subsequently modified to support optimal infill strategies for the model building - model validation sequence and to deal with constrained non-orthogonal variables space.

Automotive Product Development organisations are challenged with ever increasing levels of systems complexity driven by the introduction of new technologies to address environmental concerns and enhance customer satisfaction within a highly competitive and cost conscious market. The technical difficulty associated with the engineering of complex automotive systems is compounded by the increase in sophistication of the control systems needed to manage the integration of technology packages. Most automotive systems have an electro-mechanical structure with control and software features embedded within the system. The conventional methods for design analysis and synthesis are engineering discipline focused (mechanical, electrical, electronic, control, software).

Function analysis provides the backbone of systems engineering design and underpins the use of Design for Six Sigma and Failure Mode Avoidance tools. Identification and management of interfaces is a key task in systems engineering design, in ensuring that the system achieves its functions in a robust and reliable way. The aim of the work presented in this paper was to develop and implement a structured approach for function analysis of a complex system, which focuses on the identification and characterization of interfaces. The proposed approach is based on the principle of separation of the functional and physical domains and development of function decomposition through iteration between functional and physical domains. This is achieved by integrating some existing / known engineering tools such as Boundary Diagram, State Flow Diagram, Function Tree and an enhanced interface analysis within a coherent flow of information.

The quality of the output generated by a team is directly influenced by how well the team works together. Despite the complexity of the team system, within a typical Design for Six Sigma (DFSS) project the consideration given to the team process is often disproportionately small in comparison to that paid to the technical aspects of the project. This paper presents an efficient approach to teamwork within an engineering design context such as a DFSS project, in which team skills are modelled on DFSS technical processes allowing team members to learn both technical and teamwork skills within the common context of the technical process. DFSS engineering tools used within the framework of Failure Mode Avoidance are used to identify key potential failure modes in the team process and their effects and causes. A series of effective and efficient countermeasures to the team process failure modes are introduced as straight forward and easy to use interlinking teamwork tools.

Tata Motors Limited plan to launch a range of full electric vehicles (FEVs) to the European market. Regenerative braking is advantageous in maximising range between recharging, but presents challenges of acceptable performance, weight, cost and the ‘blending’ of regenerative braking with friction braking. Control systems for regenerative braking have been developed by manufacturers to enable recuperation of kinetic energy which would otherwise be converted to heat and wasted through the use of friction brakes. This paper presents the approach taken by Tata Motors Ltd. to optimise the design and operation of a regenerative braking system to maximise range and energy efficiency. The Tata Ace EV is a Class N1 light commercial FEV with drive to the rear wheels only. This presents the challenge of harvesting energy from the axle which contributes a varying amount of the vehicle braking effort depending upon load.

This paper presents an approach to product design verification in which efficient and effective design verification is a key deliverable of a function failure avoidance approach to engineering. The traditional approach to design verification is discussed. The relative advantages of conducting design verification at different levels within the system hierarchy are identified and the manner in which component level testing can be made representative of usage in the field is illustrated within an automotive case study. The use of small samples sizes, a reduced number of tests and a reduction of testing complexity as a part of effective design verification is explained. The role of computer based models as the basis of virtual testing within design verification is discussed.

This paper presents an approach to product design and development based on function failure avoidance, using of series of well known engineering tools including Function Fault Tree Analysis, P-Diagram and Design Verification. A 4-step function failure mode avoidance process is presented. The use of the engineering tools in an integrated and synergistic manner to achieve robust and reliable product design is illustrated by considering information flow within an automotive case study. The central role of FMEA within the process is described. The authors’ experience of using the process is discussed.

This paper presents a design for reliability methodology based on the DfSS DCOV process, applied to the development of a cost effective timing chain drive for a four cylinder diesel engine. A CAE model for the timing chain drive was used to study the distribution of the chain loads, which provided an essential input both for the concept selection stage and for the development of a reliability model for the timing chain. A DoE study on the CAE model aimed at investigating the significant factors for chain load variability lead to a reliability improvement achieved by reducing the variability in the chain load through revising the tolerances for the sprocket tooth profile. The paper demonstrates the efficiency of the process and the usefulness of computer simulation in achieving reliability and robustness enhancement while reducing design and development time and costs.

This paper presents an investigation into the functional robustness of an in-tank fuel delivery system (FDS) used in a saddle type fuel tank application for a high performance petrol engine. Robust design tools were used to identify the noise factors that affect the performance of the in-tank FDS. A transfer function relating the system's response to key control and noise factors was developed using a combination of theoretical modeling based on fluid mechanics and component level experimentation. The transfer function was validated with data from system level testing. A sensitivity study using the transfer function was conducted to validate the performance of the system against key noise factors.

This paper introduces a function failure approach to Fault Tree Analysis (FFTA) and illustrates its application through an automotive case study. The methodology is structured and straightforward to use. It is argued that the FFTA methodology integrates and interconnects well with other failure mode avoidance tools in common use in the automotive engineering design, such as FMEA and P-Diagram. FFTA shares the same platform for function based system analysis as other analysis tools and delivers complementary information

This paper discusses a life prediction modelling approach and its application to customer correlation of engine tests. The approach is based on the realisation that failure of most automotive components can be regarded as the result of degradation, which can be modelled as a stochastic linear damage accumulation process. A case study for validation of an extended oil drain interval is used to illustrate the practical application of the approach.