Blind Deconvolution for Two-thermocouple Sensor Characterisation

Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in the harsh environment found in combustion systems and automotive engine exhausts, large wire diameters are required and consequently the measurement bandwidth is reduced. This paper describes two new algorithmic compensation techniques based on blind deconvolution to address this loss of high-frequency signal components using the measurements from two thermocouples. In particular, a continuous-time approach is proposed, combined with a cross-relation blind deconvolution for parameter estimation. A feature of this approach is that no a priori assumption is made about the time constant ratio of the two thermocouples. The advantages, including small estimation variance and limitations of the method, are highlighted using results from simulation and test rig studies.

Modelling of Unsteady Gas-Dynamic Flow in a Pipe and at its Exit Using CFD

Traditionally the simulation of the thermodynamic aspects of the internal combustion engine has been undertaken using one-dimensional gas-dynamic models to represent the intake and exhaust systems. CFD analysis of engines has been restricted to modelling of in-cylinder flow structures. With the increasing accessibility of CFD software it is now worth considering its use for complete gas-dynamic engine simulation. This paper appraises the accuracy of various CFD models in comparison to a 1D gas-dynamic simulation. All of the models are compared to experimental data acquired on an apparatus that generates a single gas-dynamic pressure wave. The progress of the wave along a constant area pipe and its subsequent reflection from the open pipe end are recorded with a number of high speed pressure transducers. It was found that there was little to choose between the accuracy of the 1D model and the best CFD model. The CFD model did not require experimentally derived loss coefficients to accurately represent the open pipe end; however, it took several hundred times longer to complete its analysis. The best congruency between the CFD models and the experimental data was achieved using the RNG k-e turbulence model. The open end of the pipe was most effectively represented by surrounding it with a relatively small volume of cells connected to the rest of the environment using a pressure boundary.

SiGe HBTs on Bonded SOI Incorporating Buried Silicide Layers

The performance of silicon bipolar transistors has been significantly improved by the use of ultra narrow base layers of SiGe. To further improve device performance by minimising parasitic resistance and capacitance the authors produced an unique silicon-on-insulator (SOI) substrate incorporating a buried tungsten disilicide layer. This structure forms the basis of a recent submission by Zarlink Semiconductors ( Silvaco, DeMontfort & Queen�s) to DTI for high voltage devices for automotive applications. The Queen�s part of the original EPSRC project was rated as tending to outstanding.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.

CO oxidation and NO reduction on metal surfaces: density functional theory investigations

This article reviews the accumulated theoretical results, in particular density functional theory calculations, on two catalytic processes, CO oxidation and NO reduction on metal surfaces. Owing to their importance in automotive emission control, these two reactions have generated a lot of interest in the last 20 years. Here the pathways and energetics of the involved elementary reactions under different catalytic conditions are described in detail and the understanding of the reactions is generalized. It is concluded that density functional theory calculations can be applied to catalysis to elucidate mechanisms of complex surface reactions and to understand the electronic structure of chemical processes in general. The achieved molecular knowledge of chemical reactions is certainly beneficial to new catalyst design.

The investigation of mechanisms in environmental catalysis using time-resolved methods

The formation of nitrogen oxides (NOx) during a combustion process is difficult to avoid because of the large exotherm and the consequent problem of avoiding local high-temperature spikes. Consequently, for many applications, such as for automotive power generation, there will be a continuing need to use catalytic after-treatment to reduce harmful emissions. The investigation of the mechanisms of the key catalytic reactions in environmental catalysis can provide an insight into the action of the catalyst, and time-resolved methods offer a powerful means to study these processes under realistic conditions. The use of Temporal Analysis of Products (TAP) and Steady State Isotopic Transient Kinetic Analysis (SSITKA) methods to investigate the reduction of NOx under various experimental conditions is described. From a detailed analysis of the SSITKA profiles, it is shown that at low temperatures the mechanism for the formation of N-2 and N2O from NO may differ from the conventional high-temperature mechanism. This is supported by density functional theory calculations, which show that the barrier to the formation of N2O from the reaction of N(ads) and NO(ads) may be too high to allow this process to occur at low temperatures. The alternative reaction of NO(ads) + NO(ads) = N2O(g) + O(ads) is shown to be much more favorable and is consistent with the SSITKA analysis. The remarkable effect of hydrogen as a reductant at low temperatures is described, and alternative interpretations of the role of hydrogen are discussed.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Iterative Multiuser Detection and Decoding for DS-CDMA System With Space-Time Linear Dispersion

This paper considers a Q-ary orthogonal direct-sequence code-division multiple-access (DS-CDMA) system with high-rate space-time linear dispersion codes (LDCs) in time-varying Rayleigh fading multiple-input-multiple-output (MIMO) channels. We propose a joint multiuser detection, LDC decoding, Q-ary demodulation, and channel-decoding algorithm and apply the turbo processing principle to improve system performance in an iterative fashion. The proposed iterative scheme demonstrates faster convergence and superior performance compared with the V-BLAST-based DS-CDMA system and is shown to approach the single-user performance bound. We also show that the CDMA system is able to exploit the time diversity offered by the LDCS in rapid-fading channels.

Project Omnivore: A Variable Compression Ratio ATAC 2-Stroke Engine for Ultra-Wide-Range HCCI Operation on a Variety of Fuels

The paper describes the principal features of Omnivore, a spark-ignition-based research engine designed to investigate the possibility of true wide-range HCCI operation on a variety of fossil and renewable liquid fuels. The engine project is part-funded jointly by the United Kingdom's Department for the Environment, Food and Rural Affairs (DEFRA) and the Department of the Environment of Northern Ireland (DoENI). The engineering team includes Lotus Engineering, Jaguar Cars, Orbital Corporation and Queen's University Belfast.

The determinants of knowledge transfer within collaborative new product development projects

Purpose – This paper explores the factors which determine the degree of knowledge transfer in inter-firm new product development projects. We test a theoretical model exploring how inter-firm knowledge transfer is enabled or hindered by a buyer’s learning intent, the degree of supplier protectiveness, inter-firm knowledge ambiguity, and absorptive capacity. Design/methodology/approach – A sample of 153 R&D intensive manufacturing firms in the UK automotive, aerospace, pharmaceutical, electrical, chemical, and general manufacturing industries were used to test the framework. Two-step structural equation modeling in AMOS 7.0 was used to analyse the data. Findings – Our results indicate that a buyer’s learning intent increases inter-firm knowledge transfer, but also acts as an incentive for suppliers to protect their knowledge. Such defensive measures increase the degree of inter-firm knowledge ambiguity, encouraging buyer firms to invest in absorptive capacity as a means to interpret supplier knowledge, but also increase the degree of knowledge transfer. Practical implications – Our paper illustrates the effects of focusing on acquisition, rather than accessing, supplier technological knowledge. We show that an overt learning strategy can be detrimental to knowledge transfer between buyer-supplier, as supplier’s react by restricting the flow of information. Organisations are encouraged to consider this dynamic when engaging in multi-organisational new product development projects. Originality/value – This paper examines the dynamics of knowledge transfer within inter-firm NPD projects, showing how transfer is influenced by the buyer firm’s learning intention, supplier’s response, characteristics of the relationship and knowledge to be transferred.