Manufacturers of diesel engines are under increasing pressure to meet progressively stricter NO x emission limits. A key NO x abatement technology is selective catalytic reduction in which ammonia, aided by a catalyst, reacts with NO x in the exhaust stream to produce nitrogen and water. The conversion efficiency is temperature dependent: at low temperature, reaction rates are temperature limited, resulting in suboptimal NO x removal, whereas at high temperatures, they are mass transfer limited. Maintaining sufficiently high temperature to allow maximal conversion is a challenge, particularly after cold start, as well as during conditions in which exhaust heat is insufficient, such as periods of low load or idling. In this work, a nonlinear model predictive controller simultaneously manages urea injection and power to an electric catalyst heater, in the presence of constraints.

Despite the continuously tightening emissions legislation, urban concentrations of nitrogen oxides (NOx) remain at harmful levels. Road transport is responsible for a large fraction, wherein diesel engines are the principal culprits. Turbocharged diesel engines have long been preferred in heavy duty applications, due to their torque delivery and low fuel consumption. Fleet operators are under pressure to understand and control the emissions of their vehicles, yet the performance of emissions abatement technology in real-world driving is largely unquantified. The most popular NOx abatement technology for heavy duty diesel vehicles is selective catalytic reduction. In this work, we empirically determine the efficiency of a factory-fitted SCR system in realworld driving by instrumenting passenger buses with both a portable emissions measurement system (PEMS) and a custom built telematics unit to record key parameters from the vehicle diagnostics systems. We find that even in relatively favourable conditions, while there is some improvement due to the use of SCR, the vehicles operate far from the design emissions targets. The archival value of this paper is in quantification of real world emissions versus design levels and the factors responsible for the discrepancy, as well as in examination of technologies to reduce this difference.

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Reduction of oxides of nitrogen (NOx) emitted from diesel exhaust systems is a current problem due to increased stringency in worldwide emissions legislation. One of the most successful approaches to reduce tailpipe NOx is to reduce NOx by ammonia over a catalyst, known as Selective Catalytic Reduction (SCR). Control of the ammonia injection in such systems is typically a map-based approach, often augmented by feedback from NOx sensors to account for mechanical variation and ageing. We show that a predictive control approach to this system yields several compelling improvements over such industry standard controllers during a representative test cycle. These include better NOx conversion performance whilst simultaneously minimising the quantity of ammonia released to the environment, along with reduced design effort.

Abstract-In this paper we detail the series of digital microelectronics testbed boards which have been developed to meet the requirements of the microelectronics undergraduate programmes at the University of Southampton. We discuss how our boards solve many of the issues with the digital testbeds used previously for the microelectronics programmes and those which are available on the market. The digital testbed solution described in this paper is modular, and comprises multiple boards which each perform a specific function. This modular design is compact and easily expandable, while being cost effective such that they can be given to students to use at home. The boards are well suited for use with modern digital components, and fit in well with teaching of microcontrollers, programmable logic, and discrete logic.