The effect of transport-related pollution on human health is fast becoming recognized as a major issue in cities worldwide. Cyclists, in particular, face great risks, as they typically are most exposed to tail-pipe emissions. Three avenues are being explored worldwide in the fight against urban pollution: (i) outright bans on polluting vehicles and embracing zero tailpipe emission vehicles; (ii) measuring air-quality as a means to better informing citizens of zones of higher pollution; and (iii) developing smart mobility devices that seek to minimize the effect of polluting devices on citizens as they transport goods and individuals in our cities. Following this latter direction, in this paper we present a new way to protect cyclists from the effect of urban pollution. Namely, by exploiting the actuation possibilities afforded by pedelecs or e-bikes (electric bikes), we design a cyber-physical system that mitigates the effect of urban pollution by indirectly controlling the minute ventilation (volume of air inhaled per minute) of cyclists in polluted areas. Results from a real device are presented to illustrate the efficacy of our system.
The effect of a three-way catalytic converter on particulate matter from a gasoline direct-injection engine during cold-start.
AbstractThis work investigates the effect of a three-way catalytic converter and sampling dilution ratio on nano-scale exhaust particulate matter emissions from a gasoline direct-injection engine during cold-start and warm-up transients. Experimental results are presented from a four cylinder in-line, four stroke, wall-guided direct-injection, turbo-charged and inter-cooled 1.6 l gasoline engine. A fast-response particulate spectrometer for exhaust nano-particle measurement up to 1000 nm was utilised. It was observed that the three-way catalytic converter had a significant effect on particle number density, reducing the total particle number by up to 65 % over the duration of the cold-start test. The greatest change in particle number density occurred for particles less than 23 nm diameter, with reductions of up to 95 % being observed, whilst the number density for particles above 50 nm diameter exhibited a significant increase. The exhaust temperature plays a significant role on the influence of the catalytic converter on the nano-scale particulate matter. It is evident that the dilution ratio of the exhaust sample has a distinct effect on the particulate matter number and size distribution, influencing the engine-out PM more significantly than the tailpipe-out PM during cold-start engine operation. The catalytic converter also has a considerable effect on the estimated total particle mass.
Continued legislative pressure to reduce NO x emissions from diesel engine combustion systems generates a desire for cycle-by-cycle emissions data, with a view to their use in a feedback control strategy, perhaps in conjunction with an exhaust catalytic reactor. While NO x sensors that provide fast, robust, reliable, and continuous measurements in a diesel exhaust at a reasonable price are currently the subject of much development, the present work focuses on an indirect approach. This has led to the development of a semi-empirical model that can be used to estimate NO x emissions, based on more easily measured input data, primarily in the form of instantaneous in-cylinder pressure as a function of crank angle. The model computations are based on fundamental thermodynamic principles, but key empirical constants have been derived with the aid of statistical techniques. The approach taken relied on the availability of an extensive bank of experimental data from three different designs of direct injection diesel engine, each utilizing common rail type fuel injection systems and, in some cases, with the use of multiple injections per cycle.and application of the model to different engines, david.timoney@ucd.ie and thus a generic multizone model has to date not ‡ Now at: Departamento de Tecnología, Universitat Jaume 1, been identified. Also, as the number of model zones increases, so too does the computational time.
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