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The paper addresses the impact of traffic light information availability in terms of fuel consumption and emissions by means of comparing 3 different scenarios that a driver of a diesel light duty vehicle may face when trying to cover a particular route of 1km with two traffic lights in between. The first scenario is that the driver does not know in advance the state of the traffic lights. The second scenario assumes that the driver knows the state of the traffic lights but has not modelling nor computation capabilities to solve the associated Optimal Control problem. In the third scenario, the driver knows in advance the state of the traffic lights and also is able to solve the corresponding Optimal Control problem that leads to fuel consumption or NOx emissions minimisation. In the present study the vehicle speed trajectories associated to the previously described 3 scenarios have been computed and then tested in a Euro 5 Diesel vehicle installed in a chassis dynamometer. The obtained results show that: Traffic light information is essential for fuel minimisation in urban conditions, promoting reductions of 7.5-12% and 13-32% for fuel consumption and NOx emissions in the studied case. Also, differences in the engine operating conditions for high efficiency and low NOx emissions may lead to extremely high fuel consumption when NOx minimisation is foreseen or viceversa.
|Number of pages
|Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
|Early online date
|2 Aug 2019
|Published - 1 Mar 2020
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- 1 Finished
2/01/14 → 1/01/17
Project: Research council
- Department of Mechanical Engineering - Professor
- Institute for Advanced Automotive Propulsion Systems (IAAPS) - Centre Director
- Made Smarter Innovation: Centre for People-Led Digitalisation
- EPSRC Centre for Doctoral Training in Advanced Automotive Propulsion Systems (AAPS CDT)
Person: Research & Teaching, Core staff, Affiliate staff