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Improving CO2 emission assessment of diesel-based powertrains in dynamic driving cycles by data fusion techniques

handle: 10251/183669
This article proposes a method based on the Kalman filter to improve the accuracy of the CO2 measurement in driving cycles such as worldwide harmonized light vehicles test cycles or real driving cycles which are inherently subject to a loss in accuracy due to the dynamic limitations of the CO2 analysers. The information from the analyser is combined with the electronic control unit estimation of the fuel injection. The characteristics of diesel engines and, in particular, the high efficiency of the combustion process and the diesel oxidation catalyst allows to compute the CO2 emissions from the fuel consumption estimation of the electronic control unit by applying the carbon balance method assuming negligible HC and CO emissions. Then, the assessment of the CO2 analyser response time and accuracy allows to pose an estimation problem that can be solved by a Kalman filter. The application of the method to different driving cycles shows that analyser dynamic limitations may lead to an overestimation of the CO2 figures that can reach 4% in highly dynamic tests such as the worldwide harmonized light vehicles test cycles. The technique thus has further potential application to replicating real driving cycles on the chassis dynamometer for real driving emission testing.
- University of Bath United Kingdom
- Bath Spa University United Kingdom
- Engineering and Physical Sciences Research Council United Kingdom
- Engineering and Physical Sciences Research Council United Kingdom
- Universitat Politècnica de València Spain
Worldwide harmonized light vehicles test cycles, Real driving emissions, INGENIERIA AEROESPACIAL, Data fusion, CO(2)emissions, MAQUINAS Y MOTORES TERMICOS
Worldwide harmonized light vehicles test cycles, Real driving emissions, INGENIERIA AEROESPACIAL, Data fusion, CO(2)emissions, MAQUINAS Y MOTORES TERMICOS
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average visibility views 34 - 34views
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