Real World Emissions Analysis Using Sensor-based Emissions Measurement System for Light-duty Direct-Injection Gasoline Vehicle

2022-01-0572

03/29/2022

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WCX SAE World Congress Experience
Authors Abstract
Content
In recent years, particulate matter (PM) emitted from direct-injection gasoline vehicles is becoming an increasingly concerning problem. In addition, it is often reported that ammonia (NH3) is emitted from gasoline vehicles equipped with a three-way catalyst. These emissions might be largely emitted especially when driving in on-road driving conditions. In this study, we investigated the emissions, NOx, NH3, and PM/PN (particulate number) of a light-duty direct-injection gasoline vehicle when driving on actual roads. Using a small direct-injection gasoline vehicle equipped with a three-way catalyst, experiment was conducted 8 times on the same route, and these emissions were measured. In this study, vehicle specific power (VSP) was introduced, which can be calculated using vehicle parameters, vehicle speed, and road gradient. The effects of parameters acquired through on-board diagnostics (OBD) port and VSP on emissions were investigated. Based on these measurements, "where" and "how much" NOx, NH3, and PM/PN were emitted were emphasized. As a result, it was clarified that a large amount of NOx is emitted after the fuel is cut during deceleration, NH3 is emitted when the air-fuel ratio becomes rich, and PM/PN is emitted during rapid acceleration of the vehicle. Cross-correlation function is also introduced to identify parameters that has similar properties to avoid redundancy when analyzing the causes and effects of the exhaust gas emissions.
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DOI
https://doi.org/10.4271/2022-01-0572
Citation
Eang, C., Sato, S., Tanaka, K., Tange, T. et al., "Real World Emissions Analysis Using Sensor-based Emissions Measurement System for Light-duty Direct-Injection Gasoline Vehicle," SAE Technical Paper 2022-01-0572, 2022, https://doi.org/10.4271/2022-01-0572.
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-0572
Content Type
Technical Paper
Language
English