Road Grade Influence on the Exhaust Emissions of a Scooter Fuelled with Bioethanol/Gasoline Blends

Abstract

Recently, the International Agency for Research on Cancer has assessed evidence that exposure to outdoor air pollution causes lung cancer and increases the risk of bladder cancer. Because air pollution in urban areas is mainly caused by transportation, it is necessary to evaluate pollutant exhaust emissions from vehicles and scooters during their real-world use. Laboratory tests, with the exception of the high repeatability of the results, often cannot explain the influence of some parameters, such as ambient conditions, traffic congestion, and road gradients. Therefore, experiments were conducted to study the effects of road gradients on the exhaust emissions of a medium displacement scooter, which represents a very popular means of travel in Southern Italy. First, the scooter was instrumented with a global positioning system (GPS) to acquire speed profiles and positions in an urban route of Napoli city, which is characterized by significant changes in the road gradient. The velocity profile has several missing points due to GPS signal loss over some stretches of road adjacent to tall buildings. The road gradient values were built into an algorithm to synchronize the missing data through Google elevation API based on a model of the same path with a complete set of data. Afterwards, some representative slope values for each kinematic sequence/driving cycle were evaluated. These new variables were found to contribute to the individual real-world driving cycles. The resulting real-world driving cycle was tested using a chassis-dynamometer to continuously simulate the exact road gradient. A series of experiments with and without the road gradient simulations were performed to evaluate the influence of the road gradient on the exhaust emissions of carbon monoxide, total hydrocarbons, nitrogen oxides, and carbon dioxide. This analysis was performed using a two-wheeler vehicle fuelled with commercial gasoline and two blends with a maximum bioethanol content of 20% vol. Gaseous emissions were correlated to the vehicle specific power (VSP), which is the most useful parameter for addressing the road gradient together with the kinematic characteristics of the driving cycle and the vehicle characteristics. Through a multivariate statistical approach, this type of gradient analysis can permit correlation of the emission profiles for a specific road position, and evaluate its influence on their behavior. A strict dependence on carbon dioxide emissions and fuel consumption exists for the VSP. The road gradient greatly increases the vehicle power demands, resulting in an increasing amount of fuel consumed for each kilometer driven.