Abstract:The use of ethanol in gasoline has become a worldwide tendency as an alternative to reduce net CO 2 emissions to the atmosphere, increasing gasoline octane rating and reducing dependence on petroleum products. However, recently environmental authorities in large urban centers have expressed their concerns on the true effect of using ethanol blends of up to 20% v/v in in-use vehicles without any modification in the setup of the engine control unit (ECU), and on the variations of these effects along the years of operation of these vehicles. Their main concern is the potential increase in the emissions of volatile organic compounds with high ozone formation potential. To address these concerns, we developed analytical and experimental work testing engines under steady-conditions. We also tested carbureted and fuel-injected vehicles every 10,000 km during their first 100,000 km of operation. We measured the effect of using ethanol-gasoline blends on the power and torque generated, the fuel consumption and CO 2 , CO, NOx and unburned hydrocarbon emissions, including volatile organic compounds (VOCs) such as acetaldehyde, formaldehyde, benzene and 1,3-butadiene which are considered important ozone precursors. The obtained results showed statistically no significant differences in these variables when vehicles operate with a blend of 20% v/v ethanol and 80% v/v gasoline (E20) instead of gasoline. Those results remained unchanged during the first 100,000 km of operation of the vehicles. We also observed that when the vehicles operated with E20 at high engine loads, they showed a tendency to operate with greater values of λ (ratio of the actual air-fuel ratio to the stoichiometric air-fuel ratio) when compared to their operation with gasoline. According to the Eco-Indicator-99, these results represent a minor reduction (<1.3%) on the impact to human health, and on the deterioration of the ecosystem. However, it implies a 12.9% deterioration of the natural resources. Thermal equilibrium analysis, at the tailpipe conditions (~100 • C), showed that ethane, formaldehyde, ethylene and ethanol are the most relevant VOCs in terms of the amount of mass emitted. The use of ethanol in the gasoline reduced 20-40% of those emissions. These reductions implied an average reduction of 17% in the ozone formation potential.
This work compares the Micro-trips (MT), Markov chains–Monte Carlo (MCMC) and Fuel-based (FB) methods in their ability of constructing driving cycles (DC) that: (i) describe the real driving patterns of a given region and (ii) reproduce the real fuel consumption and emissions exhibited by the vehicles in that region. To that end, we selected four regions and monitored simultaneously the speed, fuel consumption and emissions of CO2, CO and NOx from a fleet of 15 buses of the same technology during eight months of normal operation. The driving patterns exhibited by drivers in each region were described in terms of 23 characteristic parameters (CPs) such as average speed and average positive kinetic energy. Then, for each region, we constructed their DC using the MT method and evaluated how close it describes the observed driving pattern in each region. We repeated the process using the MCMC and FB methods. Given the stochastic nature of MT and MCMC methods, the DCs obtained changed every time the methods were applied. Hence, we repeated the process of constructing the DCs up to 1000 times and reported their average relative differences and dispersion. We observed that the FB method exhibited the best performance producing DCs that describe the observed driving patterns. In all the regions considered in this study, the DCs produced by this method showed average relative differences smaller than 20% for all the CPs considered. A similar performance was observed for the case of fuel consumption and emission of pollutants.
Type-approval driving cycles currently available, such as the Federal Test Procedure (FTP) and the Worldwide harmonized Light vehicles Test Cycle (WLTC), cannot be used to estimate real fuel consumption nor emissions from vehicles in a region of interest because they do not describe its local driving pattern. We defined a driving cycle (DC) as the time series of speeds that when reproduced by a vehicle, the resulting fuel consumption and emissions are similar to the average fuel consumption and emissions of all vehicles of the same technology driven in that region. We also declared that the driving pattern can be described by a set of characteristic parameters (CPs) such as mean speed, positive kinetic energy and percentage of idling time. Then, we proposed a method to construct those local DC that use fuel consumption as criterion. We hypothesized that by using this criterion, the resulting DC describes, implicitly, the driving pattern in that region. Aiming to demonstrate this hypothesis, we monitored the location, speed, altitude, and fuel consumption of a fleet of 15 vehicles of similar technology, during 8 months of normal operation, in four regions with diverse topography, traveling on roads with diverse level of service. In every region, we considered 1000 instances of samples made of m trips, where m varied from 4 to 40. We found that the CPs of the local driving cycle constructed using the fuel-based method exhibit small relative differences (<15%) with respect to the CPs that describe the driving patterns in that region. This result demonstrates the hypothesis that using the fuel based method the resulting local DC exhibits CPs similar to the CPs that describe the driving pattern of the region under study.
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