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Differences between the results obtained in laboratory and road tests of vehicles depend on a number of factors. Among the most important of these are driving cycle and road load. These parameters also affect the hybrid drive control, including the combustion engine operation or driving in electric mode. In most studies, tests carried out on chassis dynamometers concern type approval cycles (NEDC—New European Driving Cycle, WLTC—World-wide harmonized Light duty Test Cycle, FTP— Federal Test Procedure), which differ from real on-road tests. Consequently, the different driving cycles do not allow for results similar to those obtained during on-road driving, especially as the actual cycles on the road are unrepeatable. It is also important to determine the effect of the motion resistance function adopted for chassis dynamometer tests on exhaust emissions and fuel consumption. For this purpose, the authors tested a hybrid car under road and laboratory conditions for the same driving cycle. The analysis was conducted for an example urban road cycle in Rzeszow (URRC). The purpose of the study was to determine the differences in the results of gaseous emissions (THC, CO, CO2, NOx) and fuel consumption (energy) of a hybrid car under road conditions, with the results of tests conducted on a chassis dynamometer, for the same cycle and three functions of resistance. [ABSTRACT FROM AUTHOR]

The results of diagnostic tests under steady-state speed conditions of an unloaded engine do not fully reflect the emissivity of vehicles adapted to run on natural gas. Therefore, it is reasonable to pay attention to the emissions performance of these vehicles under dynamic conditions. In this regard, the tests were carried out on a chassis dynamometer with the engine fueled by gasoline and natural gas. Due to the area of operation of natural gas vehicles being usually limited to urban areas, the urban phases of the NEDC (New European Driving Cycle) and WLTC (Worldwide harmonized Light-duty vehicles Test Cycle) were adapted. While CO2 emissions are lower when fueled by natural gas, CH4 emissions can be high, which is related to momentary changes in the composition of the combustible mixture. Although CH4 emissions are higher when the engine runs on natural gas, the CO2eq value is, depending on the driving cycle, about 15–25% lower than when running on petrol. Additionally, studies have shown that in engines adapted to run on CNG (compressed natural gas), it is advisable to consider the use of catalytic converters optimized to run on natural gas, as is the case with vehicles which are factory–adapted to run on CNG. [ABSTRACT FROM AUTHOR]

Among the solutions that make it possible to reduce CO2 emissions in the transport sector, particularly in urban traffic conditions, are hybrid vehicles. The share of driving performed in electric mode for hybrid vehicles is highly dependent on motion resistance. There are different methods for determining the motion resistance function during chassis dynamometer testing, leading to different test results. Therefore, the main objective of this study was to determine the effect of the chassis dynamometer load function on the energy demand and CO2 emissions of a full-hybrid passenger car. Emissions tests according to the New European Driving Cycle (NEDC) were carried out on a chassis dynamometer for three different methods of determining the car's resistance to motion. The study showed that adopting the motion resistance function according to different methods, results in differences in CO2 emissions up to about 35% for the entire cycle. Therefore, the authors suggest that in the case of tests carried out with chassis dynamometers, it is necessary to also provide information on the chassis dynamometer loading function adopted for the tests. [ABSTRACT FROM AUTHOR]

Road transport contributes to almost a quarter of carbon dioxide emissions in the EU. To analyze the exhaust emissions generated by vehicle flows, it is necessary to use specialized emission models, because it is infeasible to equip all vehicles on the road in the tested road sections with the Portable Emission Measurement System (PEMS). However, the currently used emission models may be inadequate to the investigated vehicle structure or may not be accurate due to the used macroscale. This state of affairs is especially related to full hybrid vehicles, since there are none of the microscale emission models that give estimated emissions values exclusively for this kind of drive system. Several automakers over the past decade have invested in hybrid vehicles with great opportunities to reduce costs through better design, learning, and economies of scale. In this work, the authors propose a methodology for creating a CO2 emission model, which takes relatively little computational time, and the models created give viable results for full hybrid vehicles. The creation of an emission model is based on the review of the accuracy results of methods, such as linear, robust regression, fine, medium, coarse tree, linear, cubic support vector machine (SVM), bagged trees, Gaussian process regression (GPR), and neural network (NNET). Particularly in the work, the best fit for the road input data for the CO2 emission model creation was the GPR method. PEMS data was used, as well as model training data and model validation. The model resulting from this methodology can be used for the analysis of emissions from simulation tests, or they can be used for input parameters for speed, acceleration, and road gradient. [ABSTRACT FROM AUTHOR]