This study compared CO₂ emissions during a WLTP (Worldwide Harmonized Light-Duty Vehicles Test Procedure) test performed on a chassis dynamometer for the same flex-fuel vehicle, fuelled sequentially with E10 gasoline and E85 fuel. Based on the test data, a CO₂ emissions map was created, describing its dependence on speed and acceleration. The use of a 3D surface enabled the visualisation of the whole dynamics of emissions as a function of engine load in the WLTP cycle, including the identification of distinct emission peaks in areas of high positive acceleration. Analysis of the emission surface enabled the identification of structural differences between the fuels. For E85, more pronounced emission increases are observed in areas of intense acceleration, a consequence of the higher fuel demand resulting from the lower calorific value of bioethanol. In steady-state and moderate-load driving, CO₂ emissions for both fuels are similar. The results confirm that the main differences between E10 and E85 are not simply a shift in emission levels per se, but stem from variations in engine load during the dynamic cycle. Although E85 emits measurable CO₂ emissions, its carbon is not of fossil origin, highlighting the importance of biofuels in the context of greenhouse gas emission reduction strategies and the pursuit of climate neutrality. The presented methodology, combining chassis dynamometer tests with analysis of the speed-acceleration emission map, provides a tool for clearly identifying emission zones and can serve as a basis for further optimisation of engine control strategies and assessing the impact of fuel composition on emissions under dynamic conditions.

The start-up is a transient state of operation of an internal combustion engine during which many negative phenomena occur that affect the technical condition of the engine, its electrical equipment and the natural environment. The start-up process of an internal combustion engine is influenced...

This study presents a data-driven analysis of electric powertrain energy flow and traction battery behavior in a modern battery electric vehicle based on real-world on-board diagnostic (OBD) measurements. Time-resolved signals acquired during an urban trip by a Renault 5 E-Tech Electric were processed to reconstruct instantaneous energy exchange between the traction system and the battery, identify distinct operating regimes, and derive physically interpretable empirical models of selected drivetrain relationships. The analysis focused on the traction power, battery current, battery voltage, state of charge, accelerator pedal position, and cell voltage imbalance. The recorded data were decomposed into propulsion, regenerative, and auxiliary-load-dominated operating regimes, which improved the interpretability of the measured signals and the quality of the regression-based models. A second-order model was used to describe the relationship between traction power and accelerator pedal position, while a linear current-voltage model provided a locally accurate approximation of battery electrical behavior. In addition, the dependence of the cell voltage imbalance on the battery current was analyzed as a diagnostic indicator of load-dependent battery response. The results show that auxiliary loads, especially cabin and battery heating under winter conditions, introduce a significant baseline power demand that affects the apparent drivetrain response. Within the analyzed single-trip dataset, the recorded battery signals showed a low cell-voltage imbalance and a consistent local current–voltage trend over the observed operating range. These findings should be interpreted as preliminary and vehicle-specific, since they were obtained from one short winter urban trip and from a restricted set of OBD-accessible signals. Although the study is limited to a single vehicle and a single short trip, it demonstrates that accessible real-world OBD data can support physically interpretable, exploratory analysis of electric powertrain operation and battery response under practical measurement constraints.