Energy consumption in electric vehicles is a key element of their operation, determining energy efficiency and one of its main indicators, i.e., range. Therefore, in this article, mathematical models were developed to evaluate the impact of selected factors on energy consumption in electric vehicles. The phenomenon of energy recuperation was also examined. The study used data from mileage measurements of the electric vehicle (EV) driving on a motorway and in built-up areas. The results obtained showed a strong correlation between acceleration, vehicle speed, battery power, and energy consumption. In urban conditions, engine RPM and vehicle speed had an additional impact on energy consumption. Findings from this study can be used to optimize vehicle acceleration control modules to increase their range, develop eco-driving styles for EV drivers, and better understand the energy efficiency factors of EVs.

This paper investigates the emission characteristics of hydrogen-enriched gasoline (95G5H₂) under dynamic driving situations in order to fulfill the growing need for cleaner and more efficient automobile fuels. This study aimed to investigate the impact of hydrogen addition on pollutant-specific emissions, including CO, CO₂, HC, and NO_x, using a Nissan Qashqai that ran on both pure gasoline (100G) and 95G5H₂. Emission statistics were obtained by computer simulations of the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) applied using AVL CRUISE software. The paper presents a method of comparing the characteristics of pollutants emitted by the combustion engine and comparing the pollutants emitted when powered by regular fuel and fuel with hydrogen. The tests were performed in real conditions, and the presented method shows the amount of pollutants emitted when the vehicle is directly in motion, which allows for effective comparison of the amount of pollutants emitted for different fuels. 95G5H₂ sharply reduces CO-, CO₂-, and HC-specific emissions by 22.19%, 14.55%, and 35.46%, respectively, when compared to 100G. However, NO_x-specific emissions increased by 20.17%, suggesting a compromise between higher combustion efficiency and higher burning temperatures. The study shows that 95G5H₂ fuel performs better in urban driving cycles, including plenty of acceleration and deceleration, which usually results in incomplete combustion. Although additional refinement is needed to cut NO_x-specific emissions, the results demonstrate that hydrogen-enriched fuels have considerable potential to lower vehicle-specific emissions. The significant conclusions of the study on the advantages of hydrogen-enriched fuels, both practically and environmentally, will help in the future development of environmentally friendly transportation solutions.

The article presents the possibility of verifying the efficiency of a diesel particulate filter (DPF) with the use of particle counters using two different measurement methods. The tests were carried out at a vehicle inspection station using a condensation particle counter (CPC) and a diffusion charger (DC). This article presents the results of measurements of 50 vehicles. Removal of the diesel particulate filter from a vehicle is prohibited but is a known phenomenon throughout the EU. The task of periodic technical inspections is to eliminate vehicles that are inoperative and do not meet the environmental protection requirements. However, to date, European vehicle inspection stations do not have an effective tool to counter tampering with diesel particulate filters. The performed measurements allowed us to prove the hypothesis that both methods of measurement allow the effective confirmation of the presence of DPF in a vehicle during the periodic technical inspection of the vehicle and verification of the quality of its operation. In addition, the advantages and disadvantages of both measurement methods were assessed.

Using the standardised SORT, the article analyses instantaneous energy consumption and recuperation processes in an electric bus. The test includes three scenarios: SORT 1 (heavy urban traffic), SORT 2 (mixed driving conditions), and SORT 3 (suburban routes), enabling precise assessment of the energy efficiency of vehicles while eliminating environmental variables. The recuperation system significantly enhances energy efficiency, though its effectiveness varies based on the driving scenario. Modelling methods were compared as follows: linear regression, KNN algorithms, and neural networks, achieving a high fit (R² > 90%). While KNN and neural networks were better at reproducing nonlinearities, they indicated the need for additional variables and time delays to enhance accuracy. The article sets itself apart by incorporating predictive models and examining recuperation efficiency across various scenarios. It emphasizes the importance of combining SORT results with real operational data and developing adaptive energy management systems. The results indicate the potential for optimizing electric buses for public transport, including route planning and further improving recuperation technology, which can significantly reduce energy consumption and greenhouse gas emissions.

Assessing vehicle emissions is crucial for understanding their environmental impact and developing effective emission reduction strategies. This article discusses modern research tools that combine traditional laboratory measurements on chassis dynamometers with advanced theoretical models. Probabilistic methods, including stochastic processes based on Markov and semi-Markov chains, are important tools for modelling driving cycles, considering the variability of road conditions and driver behaviour. The article also presents mathematical approaches to emission data analysis, considering both the states of the technical system and the transitions between them, which allows for precise modelling of real vehicle operating conditions. Ultimately, the synergy of experimental measurements with computational modelling offers a more complete and accurate tool for assessing pollutant emissions, which is crucial in global efforts to improve air quality.

The progression of passenger vehicles is progressing, and regulations are continually being revised, resulting in a decrease in car exhaust emissions. The European Commission has revised the RDE test procedure to include exhaust emissions during a cold start, as part of package 3. The article carried out simulations using COPERT software, which uses tests based on WLTP, assuming ambient temperatures from -10◦C to +20◦C, at intervals of 5◦C. This paper aims to present the results of mathematically modelling the influence of ambient temperature on the cold-start emissions of carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOC), hydrocarbons (treated as Volatile organic compounds - VOC), total particulate matter (TSP) and particle number (PN) in passenger cars and light-duty vehicles. The modelling results show that a change in ambient temperature significantly affects carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOC), hydrocarbons (treated as Volatile organic compounds - VOC), total particulate matter (TSP) and particle number (PN) in cold-start emissions.