This article focuses on the study of the reliability of unmanned aerial vehicles (UAVs), whose role in various sectors, including the rescue sector, is dynamically increasing. The aim of the study was to analyze the key factors affecting UAV failure rate and determine their impact on the time to failure. Statistical analysis and simulations were conducted within the study, based on collected data, to investigate the relationship between the type of failure and the system's time to failure. The results of the analyses showed that the time to failure differs significantly depending on the cause, particularly for battery-related failures. It was also found that unfavorable atmospheric conditions, such as strong wind, high temperature, and high humidity, significantly shorten the system's time to failure compared to normal conditions, with this effect being similar for different types of unfavorable weather.
Mobile emission measurement systems (PEMS), according to current legal acts, can measure nitrogen oxide emission intensity using two different methods, one of which uses the chemiluminescence method and the other the ultraviolet light method. Stationary (laboratory) systems, according to the regulation, use only the chemiluminescence method. The following article analyses the results of tests obtained during WLTC tests from laboratory analysers (chemiluminescence method) with the results from two mobile analysers using nitrogen oxide analysers operating on the basis of two different methods. As a result of this analysis, the differences in the results of nitrogen oxide emissions from mobile systems compared to measurements from stationary systems in the WLTC test on a chassis dynamometer were described. The research was performed at the BOSMAL Institute of Automotive Research and Development using a passenger car equipped with a spark-ignition engine. The analysis showed differences in the results of nitrogen oxide emissions between mobile analysers for measuring nitrogen oxide emission intensity using the NDUV method and mobile analysers CLD. Measurements with mobile analysers also differ noticeably from the results obtained from stationary (laboratory) analysers. However, the greatest influence on the difference in the obtained results is the applied measurement method.
One of the commonly used methods for determining fuel consumption in internal combustion engines is based on the carbon mass balance. It assumes a direct relationship between the mass of fuel burned in the engine and the mass of emitted carbon-containing substances. Therefore, the accuracy and repeatability of fuel consumption results depend on the quality of measurement method used for determining pollutant emission. This paper focuses on the results of motor vehicle pollutant emissions and fuel consumption obtained in interlaboratory tests. Two different chassis dynamometer laboratories were compared, both using two measurement methods: 1) analysis of the concentrations of diluted exhaust components collected in bags, 2) continuous analysis of the emission intensity of diluted exhaust components. The tests were conducted in the Worldwide harmonized Light vehicle Test Cycle using a passenger car with a spark-ignition engine. Significant differences were observed in the results obtained in two laboratories. The average specific distance emission of particle mass had the highest non-repeatability, whereas the specific distance emission of hydrocarbons and carbon dioxide had the lowest. The latter led to high repeatability in fuel consumption as determined by the carbon mass balance method, particularly in the case of the method that measured the concentrations of exhaust gases collected in bags.
The article considers the issues of non-repeatability of exhaust emission and fuel consumption test results for road vehicles tested on a chassis dynamometer. Empirical results of passenger car tests on a chassis dynamometer in the WLTC (Worldwide Harmonized Light Vehicles Test Cycle) test were used. Tests were conducted in four repeated sets to assess the repeatability of the test results. The road emission of hydrocarbons, non-methane hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter and carbon dioxide, the road number of particulate matter and operational fuel consumption were determined. The coefficient of variation of the values measured in the four tests was determined, taken as a measure of the repeatability of the test results. The coefficient of variation of the road emission of carbon dioxide and operational fuel consumption is the lowest. No significant differences were found in the values of the measured exhaust emission.
The article presents an assessment of the repeatability of exhaust emission results in the WLTC test using two types of measurement systems: stationary laboratory analysers and a PEMS. The tests were conducted in laboratory conditions at BOSMAL Institute of Automotive Research and Development on a passenger car with a gasoline engine on a chassis dynamometer. The assessment included CO2, CO, NOx, THC emissions, and the particle number in each phase of the WLTC test and in the entire test. The coefficient of variation was used to assess the repeatability. The results showed greater repeatability of measurements in the case of laboratory analysers, especially for CO2 and CO. The PEMS system showed greater variability, especially in the dynamic test phases. Despite this, the results validation confirmed the compliance of the PEMS system with regulatory requirements. The article emphasizes the importance of the precision of exhaust emission tests in the context of measurement technologies development and the implementation of more restrictive emission standards, and it indicates CO2 as the most stable parameter for both systems.
The aim of this study is to quantitatively analyze the factors influencing energy consumption in unmanned aerial vehicles (UAVs) based on operational data from 177 flights of the DJI Matrice 30T drone. Battery consumption model-ling was proposed using variables available at the UAV user level. A comparison of analytical methods (linear regression, LASSO) and machine learning algorithms (Random Forest, XGBoost) was performed. The models were then evaluated using the coefficient of determination R^2 and the root mean square error RMSE. Analytical methods show moderate effectiveness (R^2 = 0.425, RMSE = 14.87%), while machine learning models show significantly higher predictive accuracy: Random Forest achieved R^2 = 0.983 and RMSE = 0.328%, and XGBoost R^2 – 0.973 and RMSE = 3.26%. The analysis of variable significance shows that the greatest impact on energy consumption is exerted by: flight time, distance traveled, and discharge current. Seasonal factors also proved to be significant, indicating the impact of weather conditions on battery discharge dynamics. The results confirm the superiority of adaptive machine learning methods over classical analytical models in forecasting UAV energy consumption based on operational data and indicate the direction for further research taking into account detailed meteorological data. Unlike previous studies, this study is based on operational data from actual UAV missions and uses only variables available from the user’s perspective. It also provides a methodical comparison of analytical approaches and machine learning algorithms on a single real-world flight log dataset and additionally considers the impact of seasonality and operating conditions on battery consumption – an aspect largely overlooked in the literature.
Efficient delivery scheduling remains a key challenge in transport logistics, especially under real-world constraints such as vehicle capacity, time windows, traffic conditions, and weather. To address this, a hybrid metaheuristic algorithm combining Adaptive Large Neighborhood Search (ALNS) and Tabu Search was developed, where an initial greedy solution is iteratively improved through global diversification and local optimization. The approach balances solution quality and computational time by integrating broad search mechanisms with focused refinements. A case study using real company data validates the method’s effectiveness in reducing route cost and improving operational efficiency. The results also highlight improved route structure and service consistency. This confirms the practical relevance of the model and its potential for broader application in logistics optimization.
The article presents the worldwide harmonized light-duty test cycle results of a diesel engine passenger vehicle carried out on a chassis dynamometer. Pollutant emissions from exhaust and fuel consumption were measured. Vehicle velocity was treated as a variable determining pollutant emissions and fuel consumption because the engine operating states depend on engine velocity and load during engine operation, and these states in turn affect pollutant emissions and fuel consumption. Actions taken to reduce pollutant emissions and consumption of fuel are often in opposition to each other. Therefore, there is a need to optimize these activities. There is also a need to know the relationship between the effects of taking specific actions that serve to achieve individual goals in order to rationalize actions aimed at reducing pollutant emissions and fuel use. The originality of the article lies in the use of the correlation theory between pollutant emission and fuel consumption as well as the processes that determine them, primarily vehicle velocity, to rationalize these activities. Pearson's linear correlation theory was used to assess the relationships between individual variables. Significant differences were found in the correlation coefficients between individual variables, which confirmed the need to take integrated actions to reduce pollutant emissions and fuel consumption.
The article considers variables registered in the WLTP procedure. The test results of a passenger car with a compression-ignition engine have been analysed. The tests were carried out on a chassis dynamometer. The tests were performed for engine cold start and ran up to the point of reaching stabilized operating conditions. The average specific distance emissionsand volumetric fuel consumption were assessed for individual test phases as well as for the entire test. It was found that the results in the first test phase, which corresponded to the engine cold start up to stabilized operating conditions, had the mostsignificant impact on the overall exhaust emission and fuel consumption results in the test. The specific distance emissions of carbon monoxide, non-methane hydrocarbons and nitrogen oxides were by far the highest in the first phase of the test. In the fourth phase of the test, the specific distance emissions of methane and carbon dioxide turned out to be the highest, as well as the operational volumetric fuel consumption being the highest.
The article presents considerations on the processes taking place in the combustion engine in the real driving operating conditions of a vehicle performing the RDE (Real Driving Emissions) test. The tests were carried out using a passenger car with a spark-ignition engine. The processes considered in the article were related to the engine operating states, exhaust emissions and fuel mass consumption, and the vehicle velocity, which determines the engine operating conditions. The RDE test was carried out using PEMS (Portable Emissions Measurement System) equipment, and the following variables were recorded: vehicle velocity, control, engine speed, relative torque and relative engine power, emission pollutant intensity of carbon monoxide, hydrocarbons, nitrogen oxides and carbon dioxide, the intensity of particle number and the fuel mass consumption intensity. The recorded signals were digitally processed, and the statistical properties of the variables and the mutual relation between the engine operating states were examined. The properties of the measured variables were investigated in the entire RDE test and in its constituent phases: the first, corresponding to vehicle traffic in cities, the second - outside cities, and the third - on highways and expressways. The pollutant specific distance emission and the particle number specific distance as well as the specific distance fuel mass consumption were determined in relation to the average vehicle velocity, and based on these results, the exhaust emissions and fuel mass consumption characteristics were created. Correlational studies of the considered variables were also performed. Pearson's linear correlation coefficients for the combinations of the measured variables were determined.
The paper presents results of considerations on the repeatability of the passenger car test results obtained in the WLTP procedure on a chassis dynamometer. The research concerned the aspects of exhaust emissions and fuel consumption. Measurements were carried out in the WLTC test with a cold engine start and then in four WLTC (Worldwide harmonized Light vehicles Test Cycle) tests with a hot engine start. The following values were measured: average specific distance emissions of hydrocarbons, non-methane hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter and carbon dioxide, specific distance particulate number, and operational fuel consumption. Thus, it was possible to assess the impact of the engine's thermal state at start-up on the test results and the nature of test results repeatability with the start-up of a hot engine. The repeatability of the test results was assessed based on the coefficient of variation obtained in the individual tests and the relationship of the maximum difference between measurement results values in the individual tests for a hot engine start. The obtained test results turned out to be very diverse for the considered parameters and indicated low repeatability. Values of carbon dioxide emissions and operational fuel consumption were definitely the least varied in individual hot engine start tests. The exhaust emission of particulate matter varied the most in individual test iterations. However, the specific distance particulate number was relatively similar between individual tests, less so than the exhaust emission of other pollutants. In the case of different engine thermal state at start-up, the emitted particulate number varied the most in the test results, while the emission of carbon dioxide and operational fuel consumption varied the least. The repeatability of executing the velocity process in WLTC tests at hot engine and cold engine start-up was also examined as processes determining exhaust emissions and fuel consumption. These tests were much more repeatable than the exhaust emission and fuel consumption.
This paper discusses emissions from plug-in hybrid vehicles under various driving scenarios and reports experimental data obtained under laboratory and real-world conditions. Two European plug-in hybrid passenger cars were tested using the two test types in use in the EU (chassis dynamometer and on-road), with some modifications. The best-case and near-worst-case battery states of charge were used for testing. Behavior in terms of CO2 emissions, regulated emissions, and unregulated emissions was characterized and analyzed. Differences were generally much greater for on-road testing, especially for urban driving, during which the potential for purely electrical propulsion of the vehicle is greatest. The long distances covered by current EU legislative test procedures limit the impacts of some effects. Regardless of the traction battery’s state of charge, regulated emissions were well below the applicable EU limits under all driving conditions - for example, combined emissions of reactive nitrogen compounds (nitrogen oxides, ammonia, and nitrous oxide) were consistently < 10 mg/km when tested under laboratory conditions. The two vehicles tested showed that the state of the battery had a large impact on the proportion of electrical propulsion and the resulting CO2 emissions, but differences in regulated pollutants decrease with increasing distance and are generally relatively limited for longer journeys, which include non-urban driving.
The article contains the research results and analysis of the processes that take place as part of a gasoline engine light duty vehicle Real Driving Emissions test. Dimensionless characteristics of exhaust emission and fuel mass consumption in the RDE test were also determined: emission intensity, particle number emission intensity, fuel mass consumption intensity. An algorithm for determining the characteristics specific distance pollutant emission, specific distance particle number and specific distance fuel mass consumption in the vehicle speed domain in the RDE test was presented using the Monte Carlo method. The determined characteristics were approximated by polynomial functions in the form of sets of points. These relationships were characterized by a large dispersion of values, which was primarily due to the fact that the random values of the averaging limits contain very different engine operating conditions.
Exhaust emissions testing of vehicles under real driving conditions (real driving emissions, RDE) using portable exhaust emissions measurement systems (PEMS) was introduced a few years ago by the European Commission as a mandatory test during type approval and later also for in-service conformity. This paper compares results from mobile systems for measuring exhaust gas emissions (PEMS) with a stationary laboratory (BOSMAL’s Exhaust Emissions Testing Laboratory). The tests were carried out using a passenger car equipped with a spark ignition engine, which was tested on a chassis dynamometer over the WLTC cycle. The results showed that the differences between PEMS analysers and stationary analysers range from a few percent to a dozen or so percent, depending on the component and the measurement method.
The article presents a method of determining the characteristics of exhaust emissions and fuel mass consumption in real driving conditions based on a single test using the Monte Carlo method. The exhaust emission characteristics used are the relations between the emissions and the average vehicle speed, and the characteristic of the fuel mass consumption is the dependence of the fuel mass consumption at the average vehicle speed. The results of empirical research of a passenger car with a spark-ignition engine in the RDE test were used. The use of the Monte Carlo method made it possible to select the initial and final moments of averaging the process values, thanks to which it was possible to determine the discrete values of the characteristics for various values of average vehicle speeds. The determined discrete characteristics of the particulate mass and number emissions and fuel mass consumption relative to the average vehicle speed were approximated by polynomial functions of the second and third degree. The determined discrete characteristics, presented as sets of points, were characterized by a relatively small dispersion in relation to their polynomial approximations. The average relative deviation of the points of discrete characteristics from the value of the polynomial was in most cases small – less than 4%, only in the case of the number of particles emitted deviated from this, as the average relative deviation of the measured points from the determined polynomial was nearly 14%. Combined with the results of RDE empirical studies, the Monte Carlo method proved to be an effective method for determining the characteristics of exhaust emissions, measured in real vehicle operating conditions. The main advantage of the proposed method was a significant reduction in the actual workload necessary to carry out the empirical research – where it became possible to determine the characteristics in a large range of vehicle average speed values with just one drive test. Using standard methods of measuring this type of data, it would be necessary to conduct multiple tests, driving at different average vehicle speeds.
The search for substitutes for modern fossil fuels incentivises the use of new propulsion systems (hybrid or electric) and the use of new fuels (gaseous, mainly hydrogen). The article discusses the basic issues related to hydrogen fuel: from its extraction, through the discussion of its properties to its use and applications. Analyzes of the energy consumption involved in its extraction or production were presented, classifying hydrogen in those terms. Great emphasis was placed on design solutions for the use of hydrogen in internal combustion engines, together with discussing the concept of its combustion. The methods of storing hydrogen in a condensed and compressed form were also presented, indicating at the same time the most modern solutions available, such as mixed systems – storage in cryo-compressed form. It has been shown that the combustion of hydrogen in internal combustion engines increases their efficiency, and at the same time significantly reduces the exhaust emissions of toxic gases – including the emission of nitrogen oxides.
The use of comfort systems, the number of which in vehicles is constantly increasing, has a direct impact on fuel consumption and engine load. As part of the article, the vehicle's drive in real operating conditions was analyzed in terms of the emission of toxic compounds. The tests were carried out without and with the systems turned on, using the PEMS apparatus, where road emissions of carbon dioxide, carbon monoxide, hydrocarbons, nitrogen oxides and solid particles were measured in terms of mass, number and size distribution of diameters. The track was driven four times with different setting of the powertrain of examined car. The differences concerned the number of comfort systems in the vehicle and the mode of operation of the combustion engine.
The paper describes the method of determination of exhaust emission characteristics from a vehicle engine based on the results obtained in a driving test simulated on an engine dynamometer. These characteristics are the relations between the specific distance emissions and the zero-dimensional characteristics of the process of vehicle velocity: the average velocity value and the average value of the absolute value of the product of vehicle velocity and acceleration. The exhaust emission characteristics are used to simulate the emissions from vehicles operating in different types of traffic conditions. The engine operating states in the engine dynamometer tests were determined by the operating conditions of the vehicle during the test. The authors applied the Monte Carlo method in order to determine the characteristics of different values of the zero-dimensional characteristics of the vehicle velocity process. This enabled the determination of the characteristics based on the test results from a single realization of the process of vehicle velocity. Additionally, the developed method allowed a replacement of the empirical research on the chassis dynamometer with the one performed on the engine dynamometer. The obtained exhaust emission characteristics are in line with the characteristics obtained on the chassis dynamometer in multiple tests.
Internal combustion engines represent the largest share of motor vehicle propulsion types. Despite the introduction of alternative drives (hybrid and electric), combustion engines will continue to be the main factor in the development of transport. Therefore, work related to their technological development and reduction of their harmful effects on human health and the environment is required. The development of internal combustion engines can be seen in two directions: technological changes resulting in increased efficiency of such engines and the second direction connected with limitation of exhaust gas emission. The present work is included in the second direction of research interests and concerns the analysis of various operating conditions of internal combustion engines. The operating states, both static and dynamic, determine the operational properties of internal combustion engines, such as fuel and energy consumption as well as pollutant emissions. Sofar, such operating conditions have only been mapped on a chassis dynamometer in various homologation tests. The course of the type approval test was known and the conditions of measurement were also known, which made it impossible to introduce a random factor into such tests. Currently, these properties are determined in tests performed in real vehicle operating conditions – RDE (Real Driving Emissions). Such tests are representing real operating conditions of motor vehicles. Limitations for performing tests in real traffic conditions are, apart from formal requirements concerning the duration and distance of individual parts, the dynamic conditions of vehicles determined by the speed and acceleration of the vehicle. The study analyzed the properties of vehicle speed processes and engine operating states in the RDE test, taking into account its individual phases – driving in urban, rural and motorway conditions. Engine operation states are the processes of the engine rotational speed and its relative torque. It was found that the dynamic properties of the vehicle speed process are much more significant than the engine operating states. It was also found that the road emission of pollutants in the RDE test, which is the property of vehicles measured in the test, the motorway phase properties have greatest impact.
Biofuel use is one of the basic strategies to reduce the negative impact of aviation on the environment. Over the past two decades, a number of biofuels produced from plants, lubricants and maintenance products have been developed and introduced. New fuels must have specific physicochemical parameters and meet stringent standards. his article presents a comparative analysis of the exhaust emissions measurement results from jet engines powered by traditional aviation kerosene and its blends with ATJ (Alcohol to Jet) biofuel. The concentrations of carbon dioxide, carbon monoxide and hydrocarbons were measured. Measurements were conducted in laboratory conditions for various engine load values. Based on the analysis, it was found that the use of biofuel increases the concentration of carbon monoxide and hydrocarbons in the exhaust gas relative to aviation kerosene. The use of biofuel did not result in an increase in fuel consumption and related carbon dioxide emissions. Based on the conducted research, it was found that biofuel use did not affect the ecological properties of the engine significantly. In addition, a correlation analysis of the measurement results from both engines was carried out.
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