Vol 19, No 3 (2025)

BACKGROUND: For oil well pumps, an important parameter is the inlet gas content in the pumped liquid before entering the pumping module. Exceeding the permissible gas content leads to a decrease in the pump pressure and disruption of the supply. Modeling of this process with analytical tools only is very difficult due to the complexities of the gas separation process and the nonlinear geometry of the flow part, whereas, experimental research is very expensive. Therefore, one of the most promising solutions to this problem is the use of modern computational fluid dynamics tools that are capable of considering most of these factors and significantly cheaper.

AIM: Development of a design geometry, the consideration of which is necessary for high-quality modeling of the gas separator working process. Determination of a list of mathematical models that need to be considered.

METHODS: This study uses a numerical simulation method based on solving discrete analogues of the basic equations of hydrodynamics and multiphase flow.

RESULTS: Key elements of the gas separator geometry, necessary to be considered, are defined. The mathematical model, which simulates the separation process accurately, is built.

CONCLUSION: Based on the study results, it can be argued that it is necessary to include a gas separator in the calculation of the casing pipe in the hydrodynamic modeling in order to consider two key flow modes in the pipe: recirculation and fountain.

BACKGROUND: The study of internal combustion engine (ICE) processes has traditionally relied on costly and time-consuming physical experiments. Despite the widespread development and application of modern computer modeling methods (CFD, detailed chemical kinetic modeling) in global practice, the task of creating effective tools for operational engineering analysis, especially for the specific class of automotive and tractor diesel engines and alternative fuels, remains relevant.

AIM: Development of a mathematical model and analysis of the parameters of the working process of an automotive internal combustion engine operating on biofuel blends.

METHODS: The research methods were empirical analysis, analytical calculation, validation of calculated and experimental data. A zero-dimensional thermodynamic model of the diesel engine cycle was developed. Analytical calculations and plotting of graphs were performed using both standard applications and original author’s programs.

RESULTS: It was found that the introduction of additional ingredients into the main mineral fuel, one of which is highly reactive and the other is energy-saturated, causes an increase in the energy properties of the composition – reduces the time of preparatory reactions. Considering the fact that the motor characteristics of a mixture of alcohol with rapeseed or colza oil are almost equal to the characteristics of gasoline, mathematical models tested in studies of diesel operation on mixtures of diesel fuel and gasoline were used in determining the characteristics of the rapid combustion phase (RCP). However, in all cases, changes in the physical and chemical properties of the new compositions were taken into account.

CONCLUSION: The results showed that adding biocomponents (up to 25%) to diesel fuel increases the severity of the combustion process by 6–12%, which can lead to an increase in dynamic loads on engine components. At the same time, the developed model demonstrates high consistency with experimental data and allows optimizing the composition of fuel mixtures to reduce emissions. The main limitation of the study is the lack of long-term data on the effect of biofuels on engine life. Prospects for the work are associated with expanding the model for other types of internal combustion engines, analyzing combined additives, and assessing the economic feasibility of switching to biofuels.

BACKGROUND: More efficient on-board energy consumption has allowed hybrid powertrains to become firm in the market.

The conditions for using a hybrid powertrain as part of small-scale mechanization vehicles intended for off-road use differ significantly from the conditions for use in road vehicles.

The development of this type of transmission design, the control system and the algorithm for its efficient operation is a relevant technical problem.

AIM: Study of the possibilities of using neural network learning in estimating the vertical force in contact patches of wheels to create algorithms for efficient control of the hybrid powertrain of an all-terrain vehicle.

METHODS: Modeling of operation conditions is performed in the MATLAB software and its applications Simulink and Neural Network. Using fundamental blocks of these applications, a model of the hybrid-powered three-axle all-terrain vehicle motion on uneven solid support surface is built.

RESULTS: Based on the results of testing the work of the trained neural network, using the simulation modeling method, a conclusion was made about the sufficient accuracy of the indirect estimation method. The root-mean-square deviation of the determined forces from those obtained in the motion model was 9.5%.

CONCLUSION: The practical value of the study lies in the possibility of using the proposed approach to determining the vertical force in the contact patch of the wheel with a solid support surface when developing laws for the efficient control of the electric drive of the third axle of an all-terrain vehicle with a hybrid powertrain.

BACKGROUND: Controlling robotic platform (RP) with multiple servo drives in difficult conditions, such as areas of man-made or natural disasters, requires significant effort from the operator. Therefore, automating the motion control of RP can improve task efficiency and reduce the operator’s workload, especially when overcoming large obstacles.

AIM: Enhancement of the mobility of a robotic platform by developing a comprehensive motion control law focused on automating obstacle navigation in low-visibility conditions.

METHODS: To create the motion control law, a computer simulation model, enabling the study of RP dynamics on a surface with a complex profile in a close to “real-time” mode, was developed. The proposed control law is based on a finite-state machine approach and includes four modes: manual control, automated obstacle overcoming, transport mode, and stepping mode. A key feature of this control law is the use of the environmental data obtained by analyzing force factors at the wheel axles during motion. This approach allows the developed control law to be applied in low-visibility conditions, unlike the algorithms relying on computer vision, which can be crucial for operation in disaster zones. The effectiveness of the developed control law was evaluated by overcoming typical obstacles (ledges, cliffs, ditches) through a comparison of automated and manual control results in virtual tests.

RESULTS: The proposed control law demonstrates significant advantages when using the automated obstacle-overcoming mode compared to manual RP control, both in terms of motion energy efficiency and maneuver execution time (average velocity). Additionally, the use of a force-sensing wheel system and automated drive control ensures better safety, even in low-visibility conditions.

CONCLUSION: The proposed control law significantly improves obstacle navigation efficiency, reducing the operator’s workload and enhancing RP safety in challenging environments. Further research involves conducting field tests to adapt the system to real-world robotic systems.

BACKGROUND: Algeria has historically relied on its abundant oil and gas reserves, yet in recent years has begun transitioning toward low-carbon development. With high levels of solar irradiation, the country considers photovoltaic (PV) generation to be the most promising renewable energy option.

AIM: Presentation of the current state of Algeria’s public EV-charging network, detailing the number of chargers now installed, their power ratings and their uneven geographic distribution. Study of how co-locating PV systems with those chargers might relieve stress on the national grid, lower operating costs and reduce CO₂ emissions. Development of a set of technical and economic scenarios—ranging from micro-siting a single fast-charging station to planning grid-wide integration—as a basis of national policy and future investment.

METHODS: Researchers combined official fleet, road and fuel data with literature sources, then compared insolation in provincial area to define prime PV sites. A mixed integral optimisation that sizes PV, batteries and power converters for one fast-charging station under variable sun and demand conditions was conducted. A grid-wide load-flow was studied to see how mass EV use affects stability and lifecycle carbon.

RESULTS: Only a few public chargers, clustered in the north of Algeria, exist today. Reaching ~328 000 EVs (≈ 8% of the light-duty fleet) by 2030 could displace 1.9 Mt of gasoline but add 3.6 TWh—≈ 5% of 2017 generation — to the grid. Ensuring most of that energy with solar needs about 330 000 modules (300 W each, 660 ha) and US $ 710 million, which is under 3% of the expected economic gain from electrification. Ten big PV plants in the south feeding AC lines to DC fast-charge hubs in northern cities emerges as the lowest-cost layout [18], saving 0.3 billion m³ of gas yearly and helps avoiding peaks of demand when storage is right-sized.

CONCLUSION: Algeria’s insolation and surging road traffic make PV-powered charging both viable and profitable. Despite of difficulties, coordinated state-industry-researchers action could turn Algeria into a regional sustainable mobility leader.