Simulation Test Results Research Articles

Characteristics of coal crack development and gas desorption in the stress affected zone of rock pillar

Coal (Rock) pillar retaining in the mining of protective layer would cause gas dynamic disaster in the protected layer. Based on the gas geological conditions of the two-layer coal seam in Jinhe Coal Mine of Yaojie Mining District, the stress evolution law of coal seam in the rock pillar affected area was studied by theoretical analysis and numerical simulation, and the crack development law of coal seam in different loading stages under conventional triaxial loading was studied by CT scanning technology. With the analysis of the stress evolution and crack development of coal in rock pillar affected area, the gas extraction effect under different stress states and the gas desorption law after pressure relief antireflection were studied on site. The results showed that the stress of coal in the rock pillar affected area is in the approximate elastic stage of the conventional triaxial stress-strain curve, and the cracks of coal are mainly closed at this stage. Meanwhile, the increase of stress leaded to the decrease of coal permeability and the poor gas extraction effect. CT scanning tests under conventional triaxial loading were carried out in the laboratory, and three-dimensional visual models of coal sample cracks were constructed at different loading stages. When loading to the linear elastic stage, the crack volume and surface area were reduced by 74% and 71% compared with the ones in initial state. At the same time, the expression between stress σ and crack density T was further established. After comprehensive control measures such as intensive drilling discharge, presplitting blasting and coal water injection were taken to the coal in rock pillar affected area, the crack density T could reach the crack development level of the conventional triaxial loading softening stage, realizing the crack development of the coal under low stress. The enclosed gas in front of the coal could desorption flow during the roadway driving. And the predict index value K1 also decreased from 0.57 mL/(g·min1/2) to 0.17 mL/(g·min1/2) continuously. The safety of coal roadway in rock pillar affected area was realized, and the accuracy of numerical simulation and laboratory test results was verified, which had certain reference significance for coal roadway excavation under this similar conditions.

The Fusiongram: a periodic weak fault feature extraction strategy and its application in bearing fault diagnosis

Abstract The weak periodic transient impact responses caused by localized defects in rolling bearings are often obscured by complex interferences, such as white noise, random transient impact responses, and periodic responses from system operations. Meanwhile, the fault feature information contributing to damage detection may be distributed across different frequency bands in the vibration signal. Therefore, under the influence of complex interference, it is a challenging problem regarding how to 1) accurately select the frequency bands containing rich fault feature information, 2) effectively extract damage information from different frequency bands, and thereby, 3) successfully achieve fault diagnosis for machinery condition monitoring. To address these issues, this research introduces a novel signal processing strategy, termed as Fusiongram, for extracting weak periodic fault features amidst the influence of complex interferences. Firstly, the method of complementary hierarchical decomposition is proposed, in which the signal is decomposed into multiple components with overlapping frequency contents. Then, an index with interference resistance is constructed to select the components carrying rich damage feature information. Finally, the adaptive threshold denoising and multicomponent normalized averaging techniques are employed to fuse the information from the squared envelope spectra of the selected components, thus obtaining the reconstructed squared envelope spectra for fault diagnosis. The Fusiongram is able to achieve the goal of weak fault feature extraction from signals with complex interference. The analysis results of numerical simulation and experimental testing verify the effectiveness and advantages of the proposed strategy.

Estimation and research of the temperature field models of large space spherical mesh shell structures under localized fire

This paper firstly investigated fire dynamics characteristics and the temperature field distributions of large space spherical mesh shell (SMS) structures under localized fire in FDS, and divided the temperature fields into plume region, smoke accumulation region and ceiling jet region. Based on the classical axisymmetric plume model, the predictive models for the steady-state and transient temperature fields in different fire regions for large space SMS structures were proposed in this paper. Thereafter, the proposed temperature models were compared with the simulated results and experimental test results by other scholars, and they were in good agreement. In order to further discover the realistic fire development progress and temperature distribution of large space fire, and validate the proposed temperature field models, this paper designed and conducted three full-scale large space fire tests (Test-1 ∼ Test-3) with different fire source powers in a large space building. Results showed that temperature fields of large space fires could be consisted of near-fire region (Flame region) and far-fire region (Plume region and Ceiling jet region). The steady-state fire source powers were tested for 443 kW, 886 kW, 1090 kW for Test-1, Test-2 and Test-3, respectively, while their maximum temperatures of the roof reached 75 °C, 105 °C and 120 °C. Based on McCaffrey plume model, we further proposed the transient temperature model in flame region for large space structures, and its accuracy was verified by the test results. Moreover, the proposed steady-state and transient temperature fields for large space SMS structures were compared with the tested temperature field data, and the tested and predicted temperature curves were generally in good agreement in plume and ceiling jet regions. Finally, the test results aimed to provide a scientific basis and reference for the fire safety and structural fire-resistant design of large space buildings.

Fault location method for new distribution networks based on waveform matching of time–frequency travelling waves

AbstractSome existing fault location methods for distribution networks rely too much on the local wave head information of the time or frequency domain signals, making it difficult to adapt to the increasingly complex structure and operating conditions of the distribution network after the new energy access. For improvement, the travelling wave (TW) time and frequency ranges that can effectively avoid waveform distortion caused by new energy access are analysed. The one‐to‐one matching relationship between the TW waveforms in these ranges and the fault positions is revealed. A fault TW time–frequency matrix with specific time and frequency windows is constructed, and a new distribution network fault location method is proposed based on the matching technique of waveform features, which realises the accurate fault location by exploring the proportionality between the cumulative trend of the matrix energy amplitude deviation and the fault point position. Simulation test results show that the proposed method is not affected by the complex structure of distribution networks such as new energy access and overhead‐cable line mixing on fault location and flexibly transforms the fault location problem into a time–frequency TW waveform matching problem, which improves the accuracy and robustness of the fault location for new distribution networks to a degree.

Signal Denoising Method Based on EEMD and SSA Processing for MEMS Vector Hydrophones

The vector hydrophone is playing a more and more prominent role in underwater acoustic engineering, and it is a research hotspot in many countries; however, it also has some shortcomings. For the mixed problem involving received signals in micro-electromechanical system (MEMS) vector hydrophones in the presence of a large amount of external environment noise, noise and drift inevitably occur. The distortion phenomenon makes further signal detection and recognition difficult. In this study, a new method for denoising MEMS vector hydrophones by combining ensemble empirical mode decomposition (EEMD) and singular spectrum analysis (SSA) is proposed to improve the utilization of received signals. First, the main frequency of the noise signal is transformed using a Fourier transform. Then, the noise signal is decomposed by EEMD to obtain the intrinsic mode function (IMF) component. The frequency of each IMF component in the center further determines that the IMF component belongs to the noise IMF component, invalid IMF component, or pure IMF component. Then, there are pure IMF reserved components, removing noisy IMF components and invalid IMF components. Finally, the desalinated IMF reconstructs the signal through SSA to obtain the denoised signal, which realizes the denoising processing of the signal, extracting the useful signal and removing the drift. The role of SSA is to effectively separate the trend noise and the periodic vibration noise. Compared to EEMD and SSA separately, the proposed EEMD-SSA algorithm has a better denoising effect and can achieve the removal of drift. Following that, EEMD-SSA is used to process the data measured by Fenhe. The experiment is carried out by the North University of China. The simulation and lake test results show that the proposed EEMD-SSA has certain practical research value.

Trajectory tracking control of a four-bar linkage prosthetic knee with magnetorheological damper

In order to improve biomimicry, a four-bar linkage prosthetic knee with magnetorheological (MR) damper was developed in this paper. The principle and structure of four-bar linkage MR prosthetic knee was introduced and its kinetic model was established. A MR damper matching the proposed prosthetic knee was designed, fabricated and tested, and the forward and inverse mechanical model were conducted. In addition, to solve the problems of complex model, poor bionics and low trajectory tracking accuracy in the MR prosthetic knee, a PD-type iterative learning control (ILC) controller was developed. The simulated and experimental test results show that the positive maximum error of the knee joint swing trajectory based on PD-type ILC controller are 2.2°(speed of 0.5 m/s), 4.1°(speed of 1.0 m/s), and 1.9°(speed of 1.5 m/s), respectively, and the negative maximum error of that are −1.4°(speed of 0.5 m/s), −6.7°(speed of 1.0 m/s), and −5.5°(speed of 1.5 m/s), respectively, which effectively tracks the reference swing trajectory.

Deformation-Adapted Spatial Domain Filtering Algorithm for UAV Mining Subsidence Monitoring

Underground coal mining induces surface subsidence, leading to disasters such as damage to buildings and infrastructure, landslides, and surface water accumulation. Preventing and controlling disasters in subsidence areas and reutilizing land depend on understanding subsidence regularity and obtaining surface subsidence monitoring data. These data are crucial for the reutilization of regional land resources and disaster prevention and control. Subsidence hazards are also a key constraint to mine development. Recently, with the rapid advancement of UAV technology, the use of UAV photogrammetry for surface subsidence monitoring has become a significant trend in this field. The periodic imagery data quickly acquired by UAV are used to construct DEM through point cloud filtering. Then, surface subsidence information is obtained by differencing DEM from different periods. However, due to the accuracy limitations inherent in UAV photogrammetry, the subsidence data obtained through this method are characterized by errors, making it challenging to achieve high-precision ground surface subsidence monitoring. Therefore, this paper proposes a spatial domain filtering algorithm for UAV photogrammetry combined with surface deformation caused by coal mining based on the surface subsidence induced by coal mining and combined with the characteristics of the surface change. This algorithm significantly reduces random error in the differential DEM, achieving high-precision ground subsidence monitoring using UAV. Simulation and field test results show that the surface subsidence elevation errors obtained in the simulation tests are reduced by more than 50% compared to conventional methods. In field tests, this method reduced surface subsidence elevation errors by 39%. The monitoring error for surface subsidence was as low as 8 mm compared to leveling survey data. This method offers a new technical pathway for high-precision surface subsidence monitoring in mining areas using UAV photogrammetry.

A Novel Shunt Zigzag Double-Tap Low-Harmonic Multi-Pulse Rectifier Based on a Three-Stage Power Electronic Phase-Shifting Transformer.

To solve the problem of the large size of traditional industrial frequency phase-shift transformers and the harmonic distortion of multi-pulse wave rectifier systems, this paper proposes a three-stage shunt zigzag power electronic phase-shift transformer based on a double-tap multi-pulse wave rectifier, which combines the power factor correction (PFC) converter with the voltage-type SPWM inverter circuit to form a power electronic converter to realize the frequency boost and power factor correction. Through AC-DC-AC conversion, the frequency of the three-phase AC input voltage is increased, the number of core and coil turns in the transformer is reduced to reduce the size of the phase-shifter transformer, a zigzag structure of the phase-shifter transformer is used to solve the unbalanced distribution of current between the diode bridges, and a passive harmonic suppression method on the DC side is used to generate a loop current by using a group of single-phase rectifier bridges to regulate the input line current of the phase-shifter transformer. The phase-shifted voltage is input into two three-phase diode rectifier bridges to rectify and supply power to the load. Simulation and semi-physical test results show that the proposed method reduces the total harmonic distortion (THD) value of the input current of the phase-shifted transformer to 7.17%, and the THD value of the grid-side input current is further reduced to 2.49%, which meets the harmonic standard and realizes the purpose of power factor correction as well as being more suitable for high-power applications.

Research on Optimal Driving Torque Control Strategy for Multi-Axle Distributed Electric Drive Heavy-Duty Vehicles

Multi-axle distributed electric drive heavy-duty vehicles have the characteristics of high transmission efficiency, strong maneuverability, and good passability, making them widely used in large cargo transportation. However, the current driving torque control strategies of multi-axle distributed electric drive heavy-duty vehicles lack comprehensive consideration of their longitudinal and lateral dynamic characteristics, making it difficult to comprehensively optimize multiple performances such as power economy, comfort, and stability. In order to solve the above problems, This work focuses on a five-axle distributed electric drive heavy-duty vehicle. Firstly, given the differences in dynamics between two-axle vehicles and multi-axle vehicles, the dynamic model of the multi-axle distributed electric drive heavy-duty vehicle and its critical components is constructed. Then, by analyzing the characteristics of power economy, comfort, and stability of the multi-axle distributed electric drive heavy-duty vehicle, an optimal driving torque control strategy based on multiple performance coordination is proposed. Finally, on the hardware-in-the-loop (HiL) platform, the performance of the optimal driving torque control strategy proposed in this paper is verified by using the China Heavy-Duty Commercial Vehicle Test Cycle for Truck (CHTC-HT) and a straight-line acceleration driving condition on a split friction road. The simulation test results show that, compared with the traditional torque average distribution strategy, the proposed optimal driving torque control strategy can reduce the energy consumption rate by 3.45% in CHTC-HT. The strategy is attributed to the driving torque distribution based on the vehicle’s optimal instantaneous energy consumption, and vehicle comfort is also ensured by the driving mode switching frequency suppression. Subsequently, the vehicle’s stability on the split friction road is effectively improved by the torque coordination compensation strategy. This control strategy significantly improves the comprehensive performance of multi-axle distributed electric drive heavy-duty vehicles.

An Application of Uncertainty Quantification to Efficiency Measurements and Validating Requirements through Correlating Simulation and Physical Testing Results.

Validation is a critical aspect of product development for meeting design goals and mitigating risk in the face of considerable cost and time commitments. In this research article, uncertainty quantification (UQ) for efficiency testing of an Electric Drive Unit (EDU) is demonstrated, considering confidence in simulations with respect to the validation campaign. The methodology used for UQ is consistent with the framework mentioned in the guide to the expression of uncertainty in measurement (GUM). An analytical evaluation of the measurement chain involved in EDU efficiency testing was performed and elemental uncertainties were derived, later to be propagated to the derived quantity of efficiency. When uncertainties were associated with measurements, the erroneous measurements made through sensors in the measurement chain were highlighted. These results were used for the assessment of requirement coverage and the validation of test results.

Assisting autonomous precision medical rehabilitation through gesture recognition devices

With the aging of the population and the increase of various chronic diseases, there is a growing demand for effective and accessible medical rehab solutions. In order to overcome the above problems, this project innovatively adopts the gesture recognition technology to design and fabricate the realization of an autonomous accurate medical rehab gesture recognition assistance system. In terms of hardware, this paper uses Arduino as the main controller, Paj7620 as the gesture recognition device, and OLED 0.96 display as the system display. In terms of software, this paper utilizes Arduino IDE software to successfully write the code and realize all the functions. In terms of combining with actual medical rehab needs, the team chose elbow fracture rehab as a typical type of rehab, and designed a three-device obtuse triangle placement scheme for precise monitoring of rehab training. Initial simulation test results show that over 70% of participants reported an improvement in their rehabilitation outcomes, and about 90% found the system easy to use. The results of this project will directly benefit patients requiring long-term rehabilitation.

Solving satellite image data downlink scheduling problem with family attribute via a bi-stage differential evolutionary algorithm

Due to the asynchronous development of observation and transition capabilities, the original image data (OID) obtained by a one-time observation cannot be completely transmitted in one transmission cycle between the EOS and GS, which is named a visible time window (VTW). First, it is needed to segment the OID into several segmented image datasets (SIDs), which are then transmitted in several VTWs. Furthermore, this can cause the satellite image data downlink scheduling problem (SIDSP). This study defines an innovative SIDSP as a satellite image data downlink scheduling problem with the family attribute (SIDSPFA), where massive OID are segmented using a fast segmentation operator, and all SIDs and other no-segmented OID are transmitted in the second step. In addition, two optimization objectives, namely the failure rate (FR) and Segmentation Time (ST) of the image data transmission, are defined to formalize the SIDSPFA as a bi-objective discrete optimization model. Further, a bi-stage differential evolutionary algorithm (DE-CD) is developed. The results of the extensive simulation tests verify the efficiency of the models, strategies, algorithms, and operators used in this study.

Application of an offline grey box method for predicting the manoeuvring performance

The prediction of manoeuvring performance for safe navigation and effective design of ships increasingly depends on artificial intelligence (AI), mainly digital twin technology. This technology requires a digital model of the physical ship. The hydrodynamic coefficients and parameters of these models are commonly obtained through two experimental methods: the planar motion mechanism (PMM) and the circular motion test (CMT). These methods are time-consuming and expensive, which may not be feasible during the early stages of the design process. This study investigates a cost-effective alternative approach to these methods by implementing a grey box method on ships. For the first of these implementations, a full-scale tanker ship was applied with artificial training data of zigzag manoeuvres. A validation study was carried out by comparing the simulation and free-running model test results of the tanker. For the second of these implementations, a scale model of a car carrier was selected, and several numerical search methods were combined to obtain a more accurate digital model. The 3-degree-of-freedom (DOF) Manoeuvring Modelling Group (MMG) models identified through this combination were validated with simulations and compared with the free-running model test results for various manoeuvres. The contribution of this study lies in the accurate capture of the manoeuvring characteristics of the physical model, which is achieved through the use of the adjustment interval and the combination of various numerical search method of the grey box method. Consequently, the developed model can be used in future studies as a faster decision-making tool for determining the straight-line stability or instability of a ship in the ship design and in predicting the manoeuvring performance of the ship.

Three-dimensional internal multiple elimination in complex structures using Marchenko autofocusing theory

Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media. They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image. With the development of seismic exploration into deep and ultradeep events, especially those from complex targets in the western region of China, the internal multiple eliminations become increasingly challenging. Currently, three-dimensional (3D) seismic data are primarily used for oil and gas target recognition and drilling. Effectively eliminating internal multiples in 3D seismic data of complex structures and mitigating their adverse effects is crucial for enhancing the success rate of drilling. In this study, we propose an internal multiples prediction algorithm for 3D seismic data in complex structures using the Marchenko autofocusing theory. This method can predict the accurate internal multiples of time difference without an accurate velocity model and the implementation process mainly consists of several steps. Firstly, simulating direct waves with a 3D macroscopic velocity model. Secondly, using direct waves and 3D full seismic acquisition records to obtain the upgoing and downgoing Green’s functions between the virtual source point and surface. Thirdly, constructing internal multiples of the relevant layers by upgoing and downgoing Green’s functions. Finally, utilizing the adaptive matching subtraction method to remove predicted internal multiples from the original data to obtain seismic records without multiples. Compared with the two-dimensional (2D) Marchenko algorithm, the performance of the 3D Marchenko algorithm for internal multiple predictions has been significantly enhanced, resulting in higher computational accuracy. Numerical simulation test results indicate that our proposed method can effectively eliminate internal multiples in 3D seismic data, thereby exhibiting important theoretical and industrial application value.

Safe Trajectory Planning for Incremental Robots Based on a Spatiotemporal Variable-Step-Size A* Algorithm.

In this paper, a planning method based on the spatiotemporal variable-step-size A* algorithm is proposed to address the problem of safe trajectory planning for incremental, wheeled, mobile robots in complex motion scenarios with multiple robots. After constructing the known conditions, the spatiotemporal variable-step-size A* algorithm is first used to perform a collision-avoiding initial spatiotemporal trajectory search, and a variable time step is utilized to ensure that the robot completes the search at the target speed. Subsequently, the trajectory is instantiated using B-spline curves in a numerical optimization considering constraints to generate the final smooth trajectory. The results of simulation tests in a field-shaped, complex, dynamic scenario show that the proposed trajectory planning method is more applicable, and the results indicate higher efficiency compared to the traditional method in the incremental robot trajectory planning problem.

A single-IC realizable, electronically tunable, OTA-based full-wave rectifier with simultaneous positive and negative outputs

A new voltage-mode full-wave rectifier (FWR) is proposed in this study. The proposed FWR employs two single-output operational transconductance amplifiers (OTAs), four diodes, and two grounded resistors. It has high input impedance and does not need any extra bias current or voltage sources. It simultaneously provides positive and negative rectified output signals over separate output terminals. The amplitudes of both output signals can be adjusted by varying the resistor values or the transconductance (gm) values of the OTAs. It does not include any floating passive elements, so it is suitable for integrated circuit (IC) implementations. The proposed FWR can be implemented by using a single commercially available IC such as LM13700. However, the proposed FWR has a single matching condition for gm values of the OTAs. Several simulation and experimental test results are added to confirm the theory and show the operability of the proposed circuit.

Active suspension hierarchical control with parameter uncertainty and external disturbance of electro-hydraulic actuators

In order to improve the ride comfort and handling stability of the electro-hydraulic active suspension system, a hierarchical control strategy is proposed. For the active suspension system with body mass uncertainty and safety constraints, an enhanced constraint adaptive backstepping controller is designed to generate the target force of body vertical motion. When dealing with constraints, nonlinear filters are introduced, backstepping technology and quadratic Lyapunov function are used to combine the control target and domain constraints, and the vertical displacement of the body and the suspension deflection control index are synthesized into a single controlled variable, so that the control variable converging to zero meets the suspension dynamic displacement limit. The ride comfort and safety of the active suspension system are improved. Secondly, stability analysis is conducted on the zero dynamic error system to ensure that all safety performance indicators are bounded. The effects of external disturbances, parameter uncertainties and modelling errors on the force tracking accuracy of asymmetric cylinder electrohydraulic systems are addressed. A backstepping dynamic surface control method based on a nonlinear perturbation observer is proposed, which estimates the composite perturbation terms such as modelling error and external perturbation, and uses the estimated value of the nonlinear observer to design a feedforward compensating control term to offset the effect of the composite perturbation on the system performance. In addition, the dynamic surface control method is used to calculate the derivative of the target force input, which avoids the derivative explosion phenomenon and reduces the computational complexity of the system. Simulation test results show that this method reduces the computational complexity of the system and improves the control performance. And under random and bumpy road conditions, the root-mean-square value of sprung mass acceleration performance index is reduced by 48.354 % and 72.677 % compared with passive suspension, which improves the ride comfort of the vehicle.

Simulation test of 50 MW grid-connected “Photovoltaic+Energy storage” system based on pvsyst software

With the implementation of the national “double carbon” strategy, the installed capacity of new energy power generation continues to grow, and stable photovoltaic power generation solutions have received increasing attention. The PV + energy storage system with a capacity of 50 MW represents a certain typicality in terms of scale, which is neither too small to show the characteristics of the system nor too large to simulate and manage. This study builds a 50 MW “PV + energy storage” power generation system based on PVsyst software. A detailed design scheme of the system architecture and energy storage capacity is proposed, which is applied to the design and optimization of the electrochemical energy storage system of photovoltaic power station. Based on the results of PVsyst operation simulation test, the operation performance of 50 MW “PV + energy storage” power generation system is explored. The results show that the 50 MW “PV + energy storage” system can achieve 24-h stable operation even when the sunshine changes significantly or the demand peaks, maintain the balance of power supply of the grid, and save a total of 1121310.388 tons of CO2 emissions during the life cycle of the system. The various parts of the system, including the photovoltaic array, the energy storage unit and the grid interface, demonstrated efficient collaborative performance in the simulation environment of PVsyst.The analysis of power generation shows obvious seasonal changes. The unit power generation is higher from March to September, and the more the power generation is the overall annual power generation shows good consistency and predictability under the regulation of the energy storage system. Through the analysis of different operating scenarios, the key parameters that affect the system performance are further determined, such as lighting conditions, battery storage capacity, power consumption device efficiency. For lighting conditions, the total radiation amount of the incident lighting surface takes the most proportion in the interval of 380–900 W/m2 and 25-60kwh/m2/Bin. The simulation test also reveals the important role of energy storage unit in power grid demand peaking and valley filling, which has an important impact on balancing the instability of photovoltaic power generation and improving the system response ability.

An active jamming-based helper deployment scheme for underwater acoustic sensor networks

Underwater acoustic sensor networks (UASNs) are usually deployed in unattended, opaque and even hostile environments; thus, they may face serious threats. In the last few years, physical layer security (PLS) has emerged as a new technique that can improve the security performance of networks. In this paper, we research the physical layer security scheme of UASNs by actively jamming against eavesdropping attacks. Utilizing the large propagation delay of the underwater acoustic (UWA) signal, the jamming signals can interfere with legitimate signals to prevent eavesdropping. Therefore, we propose an active jamming-based helper deployment scheme (AJHDS) for UASNs, which deploys the helpers to the target water area and realizes the secure transmission of the network. Both the simulation and field test results show that the scheme can significantly reduce the interception capability of eavesdroppers. Furthermore, the field sea experiment evaluates that the location of helpers affects the eavesdropper’s acquisition of legitimate data packets.

Simulation studies of pollutant emissions from road vehicles using models for inventories of pollutant emissions

Countries are obliged by international regulations to conduct annual pollutant emissions inventories. Road transport is one of the sectors for which an inventory of pollutant emissions is carried out. Determining pollutant emissions from road transport is possible only by modeling these emissions – that is why unified emission models are used. In this work, the COPERT and HBEFA INFRAS software are used to determine pollutant emissions characteristics for various vehicle traffic models. The article presents the principles of modeling pollutant emissions from road vehicles. The rules for qualifying road vehicles into elementary and cumulative categories have been systematized. Models of road vehicle traffic and ways of taking them into account in modeling pollutant emissions are presented. The following emissions of pollutants harmful to the health and life of living organisms are considered: carbon monoxide, non-methane volatile organic compounds, nitrogen oxides and total suspended particles. The trends of the national annual emissions of the tested pollutants in the years 2000 – 2020 and the results of simulation tests of pollutant emissions models are presented.