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Purpose: The serious wear problem of heavy-haul freight vehicle wheels affects the safety and economy of vehicle operation. This paper aims to study wheel wear evolution law and the influence of line parameters on wheel wear of heavy-haul freight, and provide the basis for operation and line maintenance. Design/methodology/approach: The wheel wear test data of heavy-haul freight vehicles were analyzed. Then a heavy-haul freight vehicle dynamic model was established. The line parameters influencing wheel wear in heavy-haul freight vehicles were also analyzed by the Jendel wear model, and the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear were analyzed. Findings: A rail cant of 1:40 results in less wheel wear; an increase in the rail gauge can reduce wheel wear; and when matched with the CHN60 rail, the wear depth is relatively small. A decrease of 9.21% in wheel wear depth when matched with the CHN60 rail profile. The ramp of the heavy-haul line is necessary to consider for calculating wheel wear. When the ramp is considered, the wear depth increases by 8.47%. The larger the ramp, the greater the braking force and therefore, the greater of the wheel wear. Originality/value: This paper first summarizes the wear characteristics of wheels in heavy-haul freight vehicles and then systematically analyzes the effect of line parameters on wheel wear. In particular, this study researched the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0038/ [ABSTRACT FROM AUTHOR]

This paper proposes a monitoring procedure based on characterizing state probability distributions estimated using particle filters. The work highlights what types of information can be obtained during state estimation and how the revealed information helps to solve fault diagnosis tasks. If a failure is present in the system, the output predicted by the model is inconsistent with the actual output, which affects the operation of the estimator. The heterogeneity of the probability distribution of states increases, and a large proportion of the particles lose their information content. The correlation structure of the posterior probability density can also be altered by failures. The proposed method uses various indicators that characterize the heterogeneity and correlation structure of the state distribution, as well as the consistency between model predictions and observed behavior, to identify the effects of failures.The applicability of the utilized measures is demonstrated through a dynamic vehicle model, where actuator and sensor failure scenarios are investigated. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, improvements in reducing transmitted accelerations in a full vehicle are obtained by optimizing the gain parameters of an active control in a roughness road profile. Design/methodology/approach: For a classically designed linear quadratic regulator (LQR) control, the vibration attenuation performance will depend on weighting matrices Q and R. A methodology is proposed in this work to determine the optimal elements of these matrices by using a genetic algorithm method to get enhanced controller performance. The active control is implemented in an eight degrees of freedom (8-DOF) vehicle suspension model, subjected to a standard ISO road profile. The control performance is compared against a controlled system with few Q and R parameters, an active system without optimized gain matrices, and an optimized passive system. Findings: The control with 12 optimized parameters for Q and R provided the best vibration attenuation, reducing significantly the Root Mean Square (RMS) accelerations at the driver's seat and car body. Research limitations/implications: The research has positive implications in a wide class of active control systems, especially those based on a LQR, which was verified by the multibody dynamic systems tested in the paper. Practical implications: Better active control gains can be devised to improve performance in vibration attenuation. Originality/value: The main contribution proposed in this work is the improvement of the Q and R parameters simultaneously, in a full 8-DOF vehicle model, which minimizes the driver's seat acceleration and, at the same time, guarantees vehicle safety. [ABSTRACT FROM AUTHOR]

This paper presents a new type of monorail rapid transit vehicle, which can operate in formation. In order to optimize the dynamic performance of the formation vehicles when passing through the small radius curve, this paper first analyzes the structure of the new monorail rapid transit vehicle, and establishes the vehicle dynamic model and multibody dynamics simulation model. Then the improved artificial potential field algorithm is used to build the formation vehicle operation controller. Finally, the dynamic performance evaluation index of the new monorail rapid transit formation vehicle is formulated, and the formation vehicle passing through the small radius curve scene is simulated. The simulation results show that the controller of the formation vehicle with dynamic optimization control can effectively optimize the load transfer coefficient of running wheels, unbalanced centrifugal acceleration and roll angle of vehicle body when passing through the curve. Through this control method, the dynamic performance of formation vehicles passing through small radius curve lines can be optimized. [ABSTRACT FROM AUTHOR]

Aiming to promote the control performance of traditional fixed-parameter model predictive control (MPC), a new longitudinal and lateral coupling path tracking control method for the autonomous vehicle is proposed. First, a dynamic model of the autonomous vehicle, which can describe the longitudinal and lateral motion states, is established. Secondly, both the tire side-slip angle and centroid side-slip angle constraints are introduced in the path tracking controller design, which improves the accuracy of the prediction model at high speed. Furthermore, the key parameters of the proposed path tracking controller are optimized. The simulation and experimental results show that compared with the traditional MPC tracking control method, the lateral error and directional error of the proposed optimized path tracking control method under high speed decrease by 19.17 % and 11.89 %, respectively, which improves the path tracking performance significantly. [ABSTRACT FROM AUTHOR]

Braking control of urban rail vehicles with multiple carriages is critical to ensure the safe operation of urban rails. However, existing decentralized braking control methods lead to the inconsistent speed and excessive coupler force among carriages, which compromises the operation safety of urban rails. To address this issue, a cooperative braking strategy is proposed for urban rail vehicles based on Koopman model predictive control method. First, a cyber‐physical model is established, where the physical layer characterizes the dynamic model of multiple carriages using the Koopman operator. The cyber layer represents the communication topology of carriages with graph theory. Second, a cooperative braking controller is designed with the distributed model predictive control method. An optimisation problem is formulated to minimize the speed inconsistency and relative displacement difference among carriages. Third, extensive simulations under various scenarios, including normal and extreme operating conditions, are conducted to verify the effectiveness of the proposed method. Simulation results show that, compared with the classical decentralized method, the proposed braking method reduces the average relative displacement by 78% while reducing the speed error by 29%. [ABSTRACT FROM AUTHOR]

Road excitation is the basic input of vehicle vibration, which greatly impacts on vehicle ride comfort. In addition, it can cause vertical vibration of the vehicle, leading to deformation of the powertrain mount. Similarly, the longitudinal movement of the powertrain can also cause deformation of the powertrain mount. Due to the effect of the powertrain mount, there is a mutual coupling between the vehicle in the longitudinal and vertical directions, which has a great influence on the smoothness and comfort of the vehicle. In order to reveal the impact of random road excitation on the vehicle dynamic characteristics of a dual clutch transmission (DCT) vehicle under starting and shifting conditions, a longitudinal-vertical coupled dynamic model of the DCT vehicle considering the powertrain mount was established. This model includes dynamic torque model of the engine, powertrain mount model, transmission system model, tire model and road excitation model. The influence of random road excitation on the vehicle's dynamic characteristics is analyzed under starting, shifting, and different starting and shifting intentions. The simulation results of the longitudinal-vertical coupling dynamic DCT vehicle model considering road excitation are compared with vehicle test results, the model is found to accurately reflect the influence of road excitation on the dynamic performance of DCT vehicles under starting and shifting conditions, thus verifying the correctness of the model. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of path following and dynamic obstacle avoidance for an underwater biomimetic vehicle-manipulator system (UBVMS). Firstly, the general kinematic and dynamic models of underwater vehicles are presented; then, a nonlinear model predictive control (NMPC) scheme is employed to track a reference path and collision avoidance simultaneously. Moreover, to minimize the tracking error and for a higher degree of robustness, improved extended state observers are used to estimate model uncertainties and disturbances to be fed into the NMPC prediction model. On top of this, the proposed method also considers the uncertainty of the state estimator, while combining a priori estimation of the Kalman filter to reasonably predict the position of dynamic obstacles during short periods. Finally, simulations and experimental results are carried out to assess the validity of the proposed method in case of disturbances and constraints. [ABSTRACT FROM AUTHOR]

In order to improve the path following performance and solve the stability problems of autonomous distributed drive electric buses, this paper proposed a path following and lateral-yaw-roll stability integrated control method. Firstly, to cope with the varying speed during different maneuvers and roll motion of autonomous distributed drive electric buses, a nonlinear 4-DOF vehicle dynamic model which includes rolling and longitudinal movement is established. Secondly, a hierarchical control method is built, in the upper layer, a model predictive controller (MPC) is designed to generate the control inputs, which is obtained through an optimization problem including path following error and vehicle stability condition, especially the roll stability for buses, and for the lower layer, the torque of each drive wheel is distributed through solving an optimization problem about drive requirement and tire utilization. Finally, the validation of the proposed method is carried out through TruckSim-Simulink co-simulation, the results illustrate that both following accuracy and vehicle stability are obtained more effectively than the popular linear MPC method, especially roll stability is guaranteed under extreme condition. [ABSTRACT FROM AUTHOR]

This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the control of differential steering for four-in-wheel-motor electric vehicles. The so-called differential steering means that the front wheel steering is realized through the differential driving torque between the left and right front wheels. With the consideration of tire friction circle, a hierarchical control method is proposed to realize the differential steering and the constant longitudinal speed simultaneously. Firstly, the dynamic models of the front wheel differential steering vehicle, the front wheel differential steering system and the reference vehicle are established. Secondly, the hierarchical controller is designed. The upper controller is to obtain the resultant forces and resultant torque required by the front wheel differential steering vehicle tracking the reference model through the sliding mode controller. In the middle controller, the minimum tire load ratio is selected as the objective function. Combined with the constraints, the resultant forces and resultant torque are decomposed into the longitudinal and lateral forces of four wheels by the quadratic programming method. The lower controller provides the required longitudinal forces and tire sideslip angles for the front wheel differential steering vehicle model through the tire inverse model and the longitudinal force superposition scheme. Simulation results show that the hierarchical controller can guarantee the vehicle to track the reference model well on both of the high and low adhesion coefficient road with all of the tire load ratios smaller than 1. It can be drawn that the control strategy proposed in this paper is effective. [ABSTRACT FROM AUTHOR]

The intelligent tracing car is a complex system with high linearity, and the design of path tracking strategy is one of the most important technologies in intelligent tracing car field. This paper proposed a novel path tracking strategy based on control dynamic model of the intelligent tracing car. The vehicle dynamic models are established separately according to the vehicle parameters and kinetic equation. The traditional path tracking strategy used the distance between the desired and actual displacements to compute the error for position control. However, the paper utilized the past and current states of the desired displacement to figure out a motion vector. The error was acquired through calculating the difference between the desired and current displacements along this motion vector. Simulation results showed excellent performance in position control and speed control for the intelligent tracing car. [ABSTRACT FROM AUTHOR]

The irregular ocean environment brings difficulties to observation and affects the movement state of underwater vehicles. Multisource information fusion can provide more reliable results on information-rich datasets. This paper proposes a multisource information fusion-based environment perception and dynamics model for underwater vehicles in irregular ocean environments. First, the multisource observation data is decomposed by the latent feature disentanglement learning model into the latent stable and dynamical features. The dynamical feature is predicted by the retrospect regression method and then integrated with the latent stable feature to predict the ocean field. After that, the environment-vehicle coupling effect is explored by thermodynamics and statics simulation. Then, a real-time dynamic model of the underwater vehicle is constructed by combining multisource information from physical principles, environmental perception, and sensor observations. Finally, extensive experiments are performed on a novel underwater glider and a publicly available South China Sea dataset to verify the proposed method. • An environment perception model is proposed for the underwater vehicle array. • A real-time dynamic model is proposed for the underwater vehicle. • Environment-vehicle coupling effect is explored. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the measured values of key state parameters such as the lateral velocity and yaw rate of the vehicle are easily interfered by random errors, a filter estimation method of vehicle state is proposed based on the principle of robust filtering and the unscented particle filter algorithm. Based on the establishment of a 3-DOF non-linear dynamic model and the Dugoff tire model of the vehicle, the adaptive robust unscented particle filter(ARUPF) is used to filter and estimate the parameters of the vehicle state, and to realize the longitudinal and lateral speed as well as the yaw rate of the vehicle during the driving process. The simulation and the real vehicle test results show that based on the adaptive robust unscented particle filter algorithm, the vehicle driving state estimation can be realized, the measurement parameters can be effectively filtered, and the estimation accuracy is high. [ABSTRACT FROM AUTHOR]

The differential steering can be used not only as the backup system of steer-by-wire, but also as the only steering system. Because the differential steering is realized through the differential moment between the coaxial left and right driving wheels, the sharp reduction of the load on the inner driving wheel will directly lead to the failure of the differential steering when the four-wheel independent drive electric vehicle approaches the rollover. Therefore, this paper not only realizes the trajectory tracking of autonomous ground vehicle through the differential steering, but also puts forward the body attitude control to improve the handling stability. Firstly, the dynamic and kinematic models of differential steering autonomous ground vehicle (DSAGV) and its roll model are established, and the linear three-degree of freedom vehicle model is selected as the reference model to generate the ideal body roll angle. Secondly, a model predictive controller (MPC) is designed to control the DSAGV to track the given reference trajectory, and obtain the required differential moment and the resulting front-wheel steering angle. Then, a sliding mode controller (SMC) is adopted to control the DSAGV to track the ideal body roll angle, and obtain the required roll moment. The simulation results show that the proposed MPC and SMC can not only make the DSAGV realize the trajectory tracking, but also achieve the body attitude control. [ABSTRACT FROM AUTHOR]

• Dynamic model of the tracked vehicle considered this type of forces which is traction, hydrodynamic, centrifugal, lateral friction, longitudinal resistive, bulldozing, and compaction force. • Path tracking is vital in autonomous vehicles since it is designed to deliver appropriate steering, throttle, and brake input to control the vehicle's direction and speed along a predefined path. • Model Predictive Control (MPC) may handle system limits and future predictions. • The objective of a path tracking controller is to eliminate any variation in vehicle direction from the specified path. This paper provides a review of path tracking strategies used in autonomous vehicle control design. Several elements of modelling process and path tracking control are examined, including the vehicle model implemented, the path tracking control algorithms used, and the criteria for evaluating the controller's performance. Path tracking control is classified into several forms based on its methodology and linearity. Vehicle models are grouped into numerous types based on the linearity and the intended behaviour to be observed. This study explores each of these strategy in terms of the applicability and disadvantages/advantages. The main challenges in the field of path tracking control are defined and future research directions are offered based on the critical reviews. Based on the entire review, a model-based controller based on a linear vehicle model and assessed with hardware-in-the-loop (HIL) is suggested. This review is aimed to serve as a starting point for determining which controllers to use in path tracking control development for an autonomous tracked vehicle. [ABSTRACT FROM AUTHOR]

For traditional predictor-corrector guidance algorithm for reentry glide vehicle, it cost a lot of time to obtain predicted flight range with a slow speed to iterate. In this paper, according to residual network (ResNet)'s block and dynamic model of vehicle, through analyzing the characteristics of predicted flight range with constraints, the flight range prediction block and flight range prediction neural network are designed, which can obtain the predicted range accurately and quickly; then aiming at the separation between guidance logic and no-fly zone avoidance logic, which may lead to guidance failure and increasing of the sign variation number of the bank angle, the no-fly zone crossrange and the no-fly zone mapping crossrange are proposed in this paper. According the repulsion force of artificial potential field, an adaptive crossrange corridor combining guidance logic and no-fly zone avoidance logic is proposed, and the convergence of the corridor is analyzed theoretically. Through simulation, the block number of flight range prediction network is determined firstly. By this method, the efficiency of lateral guidance can be improved. Then, through the simulation with the different no-fly zones under different disturbed conditions, the stability and validity of the guidance method are verified. Finally, compared with other predictor-corrector algorithms, the proposed method can realize guidance with less sign variation number of bank angle and better avoidance for no-fly zones. [ABSTRACT FROM AUTHOR]

In complex driving scenarios, automated vehicles should behave reasonably and respond adaptively with high computational efficiency. In this paper, a computational efficient motion planning method is proposed, which considers traffic interaction and accelerates calculation. Firstly, the behavior is decided by connecting the points on the unequally divided road segments and lane centerlines, which simplifies the decision-making process in both space and time span. Secondly, as the dynamic vehicle model with changeable longitudinal velocity is considered in the trajectory generation module, the C/GMRES algorithm is used to accelerate the calculation of trajectory generation and realize on-line solving in nonlinear model predictive control. Meanwhile, the motion of other traffic participants is more accurately predicted based on the driver's intention and kinematics vehicle model, which enables the host vehicle to obtain a more reasonable behavior and trajectory. The simulation results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

To improve the multidirectional motion control accuracy and driving stability of Distributed Drive Autonomous Vehicles (DDAVs) under extreme conditions, the extreme speed estimation method based on dynamic boundary and the multidirectional motion coupling control law design method based on multi degrees of freedom vehicle dynamic model are proposed. The extreme speed estimation method identifies the stable state of DDAVs by the dynamic boundary composed of yaw rate, sideslip angle and roll angle, and then estimates the extreme speed of the vehicle. The design method of multidirectional motion coupling control law adopts eight-degrees-of-freedom (8-DOF) vehicle dynamic model to design path tracking control law, speed tracking control law, yaw stability control law, and active suspension control law at the same time, so as to realize multidirectional motion coupling control. Based on the above method, the Multidirectional Motion Coupling Control System (MMCCS) of DDAVs is designed. The effectiveness of the proposed method is verified by double-line-shifting and serpentine driving simulations under different road adhesion conditions. The superiority of the method is proved by comparing the existing integrated control method. [ABSTRACT FROM AUTHOR]

A path following control strategy for a four-wheel-independent-drive electrical vehicle (4WID-EV) based on backstepping and model predictive control is presented, which can ensure the accuracy of path following and maintain vehicle stability simultaneously. Firstly, a 2-DOF vehicle dynamic model and a path following error model are built and the desired yaw rate is obtained through backstepping. Then, a model predictive controller is adopted to track the desired yaw rate and obtain the optimal front wheel steering and external yaw moment. Meanwhile, an optimal torque distribution algorithm is carried out to allocate it to each tire. Finally, the effectiveness and superiority of the strategy is validated via CarSim–Simulink joint simulation. Results show that the strategy has higher following accuracy, smaller sideslip angle, and better yaw rate tracking. [ABSTRACT FROM AUTHOR]

This paper presents a novel algorithm that aims to estimate an accurate dynamic model for a vehicle suspension system. The proposed method addresses the uncertainties associated with the system model and unknown road input by incorporating complementary terms. These terms are calculated using information from accelerometers installed on both the sprung and unsprung masses. To correct measurement errors, including bias and noise, the paper suggests fusing the accelerometer data with displacement data. The paper further introduces an adaptive solution for adjusting the estimator coefficients, enabling effective data fusion. An experimental implementation is conducted on a quarter-car suspension platform, equipped with additional sensors to verify the estimated responses. Comparative results with the unknown-input Kalman filter highlight the superior accuracy of the proposed estimator in constructing a precise dynamic model for the system. Additionally, the results demonstrate the effectiveness of data fusion-based adaptive tuning of the estimator coefficients in correcting measurement errors. • Novel estimation of accurate dynamic model for vehicle suspension system. • Suggesting data fusion to correct measurement errors of accelerometers. • Adaptive solution for adjusting the estimator gains for effective data fusion. • Stochastic analysis of the proposed estimation algorithm. • Experimental implementation of the estimator on a quarter-car suspension platform. [ABSTRACT FROM AUTHOR]

• A navigation accuracy compensation algorithm for INS is proposed for low-cost USVs. • An event-triggering mechanism is introduced, and the thrust models of the USVs are adopted to design the event trigger. • According to different events, various weights can be assigned to various integrators and PF. • Field experiments are conducted to verify the navigation performance of our algorithm. Integrated navigation is often used for navigation of unmanned surface vehicles (USVs). For a class of cost-sensitive USVs, it is desirable to compose integrated navigation by low-cost inertial navigation systems (INS) and global positioning systems (GPS). In the cases of GPS signal failure or interference, only INS onboard can be used for navigation, which often leads to the navigation accuracy deteriorating and may fail to meet application requirements. Therefore, a navigation accuracy compensation algorithm for low-cost USVs is proposed. An event-triggering mechanism is introduced, and the thrust models of the USVs are adopted to design the event trigger. According to different events, various weights can be assigned to the integrator based on INS, and measurement-based linear velocity V INS and heading angle ψ I N S can be obtained. Moreover, based on dynamic models, the model-based linear velocity V m and heading angle ψ m also can be calculated. Meanwhile, the event trigger is combined with the Particle Filter (PF) algorithm to accurately estimate the linear velocity V ^ P F and heading angle ψ ^ PF for navigation. Finally, field experiments are conducted and the differential GPS (DGPS) is used as the benchmark for comparison. The results show that our algorithm can improve navigation performance for the low-cost USVs. [ABSTRACT FROM AUTHOR]

This article formulates a front-wheel-drive three degree-of-freedom (3DOF) four-wheel planar vehicle model with the Magic Formula tire model. The state variables' evolutions of the model, i.e., trajectories of the model under acceleration and deacceleration conditions, are analyzed. The process of evolution is divided into desirable and undesirable phases based on the response characteristics of the vehicle to the driver input during the process. The trajectories are categorized as unsaturated trajectories and saturated trajectories by the existence of saturated tires during these phases. The response of state variables to driver input under acceleration conditions during undesirable phases are zero or even opposite, while the response of undesirable phases under the deacceleration condition is partially positive. Besides, the existing yaw rate safety envelope is recalibrated by using a longitudinal and lateral tire force coupling model. A more accurate yaw rate safety envelope is obtained from the given driver input. Furthermore, a longitudinal speed safety envelope is proposed according to the relationships among slip angle, yaw rate, and longitudinal speed. These safety envelopes are determined by driver input, tire properties, and grip condition. After overlaying yaw rate and longitudinal speed safety envelopes in the state space, the feasibility of using the safety envelope as trajectory classification criteria is discussed. [ABSTRACT FROM AUTHOR]

An eight-degree-of-freedom vehicle dynamic model with electromechanical coupling was established for a four-wheel-independent-drive electric vehicle (4WID-EV). Based on the single-point preview optimal curvature theory, an adaptive fuzzy PID driver model with lateral acceleration feedback was designed, and the control of vehicle trajectory tracking was achieved in the driver-vehicle-road closed-loop coupling model. With the sideslip angle and yaw rate as control variables, the upper layer of a fuzzy sliding mode controller and the lower layer of an optimal distribution controller of the yaw moment were designed. The optimal longitudinal forces of four driving wheels were determined to achieve vehicle-handling stability. J-turn, fishhook, and snake-shaped pile simulations were carried out in MATLAB/Simulink. The results showed that the fuzzy sliding mode controller significantly improved the driving stability of the system, and it had a better anti-chattering ability than the sliding mode control strategy. The established lateral acceleration feedback adaptive fuzzy PID driver model had good trajectory tracking ability. Integration of the two controllers can better achieve both trajectory tracking and driving stability of a 4WID-EV. [ABSTRACT FROM AUTHOR]

This study proposes an improved dynamic substructuring model using the estimated frequency response function information at coupling points between substructures. An assembled system generally consists of two or more substructures connected by a bolt. Individual substructure evaluation excluding the effects of other components is important in the development stage of a general mechanical system because the vibro-acoustic performance of the system depends on the specific combination of substructures. Therefore, this study predicted the final coupling system performance using information from the initial evaluation of the individual substructures. Accurate measurements of the joint properties are required to accurately estimate the dynamic assembled system characteristics; however, physical constraints typically limit such measurements at actual coupling points. Accordingly, a method that utilizes generalized coupling properties to estimate the dynamic characteristics of a new coupling system based on the characteristics of an original substructure is proposed. Virtual point transformation is then used to estimate accurate frequency response functions at the coupling points of the assembled system based on convenient measurements. The proposed method was validated using a vehicle suspension that was hard mounted in a test jig and onto an actual vehicle body to estimate the vibration characteristics of the assembled system. The findings of this study contribute to the accurate estimation of the dynamic properties of many real-world bolt-assembled systems. [ABSTRACT FROM AUTHOR]

Reverse Horizontal Curves (RHCs) are among the most accident-prone road points, with many annual fatalities and injuries. These fatalities can increase dramatically if the RHCs and longitudinal slopes are combined. The importance of increasing the safety of RHCs, especially in mountainous routes, is doubled due to the possibility of combining RHCs with vertical extensions or combining them with so-called steep slopes. This study used vehicle dynamic modeling to evaluate the lateral friction of various vehicles. Including the E-Class Sedan, E-Class SUV, Truck, and Bus, moving on RHCs combined with a longitudinal slope (downgrade, upgrade, and direct distance). Then, the RHC lateral friction model was presented using the multiple regression model based on the effective parameters, including design speeds, direct distance, and different longitudinal slopes. The results showed that speed, longitudinal slope, and vehicle type had the most impact, and direct distance had the most negligible impact in friction coefficient models. Based on the modeling results, the higher the design's speed and the shorter the direct distance, the lower the lateral friction coefficient for the Sedan and SUV. Hence, the safety of the vehicles is greater. For trucks, reduced speed, increased direct distance, and reduced slope led to increased safety. In the results, the most critical state was the lateral friction coefficient at a speed of 80 km/h and a direct distance of 116 m for the SUV. [ABSTRACT FROM AUTHOR]

The levitation bogie of the TR-series maglev vehicle is redesigned by adding an intermediate buffer layer between the levitationbogie and the levitation module to improve the curve negotiation capacity of the high-speed maglev vehicle and reduce the vertical coupleddynamic effect of the vehicle and the track beam. As the existing TR08 maglev vehicle dynamic model has been verified by experiments, anew type of dynamic model of maglev vehicle is constructed by transplanting the functional module of TR08 model. The vehicle-elastic trackbeam coupled dynamic model and the vehicle-curved track dynamic model are established. Simulation analyses of the dynamic response ofvehicles and track beams show that: the curve negotiation capacity of the new-type maglev vehicle is better than that of TR08 type maglevvehicle; the resonance effect does not occur between the vehicle and the track beam; the vertical dynamic displacement of the track beammid-span decreases by 23% compared with the TR08 type; the redesigned levitation bogie structure and the track beam have less dynamicinteraction, indicating that the working environment of the electromagnet in the new maglev vehicle has been improved, which can effectivelyreduce the burden of electrical decoupling of the control system. [ABSTRACT FROM AUTHOR]

• A novel physics-guided prediction model is proposed for dynamic AC operation. • A hybrid neural network is proposed for heat exchanger modelling. • VCS simulation integrates both deep learning and physics-based component models. • Validation of the proposed models is based on data from operating vehicle AC. Air conditioners (AC) are responsible for the largest portion of energy use among all auxiliary components of vehicles. Most white-box models developed for dynamic modeling of vapor compression systems (VCS) are not adequate to model vehicle ACs due to stronger dynamics and disturbances caused by frequent door open/close, random numbers of passengers entering/leaving the vehicles as well as intermittent shading effect on roads. In this study, a novel physics-guided deep learning method is proposed for dynamic modeling of vehicle ACs based on both domain knowledge and historical operational data. To maximize the practical values of the model in control and diagnosis of ACs, this research aims at developing an integrated VCS model consisting of individual models of major AC components rather than a black-box model of the entire system. Domain knowledge guides the determination of model inputs and outputs, design of the model structure, and understanding of temporal relationship in developing dynamic heat exchanger models. A newly developed NARX-LSTM-MLP neural network is proposed for heat exchange process modelling. The compressor is modelled by a multiple-layer perception (MLP). Component models are integrated by referring to the physical system structure. Field AC operation data from a city bus collected by IoT sensors are used in this study. Validation results indicate good accordance between measurements and simulation results. The model developed is less expensive, more convenient, and more feasible for health monitoring of numerous vehicle ACs at city level in the context of IoT. [ABSTRACT FROM AUTHOR]

In this paper, a coupling longitudinal-vertical dynamic model of a wheeled vehicle under off-road conditions is established. In the present model, the vehicle's travelling velocity changes as the vehicle heaves under ground excitations. The relative movements between the vehicle body and the wheels in both longitudinal and vertical directions are taken into account. From this model, the vehicle's vertical and pitch motions as well as the longitudinal dynamics are studied. For validation purposes, an experiment was carried out on a wheeled vehicle as travelling through a single speed bump. Through comparisons, it indicates that the proposed model performs well in predicting the dynamic characteristics of the vehicle on an uneven road. Thus, the model is further applied to quantitatively investigate the energy consumption of a vehicle under off-road conditions. It has been found that the energy consumption distribution is strongly affected by the vehicle speed and the road conditions. Both a higher vehicle speed and a larger road roughness coefficient lead to a lower drive power efficiency and a greater power loss. [ABSTRACT FROM AUTHOR]

Demand for Li-ion batteries is soaring daily in the global Electric Vehicle (EV) market. Therefore, developing an accurate, efficient and low-cost Battery Management System (BMS) plays a pivotal role in the battery's performance. One of the significant roles of the BMS is the accurate State of Charge (SoC) estimation of batteries. This paper uses Thevenin's model-based Extended Kalman Filter (EKF) algorithm for SoC estimation. In order to prove the validity of the estimation model, SoC estimated using the EKF model is verified with the SoC obtained from the vehicle dynamic model developed in the MATLAB Simulink environment considering various drive cycles like LA92, FTP-72, and NEDC. The Root Mean Square Error (RMSE) chosen as the performance index has achieved much smaller values as 0.0277%, 0.00278%, and 0.0145% for one cycle of LA92, FTP-72, and NEDC drive cycles, respectively, and hence this approves its real-time applications. The proposed work provides a reliable and trustable estimated SoC for range estimation of the EV since the estimated SoC value here takes into account not only the drive cycle load current demand but also it considers other external factors like the weight of the vehicle, wind, rolling resistance between road and tire etc. For that purpose, the SoC estimation algorithm in this proposed work incorporates a vehicle dynamic model developed in the Simulink environment. It delivers a reliable estimated SoC on which the EV driver can depend on calculating its remaining range. • An EKF based State of Charge method has been employed for a Turnigy Graphene 5000 mAh battery. • Thevenin's battery model is used for representing the dynamic behaviour of the battery. • Robustness of the model is verified under different temperature like, −10 °C, 10 °C, 25 °C, and 40 °C and along with a 10% initial SoC offset. • Vehicle Glider model is developed in the MATLAB Simulink environment for a battery pack of 50 Ah. • The estimated SoC matches with vehicle dynamic model SoC for various drive cycles with low Root Mean Square Error (RMSE). [ABSTRACT FROM AUTHOR]

• Based on the variable wheelbase characteristics, this study examines the impact of wheelbase changes on the response characteristics of sideslip angle and heading angle relative to the front wheel angle. • A control strategy for adaptive heading tracking is formulated by adjusting the wheelbase under different working conditions. • Considering the influence of noise interference and time delay, a robust active disturbance rejection control (r-ADRC) method is proposed by combining ADRC with a robust term. • A torque distribution method for tire load rate is utilized, and the real-time vertical load of each wheel is calculated, taking into account the change in wheelbase. • The theory of wheelbase-changing and heading tracking strategy are verified through co-simulation of the UGV and experiments of the scaled prototype. In order to fully exploit the variable wheelbase characteristics of the unmanned ground vehicle (UGV) with variable configuration, this paper proposes an adaptive heading tracking control strategy based on wheelbase changes. This strategy involves adjusting the wheelbase according to different working conditions to optimize various driving performance aspects. Firstly, the impact of changing wheelbase on the response characteristics of sideslip angle and heading angle relative to the front-wheel steering angle is analyzed by using a lateral vehicle dynamic model. The configurations where the 2nd axle moves forward by 0.5 m, remains unchanged, and moves backward by 0.5 m are defined as the 'stable configuration', 'balanced configuration', and 'maneuverable configuration', respectively. Considering time lag effects of hydraulic systems and external random noise interference, a robust-active disturbance rejection control (r-ADRC) method is developed by incorporating a robust term into active disturbance rejection control (ADRC) in order to achieve desired front-wheel steering angle. Additionally, a torque distribution method based on the tire load rate and the real-time vertical load of each wheel is applied to ensure uniform tire wear and enhance longitudinal driving stability. Finally, simulations under various typical working conditions as well as scaled prototype experiments are conducted, and both the theory behind the changing wheelbases and the effectiveness of proposed control strategy are verified. According to different vehicle configurations and mission requirements, the maneuverability and stability of the ground unmanned vehicle are ensured respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

A positioning system estimates the position and orientation of a vehicle. Autonomous driving systems plan paths and control the vehicle based on the information from the positioning system. Recently, methods of estimating the position in urban areas have been actively studied. In U-turn sections, which are common in urban areas, vehicles perform a rotation to reverse the direction of travel. Through these sections, drivers can reduce the travel distance and save time but with a high risk of an accident. Despite there being a need for the development of autonomous driving schemes for U-turn sections, the existing research is limited. This study proposes an interacting multiple model (IMM) filter-based position estimation algorithm for urban U-turn sections. To reflect the dynamic characteristics of a vehicle during U-turn maneuvers, a multiple vehicle model was used. This model includes kinematic and dynamic vehicle models. The state estimates of the vehicle model and gyroscope are combined using an IMM filter. The position estimation algorithm developed in this study is verified via experiments. The experimental results indicate that, during urban U-turn maneuvers, the position estimation accuracy of the IMM filter-based algorithm is improved than that of the single vehicle model. [ABSTRACT FROM AUTHOR]

Summary: To address the difficulties of under‐actuation, nonlinearity, strong coupling, disturbances and measurement noise in four‐wheel steering (4WS) vehicle tracking control, this paper presents an innovative control strategy based on differential flatness and linear active disturbance rejection controller (LADRC). The flatness property of 4WS vehicle is derived from a simplified dynamic model that ignores some complicated dynamics and external disturbances. The impact of these neglected components on the system is treated as part of the total‐disturbance, which is estimated by the observer and compensated by LADRC. Three flatness‐based control schemes, including feedback linearization controller with PID corrective term, traditional LADRC and LADRC with robust generalized proportional integral observer (RGPIO), are designed and investigated in this paper. Moreover, an overtaking scenario is selected as an application example for the tracking controllers, and the corresponding trajectory planner is designed. The tracking performances of these schemes for the overtaking trajectory are simulated on a three‐degree‐of‐freedom dynamic model and a more complete dynamic model of the 4WS vehicle, respectively. Results show the effectiveness of these schemes, especially the excellent tracking performance of LADRC with RGPIO in the presence of strong external disturbances and measurement noise. [ABSTRACT FROM AUTHOR]

In this work a parameter optimization method is applied to determine the best values of damping and stiffness properties which will minimize the magnitude of the vertical acceleration of the ambulance stretcher. Thus, an 8-DOF vehicle dynamic model was developed to be used for the parameter optimization method. Subsequently, the results obtained by the model were compared to a full vehicle multi-body model of Carsim software. Damping and stiffness properties, which are obtained by a parameter optimization method, contribute to reducing the magnitude of the vertical acceleration of the ambulance stretcher. The approach developed in this study provides sources for designing a mechanism to reduce the vertical acceleration to which the patient is exposed during transportation in an ambulance. [ABSTRACT FROM AUTHOR]

Articulated tracked vehicles (ATVs) exhibit enhanced steerability but reduced yaw stability. Apart from the track-terrain contact, the dynamics of the articulated frame steering (AFS) system strongly influences the stability of ATVs. We developed a detailed hydraulic steering system and a yaw-plane ATVs model for vehicle stability research. The transient characteristic of track-ground contact was considered. The multibody dynamics model by Recurdyn/Track software was compared with the established model to verify the model correctness at time-domain and frequency-domain. The result suggests that the vehicle yaw stability can be evaluated in terms of the oscillation frequency, damping ratio, overshoot, and steady-state deviation of articulation angle response. A multi-objective optimization is proposed to obtain the optimized structural parameters of AFS system by employing response surface method (RSM) and non-dominated sorting genetic algorithm II (NSGA-II). The optimal solutions revealed that more compact mechanism design of AFS system contributes to a compromise stability performance with 4.44 % decrease in the oscillation frequency and 10.3 % decrease in the damping ratio. [ABSTRACT FROM AUTHOR]

Straddle-type monorail, as a unique technology, energy saving and environmental protection, is different from the subway of urban rail transit system. In order to study the curving performance of a new type of the straddletype monorail vehicle with single-axle bogies, the three-dimensional spatial dynamics model which consists of the vehicle model and track model designis proposed by the multibody dynamics soft ADAMS. The monorail vehicle dynamic model which consists of three types of tire -track contact model and the nonlinear model of the horizontal stop is established. Based on the dynamic model, the influences such as pre pressure and curve super-high rate parameters of the curve passing for the dynamic characteristics are discussed. The simulation results show that the suitable preload for the guide and stabilizer tires of straddle-type vehicle with single-axle bogies is 5KN and after selecting the appropriate pre-pressure, the super-high rate is recommended to be 8%-10%. [ABSTRACT FROM AUTHOR]

The ride comfort and the cargo safety are of great importance in the vibration design of heavy-duty vehicle. Traditional ride comfort design method based on the response of components of vehicles or interaction between human and seat overlooks the most direct criterion, the response of occupants, which makes the optimisation not targeted enough. It will be better to conduct the ride comfort design with the biodynamic response of driver. To this end, a 17-degrees-of-freedom (DOFs) vertical-pitch-roll vehicle dynamic model of a three-axle heavy-duty truck coupled with a 7 DOFs human model is developed. The ride comfort of human body under the vertical, the pitch, and the roll vibrations can be evaluated with the weighted root-mean-square (r.m.s.) acceleration of the driver in multiple directions. The flexibilities of chassis and carriage are also considered to improve the accuracy of the prediction of the ride comfort and to constrain the mounting optimisation of cab and carriage. After validation, the sensitivity analysis of the mounting system, the suspensions, and arrangement of sprung masses is carried out and significant factors to ride vibration are identified. The optimal combination of design parameters is obtained with the objective of minimizing the vibration of the driver and carriage simultaneously. The optimisation result shows that the weighted driver vibration is reduced by 27.9% and the carriage vibration is reduced by 31.8% at various speeds. [ABSTRACT FROM AUTHOR]

Further research on motion control of a 4WS4WD path-following vehicle is carried out in this paper. Focuses are placed on understanding and testing the vehicle path-following control models developed previously at a deep level. Control models are in relation to parameters introduced, and the effects of these parameters are discovered. Control models are interpreted by dynamic simulation using a 3DOF vehicle model with three cases. Three kinds of planned paths are considered in these cases to test control performances, which include the straight, circular, and sinusoidal paths. Interesting dynamic results are obtained and analyzed qualitatively, e.g., various steering modes. Simulation studies are extended with consideration of a fine vehicle dynamic model established in CarSim and a complex path composed of straight and curved segments. Control models are examined in a complex problem, and results obtained show that they are validated with robustness in dynamic environment. [ABSTRACT FROM AUTHOR]

Steep downgrades are known as a part of mountain roads with a significant number of severe crashes. Generally, using speed limiters such as speed bumps and speed humps are considered the most effective (considering both the time and cost) ways to reduce the number of victims. The efficiency of speed limiters depends on the driver's consciousness and the car's braking system; the latter could be problematic in wet and dark conditions of the road. The main goal of the current study is to propose an approach to correct the longitudinal profile of roads by replacing the consecutive downgrades and upgrades with a continuous downgrade. The vehicle's speed is reduced by using this method before entering an accident-prone site without the driver's involvement and breaking. To this end, a well-known software program is used under two speeds (70 and 100 km/h) in 68 different routes to analyze speed along the proposed routes. Also, another computer model is used for dynamic simulation. Dynamic analyses and regression models show that the vehicle's speed in the new proposed route is significantly reduced compared with the continuous downgrade. Moreover, results indicate that the upgrade slope of the proposed route has the most impact on reducing the final speed of the vehicles. [ABSTRACT FROM AUTHOR]

A robust model predictive control (MPC) method with dual closed-loops is presented to handle trajectory tracking of autonomous underwater vehicle (AUV) with uncertain model parameters and random external perturbations. First, constraint conditions are set for the motion state and control input of the underwater vehicle based on its motion characteristics. The position controller takes the velocity increment as input, thus providing a smoothly varying desired velocity for the velocity controller. The velocity controller comprises nominal MPC and a nonlinear auxiliary control law to overcome the effect of random perturbations on AUV tracking control. Then, a finite-time extended state observer (FTESO) is designed to compensate for dynamic model uncertainty. Furthermore, Lyapunov stability theory is employed to analyse the stability of the controller and FTESO. Ultimately, through comparative simulation experiments, the proposed control framework's effectiveness and robustness are verified, proving it to be a feasible AUV trajectory tracking control method. • A dual closed-loop 3D trajectory tracking control framework based on tube MPC is designed. • A finite time extended state observer is designed to estimate and compensate for the uncertainty of the AUV dynamic model. • By designing a nonlinear auxiliary control law, the influence of external disturbances on AUV is solved, and the robustness of system is improved. • The stability and feasibility of the state observer and tube MPC-based controller are rigorously demonstrated. [ABSTRACT FROM AUTHOR]

A robust model predictive control (MPC) method with dual closed-loops is presented to handle trajectory tracking of autonomous underwater vehicle (AUV) with uncertain model parameters and random external perturbations. First, constraint conditions are set for the motion state and control input of the underwater vehicle based on its motion characteristics. The position controller takes the velocity increment as input, thus providing a smoothly varying desired velocity for the velocity controller. The velocity controller comprises nominal MPC and a nonlinear auxiliary control law to overcome the effect of random perturbations on AUV tracking control. Then, a finite-time extended state observer (FTESO) is designed to compensate for dynamic model uncertainty. Furthermore, Lyapunov stability theory is employed to analyse the stability of the controller and FTESO. Ultimately, through comparative simulation experiments, the proposed control framework's effectiveness and robustness are verified, proving it to be a feasible AUV trajectory tracking control method. • A dual closed-loop 3D trajectory tracking control framework based on tube MPC is designed. • A finite time extended state observer is designed to estimate and compensate for the uncertainty of the AUV dynamic model. • By designing a nonlinear auxiliary control law, the influence of external disturbances on AUV is solved, and the robustness of system is improved. • The stability and feasibility of the state observer and tube MPC-based controller are rigorously demonstrated. [ABSTRACT FROM AUTHOR]

The supercavitating vehicle is a new generation of high-speed underwater vehicles enveloped by a large bubble of gas or vapor (i.e., a supercavity) to reduce navigation resistance by an order of magnitude, except for the head and tail. However, due to the limited hydrodynamic forces, it is difficult to ensure stable motion. The overall shape of the vehicle is not only the critical factor to ensure a suitable relative position between the vehicle and its supercavity for stable motion, but also directly affects the ease of generation and development of the supercavity. Therefore, this study focuses on the characteristic parameters of the overall shape of the vehicle and first establishes a multi-objective optimization model based on the dynamic model of the supercavitating vehicle with the incipient supercavitation number and the vehicle volume as the optimization objectives. Then, given the relatively good global, robust and universal characteristics of the adaptive genetic algorithm compared to other algorithms, a multi-objective optimization algorithm is developed and improved using the subsection optimization method for the main optimization variable. The characteristic parameters of the overall shapes are optimized for natural and ventilated supercavitating vehicles using the algorithm based on the multi-objective optimization model so that it is easier to create a supercavity under the conditions of the same flow and force equilibrium and the vehicle has a larger volume. By optimizing the vehicles under different navigation depths and slenderness ratios, the design rules for the characteristic parameters of the overall shape and the control surface parameters are obtained based on the optimization objectives, and the motion state and hydrodynamic characteristics of the optimized vehicles are revealed. • A multi-objective optimization model is established for the SCAV's overall shape. • An adaptive multi-objective optimization algorithm is improved and developed. • Natural and ventilated SCAVs' overall shapes are optimized to achieve the optimal solution sets. • Design rules for the SCAV's overall shape and control surface parameters are obtained. • Motion state and hydrodynamic characteristics of the optimized SCAVs are revealed. [ABSTRACT FROM AUTHOR]

• The paper presents a simple, reliable and fast dynamics model of off-road track vehicle. • The numerical model was formulated by a new method – DBD (Discrete Body Dynamics). • The proposed method was demonstrated using an M113 track vehicle. • The time computation of the new code was faster compared with that obtained from commercial Multi-Body Dynamic programs. • The method is simple enough to be used in prediction of trafficability for off-road applications. The paper presents a simple, fast, and reliable dynamic model for an off-road track vehicle operating on terrain with obstacles. The method has been proven previously for wheeled-vehicle formulation. The model is based on a discrete body dynamics (DBD) method, which leads to simplistic linear decoupled motion equations. In this method, joints and bodies with relatively small mass are replaced with stiff springs and dampers, eliminating the system's constraints and reducing the number of system bodies; this is important for accelerating the simulation runtime of the track vehicle model. The track in this approach is based on modeling each link as a point-mass. Two consecutive links are connected by stiff springs and dampers. This approach reduces the calculation time and increases system stability. The track–soil interaction was modeled using Bekker's and Janosi's formulation (Bekker, 1956; Hanamoto and Janosi, 1961). Specific soil properties were obtained for each link–soil interaction from soil classification and GIS. The link–ground contact was determined from topographic surface and adjustment of the force and direction acting on the track. The results of the simulation using the DBD method were compared with Siemens' VL commercial multibody dynamics program and with experiments reported in the literature. Results using the proposed method were found to be similar to the commercial program based on published experiments. The solution runtimes obtained for unpaved soil were two orders faster with the DBD method compared with the Siemens' VL program. The model was written as an independent software infrastructure, enabling easy integration with any other software component, such as a control system. The algorithm is in a suitable form for parallel processing calculation to speed up the runtime simulation close to real-time. [ABSTRACT FROM AUTHOR]

To assess the effect of the mass-stiffness distribution of the cab and vibratory roller on the ride quality, the acceleration-frequency characteristics of the isolation systems are researched based on the nonlinear dynamic model of the vehicle. The complex domain is used to solve the vibration equations in the frequency region. The effect of the mass and stiffness parameters of the cab and vehicle is then analyzed via MATLAB software. The research results show that the resonant frequency of the cab's isolations and their acceleration-frequency is insignificantly affected by the mass-stiffness distributions in the case of without the excitation of the vibrator drum. Conversely, under an excitation 28 Hz of the vibrator drum, the mass-stiffness distributions strongly affect on the acceleration-frequency of the cab isolations, especially, when increasing the stiffness coefficient and reducing the cab mass with α = 1.5, the vehicle’s ride quality and structural durability of the vibratory rollers are greatly improved. [ABSTRACT FROM AUTHOR]

Utmost models for vehicle steering detailed in the writing accept consistent travel times. Plainly, disregarding the way that the movement time between two areas does not depend just on the separation voyaged, yet on numerous different variables including time, sways the use of the models to genuine issues. In the present research, a multi-target dynamic vehicle-directing issue with fuzzy time series is displayed. In this issue, majority of the work where information is known ahead of time, some setoff ongoing solicitations arrive arbitrarily after some time and the dispatcher does not have any deterministic or probabilistic data on the area and size of them until they arrive. The manuscript utilizes an immediate understanding of the multi-target dynamic vehicle-directing issue with fuzzy time series as a multi-target issue where the required armada measure, generally all out voyaging separation, and hold-up time forced on vehicles are limited, and the general clients' inclinations for administration are boosted. The presentation of the proposed methodology is assessed in various strides on different test issues summed up from a lot of static occasions in the writing. In the initial step, the exhibition of the proposed methodologies is checked in static conditions and after that, different presumptions and improvements are included progressively, and changes are analyzed. Computational tests on informational collections represent the productivity and adequacy of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper presents a rigorous analysis of a promising bi-modal multirotor vehicle that can roll and fly. This class of vehicle provides energetic and locomotive advantages over traditional unimodal vehicles. Despite superficial similarities to traditional multirotor vehicles, the dynamics of the vehicle analyzed herein differ substantially. This paper is the first to offer a complete and rigorous derivation, simulation, and validation of the vehicle's terrestrial rolling dynamics. Variational mechanics is used to develop a six degrees-of-freedom dynamic model of the vehicle subject to kinematic rolling constraints and various nonconservative forces. The resulting dynamic system is determined to be differentially flat and the flat outputs of the vehicle are derived. A functional hardware embodiment of the vehicle is constructed, from which empirical motion data are obtained via odometry and inertial sensing. A numerical simulation of the dynamic model is executed, which accurately predicts complex dynamic phenomena observed in the empirical data, such as gravitational and gyroscopic nonlinearities; the comparison of simulation results to empirical data validates the dynamic model. [ABSTRACT FROM AUTHOR]

• The paper presents a reliable dynamics model of off-road vehicle operation in RT. • The numerical model was formulated by a new method – DBD (Discrete Body Dynamics). • The proposed method was demonstrated using an ATV vehicle. • DBD is faster than Multi-Body Dynamics programs. This paper presents a simple, reliable dynamics model of off-road vehicle operation in real-time (RT) on terrain with obstacles. The numerical model was formulated by a new method – DBD (Discrete Body Dynamics). The new method is based on a discrete-element method, where the equations of motion are linear and simple to solve. In this new method, the suspension systems are composed of soft and stiff springs and dampers (instead of suspension arms and joints constrains), to present the kinematics and dynamics of real suspension. Reduction of the number of bodies and avoidance of constraints significantly improves model efficiency and simplicity. The tires–soil interaction was modeled using Brixius prediction. Specific soil properties were obtained from the classification system for each tire–soil interaction, size, and geometric area. The tire–ground contact was determined by topographic surface and adjustment of the forces and direction acting on the tires. The proposed method allows quick and simple definition of a vehicle. The model is written as an independent software infrastructure, enabling easy integration with any other software component. Simulation results were compared with Siemens' VL commercial multibody dynamics program. The performance of the proposed method was very similar to the commercial program (R2 > 0.9), with the significant advantage of much higher RT performance. [ABSTRACT FROM AUTHOR]

An optimized control approach for the distributed cooperative vehicular platoon was proposed in this paper, considering actuator delay and nonideal communication condition. A hierarchical structure is used to model the vehicular platoon, where the desired acceleration is optimized by CACC controller and the longitudinal tracking controller is proposed to follow it. In the design process of CACC controller, a parameter space approach and linear quadratic regulator (LQR) method are applied to guarantee the string stability and optimized performance. The influence of communication time delay and dropout rate is revealed by the changing of string stable region. Analytical results are verified by numerical simulations of a six-vehicle platoon where the leading vehicle follows the FTP-75 drive cycle speed profile. Furthermore, a Hardware-in-the-Loop (HIL) test is carried out with Carsim to simulate a high-fidelity vehicle dynamic model and dedicated short range communication (DSRC) modems as hardware in the loop as well as the control unit to achieve the inter-vehicle communication. The results show that the designed CACC platooning controller exhibits favorable performance in highway driving scenarios. The platooning vehicles display excellent car-following behavior with high accuracy, driving comfort and safety. [ABSTRACT FROM AUTHOR]

Absorption of impact energy by the passive safety elements of the vehicle body is the basic feature to ensure conditions of safety for the driver and passengers in transport. The parts especially designed for this objective in the self-supporting car body are longitudinals. Their energy-absorbing features are designed in different ways. Evaluation of the degree to which the vehicle (body) ensures safety during a collision is difficult and expensive. Usually, tests under impact conditions are required. The most advanced and costly are the tests carried out on a complete vehicle (whole real object for tests). Whole vehicle testing can be replaced by testing of individual car body elements (for example longitudinal). The main aim of this article is to present and compare the results of dynamic studies on model energy-consuming objects (new model longitudinals and model longitudinals repaired with welding methods). For the purpose of this study, models of vehicle passive safety elements (model longitudinals) were designed. On the basis of the conducted tests, it was found that it is worth considering the replacement of collision tests of the whole vehicle by tests of its individual components. This can be considered a new approach that is not widely used. Currently, most often, crash tests of entire vehicles are conducted (high costs) or computer simulations are performed (often with unsatisfactory accuracy). [ABSTRACT FROM AUTHOR]