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Occupant comfort is a key consideration in automobile dynamics, with vibrations potentially causing long-term physical discomfort, especially for drivers. This study investigates the impact of adding TiO2 and CuO nanoparticles to fuel on engine-induced vibrations. Experiments were conducted at various nanoparticle concentrations (0, 50, 100, and 150 ppm) and engine speeds (1000, 2000, and 3000 rpm). Key performance metrics, including kinematic viscosity, density, heating value, thermal conductivity, and brake power (BP), were analyzed. The results indicated that increasing nanoparticle concentration led to a rise in BP. The highest reduction in root mean square (RMS) vibration accelerations occurred at 3000 rpm and 150 ppm, with vibration reductions of 30.33% for CuO and 28.61% for TiO2. Additionally, 8–10% of engine vibrations were transmitted to the steering wheel. The use of 150 ppm CuO nanoparticles resulted in reduced vibration transmission to the steering wheel at all tested speeds. These findings suggest that nanoparticle-enhanced fuels can significantly reduce engine vibrations, potentially improving driver comfort and reducing wear on vehicle components. [ABSTRACT FROM AUTHOR]

The significant increase in thermal efficiency and the rate of energy exchange used in fuel dynamics and automobile coolants are leading to a better understanding of nanofluids. This computational analysis explores the thermal conductivity performance for radiative cross-flow of a nanofluid across an expanding/constricting sheet with a suction effect as a result of its application. To compute or calculate the magnificent point of nanofluid flow, the entropy, and asymmetrical heat source/sink effects are also elicited. The boundary layers traverse a stream-wise procedure for expanding and contracting sheets. Additionally, the study examines the features of heat transfer and cross-flow of nanofluids using numerical simulations. By employing similarity variables, the basic PDE equations of the current model are transformed into ODEs, and they are subsequently evaluated using the bvp4c method. Therefore, the effects of embedded flow variables on drag force, heat transfer rate, and entropy generation profiles have been framed using parametric research. Multiple solutions are offered for a specific range of the contracting parameter as well as the mass suction parameter. In addition, the heat transfer rate accelerates due to the heat source and decelerates due to the heat sink. The literature that is already published has been compared favorably, and it reveals many commonalities. [ABSTRACT FROM AUTHOR]

Occupant comfort is a key consideration in automobile dynamics, with vibrations potentially causing long-term physical discomfort, especially for drivers. This study investigates the impact of adding TiO2 and CuO nanoparticles to fuel on engine-induced vibrations. Experiments were conducted at various nanoparticle concentrations (0, 50, 100, and 150 ppm) and engine speeds (1000, 2000, and 3000 rpm). Key performance metrics, including kinematic viscosity, density, heating value, thermal conductivity, and brake power (BP), were analyzed. The results indicated that increasing nanoparticle concentration led to a rise in BP. The highest reduction in root mean square (RMS) vibration accelerations occurred at 3000 rpm and 150 ppm, with vibration reductions of 30.33% for CuO and 28.61% for TiO2. Additionally, 8–10% of engine vibrations were transmitted to the steering wheel. The use of 150 ppm CuO nanoparticles resulted in reduced vibration transmission to the steering wheel at all tested speeds. These findings suggest that nanoparticle-enhanced fuels can significantly reduce engine vibrations, potentially improving driver comfort and reducing wear on vehicle components.

This study examines the impact of chip shortages on the financial leverage of automobile firms worldwide over the period COVID‐19 using a panel vector autoregression analysis. This paper analyzes the chip crisis as an exogenous shock in a highly heterogeneous and dynamic framework for automobile firms during the pandemic period. The findings show that the chip shortage has a negative effect on financial leverage of automobile firms and increases their internal financing needs during the pandemic. This study adds new insights to the current literature by considering the chip crisis to the corporate dynamics of automobile firms. [ABSTRACT FROM AUTHOR]

As an alternative to IC engine driven automobiles, electric vehicles are emerging as attractive means of transportation. Taking into account the different operating conditions of an automobile, viz. acceleration, coasting and regenerative braking, BLDC motor-based electric drive system is considered. A BLDC motor-based drive system has many advantages including independent variable speed and variable torque operation along with regeneration capability. In addition to the main battery to supply motive power, an auxiliary battery at lower voltage is normally provided for meeting loads like front and back lights, wiper control, window operations, interior lighting, music system etc. Hence it is possible to charge the auxiliary battery by recouping the kinetic energy of the automobile during braking interval through a DC–DC boost converter. In this paper, automobile dynamics including road friction, aerodynamic forces and transmission, are considered for calculating the shaft torque of the BLDC motor, while following a specified speed-time characteristic and designing a drive system and its controller for closely following the above profile. The problem is formulated by integrating all the above aspects and solved using multiple feedback loops and developing two alternate controllers, viz. MPC and PI controllers, to cover the above three modes of operation. A simulation schematic containing the above functional blocks as subsystems has been created and integrated for the simulation of the entire system, and the results are presented. The results indicate that auxiliary battery regeneration scheme makes significant energy capture possible. Experimental work on a laboratory set up consisting of a BLDC motor drive system, and ARM CORTEX M4F Microcontroller board has been carried out to validate the simulation results. [ABSTRACT FROM AUTHOR]

To improve the anti-interference and robustness of the adaptive cruise control system in car-following mode, this paper designs a robust controller for the automobile adaptive cruise control system which contains two layers, the upper and lower structures, based on the μ control theory. On the one hand, the upper controller calculates the theoretical safety distance between two automobiles based on the current working conditions, and it calculates the expected acceleration of the vehicle through an optimal control method based on the safety distance and two vehicle speeds. On the other hand, this paper constructs the lower μ integrated controller of an automobile longitudinal dynamics system based on the performance requirements of an adaptive cruise control system and solves it in Matlab. Then, through calculation and simulation, it demonstrates that the designed dual-layer LQR-μ controller has good performance robustness and robust stability, which can significantly improve the anti-interference ability and driving safety performance of the vehicle during the following cruise process. [ABSTRACT FROM AUTHOR]

In view of the large calibration workload of existing models, this paper proposes a compound correction method based on the principle of compound correction control; this method takes open-loop correction as the main body, which represents the driver's mastery of vehicle dynamics characteristics; on this basis, a closed-loop correction is added to describe driver's compensation and correction capabilities. Considering the complexity of the longitudinal force of the vehicle, based on the analysis of the longitudinal force of the vehicle, considering the actual situation of the actual driver's foot switching between the accelerator pedal and the brake pedal, a longitudinal dynamics split-phase correction method is proposed. In addition, this paper proposes a fast calibration method of the inverse model of the main characteristics of vehicle dynamics, which mainly studies the fast calibration method of the main characteristics of braking dynamics and lateral dynamics in order to reduce the time cost. The simulation shows that the compound correction model proposed in this paper not only has a small calibration workload and high control accuracy, but also has a certain adaptive ability to the nonlinear characteristics of vehicle dynamics; the main characteristics of braking dynamics and lateral dynamics proposed in this paper has high accuracy. [ABSTRACT FROM AUTHOR]

Accelerometers are indispensable for detecting accelerating forces in automotive electronic systems. Although several accelerometers have been developed, they are still unstable for vehicle dynamics’ applications in the low-frequency range (0–20 Hz). Here, we report a novel type of accelerometer based on a coiled carbon nanotube (CNT) yarn as a self-powered and low-frequency range-covered acceleration sensor. The proposed sensor is designed in a compact fiber-like structure for practical applications. Open-circuit voltage (OCV) signals are consistently generated during the stretch-and-release process of the coiled CNT yarn by the applied sinusoidal accelerations, and the OCV changes increase linearly with increasing acceleration from 4.84 to 48.37 m/s2. Our accelerometer exhibits excellent dynamic sensing performance in the low-frequency range compared with commercial accelerometers. In an application as a CNT yarn device configured with a mass load, the OCV change is linearly proportional to the applied acceleration. When our accelerometer is attached to a seatbelt in a vehicle, it generates OCV changes from the movement of the body mass underlying a certain acceleration change. Given its excellent sensing performance, the CNT yarn acceleration sensor could further be developed for practical applications, such as seatbelts and car seats with fabric and textile. [ABSTRACT FROM AUTHOR]

• Rubber-road friction analysis on rough terrain. • Measurement of friction force between tire rubber and rough terrain. • Numerical estimation of friction force. • Terrain PSD top topology. • Effect of sliding velocity. One of the most challenging aspects of vehicle dynamics is accurate modelling of the tyre-road interface. Forces between the tyre and road need to be accurately represented in simulation. This is challenging over rough roads since the friction changes along the road due to large surface asperities. The Heinrich/Klüppel friction coefficient estimation model has been implemented on smooth roads in the past. However, this study investigates the applicability of using this model over a rough but hard terrain, such as Belgian paving or cobblestones. The model is based on physical properties that can be determined mathematically or experimentally. The study includes detailed terrain topography and the difference between the top and bottom topography is used to determine the radially averaged PSD. Emphasis is placed on finding and implementing the flash temperature in a practical manner that could also be used in further studies. An experimental setup is built to validate the model. The experimental friction coefficient is compared to the friction coefficient calculated using the Heinrich/Klüppel model. The relative percentage error difference between experimental and friction model results is found to be less than 10% on a smooth concrete road and 20% on a rough road (concrete Belgian paving). [ABSTRACT FROM AUTHOR]

The short driving range per charge of electric vehicle is a critical shortcoming hindering its popularization and application. This article proposes an in-vehicle energy optimal control (EOC) to improve the efficiency of the motor drive system. This article first builds a vehicle's longitudinal dynamics model and a motor drive system's efficiency model. Then, a Lagrange–Euler-based optimal control theory is formulated with detailed proof. Based on the vehicle dynamics model, a cost function is constructed by considering the energy consumption and speed demand. Combining the cost function and the Lagrange–Euler-based optimal control theory, an in-vehicle EOC is proposed. The idea of the in-vehicle EOC is mainly to make the motor drive system operate in the high efficiency region as much as possible, which results in longer driving ranges. The in-vehicle EOC is validated on a co-simulation platform and the results show it outperforms the model predictive control method. [ABSTRACT FROM AUTHOR]

In this paper, a synthesized novel strategy of varying predictive horizon-based model predictive control is proposed for the overtaking control of unmanned ground vehicle. The whole control strategy includes path planning and path tracking. First, the preferred path in presence of diverse constraints of states, inputs, and collision avoidance can be calculated using Gauss pseudospectral method where expected position, velocity, and attitude are provided. Correspondingly, the continuous optimal control problem is converted to discrete nonlinear programming. Second, model predictive control is developed for tracking the optimized path. Considering the effect of the predictive horizon and the Gauss points' distribution on tracking performance, the varying predictive horizon is introduced to improve the tracking accuracy in non-smooth path. By the varying predictive horizon-based model predictive control method, less computation burden and better control performance are achieved. For the difference between the mathematical expressions and the real unmanned ground vehicle dynamics, genetic algorithm is utilized to identify the parameters of tire model. Simulations in MATLAB and CarSim are both implemented to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Roll and lateral dynamics of a vehicle are heavily coupled together, the increase of roll stability does not necessarily result in the improvement of stability in the lateral plane, but the decrease in lateral stability possibly contributes to instability in the roll plane. To address this challenge, a comprehensive tune of coupled roll and lateral dynamics for a vehicle fitted with hydraulically interconnected suspension system is presented in this paper. A typical sport utility vehicle is selected and modeled with 10 degrees of freedom to conduct the dynamic simulation. Also, the fluid equations of the proposed hydraulically interconnected suspension system with nonlinear damper model are derived and incorporated into the vehicle model. Furthermore, the integrated model is validated by the field test. The simulation is also conducted to assess and compare the vehicle roll and lateral dynamic performances under fishhook maneuver. The results show that the well-tuned hydraulically interconnected suspension can suppress its body motion in roll plane, enhance the yaw rate tracking ability, minimize the sideslip angle at the center of gravity, and also decrease the slip angles for tires. Last, the parameter sensitivity analysis for a strongly nonlinear hydraulically interconnected suspension system illustrates how individual hydraulically interconnected suspension parameters (roll stiffness, roll stiffness nonlinearity, roll stiffness distribution ratio, and damping ratio) contribute to different dynamic aspects of a vehicle. The results indicate that, by controlling hydraulically interconnected suspension key parameters, the vehicle dynamic performance can be effectively controlled in both roll and lateral planes. The parameter sensitivity analysis findings have pointed out the direction for controller design and laid the foundation for active hydraulically interconnected suspension system development in the future. [ABSTRACT FROM AUTHOR]

For autonomous vehicle path tracking control, the general path tracking controllers usually only consider vehicle dynamics' constraints, without taking vehicle stability evaluation index into account. In this paper, a linear three-degree-of-freedom vehicle dynamics model is used as a predictive model. A comprehensive control method combining Model Predictive Control and Fuzzy proportional–integral–derivative control is proposed. Model Predictive Control is used to control the vehicle yaw stability and track the target path by considering the front wheel angle, sideslip angle, tire slip angles, and yaw rate during the path tracking. Fuzzy proportional–integral–derivative algorithm is adopted to maintain the vehicle roll stability by controlling the braking force of each tire. Co-simulation with CarSim and MATLAB/Simulink shows the designed controller has good tracking performance. The controller is smooth and effective and ensures handling stability in tracking the target path. [ABSTRACT FROM AUTHOR]

This paper presents the design of a central feedforward control for the two chassis control systems rear-wheel steering (RWS) and torque vectoring (TV) which have related areas of intervention in lateral dynamics. A control strategy is presented in order to follow desired target values consisting of yaw acceleration and sideslip angle velocity. Central attention is given to the use of additional tyre information with the aim of enhancing vehicle handling and stability. With the knowledge of the mounted tyre type, an adaption law for the desired target values is derived. Although the focus is based on the usage of new tyre information, this modelling approach basically has the potential to reduce the need for coordination among the two systems RWS and TV, exploiting the synergies between both of them. Starting from an extended single-track model an exact Input–output linearisation method is used to design the feedforward control. This is followed by a proof of stability for the external and the internal dynamics of the controller. For the subsequent investigation, in a preliminary step, real-world in vehicle tests are carried out under varying tyre types with a wide spreading of characteristics. This serves as a basis to identify the most important tyre parameters for the controller and to derive the target goals. Finally, the controller is implemented in a 14-DOF non-linear entire vehicle model in Matlab/Simulink, that serves for simulations with a virtual vehicle plant. The performance of the presented feedforward control is assessed by specified objective criteria for steady-state and transient open-loop manoeuvres in lateral dynamics. These criteria are used to investigate the effectiveness of the control design with the aim to achieve the defined target motion. In addition to that, the manoeuvre results also serve to evaluate the control effort, involved in the coordinated cooperation of both systems. [ABSTRACT FROM AUTHOR]

We propose a real-time object-processing and smart-routing system using an unmanned aerial vehicle-mounted camera and an object-recognition algorithm to determine the image coordinates of object locations to calculate the shortest route between coordinates. This approach can reduce travel time and cost compared to conventional approaches. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive neural network (NN) controller is proposed for a class of nonlinear active suspension systems (ASSs) with hydraulic actuator. To eliminate the problem of “explosion of complexity” inherently in the traditional backstepping design for the hydraulic actuator, a dynamic surface control technique is developed to stabilize the attitude of the vehicle by introducing a first-order filter. Meanwhile, the presented scheme improves the ride comfort even when the uncertain parameter exists. Due to the existence of uncertain terms, the NNs are used to approximate unknown functions in the ASSs. Finally, a simulation for a servo system with hydraulic actuator is shown to verify the effectiveness and reliability of the proposed approach. [ABSTRACT FROM AUTHOR]

Aiming at the requirement of the intelligent vehicle for the fast and stable tracking control of the wheel slip, a novel robust adaptive anti-windup wheel slip tracking control method with fast terminal sliding mode observer is proposed. First, a fast terminal sliding mode observer based on equivalent control on the sliding surface is proposed to estimate the states of the wheel slip dynamic system to lay the foundation for the full state feedback control law design. Second, a robust adaptive anti-windup wheel slip tracking control law with lumped uncertainty observer and additional anti-windup dynamics is derived based on Lyapunov-based method. The lumped uncertainty observer utilizes the nonlinear mapping ability of the radius basis function neural network to estimate and compensate the lumped uncertainty of the system, and the unknown optimal weight vector of the radius basis function neural network is updated by adaptive law. The additional anti-windup dynamics is used to suppress the effect of the input saturation on the stability of the system. Finally, the performance of the proposed method is verified through simulations of various maneuvers on vehicle dynamics simulation software. [ABSTRACT FROM AUTHOR]

This paper concentrates on the problem of finite-time altitude and velocity tracking control for hypersonic flight vehicles that encounter unmodeled dynamics and input saturations. An adaptive neural finite-time backstepping control strategy is constructed by designing modified virtual commands and compensation signals. The minimum learning parameter algorithm based on a radial basis function is employed to approximate the unknown dynamics with low computational burden. Furthermore, an auxiliary system is established to cope with the nonlinearity caused by actuator saturation. It is concluded by a Lyapunov-based analysis that the finite-time stability is guaranteed under the developed architecture. Finally, numeral simulation is provided to demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper studies neural network models of vehicle dynamics. We consider both models with a generic layer architecture and models with specialised topologies that hard-wire physics principles. Network pre-wiring is limited to universal laws; hence it does not limit the network modelling abilities on one side but allows more robust and interpretable models on the other side. Four different network types (with and without pre-wired structure, recursive and non-recursive) are compared for the longitudinal dynamics of a car with gears and two controls (brake and engine). Results show that pre-wiring effectively improves the performance. Non-recursive networks also look to be preferable for several reasons. [ABSTRACT FROM AUTHOR]

Aiming at the difficulty of vehicle lateral control in high-speed condition, a comprehensive control method that integrates active steering (AS) and direct yaw moment control (DYC) systems is proposed for four-wheel independent driving and four-wheel independent steering (4WID/4WIS) vehicle. According to the characteristics of lateral dynamics in high-speed conditions, different principles are adopted in different steering conditions. In a slight or moderate steering, a decoupling control method is proposed, and a penalty function is used to allocate the involvement of AS and DYC for the over-actuated characteristics of 4WID/4WIS vehicle. While in a large steering, based on sideslip phase plane, handling-oriented and stability-oriented control are proposed in order to realise a fine trade-off between handling and stability performance. A transient layer is introduced in the phase plane to further improve the performance of this controller. And the allocation of active yaw moment is also discussed. Simulation results demonstrate that the proposed integrated control method can effectively improve the lateral dynamics performance of the vehicle in high-speed condition as compared to previous control methods. [ABSTRACT FROM AUTHOR]

Road roughness is a measure of how uncomfortable a ride is, and provides an important indicator for the needs of roadway maintenance or repavement, which is closely tied to the state and federal budget prioritization. As such, accurate and timely monitoring of deteriorating road conditions and following maintenance are essential to improve the overall ride quality on the road. Various technologies, including vehicle‐mounted laser profiling systems, have been developed and adopted for road roughness (e.g., IRI—International Roughness Index) measurement; however, their high cost limits their use. While recent advances in smartphone technologies allow us to use their embedded accelerometers for road roughness monitoring, the complicated process of necessary vehicle calibration hinders the widespread use of the technology in the actual practices. In this work, a deep learning IRI estimation method is proposed with the goal of using anonymous (i.e., calibration‐free) vehicles and their responses measured by smartphones as road roughness sensors. A state‐of‐the‐art deep learning algorithm (i.e., CNN—convolutional neural network) and multimetric vehicle dynamics data (i.e., accelerometer, gyroscope), possibly measured by drivers' smartphones, are employed for the purpose. Optimized CNN architecture and data configuration have been investigated to achieve the best performance. The efficacy of the proposed method has been numerically validated using real road IRI information (i.e., Speedway, Tucson, AZ), real driving speed profiles, and four different types of vehicle data with associated uncertainties. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) have the ability to make changes in travelling and driving mode of people and so on, in which vehicle can broadcast and forward the message related to emergency or present road condition. The safety and efficiency of modern transportation system is highly improved using VANETs. However, the vehicular communication performance is weakened with the sudden emergence of distributed denial of service (DDoS) attacks. Among other attacks, DDoS attack is the fastest attack degrading the VANETs performance due to its node mobility nature. Also, the attackers (cyber terrorists, politicians, etc.) have now considered the DDoS attack as a network service degradation weapon. In current trend, there is a quick need for mitigation and prevention of DDoS attacks in the exploration field. To resolve the conflict of privacy preservation, we propose a fast and secure HCPDS based framework for DDoS attack detection and prevention in VANETs. The Road Side Units (RSUs) have used HCPDS algorithm to evaluate the fitness values of all vehicles. This evaluation process is done for effective detection of spoofing and misbehaving nodes by comparing the obtained fitness value with the statistical information (packet factors, RSU zone, and vehicle dynamics) gathered from the vehicles. The credentials of all worst nodes are cancelled to avoid further communication with other vehicles. In HCPDS algorithm, the PSO updation strategy is added to Dragon fly algorithm to improve the search space. In addition, Chaos theory is applied to tune the parameters of proposed HCPDS algorithm. From the experimental results, it proved that the HCPDS based proposed approach can efficiently meet the requirements of security and privacy in VANETs. [ABSTRACT FROM AUTHOR]

The objective of this study is to model the complex behavior of non-lane based heterogeneous traffic which is predominantly occupied by vehicles with varying physical and dynamical characteristics and their staggered car following behavior. This study proposes a new continuum model by considering the properties of two-sided lateral gap in a non-lane based heterogeneous traffic stream. The model is built on a strong empirical background and modified car following theory. In particular, the model consists of density dependent disturbance propagation speed, viscosity term and a frictional clearance term to describe the complex vehicular interactions in a traffic stream. Viscosity term in the model represents the driver's reaction to a sudden change in density and further, it helps in smoothening out the shock fronts. Frictional clearance term in the model considers the effect of slow moving vehicles on the dynamics of fast moving vehicles. The results of mathematical and numerical analysis show that the proposed model satisfies all the qualitative and physical properties of the real world system. Moreover, two sided lateral gap in the model improves the stability region of traffic flow and increases the capacity and density of traffic stream. In addition, it is able to dissipate the traffic perturbation rapidly when compared to one-sided lateral gap model. It is anticipated that the new model provides the basis for evaluating alternative transport policy measures and helps in analyzing the system performance in the future. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to build an accurate mathematical model which is necessary for control design and attitude estimation of a miniature unmanned rotorcraft and its subsequent conversion to an autonomous vehicle. Design/methodology/approach: Frequency-domain system identification of a small-size flybar-less remote controlled helicopter is carried out based on the input–output data collected from flight tests of the instrumented vehicle. A complete six degrees of freedom quasi-steady dynamic model is derived for hover and cruise flight conditions. Findings: The veracity of the developed model is ascertained by comparing the predicted model responses to the actual responses from flight experiments and from statistical measures. Dynamic stability analysis of the vehicle is carried out using eigenvalues and eigenvectors. The identified model represents the vehicle dynamics very well in the frequency range of interest. Research limitations/implications: The model needs to be augmented with additional terms to represent the high-frequency dynamics of the vehicle. Practical implications: Control algorithms developed using the first principles model can be easily reconfigured using the identified model, because the model structure is not altered during identification. Originality/value: This paper gives a practical solution for model identification and stability analysis of a small-scale flybar-less helicopter. The estimated model can be easily used in developing control algorithms. [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]

Benefits of introducing active suspension in autonomous vehicles in terms of improving the driver's work/leisure ability can be tested under laboratory conditions using a high-performance shaker rig. In this paper, five different suspension configurations, including passive, semi-active, and fully active suspensions (FAS) and related optimal controls with or without road preview information, are implemented in vehicle dynamics simulator. They are experimentally examined having the driver in the loop to obtain objective and subjective measures of ride comfort and ability to do certain tasks. In total, 44 drivers of various age, gender, and driving experience performed three different tasks while being driven on shaker-rig (reading and writing, drawing, and subjective grading). The examination results show that FAS with road preview control offers highest ride comfort improvement, which can be perceived by the driver and greatly improves his/her ability to text and particularly draw. [ABSTRACT FROM AUTHOR]

A high-speed supercavitating vehicle is a future underwater vehicle which exploits the supercavitating propulsion technology providing a promising way to increase the vehicle speed. Robust control challenges include complex vehicle maneuvering dynamics caused by factors such as undesired switching, delayed state dependency, and nonlinearities. As effective and applicable controllers, a novel fractional-order sliding mode controller is proposed to robustly control the uncertain high-speed supercavitating vehicle system against external disturbances. The control scheme uses sliding mode control and can produce better control actions than conventional the integer-order counterpart. In this algorithm, the fractional calculus is applied to calculate the noninteger integral or derivative in the sliding mode control algorithm, providing new capabilities for uncertain high-speed supercavitating vehicle control in seeking to operate the underwater vehicle better. The performance of the proposed fractional-order sliding mode controller has been proven through analytic simulation results, which show fast responses with smooth control actions and the ability to deal with nonlinear planing force and external disturbance. One of the interesting features of the fractional-order control system is the time convergence rate of the sliding variable vector, which is greatly improved compared with the integer-order sliding mode control. Finally, the robust control system with a novel fractional-order sliding mode controller algorithm, using high flexibility of controlling undersea vehicles, can provide superior dynamical performance with stability compared with its integer-order counterpart against system uncertainties and disturbances. [ABSTRACT FROM AUTHOR]

The typical vehicle model and the rutting road model were established by CarSim simulation software according to vehicle dynamics theory and road engineering standards. Sixteen driving conditions were designed， and the model was verified. Based on the automobile manufacturing specifications and stability test rules, five driving stability indexes of lateral acceleration, roll angle, yaw rate, breaking distance and offset distance were selected, and their thresholds were established. The rutting with different depths was added into the pavement model, and the stability of each index was investigated by observing the numerical value. The quantitative indexes of rutting threshold of asphalt pavement under different driving conditions were proposed. The results show that under different driving conditions, the impact of rutting on driving stability is different. The rut threshold of asphalt pavement is decreased with the increasing of speed and water film thickness, and the impact of mobile rutting is more severe than that of structural rutting at the same depth. Considering the stability requirement of vehicles on rutting roads, the rutting threshold values of straight and curved roads under different driving conditions are proposed. [ABSTRACT FROM AUTHOR]

In this article, in the presence of completely unknown dynamics and unmeasurable velocities, a dynamics-level finite-time fuzzy monocular visual servo (DFFMVS) scheme is created for regulating an unmanned surface vehicle (USV) to the desired pose. Main contributions are as follows: first, with the aid of homography decomposition, a novel homography-based visual servo structure for a USV with both kinematics and dynamics is first established such that complex unknowns including unmeasurable poses and velocities, image depth, system dynamics, and time-varying inertia are sufficiently encapsulated; second, using finite-time observer technique, finite-time velocity observer (FVO) based visual-servo error dynamics are elaboratively formulated, and thereby facilitating backstepping synthesis; third, by virtue of the FVO, the adaptive fuzzy dynamics approximator together with adaptive residual feedback is deployed to compensate complex unknowns, and thereby contributing to accurate regulation of pose errors; and fourth, a completely model-free monocular visual servo approach only using a camera is eventually invented. Simulation studies on a benchmark prototype USV demonstrate that the proposed DFFMVS scheme has remarkable performance with significant superiority in both visual servo and unknowns observation. [ABSTRACT FROM AUTHOR]

Summary: The thermophysical properties of phase change material (PCM) directly affect the performance of underwater vehicles. The accuracy of the phase change transfer model is an important index for evaluating the performance of PCM as well. In this paper, a molecular dynamics approach is proposed to obtain the thermophysical properties of PCM under different pressures. On such a basis, the modified models of "temperature‐pressure‐density," "temperature‐pressure‐thermal conductivity" and "pressure‐specific heat capacity" are established. By comparing the simulation results with the unmodified phase change transfer model and the laboratory experimental results, it can be seen that the modified phase change transfer model has higher accuracy. Furthermore, an ocean thermal energy conversion system for underwater vehicles is deployed in the South China Sea to test the utilization performance. By the contrast between the simulated calculation of the modified model and the sea trial results, it is found that the root mean square (RMS) of accumulator pressure between the simulation and sea trial is 0.2565, and the energy storage volume RMS is 1.6868. When the accumulator pressure reaches 205 bar, the time error is 0.58%, and the energy storage volume error is 3.16%. The results indicate that the modified model is effective in practical application. [ABSTRACT FROM AUTHOR]

This paper focuses on racecar longitudinal control with highly-varying driving conditions. The main factors affecting the dynamic behavior of a vehicle, including aerodynamic forces, wheel rolling resistance, traction force resulting from changing tire-road interaction as well as the occurrence of sudden wind gusts or the presence of persistent winds, are considered and assumed to have unknown models. By exploiting the theory on delayed input-state observers and using measurement data about the vehicle and wheel speeds, a dynamic filter that allows the online reconstruction of the above-mentioned unknown time-varying quantities is derived. Moreover, by exploiting the notion of effective tire radius, a reduced-degree-of-freedom model for the longitudinal vehicle dynamics is obtained, which is independent of the traction force and that enables, when used with the observer filter described above, an accurate speed control compensating for the resistance forces. One appealing feature of the proposed estimation and control method is that it requires no model information about such forces, for which, at the state-of-the-art, only heuristic approximations to be a-priori identified are available. Its effectiveness is shown via the simulation of scenarios where the car is required to execute aggressive maneuvers and the asphalt road surface abruptly changes from dry to wet, snowy, and icy. The evaluation also reveals that the proposed estimation technique outperforms standard solutions even in the presence of measurement noise. [ABSTRACT FROM AUTHOR]

This study devises a variable-performance control law for rover vehicles servoing velocity and pitch angle commands. This considers both vehicle and actuator dynamics as well as load and parameter variations. The main merits are summarized as follows. First, the proposed auto-tuning law magnifies the feedback gain for desired systems to achieve transient performance improvement with the convergence property guarantee. Second, the collaboration of pole-zero cancellation controller and disturbance observers eliminates over/undershoots through closed-loop order reduction by a special form of feedback gain. Beneficial closed-loop properties are also derived from the closed-loop analysis. The prototype rover vehicle built with TETRIX and MyRIO-1900 experimentally validates the closed-loop performance and robustness improvement. [ABSTRACT FROM AUTHOR]

The work presented in this paper concerns a switching-based control formulation for multi-intersection and multiphase traffic light systems. A macroscopic traffic flow modeling approach is first presented, which is instrumental to the development of a model-based and switching-based optimization method for traffic signal operation, in the framework of adaptive dynamic programming (ADP). The main advantage of the switching-based formulation is its capability to determine both “when”’ to switch and “which” mode to switch on without the need to use the cycle-based average flow approximation typical of state-of-the-art formulations. In addition, the framework can handle different cycle times across intersections without the need for synchronization constraints and, moreover, minimum dwell-time constraints can be directly enforced to comply with minimum green/red times in each phase. The simulation experiments on a multi-intersection and multiphase traffic light systems are presented to show the effectiveness of the method. [ABSTRACT FROM AUTHOR]

This article presents a robust nonlinear model predictive control (NMPC) scheme for autonomous navigation of underwater robotic vehicles operating in a constrained workspace including the static obstacles. In particular, the purpose of the controller is to guide the vehicle toward specific way points with guaranteed input and state constraints. Various constraints, such as obstacles, workspace boundaries, predefined upper bounds for the velocity of the robotic vehicle, and thruster saturations, are considered during the control design. Moreover, the proposed control scheme is designed at dynamic level, and it incorporates the full dynamics of the vehicle in which the ocean currents are also involved. Hence, taking the thrusts as the control inputs of the robotic system and formulating them accordingly, the vehicle exploits the ocean current dynamics when these are in favor of the way-point tracking mission, resulting in reduced energy consumption by the thrusters. The robustness of the closed-loop system against parameter uncertainties has been analytically guaranteed with convergence properties. The performance of the proposed control strategy is experimentally verified using a 4 degrees of freedom (DoF) underwater robotic vehicle inside a constrained test tank with sparse static obstacles. [ABSTRACT FROM AUTHOR]

This brief presents a robust formation control method for a team of quadrotors with communication delays. The dynamics of each quadrotor is subject to nonlinearities, parametric perturbations, and external disturbances. A distributed formation controller is developed for the quadrotor team, which consists of a position controller to achieve the desired formation trajectories and patterns, and an attitude controller to regulate the attitude angles for each quadrotor. It is proven that the tracking errors can converge into a neighborhood of the origin bounded by a given constant in a finite time. Experimental results on multiple microquadrotors are provided to verify the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

Although the concept modeling method has already been proposed in the literature, there is still very limited knowledge about the validation and the application of this method for vehicle body design. This paper substantially increases this limited knowledge by developing a concept model for predicting and optimizing the structural dynamics of a vehicle body-in-white and validating this concept model against a detailed finite element model. The geometry and parameters of the concept model are extracted from its detailed finite element model. The major members and panels of the detailed finite element model are replaced by their equivalent beam and shell elements models. The joints of the concept model are represented by stiffness and mass matrices extracted from the detailed finite element model using the Guyan Reduction Method. The developed concept model is validated by comparing its structural dynamics, including the resonant frequencies and the vibration mode shapes, with the original detailed finite element model and the experimental results. The simplicity and small size of the concept model enable it to easily enhance the structural dynamics of the body-in-white by optimizing the cross-sections of the load-carrying members of the structure. The optimization in this case increased the resonant frequencies of the body-in-white while reducing the total mass by about 6 kg. The results prove that the concept modeling method can significantly enhance the body-in-white structural dynamics by reducing the complexity of the model and allowing the focus for the optimization to be on the main members of the structure at the development stage when the final design parameters are not well known and have not been fixed. [ABSTRACT FROM AUTHOR]

The tendency in the past few years has been to introduce tyres with lower rolling resistance coefficients to the market. This paper presents a mathematical method for determining the rolling resistance coefficients variation depending on the speed. The method uses power balance which results from automobile dynamics while rolling on chassis dynamometer. The rolling resistance coefficients of tyres obtained through 'drum test method', for which the rolling resistance coefficients variation is known in terms of vehicle speed, are considered as reference values, while than rolling resistance coefficients of tyres obtained through 'MAHA roller dynamometer' using the recorded lost drag power in the roll-out phase on the stand are considered as tested values. The rolling resistance coefficients variation could be determined up to the maximum permissible speed of the tyre, for all wheels trained on the stand and not just for one tyre, as determined in laboratory conditions. The test conditions are similar to those in real road conditions, where the temperature of the environment and wheels cannot be controlled. The values obtained by the authors' proposed method were compared with the values obtained by the 'drum test method'. The main contribution of the proposed method is to estimate the rolling resistance coefficients without using a very expensive test facility. [ABSTRACT FROM AUTHOR]

The information of vehicle attitude and tire force under complex environment and maneuver condition is of great significance for system risk prediction and active control system intervention. In order to collect the accurate system states, the coupling vehicle dynamics model and moving horizon estimation method are employed to solve the online optimization problem based on the premise of rolling optimization. Furthermore, the accurate observation and acquisition of the vehicle system state are realized. On this basis, the simulation process of the vehicle state observation using moving horizon estimation method and unscented Kalman filter algorithm are implemented, respectively. The corresponding observation results under complex maneuvering conditions are further validated by using the hardware-in-the-loop experimental platform. Finally, the comparison of the observation results obtained by the unscented Kalman filter and moving horizon estimation algorithms demonstrate that the moving horizon estimation method can effectively improve the observation accuracy of vehicle system state in complex environment, including vehicle roll angle and tire dynamic force. The results obtained through moving horizon estimation method are conducive to the further signal early warning, risk prediction and assessment, as well as systematic intervention and active rollover control. [ABSTRACT FROM AUTHOR]

This paper proposes a novel path-following control algorithm for articulated steer vehicles (ASV) by dynamic virtual terrain field (VTF) method. The altitude function of VTF, with robustness in fitting different working conditions, is adapted for the derivation of target steering wheel angle. Prior to the development of the controller, the nonlinear ASV model coupling with a full-hydraulic steering system is verified by real test and Adams/View software simulation. To get a precise path-following result, the sideslip angle is considered and controlled by 'direct sideslip control' and 'road roll control'. The function of VTF is established and divided into primary and dynamic terrain field reference to the parameter variabilities. According to the vehicle dynamics model and the tire forces generated from the vehicle inclination on virtual terrain, the target articulation angle composed of the main angle and compensatory angle is derived. Simulations of path-following control at different road conditions, together with other types of controllers, are conducted and compared to show the feasibility and effectiveness of the proposed path-following control algorithm. [ABSTRACT FROM AUTHOR]

This study developed a control algorithm of torque vectoring system to improve the handling performance of a green-car and evaluate the performance of vehicle dynamics to improve the controllability and stability. Firstly, this study configured the control algorithm with the supervisory controller that decides the control mode by checking the current driving status of a vehicle, target yawrate calculator that reflects the steady-state and transient-state response characteristics according to the control mode, as well as the reference yawrate calculation, desired yaw moment calculation and transferred torque calculation. The control mode consists of the agile mode that controls the torque vectoring to improve the controllability and the safe mode that controls the torque vectoring to improve stability. Secondly, this study performed the modeling of the dual motor type torque vectoring system and an EV AWD vehicle. Lastly, this study defined the driving test scenario and evaluation method as well as the quantitative performance index for each vehicle test and established the co-simulation environment for the handling test evaluation. This study found that when a vehicle is controlled by applying the torque vectoring system, handling performance was improved according to controllability and safe mode by verifying the simulation. [ABSTRACT FROM AUTHOR]

In this article, a novel hyperbolic-tangent line-of-sight (LOS) guidance-based finite-time path following (HLOS-FPF) framework is created to render an underactuated marine vehicle (UMV) rapidly and accurately follow the desired path, in the presence of complex unknowns including internal dynamics, external disturbances, and arbitrary sideslip. By defining a virtually desired sideslip angle of which the tangent-nonlinearity is exactly identified by a finite-time sideslip observer, the hyperbolic-tangent LOS (HLOS) guidance laws collaboratively governing heading, surge, and virtual ship velocity are devised in a finite-time manner such that cross-track error sensitively excites heading guidance. With the aid of nonsmooth auxiliary dynamics, guidance errors are finely dominated with finite-time convergence. Finite-time heading and surge controllers are further synthesized by integral and nonsingular terminal sliding-mode techniques, and ensure that HLOS guidance signals can be exactly tracked, whereby complex unknowns are exactly compensated by finite-time unknown observer. Eventually, nonsmooth analysis together with Lyapunov approach guarantees that the entire HLOS-FPF scheme is globally finite-time stable and contributes to exact path-following under heading-surge collaborative guidance. Simulation results and comprehensive comparisons with typical methods demonstrate remarkable superiority of the innovative HLOS-FPF scheme. [ABSTRACT FROM AUTHOR]

This paper studies the robust H∞ filtering problem for the in-vehicle networked system with sensor failure, dynamic quantization and data dropouts. The nonlinear vehicle lateral dynamics is described as the Takagi-Sugeno fuzzy system. We assume that the sensor failure is adopted to present inaccurately work of the sensor, and both the measurement and performance output signals are quantized by the dynamic quantizers before being transmitted to the network channel. Moreover, the Bernoulli random binary distribution is considered to describe the data dropouts phenomenon both in the measurement and performance outputs. The proposed filter design method is given in the form of linear matrix inequalities which guarantee that the filtering error system is stochastically stable with H∞ performance index. Finally, the co-simulation of the Matlab/Simulink and Carsim is used to validate the proposed filter design method. [ABSTRACT FROM AUTHOR]

The technology of static user-centric virtual cell (VC) has been designed in the fifth-generation (5G) ultra-dense networks (UDNs) for alleviating both frequent handover and inter-cell interference. However, to provide the user-centric services, the fairness of resource management must be involved when the common vehicular-to-X (V2X) messages are multicast to the vehicle groups. In this paper, a dynamic user-centric virtual cell (DUVC) scheme is proposed for updating adaptively the VC through the mobile tracking of the vehicles. Furthermore, an approximation algorithm is proposed for solving the max-min-fair problem of resource management in V2X communication in order to better support V2X services throughout the service VC. Numerical results are provided for demonstrating that the proposed DUVC scheme is suitable for implementing in the V2X communication. Finally, the proposed algorithm is shown to outperform three other existing algorithms in terms of fairness of resource management. [ABSTRACT FROM AUTHOR]

Information fusion of the GPS/INS integrated system is always related to characteristics of the inertial system and the sensor feature, yet prior knowledge is still difficult to obtain in real applications. To deal with the uncertainty of error covariance and state noise in vehicle navigation, this paper presents a novel approach, wherein the integration of Square-root Cubature Kalman Filters (SCKF) and Interacting Multiple Model (IMM) are also introduced. In the framework of IMM, the SCKFs with different covariance are designed to reflect various vehicle dynamics. Besides, since the IMM-SCKF can switch flexibly among the filters, the transition probability matrix is computed with maximum likelihood method to adapt to different noise characteristics. The performance of the proposed algorithm is guaranteed by theoretical analyses, and a series of vehicular experiments with different maneuvers are carried out in an urban environment. The results indicate that, in comparison with the CKF and the IMM-CKF, the accuracy of velocity and attitude are increased by the proposed strategy. • In the framework of IMM, a novel approach is proposed to deal with the uncertainty of error covariance and state noise. • The transition probability matrix is computed with recursive maximum likelihood method to adapt to different noise characteristics. • The Square-root CKF based on inertial navigation error model and measurement model is introduced. • The vehicle navigation experiments with different maneuvers are designed and implemented. [ABSTRACT FROM AUTHOR]

Hub-driven technology with its many advantages has become a potential transformation technology in the automotive industry. In order to inhibit the negative effects of the in-wheel motor, a new electric wheel configuration was presented with two-stage suspensions, and optimization was conducted for the suspension parameters. With the specially introduced flexible transmission elements and motor suspension, the electric wheel is capable of achieving power transmission and vertical vibration isolation simultaneously. A quarter-vehicle model was established, and vehicle performance-related indices were defined to evaluate the applicability of the new electric wheel. An optimization problem was then constructed for suspension parameters, where constraint conditions were derived according to vehicle dynamics. The optimal solution was sought by a genetic algorithm, aiming at utilizing the full potential of the configuration. Simulations were carried out taking the optimal suspension parameters into account, and comparison was made with vehicles equipped with other electric wheel configurations in terms of these performance indices. The results show that the proposed electric wheel reduces motor vibration, and increases wheel dynamic load and vehicle body acceleration. [ABSTRACT FROM AUTHOR]

This article describes a hybrid simulation approach meant to facilitate the realization of a simulator for underwater vehicles with one or more manipulators capable of simulating the interaction of the vehicle with objects and structures of the environment. The hybrid simulation approach is first described and motivated analytically, then an analysis of simulation accuracy is proposed, where, in particular, the implications of added mass simulation are discussed. Then, a possible implementation of the proposed architecture is shown, where a robotic simulator of articulated bodies, capable of stable and accurate simulation of contact forces, although unfit to simulate any serious hydrodynamic model, is tightly interfaced with a general purpose dynamic systems simulator that is used to simulate the hydrodynamic forces, the vehicle guidance, navigation, and control system, and also a man–machine interface. Software details and the technicalities needed to interface the two simulators are also briefly presented. Finally, the results of the simulation of three operational scenarios are proposed as qualitative assessment of the simulator capabilities. [ABSTRACT FROM AUTHOR]

Railway interaction is characterised by the coupling between the train and the track introduced through the wheel/rail contact. The introduction of the flexibility in the wheelset and the track through the finite element (FE) method in the last four decades has permitted to study high‐frequency phenomena such as rolling noise and squeal, whose origin lies in the strongly non‐steady state and non‐linear behaviour of the contact forces that arise from the small contact area. In order to address models with a large number of degrees of freedom, innovative Eulerian‐modal models for wheelsets with rotation and cyclic tracks have been developed in recent years. The aim of this paper is to extend the resulting formulation to an uncoupled linear matrix equation of motion that allows solving each equation independently for each time step, considerably reducing the associated computational cost. The decoupling integration method proposed is compared in terms of computational performance with Newmark and Runge‐Kutta schemes, commonly used in vehicle dynamics, for simulations with the leading wheelset negotiating a tangent track and accounting the rail roughness. [ABSTRACT FROM AUTHOR]

In this work, a multibody model of a small size farming tracked vehicle is shown. Detailed models of each track were coupled with the rigid body model of the vehicle. To describe the interaction between the track and the ground in case of deformable soil, custom defined forces were applied on each link of the track model. Their definition derived from deformable soil mechanics equations implemented with a specifically designed routine within the multibody code. According to the proposed model, it is assumed that the main terrain deformation is concentrated around the vehicle tracks elements. The custom defined forces included also the effects of the track grousers which strongly affect the traction availability for the vehicle. A passive soil failure model was considered to describe the terrain behaviour subjected to the grousers action. A so developed model in a multibody code can investigate vehicle performance and limit operating conditions related to the vehicle and soil characteristics. In this work, particular attention was focused on the results in terms of traction force, slip and sinkage on different types of terrain. Tests performed in the multibody environment show how the proposed model is able to obtain tractive performance similar to equivalent analytical solutions and how the grousers improve the availability of tractive force for certain type of soil characteristics. [ABSTRACT FROM AUTHOR]

The deposition of toxic metals in the ecosystem contributes to the exposure and bioaccumulation of metals in the food chain, thus affecting human health. This study aimed to access the distribution of metal pollution emitted from automobiles in the dust, soil, and plant samples collected from the roadsides of national highways. Furthermore, metals were also determined in fuels and vehicular emissions. High contents of Pb, Cd, Cr, Cu, Fe, Mn, and Zn were found in roadsides as compared to control (35 km away from roads). The comparison among plants indicated that Calotropis procera and Rumex dentatus contained significantly higher metals than other plants. The concentrations of Pb, Cd, Cr, and Fe in plants were above the safe limits of the WHO/FAO. Significant and positive correlations were found between Cr, Cu, Fe, Pb, and Zn in the dust and soil samples and Cd and Cr in dust and plants. According to the results of the PCA analysis, all metals formed the first two components explaining 89.5% of the total variance. The source of these metals was attributed to automobile exhaust and dust depositions. The findings of the present study suggest that roadside plants are heavily infested with heavy metals due to vehicular smoke pollution, so the consumption of vegetation facing vehicular pollution may lead to certain physiological disorders and diseases. [ABSTRACT FROM AUTHOR]