Lateral Dynamic Behaviour Research Articles

Evaluation of Vehicle Lateral and Longitudinal Dynamic Behavior of the New Package-Saving Multi-Link Torsion Axle (MLTA) for BEVs

To increase the package space for the battery pack in the rear of battery electric vehicles (BEVs), and thus extend their driving range, a novel rear axle concept called the multi-link torsion axle (MLTA) has been developed. In this work, the kinematic design was extended with an elastokinematic concept, and the MLTA was designed in CAD and realized as a prototype. It was then integrated into a B-class series-production vehicle by adding masses in different locations of the vehicle to replicate the mass distribution of a BEV. Both objective and subjective vehicle dynamic evaluations were conducted, which included kinematic and compliance tests, constant-radius cornering, straight-line braking, and a frequency response test, as well as subjective evaluations by both expert and normal drivers. These test results were analyzed and compared to a production vehicle. It can be concluded that the vehicle dynamic performance of the MLTA-equipped vehicle is, overall, 0.67 grades lower than that of the comparable production vehicle on a 10-grade scale. According to OEM experts, this deficit can be eliminated by tuning the different components of the MLTA and meeting the tolerance requirements of series production vehicles.

Transient lateral dynamic behavior of tire on μ-step road

Transient lateral dynamic behavior of tire on μ-step road

Research on coupled vibrations between the low-to-medium speed maglev train and a long-span continuous beam bridge

This study investigates the strong coupling vibration between low-to-medium speed maglev trains and the track beam, which results from unique transmission principle of the trains. The research focuses on the impact of train parameters on the dynamic response of the car-bridge system, using a long-span continuous beam bridge as the background. Initially, a multi-body dynamics model of maglev trains was established based on the theory of maglev force equivalence as stiffness and damping. Subsequently, the solid element available in ANSYS was employed to construct a finite element model of the large-span bridge. In SIMPACK, the train-bridge coupled system was established to evaluate the dynamic response of the coupling system under various working conditions. The results indicate that the equivalent models of maglev train demonstrates excellent control performance. The vehicle parameters of weight and speed do not significantly affect the bridge vibration characteristics. However, the lateral dynamic behavior of the bridge increases significantly when the train velocity reaches 160 km/h. The operation of double-line trains in opposing directions can result in more complex bridge vibrations, with a greater dynamic response observed. Therefore, the analysis of the coupled vibration of the car-bridge system under complex operating conditions is required in the design phase. Analyzing the coupled vibration of train-bridge systems during the design phase is crucial for ensuring the safe and efficient of maglev trains.

Friction Issues over the Railway Wheels-Axis Assembly Motion

The frictional issues during motion of the axis-wheels assembly occurring in contact wheel–rail and in bogie bearing were studied. The influence of greases upon friction therein was also considered. The lateral dynamic behavior of the four-axle freight wagon model with two-axle Y25 bogies equipped with swing bolster was analyzed. Simulation models of such a wagon with bogies with and without swing bolsters were elaborated for calculations considering the nonlinearities of wheel–rail contact geometry and nonlinear methods of bogie stability. In these two options, the cases of empty and fully loaded wagon bodies were considered. The lateral dynamic models with 22 and 24 degrees of freedom were considered to determine the nonlinear critical speeds of a freight wagon. It was found that the resistive torque in bearings of the assembly studied varied nonlinearly with wagon speed. During motion along the curve track, values of such a torque can be higher by 50% in case of the wheel under overloading and lower by 50% in case of the wheel under underloading, respectively, compared to those obtained during motion along straight track.

Integrated Chassis Control and Control Allocation for All Wheel Drive Electric Cars with Rear Wheel Steering

This study investigates a control strategy for torque vectoring (TV) and active rear wheel steering (RWS) using feedforward and feedback control schemes for different circumstances. A comprehensive vehicle and combined slip tire model are used to determine the secondary effect and to generate desired yaw acceleration and side slip angle rate. A model-based feedforward controller is designed to improve handling but not to track an ideal response. A feedback controller based on close loop observation is used to ensure its cornering stability. The fusion of two controllers is used to stabilize a vehicle’s lateral motion. To increase lateral performance, an optimization-based control allocation distributes the wheel torques according to the remaining tire force potential. The simulation results show that a vehicle with the proposed controller exhibits more responsive lateral dynamic behavior and greater maximum lateral acceleration. The cornering safety is also demonstrated using a standard stability test. The driving performance and stability are improved simultaneously by the proposed control strategy and the optimal control allocation scheme.

Condition-Based Maintenance for Normal Behaviour Characterisation of Railway Car-Body Acceleration Applying Neural Networks

Recently, passenger comfort and user experience are becoming increasingly relevant for the railway operators and, therefore, for railway manufacturers as well. The main reason for this to happen is that comfort is a clear differential value considered by passengers as final customers. Passengers’ comfort is directly related to the accelerations received through the car-body of the train. For this reason, suspension and damping components must be maintained in perfect condition, assuring high levels of comfort quality. An early detection of any potential failure in these systems derives in a better maintenance inspections’ planification and in a more sustainable approach to the whole train maintenance strategy. In this paper, an optimized model based on neural networks is trained in order to predict lateral car-body accelerations. Comparing these predictions to the values measured on the train, a normal characterisation of the lateral dynamic behaviour can be determined. Any deviation from this normal characterisation will imply a comfort loss or a potential degradation of the suspension and damping components. This model has been trained with a dataset from a specific train unit, containing variables recorded every second during the year 2017, including lateral and vertical car-body accelerations, among others. A minimum average error of 0.034 m/s2 is obtained in the prediction of lateral car-body accelerations. This means that the average error is approximately 2.27% of the typical maximum estimated values for accelerations in vehicle body reflected in the EN14363 for the passenger coaches (1.5 m/s2). Thus, a successful model is achieved. In addition, the model is evaluated based on a real situation in which a passenger noticed a lack of comfort, achieving excellent results in the detection of atypical accelerations. Therefore, as it is possible to measure acceleration deviations from the standard behaviour causing lack of comfort in passengers, an alert can be sent to the operator or the maintainer for a non-programmed intervention at depot (predictive maintenance) or on board (prescriptive maintenance). As a result, a condition-based maintenance (CBM) methodology is proposed to avoid comfort degradation that could end in passenger complaints or speed limitation due to safety reasons for excessive acceleration. This methodology highlights a sustainable maintenance concept and an energy efficiency strategy.

Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters. Primarily, the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed, and in which the relationship between the look-ahead time and vehicle velocity is revealed. Then, in order to overcome the external disturbances, parametric uncertainties and time-varying features of vehicles, a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles, which includes an equivalent control law and an adaptive variable structure control law. In this novel automatic steering control system of vehicles, a neural network system is utilized for approximating the switching control gain of variable structure control law, and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time. The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory. Finally, the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

Structural assessment of bridges through ambient noise deconvolution interferometry: application to the lateral dynamic behaviour of a RC multi-span viaduct

Operational Modal Analysis (OMA) is becoming a mature and widespread technique for Structural Health Monitoring (SHM) of engineering structures. Nonetheless, while proved effective for global damage assessment, OMA-based techniques can hardly detect local damage with little effect upon the modal signatures of the system. In this context, recent research studies advocate for the use of wave propagation methods as complementary to OMA to achieve local damage identification capabilities. Specifically, promising results have been reported when applied to building-like structures, although the application of Seismic Interferometry to other structural typologies remains unexplored. In this light, this work proposes for the first time in the literature the use of ambient noise deconvolution interferometry (ANDI) to the structural assessment of long bridge structures. The proposed approach is exemplified with an application case study of a multi-span reinforced-concrete (RC) viaduct: the Chiaravalle viaduct in Marche Region, Italy. To this aim, ambient vibration tests were performed on February 4^{text {th}} and 7^{text {th}} 2020 to evaluate the lateral and longitudinal dynamic behaviour of the viaduct. The recorded ambient accelerations are exploited to identify the modal features and wave propagation properties of the viaduct by OMA and ANDI, respectively. Additionally, a numerical model of the bridge is constructed to interpret the experimentally identified waveforms, and used to illustrate the potentials of ANDI for the identification of local damage in the piers of the bridge. The presented results evidence that ANDI may offer features that are quite sensitive to damage in the bridge substructure, which are often hardly identifiable by OMA.

Automatic adjustment of tire inflation pressure through an intelligent CTIS: Effects on the vehicle lateral dynamic behavior

The paper investigates the effect of tire inflation pressure on the lateral dynamics of a passenger car, and presents a possible control-oriented methodology aimed at adapting tire pressure to the current vehicle loading condition targeting a reference characteristic. Starting from the tire characteristics at several inflation pressure levels, the paper investigates the effect of changing selectively tire pressure on each of the two axles, through theoretical calculation of the curvature gain based on the computation of the derivatives of stability, and compares the obtained sensitivity to the results of a multibody simulation model validated through on-track tests. Finally, the work presents a possible algorithm that could be implemented on-board vehicle ECU to provide, for the current loading condition of the vehicle, a tire pressure combination that targets a specific lateral dynamics characteristic. The algorithm is intended as part of the control logic of an intelligent Central Tire Inflation System (CTIS) able to adjust automatically tire pressure according to the actual vehicle working conditions.

Effect of base shear and moment on lateral dynamic behavior of monopiles

The base shear and moment may play important roles in behaviors of offshore monopiles, and traditional p-y curves cannot model the base forces. In this study, a new semi-analytical model for monopile is proposed, from which base forces and displacements can all be obtained simultaneously. Green's functions for poro-visco-elastic soil and Timoshenko beam are used. Full bond between pile and soil is assumed, which means the results are suitable for the normal operating conditions for offshore wind turbines. Selected numerical results are examined for different pile lengths, pile thickness, load eccentricity, soil parameters and frequencies of excitation. These results show the values of base forces are notable only when the pile's aspect ratio is very small. Besides, an interesting phenomenon is found: Ignoring the base effects will only lead to a negligible influence on pile impedances and responses, even when the pile's aspect ratio is very small. The reason is that the pile shaft near the base in the “no base effect” model will take the stresses the base bears in the “with base effect” model. The pile's overall responses and impedances are not sensitive to the detailed stress distributions around the pile base in this elasto-dynamic problem.

Estimation of lateral track irregularity using a Kalman filter. Experimental validation

The aim of this work is the development of a model-based methodology for the estimation of lateral track irregularities from measurements from different sensors mounted on an in-service vehicle: a gyroscope to measure wheelset yaw angular velocity, two accelerometers to measure lateral acceleration of the wheelset and bogie frame, and an encoder to obtain forward velocity of the vehicle. The proposed methodology is based on the Kalman filtering technique, through the use of a highly simplified linear dynamic model of a bogie, capable of capturing the most relevant lateral dynamic behaviour of the entire vehicle. The simplified dynamic model (SM) is based on a vehicle running at variable forward velocity on a track, which comprises straight, curve and transition sections. Finally, the proposed methodology has been experimentally validated through an experimental campaign carried out in a 90 m 1:10 scaled track facility at the University of Seville and an instrumented scaled vehicle. The results of the estimation of the lateral alignment are analysed in the space domain and in the space frequency domain, according to standards. These results are promising, showing a good performance for monitoring lateral alignment on straight and curve tracks, with a very low computational cost. Only in the case of very sharp curves, when continuous flange contact takes place, the estimator is not able to precisely estimate lateral alignment.

How do driving modes affect the vehicle’s dynamic behaviour? Comparing Renault’s Multi-Sense sport and comfort modes during on-road naturalistic driving

Several modern vehicles provide the option to select a driving mode. However, the literature contains no empirical studies that investigate how driving modes affect the vehicle's dynamic behaviour in regular on-road driving. We examined for which CAN-bus signals the differences between Renault's Multi-Sense® comfort and sport modes are most apparent. We gathered data on a 26.3 km route containing a rural and highway section. A single person drove the route four times in comfort mode and four times in sport mode. By statistically analysing and ordering 887 CAN-bus signals, we found strong differences between the two modes for rear-wheel angle, engine torque, longitudinal acceleration, and vertical motion. Parameter identification of a quarter car model identified a 3.5 times higher damping coefficient for the sport mode compared to the comfort mode. Due to four wheel steering, compared to the comfort mode, the sport mode yielded a higher lateral acceleration and yaw rate for a given steering wheel angle and driving speed. In conclusion, this study provides quantitative insight into the extent to which the Multi-Sense driving modes impact the vehicle's lateral, longitudinal, and vertical dynamic behaviour. The results and the analysis methods help guide future driving mode designs.

Hopf Bifurcation Characteristics of the Vehicle with Rear Axle Compliance Steering

To overcome the shortage of traditional rear axle compliance steering (RACS) technology, a kind of viscoelastic smart material is introduced into the rear suspension of a vehicle to construct rear wheel semiactive steering system. This article focuses on the nonlinear dynamic behavior of the vehicle with RACS incorporating viscoelastic smart material. First of all, considering the tire nonlinearity and the fractional derivative constitutive relation of the viscoelastic material, the nonlinear dynamic model of the vehicle with RACS is formulated. Then, the lateral dynamic behavior of the vehicle with RACS is demonstrated through numerical experiments. Finally, some factors that influence shimmy of the compliance steering wheel are investigated. Numerical results demonstrate the Hopf bifurcation characteristics of the vehicle with RACS and disclose the influence factors of Hopf bifurcation characteristics for the vehicle with RACS, which lay the theoretical foundation for the development of the rear wheel semiactive steering technology.

Gain-scheduled buckling control of a circular beam-column subject to time-varying axial loads

For slender beam-columns loaded by axial compressive forces, active buckling control provides a possibility to increase the maximum bearable axial load above that of a purely passive structure. In this paper, an approach for gain-scheduled buckling control of a slender beam-column with circular cross-section subject to time-varying axial loads is investigated experimentally. Piezo-elastic supports with integrated piezoelectric stack actuators at the beam-column ends allow an active stabilization in arbitrary lateral directions. The axial loads on the beam-column influence its lateral dynamic behavior and, eventually, cause the beam-column to buckle. A reduced modal model of the beam-column subject to axial loads including the dynamics of the electrical components is set up and calibrated with experimental data. Particularly, the linear parameter-varying open-loop plant is used to design a model-based gain-scheduled buckling control that is implemented in an experimental test setup. The beam-column is loaded by ramp- and step-shaped time-varying axial compressive loads that result in a lateral deformation of the beam-column due to imperfections, such as predeformation, eccentric loading or clamping moments. The lateral deformations and the maximum bearable loads of the beam-column are analyzed and compared for the beam-column with and without gain-scheduled buckling control or, respectively, active and passive configuration. With the proposed gain-scheduled buckling control it is possible to increase the maximum bearable load of the active beam-column by 19% for ramp-shaped axial loads and to significantly reduce the beam-column deformations for step-shaped axial loads compared to the passive structure.

Gaussian and non-Gaussian stochastic response of slender continua with time-varying length deployed in tall structures

This paper presents a study to predict the probabilistic characteristics of lateral dynamic motions of a long heavy cable moving at speed within a tall host structure. The cable is subjected to a base-motion (kinematic) excitation due to a low frequency sway of the structure. The development of the deterministic equations of motion and of the stochastic models describing the lateral dynamic behaviour of the cable is presented. Due to the time-varying length of the cable, the system exhibits nonstationary dynamic characteristics and its response is governed by nonstationary ordinary differential equations. Two stochastic models of motion of the structure are considered. In the first model, the excitation is represented as a narrow-band Gaussian process mean-square equivalent to a harmonic process. The second model involves a non-Gaussian process in the form of a random train of pulses, idealizing the action of strong wind gusts. The differential equations to determine the mean values and the second-order joint statistical moments of the response are formulated and solved numerically. A parametric study is conducted to demonstrate the influence of speed of the cable on the deterministic and stochastic characteristics of the response.

Dynamic behavior of a vehicle with rear axle compliance steering

Rear axle compliance steering (RACS) is a technology of passive four-wheel steering, which is designed to improve the vehicle handling and stability at medium or high speed. This paper focuses on the dynamic behavior of the vehicle with RACS. Firstly, the compliance steering principle for different rear suspensions is illustrated. Then, the viscoelastic members with fractional order derivative properties are introduced into RACS, and the fractional order model of RACS is formulated. Next, the dynamic model of the vehicle with RACS is established, the adjusting rules for the compliance steering stiffness are derived, and the vehicle stability is investigated. Finally, numerical experiments are performed to illustrate the effects on the vehicle dynamic behavior caused by the compliance steering stiffness, the viscoelastic members and the vehicle longitudinal velocity. Research results show that, the vehicle with RACS has better dynamic characteristics than that without RACS at medium or high speed; and the compliance steering stiffness, the viscoelastic members and the vehicle longitudinal velocity have different impacts on the vehicle lateral dynamic behavior.

Multi-Mode Electric Actuator Dynamic Modelling for Missile Fin Control

Linear first/second order fin direct current (DC) actuator model approximations for missile applications are currently limited to angular position and angular velocity state variables. Furthermore, existing literature with detailed DC motor models is decoupled from the application of interest: tail controller missile lateral acceleration (LATAX) performance. This paper aims to integrate a generic DC fin actuator model with dual-mode feedforward and feedback control for tail-controlled missiles in conjunction with the autopilot system design. Moreover, the characteristics of the actuator torque information in relation to the aerodynamic fin loading for given missile trim velocities are also provided. The novelty of this paper is the integration of the missile LATAX autopilot states and actuator states including the motor torque, position and angular velocity. The advantage of such an approach is the parametric analysis and suitability of the fin actuator in relation to the missile lateral acceleration dynamic behaviour.

Vertical vs. Lateral Dynamic Behaviour of Soft Catenaries subject to Regular Loading using Field Measurements

Vertical vs. Lateral Dynamic Behaviour of Soft Catenaries subject to Regular Loading using Field Measurements

Analysis on the Applicability Domain of the Linear Models During Study of the Lateral Dynamic Behaviour of the Railway Vehicles

Analysis on the Applicability Domain of the Linear Models During Study of the Lateral Dynamic Behaviour of the Railway Vehicles

Enhancing the yaw stability and the manoeuvrability of a heavy vehicle in difficult scenarios by an emergency threat avoidance manoeuvre

This study aims to investigate the switching model predictive control strategy for a heavy-vehicle system in order to coordinate the actuator between active rear steering and differential braking control manoeuvres for emergency threat avoidance in difficult environments. We present the controller performances for the lateral dynamic behaviour, the yaw stability and the manoeuvrability of a vehicle when subjected to a sudden threat or disturbance such as a gust of wind, a road bank angle or a split- μ road surface in order to enable a fast safe lane-change trajectory to be followed. The vehicle was driven at a medium forward speed and a high forward speed in order to investigate the effectiveness of the proposed approach in avoiding the threat, maintaining the stability and enablinge a fast safe lane-change trajectory to be followed. We compared two different controllers (a model predictive controller and a switching model predictive controller) for two different control manoeuvres (active rear steering with differential braking control and active rear steering with direct yaw moment control). The simulation results demonstrate that the proposed switching model predictive control method provides an improved fast safe lane-change manoeuvre in a threat avoidance scenario for both control manoeuvres. It also demonstrated that the proposed active rear steering with differential braking control is more useful for maintaining the stability of the vehicle in a threat avoidance scenario with disturbance effects than is active rear steering with direct yaw moment control.