Vehicle Dynamic Characteristics Research Articles

MPC-Based Integrated Control of Trajectory Tracking and Handling Stability for Intelligent Driving Vehicle Driven by Four Hub Motor

Aiming at the problem of trajectory tracking and handling stability of intelligent four hub-motor independent-drive electric vehicle at high speed, an integrated control strategy based on model predictive control (MPC) is proposed. Firstly, a kinematics preview model is established considering the adaptive change of preview distance with longitudinal vehicle speed. Secondly, combined with the proposed preview model and considering the vehicle dynamic characteristics, an upper level controller of MPC is created to track the lateral deviation, heading angle deviation, sideslip angle and yaw rate to obtain the optimal solution of front wheel angle and additional yaw moment, which realize the control of handling stability while ensuring the trajectory tracking accuracy at same time. Then considering the varying road adhesion and the influence of longitudinal slip at the four tires, a lower level controller composed of torque optimal control and sliding mode controller is designed to realize the optimal torque distribution of four hub motors. Finally, through the co-simulation of MATLAB / Simulink and CarSim and the hardware-in-the-loop experiment, it is verified that the proposed integrated control strategy can effectively improve the path tracking accuracy and ensure the vehicle handling stability at high speed. Compared with the general MPC strategy, who does not control the sideslip angle and yaw rate with no preview model, the cumulative lateral tracking error of the integrated control is reduced by 51.9% and 87.7% respectively.

A Study on Vehicle Dynamic Characteristics Changes to Driving Speeds

A Study on Vehicle Dynamic Characteristics Changes to Driving Speeds

Experimental validation of a fast wheel wear prediction model

Wheel-rail wear prediction is a fundamental matter in order to study problems such as wheel lifespan prediction and evolution of vehicle dynamic characteristics with time. However, one of the principal drawbacks of the existing methodologies for calculating the wear evolution is the computational cost. The developed methodology is based on (1) representing the whole route in a reduced number of characteristic points and (2) substituting dynamic simulations by quasi-static ones, in order to reduce computational cost significantly. This paper presents its integration into the complete simulation process for predicting wheel wear evolution and its validation by comparing simulated results with in-service wheel profile measurements. The generality of the method has been verified by applying it to two different operational cases with very different track characteristics. For the validation, the evolution of the worn depth in the tread has been compared according to the travelled distance, as well as the morphology of the worn depth (worn area). Promising results have been obtained in the prediction of wheel wear evolution: in both cases, the simulated curve approaches the measurement curve satisfactorily. Therefore, it can be concluded the validation of the developed method adequately.

Real-Time Longitudinal and Lateral State Estimation of Preceding Vehicle Based on Moving Horizon Estimation

In the advanced driver assistance system (ADAS) and autonomous driving systems, accurate information on preceding vehicle motion states is vital for the path planning and control. To develop those intelligent driving systems, a modular integrated estimation algorithm for the preceding vehicle longitudinal and lateral states is proposed in this paper, the coupled nonlinear characteristics of vehicle dynamics are applied to improve state estimation accuracy. First, considering driver aggressiveness, a linear moving horizon estimator for the vehicle longitudinal speed is designed based on the car following model. Then, the estimated vehicle longitudinal speed is delivered to the lateral estimator module in real-time. For the arbitrary driving routes, the Serret-Frenet equations and nonlinear lateral dynamics are combined to describe the lateral motion of preceding vehicle. Furthermore, a nonlinear moving horizon estimator is constructed to estimate vehicle lateral states accurately. To reduce the computational burden, the multiple shooting (MS) method is introduced, then the objective function is divided into several segments to improve the strong nonlinearity produced by multiple iterations. The proposed estimation algorithm can effectively handle the initial biases, the additive biases and model error, which are common in the acquired signals, and provide an accurate estimate of preceding vehicle states.

Deep reinforcement learning based direct torque control strategy for distributed drive electric vehicles considering active safety and energy saving performance

Distributed drive electric vehicles are regarded as a broadly promising transportation tool owing to their convenience and maneuverability. However, reasonable and efficient allocation of torque demand to four wheels is a challenging task. In this paper, a deep reinforcement learning-based torque distribution strategy is proposed to guarantee the active safety and energy conservation. The torque distribution task is explicitly formulated as a Markov decision process, in which the vehicle dynamic characteristics can be approximated. The actor-critic networks are utilized to approximate the action value and policy functions for a better control effect. To guarantee continuous torque output and further stabilize the learning process, a twin delayed deep deterministic policy gradient algorithm is deployed. The motor efficiency is incorporated into the cumulative reward to reduce the energy consumption. The results of double lane change demonstrate that the proposed strategy results in better handling stability performance. In addition, it can improve the vehicle transient response and eliminate the static deviation in the step steering maneuver test. For typical steering maneuvers, the proposed direct torque distribution strategy significantly improves the average motor efficiency and reduces the energy loss by 5.25%–10.51%. Finally, a hardware-in-loop experiment was implemented to validate the real-time executability of the proposed torque distribution strategy. This study provides a foundation for the practical application of intelligent safety control algorithms in future vehicles.

T-S Fuzzy Model Predictive Control for Vehicle Yaw Stability in Nonlinear Region

Safety at high speed is the most important performance of autonomous vehicle. Wherein, yaw stability control (YSC) is a key technology to improve vehicle safety. However, the high-speed vehicles are easy to be out of control in nonlinear region, which will result in serious accidents. This study proposes a model predictive control (MPC) method based on the Takagi-Sugeno (T-S) fuzzy model to realize YSC in the nonlinear region. Firstly, a T-S fuzzy model of vehicle is established based on a two-degree-of-freedom model to describe the vehicle dynamic characteristics in the nonlinear region. Then, a robust MPC is designed and its solution is given in the linear matrix inequalities (LMIs) form. Next, a sliding mode controller (SMC) is proposed to prevent wheel lock in the YSC process. Finally, the proposed strategy is verified in simulations and experiments. The results show that the proposed strategy has similar performance in vehicle stable region with linear MPC, and shows the ability to suppress the instability of the vehicle in the nonlinear region, and its computation burden is acceptable.

Development of the Reduced-Scale Vehicle Model for the Dynamic Characteristic Analysis of the Hyperloop

This study addresses the Hyperloop characterized by a capsule-type vehicle, superconducting electrodynamic suspension (SC-EDS) levitation, and driving in a near-vacuum tube. Because the Hyperloop is different from conventional transportation, various considerations are required in the vehicle-design stage. Particularly, pre-investigation of the vehicle dynamic characteristics is essential because of the close relationship among the vehicle design parameters, such as size, weight, and suspensions. Accordingly, a 1/10 scale Hyperloop vehicle system model, enabling the analysis of dynamic motions in the vertical and lateral directions, was developed. The reduced-scale model is composed of bogies operated by Stewart platforms, secondary suspension units, and a car body. To realize the bogie motion, an operation algorithm reflecting the external disturbance, SC-EDS levitation, and interaction between the bogie and car body, was applied to the Stewart platform. Flexible rubber springs were used in the secondary suspension unit to enable dynamic characteristic analysis of the vertical and lateral motion. Results of the verification tests were compared with simulation results to examine the fitness of the developed model. The results showed that the developed reduced-scale model could successfully represent the complete dynamic characteristics, owing to the enhanced precision of the Stewart platform and the secondary suspension allowing biaxial motions.

Identification of Road Profile Parameters from Vehicle Suspension Dynamics for Control of Damping

Concept of symmetry covers physical link between road profile form, vehicle dynamic characteristics, and speed conjunction. Symmetry frame between these items is asymmetric itself and has no direct expression, but it affects a vibration level on the vehicle and driving comfort. Usually, we can change only the vehicle’s speed to achieve desired vibrations level of the driver and passengers. Recently, vehicle dynamic characteristics can be changed depending on its damping system structure, but these solutions are limited by construction and control possibilities and evidently represented by symmetric dependency between road input and the resulting acceleration of the vehicle. The main limitation of this process is to have a reliable value of the existing road profile that is mainly defined by road category but unpredictable for each road distance. Functional road profile calculations are provided in this article, where power spectral density (further-PSD) and waviness of the road play the main role in delineating road profile parameters. Furthermore, the transfer function system was created using full car dynamic model analysis. Values on vehicle suspension’s effects on acceleration were obtained from vehicle speed and road roughness. Acceleration values and transfer function were used to calculate PSD value quickly and practically. This calculated result can be formed as a control value to the vehicle damping control. In addition, the provided methodology became useful to determine road quality for adjustment of vehicle suspension parameters and set safe driving characteristics, which became part of driver assistant systems or autonomous driving mode.

Investigating the influence of connecting constraint properties and modeling parameters on vehicle dynamic responses

This paper presents a detailed investigation about the effect of structural damping and modal truncation number on vehicle dynamic characteristics. Finite element method and experimental method are applied to research vehicle’s dynamic response. According to the real vehicle’s structure, the dynamic simulation model of vehicle is established by the substructure modeling method. In order to research the influence of different variables on vehicle’s dynamic responses, the control variable method is adopted. In other words, the parameters of structural damping and mode truncation number are changed respectively. Comparing the dynamic response results, the influence rules of structural damping and mode truncation number on dynamic responses are obtained. Results show that the dynamic responses of vehicle changes significantly with the change of structural damping and mode truncation number. The studying results provide important significance for the determination of parameters. As well as, the correctness and reliability of the analysis results are verified by the experimental method.

High speed driving stability of road vehicles under crosswinds: an aerodynamic and vehicle dynamic parametric sensitivity analysis

Crosswinds affect vehicle driving stability and their influence increase with driving speed. To improve high speed driving stability, interdisciplinary research using unsteady aerodynamics and vehicle dynamics is necessary. The current demands of faster development times require robust virtual methods for assessing stability performance in early design phases. This paper employs a numerical one-way coupling between the two disciplines and uses a variety of realistic crosswind gust profiles for the aerodynamic simulations to output representative forces and moments on three vehicle dynamic models of different fidelity levels, ranging from a one-track model to a full multi-body dynamic model of a sports utility vehicle. An investigation on required model fidelity was conducted along with a sensitivity study to find key aerodynamic and vehicle dynamic characteristics to minimise the yaw velocity and lateral acceleration response during crosswinds. Transient aerodynamic simulations were used to model crosswind gusts at high speeds. Analysis of the forces and moments showed that rapid changing gusts generate overshoots in the yaw moment, due to the phase delay of the flow between the front and rear of the vehicle. A methodology for modelling this phase delay is proposed. The response of the vehicle was captured equally well by the enhanced model (mid-level fidelity) and the full multi-body dynamic model, while the simplest one-track model failed to emulate the correct vehicle response. The sensitivity study showed the importance of the positioning of the centre of gravity, the aerodynamic coefficient of yaw moment, wheel base, vehicle mass and yaw inertia. In addition, the axles' side force steer gradients and other suspension parameters revealed potential in improving crosswind stability.

Research on lateral and longitudinal correction method of automobile nonlinear dynamics

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.

Investigation on the motion conditions and dynamic interaction of vehicle and turnout due to differential wheelset misalignment

Assembly deviations of wheelsets cause differential wheelset misalignments and change the wheel-rail contact relationship in railway turnouts. In this paper, the motion conditions of wheelsets under the same bogie are analysed with differential wheelset misalignment based on the mechanical equilibrium condition. A rigid-flexible coupling model of vehicle-turnout dynamic interaction that fully considering different misalignment conditions is established to evaluate the wheel and turnout rails dynamic interaction and vehicle dynamic characteristics. The results show that wheelset misalignment can change wheel load transition position and affect wheel-rail contact conditions, especially when the misalignment direction is toward the switch rail. The larger misalignment angle will increase flange contact range and keep the normal contact stress at a higher level. Both misalignment angle and form determine the wheel-rail vertical force. The lateral force is mainly affected by the superposition effect of the eccentric load and the lateral impact of the wheel load transition.

Constraint-oriented integrated longitudinal and lateral robust control for connected and automated vehicle platoons

The coupling, nonlinearity, and uncertainty characteristics of vehicle dynamics make the accurate longitudinal and lateral control of an automated and connected vehicle platoon a tough task. Little research has been conducted to fully address the characteristics. By using the ideology of constraint-following control this article proposes an integrated longitudinal and lateral adaptive robust control methodology for a vehicle platoon with a bidirectional communication topology. The platoon control objectives contain the path tracking stability, the platoon internal stability, and the string stability. First, we establish the nonlinear kinematics path tracking model and the coupled vehicle longitudinal and lateral dynamical model that contains time-varying uncertainties. Second, we design a series of nonlinear equality constraints that directly guarantee the control objectives based on the kinematic relations. On this basis, an adaptive robust constraint-following control is proposed. It is shown that the control guarantees the uniform boundedness and the uniform ultimate boundedness of the constraint-following error and the uncertainty estimation error. Finally, simulation results are provided to validate the effectiveness of the proposed methodology.

「等高線法」を用いた車両運動性能の解析（第１報）:－「等高線法」の基本的な考え方－

「等高線法」を用いた車両運動性能の解析（第１報）:－「等高線法」の基本的な考え方－

Improvement of methods for assessing the effectiveness of dedicated lanes for public transport

There are different configurations of street and road networks in cities, which is why those transportation models that determine how effectively a public transport network is operated are different. Along with this, some transport areas may have characteristic features predetermined by the density of a street network, the intensity of individual and public traffic. The special feature of the current study is determining the operational effectiveness of dedicated lanes for public transport given a significant density of the main street and road network. Significant density is characterized by its value for the distance between adjacent intersections in the range of 150‒200 m. With such planning patterns, there is a mutual influence of the conditions of individual and public transport between adjacent intersections. An increase in the distance between intersections disrupts the stability of traffic flow through its disintegration into separate groups based on the dynamic characteristics of vehicles. A characteristic feature of the proposed procedure for evaluating the operational effectiveness of dedicated lanes is that the use of a GPS monitoring system makes it possible to relatively quickly determine the areas of the network where there are the greatest delays in movement in real time. After that, attention is focused on investigating the main factors of influence and their parameters followed by modeling. The reported results would in the future contribute to devising a clear sequence of transport-related research based on a set of their methods in order to acquire representative data and define adequate patterns. An important practical result is the use of not only established normative approaches to the design of dedicated lanes, which are common for all types of street and road networks but taking into consideration the peculiarities characteristic of their individual sections.

Pavement roughness evaluation method based on the theoretical relationship between acceleration measured by smartphone and IRI

ABSTRACT Smartphones have integrated various sensors (e.g. GPS, acceleration sensor) and can be used to evaluate roads roughness. In this study the theoretical algorithm, in which the vehicle suspension parameters were included, would be established to calculate International Roughness Index (IRI) from acceleration using smartphones. Firstly, based on Android Studio 2.0, a client application installed on smartphones was developed. Next, the physical parameters of a quarter actual vehicle model (QAVM) were identified utilizing the front wheel drop test in accordance with complex modal theory. Then, the relationships among acceleration, IRI and the profile elevation were established through the derivation of theoretical formula. Finally, a validation analysis was implemented to evaluate the feasibility and reliability of this methodology. The validation experimental results on three asphalt pavement segments indicated that the collected acceleration data utilizing smartphone were basically consistent with that by accelerometers. Meanwhile, IRI calculated by the proposed theoretical methodology was close to that obtained by digital survey vehicle (DSV) and the maximum relative error between them was below 10%. Overall, due to the consideration of vehicle dynamic characteristics, the proposed method could improve the measurement accuracy and enable various vehicles to be used for road roughness evaluation.

Study on decomposition and calculation method of EPS assist characteristic curve

Steering feel is closely related to the matching of the EPS assist characteristic curve, however, due to the lack of theoretical basis for the design of the EPS assist characteristic curve, the steering feel can only be changed indirectly by adjusting the magnitude of assist, which is very difficult. To control steering feel directly and reduce the difficulty of adjustment, this paper proposes a decomposition and calculation method of the EPS assist characteristic curve. At first, the mechanism of the EPS assist characteristic curve is revealed. It is found that the process of designing and adjusting the EPS assist characteristic curve is a process of changing the corresponding relationship between the steering wheel torque and the steering motion intensity based on considering vehicle dynamic characteristics. On this basis, the driver’s desired steering motion intensity and the pinion angle position are taken as intermediate variables, the EPS assist characteristic curve is decomposed into three parts: driving style, steady-state inverse characteristics of chassis dynamics, and steady-state inverse characteristics of steering system dynamics. According to the designed driving style and the calibrated steady-state inverse characteristics of chassis dynamics and steering system dynamics, the EPS assist characteristic curve can be directly calculated. The test results show that the EPS system adopting assist characteristic curve calculated can realize the designed driving style and provide consistent and controllable steering feel on the premise of meeting the requirements of steering portability and road feel.

WITHDRAWN: Effect of approach width on performance of signalized intersections

Saturation flow (SF) will be affected by the geometric, operating, traffic and environmental factors. This study analysis dealing with LOS at signalised intersections, effect of approach width on SF and passenger car units (PCU). Due to fundamental variations in traffic characteristics, the relations proposed by different ranchers to estimate the SF, initial time lost and PCU were not appropriate for heterogeneous conditions, due to variations in static and dynamic characteristics of vehicles with poor lane discipline. The main objective of the current research is to analyse the effect of approach width and right turning radies on SF and PCU, subsequently evaluated LOS under existing signal operating conditions. The data was collected at three signal controlled intersections in Visakhapatnam city and all the vehicles are categorized in to six classes. PCU values were estimated by taking small car as a standard vehicle by using Chandra’s formula. The relation of PCU value with approach width and turning radius is examined and represented graphically. PCU value has a linear relationship with approach width for through approaches. And PCU values of Right Turn (RT) vehicles are exponentially vary with RT radies. From the results observed that the other than two-wheeler remaining right turn vehicle, PCU’s are varies negative exponentially. LOS measured under existing fixed signal cycle time, mostly all the approaches were obtained LOS-D and only one approach of north bound of NAD intersection was obtained LOS-F. The LOS is assigned by using delay in sec., asper HCM-2010.

Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon

With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances.

Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles

Vehicle stability control under extreme conditions is influenced by the coupled nonlinear characteristics of vehicle dynamics, corresponding safety constraints, and rapid response requirements. To address these problems, this brief proposes a real-time nonlinear predictive controller for a distributed drive electric vehicle. First, nonlinear lateral dynamics of the vehicle are applied to develop the stability controller on low friction coefficient surfaces. Second, the requirement for suppressing the sideslip angle is integrated into the objective function to prevent the vehicle from destabilizing due to excessive sideslip angles. Finally, a fast solution algorithm is proposed by solving the transformed two-point boundary value problem, making it possible to apply nonlinear predictive controller to experimental road tests. The experiments with a production vehicle are conducted on the snow-covered dynamic roads of the DongFeng's winter test center. The test results on low friction coefficient roads show that the overall passing speed can be improved from 50-55 to 60-70 km/h with the proposed controller.