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Vehicle systems often operate with some degree of uncertainty. This study applies the Chebyshev interval method to model vehicle dynamic systems operating in the presence of interval parameters. A full vehicle model is used as the numerical model and the methodology is illustrated on the steering wheel angle pulse input test. In the numerical simulation, suspension stiffness coefficients and suspension damping coefficients are chosen as interval parameters and lateral acceleration and yaw rate are chosen to capture vehicle dynamic characteristics. System responses in time domain are validated against Monte Carlo simulations and against the scanning approach. Results indicate that the Chebyshev interval method is more efficient than Monte Carlo simulations. The results of scanning method are similar to the ones obtained with the Chebyshev interval method.

In contemporary trajectory planning research, it is common to rely on point-mass model for trajectory planning. However, this often leads to the generation of trajectories that do not adhere to the vehicle dynamics, thereby increasing the complexity of trajectory tracking control. This paper proposes a local trajectory planning algorithm that combines sampling and sequential quadratic optimization, considering the vehicle dynamics model. Initially, the vehicle trajectory is characterized by utilizing vehicle dynamic control variables, including the front wheel angle and the longitudinal speed. Next, a cluster of sampling points for the anticipated point corresponding to the current vehicle position is obtained through a sampling algorithm based on the vehicle's current state. Then, the trajectory planning problem between these two points is modeled as a sequential quadratic optimization problem.

The design of suspension affects the vehicle dynamics such as ride comfort and handling stability. Nonlinear characteristics and friction are important characteristics of suspension system, and the influence on vehicle dynamic performance cannot be ignored. Based on the seven-degree-of-freedom vehicle vibration nonlinear model with friction, the vibration response process of the vehicle and the influence of suspension friction on vehicle ride comfort and suspension action process were studied. The results show that friction will significantly affects the simulation of ride comfort and coincide with the function of the shock absorber. The suspension shock absorbers of vehicles were optimized with and without suspension friction. The results showed that the suspension tended to choose softer shock absorbers when there was friction. However, both of the two optimizations are able to improve the ride comfort of vehicles, and the simulation results were similar.

This paper investigates a hierarchical optimization procedure for the optimum synthesis of a double-axle steering mechanism by considering the dynamic load of a vehicle which is seldom discussed in the previous literature. Firstly, a multi-body model of double-axle steering is presented by characterizing the detailed leaf spring effect. Accordingly, the influences of dynamic load including the motion interference of steering linkage resulted from the elastic deformation of leaf spring, and the effects of wheel slip angle and the position discrepancy of wheel speed rotation centers are explored systematically. And then, a hierarchical optimization method based on target cascading methodology is proposed to classify the design variables of double-axle steering mechanism into four levels. At last, a double-axle steering mechanism of a heavy-duty truck is utilized to demonstrate the validity of this method.

To study the torque distribution of track and tire in the wheel-track hybrid drive vehicle driving along the shoreline, an analysis model of wheel-track hybrid drive vehicle was established by using multi-body dynamics (MBD), discrete element (DEM), and shoreline pavement construction methods. The vehicle speed, acceleration, torque, vertical load, sinkage, slip, and other indicators when the vehicle passes the shoal at different wheel speed of rotation are analyzed. The relationships between wheel speed of rotation and slip, sinkage and slip, and vertical load and driving moment were studied, and the laws that the sinkage of tires and tracks is positively related to their slippage and the driving moment of wheels and tracks is positively related to their vertical load were obtained.

In the petroleum and gas industry, cargo truck is one of the most important ways to transfer the skid-mounting from the manufacturer to the job location. Under the condition of bumpy road surface, the random vibration from the ground can easily cause the resonance of the internal equipment components of the skid-mounting, produce large deformation in the pipeline and equipment connection, and even the equipment will be damaged. In this paper, the finite element analysis model and dynamic rigid flexible coupling model of a TEG (Triethyleneglycol) dehydration unit regeneration skid-mounting are established by using the finite element analysis and multi-body dynamics software. The modal analysis of the skid and the vibration of the whole vehicle under different road excitation and driving conditions are carried out. Two solutions are proposed to improve the anti-vibration ability of the skid, and comparative analysis is made.

Electric vehicles driven by in-wheel-motor have the advantages of compact structure and high transmission efficiency, which is one of the most ideal energy-saving, environmentally friendly, and safe driving forms in the future. However, the addition of the in-wheel-motor significantly increases the unsprung mass of the vehicle, resulting in a decrease in the mass ratio of the vehicle body to the wheel, which will deteriorate the ride comfort and safety of the vehicle. To improve the vibration performance of in-wheel-motor driven vehicles, a semi-active inerter-spring-damper (ISD) suspension with in-wheel-motor (IWM) dynamic vibration absorber (DVA) of the electric wheel is proposed in this paper. Firstly, a structure of in-wheel-motor DVA is proposed, which converts the motor into a dynamic vibration absorber of the wheel to suppress the vibration of the unsprung mass.

As is known to all, there are some contradictions between the handling and ride performance during the design process of vehicles. Sometimes owing to serious collisions of each criterion in the high-dimensional solution space, the common method to deal with the contradiction is to transform into a single target according to weights of each objective, which may not obtain a desired result. A multi-criteria approach is therefore adopted to optimize both properties and the result of a multi-criteria design is not a unique one but a series of balanced solutions. This paper is focused on the robust design of a simplified vehicle model in terms of not only ride comfort but also handling and stability using a multi-objective evolutionary algorithm (MOEA) method. Using the proposed method, the conflicting performance requirements can be better traded off. One of the most important indexes to characterize the vertical ride comfort is the acceleration of the sprung mass.

There are many uncertain parameters in shock absorbers, which are induced by the manufacturing error, the wear of components and the aging of materials in real vehicle environment. These uncertainties often cause some deterioration of vehicle performance. To optimize the ride characteristic of a vehicle when the shock absorber includes uncertain parameters, the robust design method is used. In this paper, a Twin Tube shock absorber fluid system model has established on the multi-domain modeling environment. This model not only includes the commonly used parameters of the shock absorber but also takes into account the structure parameters of various valves in the shock absorber, which is more detailed and accurate than those models in the past literature. The robust design of the shock absorber parameters is successfully approached using the co-simulation technique, and the ride comfort performance of the vehicle is also improved.

Due to the elimination of the mechanical connection between the steering column and steering gear in the Steer-by-Wire (SBW) system, the road-feeling simulation is mainly supplied by the road-feeling motor which loads a drag torque on the steering wheel rather than the actual torque transmitted from the road. To obtain more realistic steering wheel torque, a novel feedback torque of the road-feeling motor fusion estimation method based on the Kalman filter is presented in this paper. Firstly, the model-based estimation method is utilized to estimate the aligning torque between tires and ground which is converted into the rack force through the steering system. Then the estimated rack force is used as the observed data for the Kalman Filter of the sensor-based method and the Kalman Filter-based fusion estimation method is resulted, through which the more realistic feedback torque of the road-feeling motor can be obtained.

A new recursive method is presented for real-time estimating the inertia parameters of a vehicle using the well-known Two-Degree-of- Freedom (2DOF) bicycle car model. The parameter estimation is built on the framework of polynomial chaos theory and maximum likelihood estimation. Then the most likely value of both the mass and yaw mass moment of inertia can be obtained based on the numerical simulations of yaw velocity by Newton method. To improve the estimation accuracy, the Newton method is modified by employing the acceptance probability to escape from the local minima during the estimation process. The results of the simulation study suggest that the proposed method can provide quick convergence speed and accurate outputs together with less sensitivity to tuning the initial values of the unidentified parameters.

The powertrain mounting system (PMS) plays an important role in improving the NVH (Noise, Vibration, Harshness) quality of the vehicle. In all running conditions of a vehicle, the displacements of the powertrain C.G. should be controlled in a prescribed range to avoid interference with other components in the vehicle. The conventional model of PMS is based on vibration theory, considering the rotation angles are small, ignoring the sequence of the rotations. However, the motion of PMS is in 3D space with 3 translational degrees of freedom and 3 rotational degrees of freedom, when the rotation angles are not small, the conventional model of PMS will cause errors. The errors are likely to make powertrain interfering with other components. This paper proposes a rigid body mechanics model of the powertrain mounting system. When the powertrain undergoes a large rotational motion, the rigid body mechanics model can provide more accurate calculation results.

Steering returnability is an important index for evaluating vehicle handling performance. A systematic method is presented in this paper to reduce the high yaw rate residue and the steering response time for a light duty truck in the steering return test. The vehicle multibody model is established in ADAMS, which takes into consideration of the frictional loss torque and hydraulically assisted steering property in the steering mechanism, since the friction, which exists in steering column, spherical joint, steering universal joint, and steering gear, plays an important role in vehicle returnability performance. The accuracy of the vehicle model is validated by road test and the key parameters are determined by executing the sensitivity analysis, which shows the effect of each design parameter upon returnability performance.

Many vehicles have been equipped with air springs as elastic elements to get better performance in comfort, but absorbers may not work in an optimal state due to the variation of suspension stiffness. While the function of semi-active suspension is to enable the absorber damping to be adjusted according to different road roughness levels and to coordinate between comfort and handling. To solve the problem of matching the damping coefficient of variable stiffness suspensions represented by air springs, this paper proposed a method for calculating the optimal damping ratio of a semi-active suspension system in real-time with sprung mass acceleration and dynamic tire load to establish the objective function and suspension dynamic deflection as the constraint to reflect the unification of comfort and handling.

The road adhesion coefficient has a great impact on the performance of vehicle tires, which in turn affects vehicle safety and stability. A low coefficient of adhesion can significantly reduce the tire's traction limit. Therefore, the measurement of the coefficient is much helpful for automated vehicle control and stability control. Considering that the road adhesion coefficient is an inherent parameter of the road and it cannot be known directly from the information of the on-vehicle sensors. The novelty of this paper is to construct a road adhesion coefficient observer which considers the noise of sensors and measures the unknown state variable by the trained neural network. A Butterworth filter and Adaptive Neural Fuzzy Interference System (ANFIS) are combined to provide the lateral and longitudinal velocity which cannot be measured by regular sensors.

To solve the dynamic response problem that contains uncertain parameters needs, the stochastic differential equations needs to be calculated. Interval analysis has been widely used to solve engineering problems which contain many uncertain parameters usually. But the numerical solution method for stochastic differential equations based on the interval analysis method was seldom investigated. In this study a new numerical interval method for the stochastic differential equations based on the Euler's method is presented, which can be used to solve the linear system effectively and efficiently. The probabilistic and interval dynamics analysis of a two-degree-of-freedom bike car model with uncertain parameters are presented.

Suspension kinematics and compliance strongly influence the handling performance of the vehicle. The kinematics and compliance characteristics are determined by the suspension geometry and stiffness of suspension bodies and elastic components. However, it is usually inefficient to model all the joints, bushings, and linkage deformation in a full vehicle model. By transforming the complex modeling problem into a data-driven problem tends to be a good solution. In this research, the neural-network-based suspension kinematics and compliance model is built and implemented into a 17 DOF full vehicle model, which is a hybrid model with state variables expressed in the global coordinate system and vehicle coordinate system. The original kinematics and compliance characteristics are derived from multibody dynamics simulation of the suspension system level.

In order to reasonably match the variable stiffness and location of the Powertrain Mounting System (PMS) and optimize the ride comfort of commercial vehicle, a thirteen degrees of freedom (DOF) model of a commercial vehicle was established in Adams/view. Specially, the support rod installed on the upside of the transmission case was modeled as a flexible body. The vibration isolation provided by the PMS was evaluated in three aspects: the energy decoupling of the powertrain, the response force of the mount and the displacement of the powertrain. The energy decoupling ratio, the force RMS of the mount when force excitation was applied on the powertrain and the displacement of the powertrain Center of Gravity (C.G) when displacement excitation was applied on the vehicle chassis were selected as the optimal target. Adams and MATLAB were integrated into the optimization software iSIGHT to optimize the PMS. NSGA-II is used to obtain some Pareto-optimal solutions of PMS.

In autonomous driving, variations in tire vertical load, tire slip angle, road conditions, tire pressure and tire friction all contribute to uncertainty in tire cornering stiffness. Even the same tire may vary slightly during the manufacturing process. Therefore, the uncertainty of tire cornering stiffness has an important influence for autonomous driving path planning and control strategies. In this paper, the Chebyshev interval method is used to represent the uncertainty of tire cornering stiffness and is combined with a model predictive control algorithm to obtain the trajectory interval bands under local path planning and tracking control. The accuracy of the tire cornering stiffness model and the path tracking efficiency are verified by comparing with the path planning and control results without considering the corner stiffness uncertainties.

Increased focus on vehicle comfort and ride has led the automotive industry to look into low vibration, noise and hardness alternative designs for powertrain system components. In this paper, the vibration theory and dynamic vibration absorber (DVA) theory is presented. The modal analysis of propeller shaft assembly has been accomplished. Based on dynamic vibration absorber principle, performance parameters of dynamic vibration absorber are matched and structure is also designed. LMS equipment is applied to verify the natural frequency of absorber samples. The matching of stiffness and damping of DVA is presented. The dynamic response of drive shaft system based on the mass ratio of DVA is researched in this paper. Results from simulations and tests indicates that the amplitude of propeller shaft resonance can be effectively reduced by attaching a DVA to the long propeller shaft.