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When the drill arm reaches the specified position, the rubber top disk of the propelling beam is pressed against the rock surface by the hydraulic cylinder force and the rock drill starts drilling. Because of the reaction force and the deformation of the drill arm, the propelling beam will be offset from its target position and vibrate, which will affect the drilling accuracy. To analyze the vibration of the propelling beam, the rigid-flexible coupled model is established. The minimum displacement offset of the propelling beam from the initial position is used as the optimization function and the parameters of the rubber top disk are used as optimization variables. The amplitude of the propelling beam at a steady state is used as the constraint. From the simulation results, the rigid-flexible coupled model can describe the vibration of the propelling beam better than the rigid model, especially during the rock drill working stage.

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.

This paper describes a simplified model to identify sprung mass using golden section method, the model treats the unsprung mass vertical acceleration as input and the sprung mass vertical acceleration as output, which can avoid the nonlinear influence of trye. Unsprung mass can be also calculated by axle load and the identified sprung mass. This study carries out road test on the vehicle ride comfort and takes a scheme that the group of 20 km/h is used to identify sprung mass and the group of 80 km/h is used to verify the identification result. The similarity of the results from the simulation and experiments performed are, for the sprung mass, 98.59%. A conclusion can be drawn that the simple method to measure the sprung mass in the suspension systems in used vehicles, such as the vehicle shown here, is useful, simple and has sufficient precision.

A Special Analytical Target Cascading (SATC) process is developed for design problem which is difficult to ascertain the targets cascaded from upper level to lower level. The methodology is applied to achieve improving Handling Performance and Ride Quality (HPRQ) of a passenger car. A bi-level hierarchical structure with target-transforming process is established based on conceptual suspension model and multi-body models. DOE, RSM and a combined optimization method of simulated annealing and Programming Quadratic Line search is applied to execute the optimization process. The result shows that HPRQ is improved through special ATC based on CSM and multi-body modeling technique.

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.

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.

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.

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.

Vehicle Thermal Management System (VTMS) is a cross-cutting technology that directly or indirectly affects engine performance, fuel economy, safety and reliability, driver/passenger comfort, emissions. This paper presents a novel methodology to investigate VTMS based on Modelica language. A detailed VTMS platform including engine cooling system, lubrication system, powertrain system, intake and exhaust system, HVAC system is built, which can predict the steady and transient operating conditions. Comparisons made between the measured and calculated results show good correlation and approve the forecast capability for VTMS. Through the platform a sensitivity analysis is presented for basic design variables and provides the foundation for the design and matching of VTMS. Modelica simulation language, which can be efficiently used to investigate multi-domain problems, was used to model and simulate VTMS.

The automatic mechanical transmission (AMT) was designed by automobile manufacturers to provide a better driving experience, especially in cities where congestion frequently causes stop-and-go traffic patterns. It uses electronic sensors, processors, hydraulic or pneumatic actuators execute clutch actuation and gear shifts on the command of the driver. Such systems coupled with various physical domains have great influence on the dynamic behavior of the vehicle, such as shift quality, driveability, acceleration, etc. This paper presents a detailed AMT model composed of various components from multi-domains like mechanical systems (clutch, gear pair, synchronizer, etc.), pneumatic actuator systems (clutch actuation system, gear select actuation system, gear shift actuation system, etc.). Various components and subsystem models, such as the vehicle, engine, AMT, wheels, etc., are integrated into an overall vehicle system model according to the transmission power flow and control logic.

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.

One of the most important vibration isolators in vehicles is the powertrain mounting system (PMS). It transmits the powertrain vibrations to the body, and the chassis vibrations excited by road to the powertrain. The design of a PMS is an essential part in vehicle safety and in improving the vehicle noise, vibration and harshness (NVH) performances. Many organizations are increasingly relying on design simulation rather than trail-and-error based experiments which are expensive and time-consuming for PMS evaluation. However, design parameters for PMS are always uncertain in actual cases due to tolerances in manufacturing and assembly processes. In this paper, based on a front wheel drive vehicle with a transversely four-cylinder engine, the uncertain characteristics of PMS are studied by interval analysis method.