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The soft and rough terrain on the planet's surface significantly affects the ride and safety of rovers during high-speed driving, which imposes high requirements for the control of the suspension system of planet rovers. To ensure good ride comfort of the planet rover during operation in the low-gravity environment of the planet's surface, this study develops an active suspension control strategy for torsion spring and torsional damper suspension systems for planet rovers. Firstly, an equivalent dynamic model of the suspension system is derived. Based on fractal principles, a road model of planetary surface is established. Then, a fuzzy-PID based control strategy aimed at improving ride comfort for the planet rover suspension is established and validated on both flat and rough terrains.

With the development of hardware and control theory, the application of quadcopters is constantly expanding. Quadcopters have emerged in many fields, including transportation, exploration, and object grabbing and placement. These application scenarios require accurate, stable, and rapid control, and a suitable dynamic model is one of the prerequisites. At present, many works are related to it, most of which are modeled using the Newton-Euler method. Some works have also adopted other methods, including the Lagrangian and Hamiltonian methods. This article proposes a new method that solves the Hamiltonian equation of a quadcopter expressed in quasi-coordinate. The external forces and motion of the body are expressed in the quasi-coordinate system of the body, and solved through the Hamiltonian equation. This method simplifies operations and improves computational efficiency. Additionally, a single pendulum is attached to the quadcopter to simulate application scenarios.

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.

Connected and automated vehicles (CAVs) can improve traffic efficiency and reduce fuel consumption. This paper proposes a cooperative game approach to merging sequence and optimal trajectory planning of CAVs at unsignalized intersections. The trajectory of the vehicles in the control zone is optimized by the Pontryagin minimum principle. The vehicle's travel time, fuel consumption, and passenger comfort are considered to construct the joint cost function, completing the optimal trajectory planning to minimize the joint cost function. Analyzing the different states between neighboring CAVs at the intersection to calculate the minimum safety interval. The cooperative game approach to merging sequence aims to minimize the global cost and the merging sequence of CAVs is dynamically adjusted according to the gaming result. The multi-player games are decomposed into two-player games, to realize the goal of the minimal global cost and improve the calculation efficiency.

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.

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.

For automated driving vehicles, path planning and trajectory tracking are the core of achieving obstacle avoidance. Real-time external environment perception and vehicle state monitoring play the important role in the decision-making of vehicle operation. Sensor measuring is an important way to obtain vehicle state parameters, but some parameters cannot be measured due to sensor cost or technical reasons, such as vehicle lateral velocity and side-slip angle. This disadvantage will adversely affect the monitoring of vehicle self-condition and the control of vehicle running, even it will lead to erroneous decision-making of vehicles. Therefore, this paper proposes an automated driving path planning and trajectory tracking control method based on Kalman filter vehicle state observer. Some of vehicle state data can be measured accurately by sensors.

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.

The tire is one of the key components that affect vehicle performance and ride quality. The rigid ring model has been widely used in the dynamic simulation of tire rolling uneven road surface, and calculate the tire stiffness and force of rim under quasi-static conditions. However, the traditional spring-damping between rim and belt is not accurate enough to describe the viscous damping force and hysteretic behavior of rubber. Therefore, it is necessary to propose a new rigid ring model, considering the viscoelasticity of tire side rubber and hysteretic behavior of rubber, to better adapt to the intermediate frequency response of tire. In this paper, the rigid ring model introduces the fractional derivative damping and friction force element to enhance the dynamic response of tire in higher frequency. Linear damping is replaced by a three-parameter fractional-order derivative damping model, and a Berg friction element was added between rim and belt.

In this paper, a multi-mode active seat suspension with a single actuator is proposed and built. A one-DOF seat suspension system is modelled based on a quarter car model of commercial vehicle with an actuator which is comprised of a DC motor and a gear reducer. Aiming at improving ride comfort and reducing energy consumption, a multi-mode controller is established. According to the seat vertical acceleration and suspension dynamic travel signals, control strategies switch between three modes: active drive mode, energy harvesting mode and plug breaking mode.

Tyre behavior plays an important role in vehicle dynamics simulation. The Magic Formula Tyre Model is a semi-empirical tyre model which describes tyre behavior quite accurately in the handling simulation. The Magic Formula Tyre Model needs a set of parameters to describe the tyre properties; the determination of these parameters is nontrivial task due to its nonlinear nature and the presence of a large number of coefficients. In this paper, the homotopy algorithm is applied to the parameter identification of Magic Formula tyre model. A morphing parameter is introduced to correct the optimization process; as a result, the solution is directed converging to the global optimal solution, avoiding the local convergence. The method uses different continuation methods to globally optimize the parameters, which ensures that the prediction of the Magic Formula model can be very close to the test data at all stages of the optimization process.

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.

The aerodynamic effects not only directly affect the acceleration and the fuel economy of the race car, but also have a great influence on the handling of the race car. In this paper, the vehicle multibody dynamic model with “double-wishbone suspension” and “rack and pinion steering” is established, in order to obtain aerodynamic parameters, the aerodynamic model of the vehicle is established, and the aerodynamic parameters were calculated by using CFD. In order to obtain the optimal travel track, the track model is established, according to weights allocation of the smallest curvature of each curve and the shortest curve to optimize the optimal route for racing. The influence of aerodynamic effects on the stability of vehicle control is analyzed through simulation of Endurance Racing to evaluate the maximum lateral acceleration、roll angle and other performance.

This work is motivated by the fact that the surface of a terrain may vary with local pavement properties and number of passes of the vehicle, which means the roughness coefficient and waviness of the terrain may vary in specific intervals. However, in traditional random terrain models, the roughness coefficient and waviness of the terrain are assumed as constants. Therefore, this assumption may be not very reasonable. A novel random terrain model is presented where the roughness coefficient and waviness of the terrain are expressed by interval numbers instead of constants. A 5-degree-of-freedom ride dynamic model of the vehicle with uncertain parameters is derived. The power spectral density (PSD) and root mean square value (RMS) of the vehicle ride responses are shown and analyzed. Analysis results indicate that the vehicle responses vary in specific intervals under the random terrain excitation with interval parameters.

In this paper, a detailed three dimensional (3D) flexible ring tire model is first proposed which includes a rigid rim with thickness, different layers of discretized belt points and a number of massless tread blocks attached on the belt. The parameters of the proposed 3D tire model can be divided into in-plane parameters and out-of-plane parameters. In this paper, the relationship of the in-plane parameters between the 3D tire model and the 2D tire model is determined according to the connections among the tire components. Based on the determined relationship, it is shown that the 3D tire model can produce almost the same prediction results as the 2D tire model for the in-plane tire behaviors.

Vehicle Thermal Management System (VTMS) is a crosscutting technology affecting the fuel consumption, engine performance and emissions. With the new approved fuel economy targets and the enhanced vehicle performance requirements, the ability to predict the impact on the fuel consumption of different VTMS modifications is becoming an important issue in the pre-prototype phase of vehicle development. This paper presents a methodology using different simulation tools to model the entire VTMS in order to understand and quantify its behavior. The detailed model contains: engine cooling system, lubrication system, powertrain system, HVAC system and intake and exhaust system. A detail model of the power absorbed by the accessory components operating in VTMS such as pumps and condenser is presented. The power of the accessory components is not constant but changing with respect to engine operation. This absorbed power is taken into account within the power produced by the engine shaft.

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.

Interval inverse problems can be defined as problems to estimate input through given output, where the input and output are interval numbers. Many problems in engineering can be formulated as inverse problems like vehicle suspension design. Interval metrics, instead of deterministic metrics, are used for the suspension design of a vehicle vibration model with five degrees of freedom. The vibration properties of a vehicle vibration model are described by reasonable intervals and the suspension interval parameters are to be solved. A new interval inverse analysis method, which is a combination of Chebyshev inclusion function and optimization algorithm such as multi-island genetic algorithm, is presented and used for the suspension design of a vehicle vibration model with six conflicting objective functions. The interval design of suspension using such an interval inverse analysis method is shown and validated, and some useful conclusions are reached.

The optimization of vehicle suspension kinematic/compliance characteristics is of significant importance in the chassis development. Practical suspension system contains many uncertainties which may result from poorly known or variable parameters or from uncertain inputs. However, in most suspension optimization processes these uncertainties are not accounted for. This study explores the use of Chebyshev polynomials to model complex nonlinear suspension systems with interval uncertainties. In the suspension model, several kinematic and compliance characteristics are considered as objectives to be optimized. Suspension bushing characteristics are considered as design variables as well as uncertain parameters. A high-order response surface model using the zeros of Chebyshev polynomials as sampling points is established to approximate the suspension kinematic/compliance model.

Nowadays, studying the human body response in a seated position has attracted a lot of attention as environmental vibrations are transferred to the human body through floor and seat. This research has constructed a multi-body biodynamic human model with 17 degrees of freedom (DOF), including the backrest support and the interaction between feet and ground. Three types of human biodynamic models are taken into consideration: the first model doesn't include the interaction between the feet and floor, the second considers the feet and floor interaction by using a high stiffness spring, the third one includes the interaction by using a soft spring. Based on the whole vehicle model, the excitation to human body through feet and back can be obtained by ride simulation. The simulation results indicate that the interaction between feet and ground exerts non-negligible effect upon the performance of the whole body vibration by comparing the three cases.