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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.

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.

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 rubber bushing is the key component to suppress vibration in the suspension system, an accurate constitutive model of rubber bushing should capture the amplitude and frequency dependency. Based on the lumped parameter model, three types of rubber bushing models are applied and compared, including the common Kelvin-Voigt model. To evaluate the model parameter and suitable frequency range, the quasi-static and dynamic tests have been performed. Comparing with the testing result, the fractional Kelvin-Voigt model combined with Berg’s friction has the minimum relative error of dynamic stiffness on the whole. Finally, two examples of chassis bushing under different loading conditions are presented. The rubber force and deflection are analyzed in both the time domain and the frequency domain, and the results show the difference of stiffness and hysteresis loop relative to frequency.

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.

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.

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.

The imbalance of propeller shaft is an excitation to the vehicle structure and causes noise and vibration. This paper presents an experimental study of effects of propeller shaft imbalance on vehicle vibration characteristics. A two-piece propeller shaft with unbalance is used in real vehicle test. The vehicle vibration is characterized by accelerations of the cabin floor and of the bearing which supports the propeller shaft. Through the experiment, some interesting phenomena are observed.

This paper focuses on dynamic analysis and frame optimization of a FSAE racing car frame. Firstly, a Multi-Body Dynamic (MBD) model of the racing car is established using ADAMS/Car. The forces and torques of the mechanical joints between the frame and suspensions are calculated in various extreme working conditions. Secondly, the strength, stiffness and free vibration modes of the frame are analyzed using Finite Element Analysis (FEA). The extracted forces and torques in the first step are used as boundary conditions in FEA. The FEA results suggest that the size of the frame may be not reasonable. Thirdly, the size of the frame is optimized to achieve minimized weight. Meanwhile the strength and stiffness of the frame are constrained. The optimization results reveal that the optimization methodology is powerful in lightweight design of the frame.

The sewing machine has been widely used in various aspects of life and it is essential to study its kinematic and dynamic characteristics. A dynamic model of flexible multi-link mechanism for sewing machine including joints with clearance is established to analysis its dynamic response in the present work. The configuration of the sewing machine mainly included five subsystems, feeding mechanism, needle bar mechanism, looper mechanism, shearing mechanism and adjusting mechanism. Since the sewing machine mainly consist of linkage mechanisms that are connected by revolute joints and translational joints, the existence of clearances in the joints and the flexibility of crankshafts and linkage are important factors that affect the dynamic performance. Even little clearance can lead to vibration and fatigue phenomena, lack of precision or even make overall behavior as random.

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.

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.