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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 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.

This paper presents a torque distribution strategy for four-wheel independent drive electric vehicles (4WIDEVs) to achieve both handling stability and energy efficiency. The strategy is based on the dynamic adjustment of two optimization objectives. Firstly, a 2DOF vehicle model is employed to define the stability control objective for Direct Yaw moment Control (DYC). The upper-layer controller, designed using Linear Quadratic Regulator (LQR), is responsible for tracking the target yaw rate and target sideslip angle. Secondly, the lower-layer torque distribution strategy is established by optimizing the tire load rate and motor energy consumption for dynamic adjustment. To regulate the weights of the optimization targets, stability and energy efficiency allocation coefficient is introduced. Simulation results of double lane change and split μ road conditions are used to demonstrate the effectiveness of the proposed DYC controller.

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.

A multibody model for riderless bicycle dynamics considering tire characteristics is presented. A riderless bicycle is regarded as a multibody system consisting of four rigid bodies: rear wheel, frame, front fork, and front wheel. Every two bodies are connected with a revolute joint. The mass center coordinates and Euler angles of the rigid bodies are used as the generalized coordinates to describe their positions and orientations. The system equations of motion are obtained using Lagrange equations of the first kind. Due to the existence of the three revolute constraints and the use of dependent generalized coordinates, the Lagrange multipliers are employed to account for revolute reaction forces. As for the contact between the wheel and the ground, many studies regarded the wheel as a rigid body with a knife edge, which lead to the nonholonomic constraints between the wheel and the ground.

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.

Unsuitable shift control strategies may increase the vehicle jerk and clutch wear. In order to improve the shift quality of electric vehicles (EVs) equipped with dual clutch transmission, this paper proposes an optimal shift control strategy based on linear quadratic regulator, in which weighting matrices are selected by using genetic algorithm (GA). The dynamics of the shift process of the dual clutch transmission is analyzed to establish the dynamic model of the driving system. In addition to the vehicle jerk, the friction work of clutch is also considered as one of the performance criteria and a new linear quadratic objective function is formulated. The optimal weighting matrices for obtaining a globally optimal solution are selected benefit from the global search capacity of genetic algorithm. The optimal target trajectories of the torque of the two clutches and motor are obtained by simulating the linear quadratic regulator (LQR).

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.

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.

Trajectory and velocity tracking are currently one of the core issues in autonomous vehicle control. However, most studies deal with them separately which may cause vehicle instability under extreme conditions. In this paper, a coupled longitudinal and lateral control strategy of trajectory tracking for autonomous vehicles is presented. A lateral controller is implemented with a Linear Time-Varying MPC (LTV-MPC) to generate the front steering angle required for trajectory tracking. The side-slip angle is constrained within an interval to prevent tire saturation. Furthermore, a velocity regulation module in which the reference velocity is calculated considering the curvature of the trajectory and the lateral stability criteria is designed. A longitudinal controller is proposed to provide the traction torque with the obtained reference velocity to cope with the longitudinal velocity tracking problem.

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.

The dual clutch transmission is one of the possible choices for electric vehicle drivelines. The basic principle and control mode of shifting of wet dual clutch transmission are introduced, and the dynamic process of shifting of wet double clutch transmission is studied. Combined with the dynamic model of the wet clutch engagement process, the difference between the dynamic characteristics of the dual clutch transmission modeling using the Coulomb friction model and the dual-clutch transmission model using the average flow model and the micro-convex contact theory is analyzed. The shift control strategy of the dual clutch transmission proposes a correction method to improve the shifting smoothness. Studies have shown that the torque response of the wet clutch has significant hysteresis, and the improved control algorithm can significantly improve the shifting smoothness of the wet dual clutch transmission.

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.