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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 result of rib stiffening is the redistribution of natural frequencies and mode shapes of the plate, which can significantly alter its noise and vibration character. In this paper, genetic algorithms are used as a promising tool for sound radiation minimization problems. The objective of the study is to determine effective, general design methods for determining the optimal dimensions of the stamped rib in a plate to minimize the total radiated acoustic power. Acoustic response under broad-band excitation is considered. Radiated sound power is calculated using a boundary element method, in conjunction with a finite element solver for the solution of the structural problem.

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.

Currently, the most widely used droplet collision model is O'Rourke's algorithm. However, it has large mesh dependency in spray simulations. The calculated results have different spray structures in different meshes and the predicted mean drop sizes increase with the mesh resolution. The predicted mean drop size can increase 30 microns from the coarsest mesh to the finest one. There are two reasons for this. Firstly, the O'Rourke model does not consider the collision between parcels that reside at the edges of two adjacent cells. Secondly, it assumes the probability of a pair of parcels colliding is proportional to their relative velocity. The result of this assumption is that parcels furthest apart from each other in a cell are most likely to collide because they have the greatest relative velocity. In order to reduce mesh dependency, a new model, called CMC (cross mesh collision), is proposed. It is an extension of the O'Rourke droplet collision model.

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.

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.

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.

In recent years, the tractor-semitrailer combination has become the primary vehicle of China's long-distance freight system. In this paper, with the aim of optimizing the path tracking control and following control of the tractor-semitrailer combination, a kinematics-based path tracking control scheme is proposed. Firstly, a kinematic model of the tractor-semitrailer combination has been constructed. The control of the tractor-semitrailer combination is simplified to focus on three control points based on the kinematics model. Secondly, the path tracking control algorithm and the following control algorithm of the tractor-semitrailer combination are proposed in this paper. The improved MPC is used for path-tracking control of tractor-semitrailer combinations. The cost function of rolling optimization steps is intended, and the optimal line is determined with the lateral deviation, the variation of lateral error, and the deviation of heading angle as the input.

The automatic emergency braking (AEB) system is an important part of automobile active safety, which can effectively reduce rear-end collision accidents and protect drivers' safety through active braking. AEB system has been included in many countries' new car assessment programme as the test content of active safety. In view of obviously deficiencies of the existing AEB control algorithm in avoiding longitudinal collision at high speed, it is proposed to an optimized model of the minimum safe distance for rear-end collision prevention on high-speed road in order to improve the accuracy of AEB system. Considering the influence of road adhesion coefficient and human comfort on the maximum braking deceleration, it is established to a more accurate and reasonable AEB system to avoid collision for expressway. The collision avoidance strategy is verified by simulation software.

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 present study introduces a novel approach for achieving path tracking of an unmanned bicycle in its local body-fixed coordinate frame. A bicycle is generally recognized as a multibody system consisting of four distinct rigid bodies, namely the front wheel, the front fork, the body frame, and the rear wheel. In contrast to most previous studies, the relationship between a tire and the road is now considered in terms of tire forces rather than nonholonomic constraints. The body frame has six degrees of freedom, while the rear wheel and front fork each have one degree of freedom relative to the body frame. The front wheel exhibits a single degree of freedom relative to the front fork. A bicycle has a total of nine degrees of freedom.