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Active steering systems can help the driver to master critical driving situations. This paper presents a fuzzy logic control strategy on active steering vehicle based on a multi-body vehicle dynamic model. The multi-body vehicle dynamic model using ADAMS can accurately predict the dynamic performance of the vehicle. A new hybrid steering scheme including both active front steering (applying an additional front steering angle besides the driver input) and rear steering is presented to control both yaw velocity and sideslip angle. A set of fuzzy logic rules is designed for the active steering controller, and the fuzzy controller can adjust both sideslip angle and yaw velocity through the co-simulation between ADAMS and the Matlab fuzzy control unit with the optimized membership function. To ensure the design of high-quality fuzzy control rules, a rule optimization strategy is introduced.

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.

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.

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.

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.

A simulation model of the single cone synchronizer is presented using the dynamic implicit algorithm with commercial Finite Element Analysis (FEA) software Abaqus. The meshing components include sleeve gear, blocking ring and clutch gear, which are all considered as deformation body. The processes mainly contain the contact between sleeve teeth and blocking teeth, meshing period and the impact of sleeve teeth and clutch gear teeth, and these nonlinear contact steps are realized with Abaqus. In addition, a shift force derives from experiment is applied to the sleeve ring, and a moment is added to the clutch gear to realize the relative rotational speed. Based on the FEA model, the effect of the varied frictional coefficients between the cone surfaces of blocking ring and clutch gear on the synchronizer time and contact stress is discussed. Variation of stresses and contact force with respect to time are evaluated from this analysis.

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.

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.

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.

In the present study, the research of the exhaust system is performed in three steps. In the first step, the average driving degree of freedom displacement (ADDOFD) is calculated by the free modal analysis of the exhaust system. It is easy to find the reasonable location of the hanger according to the value of the ADDOFD, since it represents the relative size of some DOF's response displacement at excitation state. The second of which is to analyse the vibration isolation performance of the exhaust system based on the first step. The dynamic analysis of the exhaust system together with the powertrain is studied, by which way the unit sinusoidal excitation is applied at the powertrain's mass centre, so that the response force at the hanger can be obtained. Finally, the relationship between the constrained model of the exhaust system and the stiffness of the hanger is investigated, which is significant in engineering.

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.

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 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.

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 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.

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.

The structure of a classic self-energizing synchronizer is presented, and a simulation model is developed for analyzing the synchronizer performance. The self-energizing synchronizer has a disk spring and several energizing teeth on the sleeve for increasing the shift force. Besides, the asymmetric arrangement of chamfer teeth is applied to increase the torque for rotating ring and shift gears smoothly. The parameterized model of the typical synchronizer is developed with ADAMS for studying the synchronizer performance. In order to truly reflect the reality, the teeth of the claw plate are connected to the gear ring through bushing force alone, and the stiffness coefficient are obtained through the analysis of finite element model. Based on the dynamic model, the behavior of synchronizer with asymmetric arrangement of chamfer teeth, and the energizing effect of stiffness of the disk spring are studied. The simulation results can be used to design the synchronizer.

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.

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.