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The main purpose of this research is to investigate the optimal design of pipeline diameter in an air brake system in order to reduce the response time for driving safety using DOE (Design of Experiment) method. To achieve this purpose, this paper presents the development and validation of a computer-aided analytical dynamic model of a pneumatic brake system in commercial vehicles. The brake system includes the subsystems for brake pedal, treadle valve, quick release valve, load sensing proportional valve and brake chamber, and the simulation models for individual components of the brake system are established within the multi-domain physical modeling software- AMESim based on the logic structure. An experimental test bench was set up by connecting each component with the nylon pipelines based on the actual layout of the 4×2 commercial vehicle air brake system.

The ride comfort of the commercial vehicle is mainly affected by several vibration isolation systems such as the primary suspension system, engine mounting system and the cab mounting system. A rigid-flexible coupling model for the truck was built and analyzed in multi-body environment (ADAMS). The method applying the excitation on the wheels center and the engine mountings in time domain was presented. The variables' effects on the ride performance were studied by design of experiment (DOE). The optimal design was obtained by the co-simulation of the ADAMS/View, iSIGHT and Matlab. It was found that the vertical root mean square (RMS) acceleration and frequency-weighted RMS acceleration on the seat track were reduced about 17% and 11% respectively at different speeds relative to baseline according to ISO 2631-1.

The suspension system of a heavy truck's driver seat plays an important role to reduce the vibrations transmitted to the seat occupant from the cab floor. Air-spring is widely used in the seat suspension system, for the reason that its spring rate is variable and it can make the seat suspension system keep constant ‘tuned’ frequency compared to the conventional coil spring. In this paper, vibration differential equation of air-spring system with auxiliary volume is derived, according to the theory of thermodynamic, hydrodynamics. The deformation-load static characteristic curves of air-spring is obtained, by using a numerical solution method. Then, the ADAMS model of the heavy truck's driver seat suspension system is built up, based on the structure of the seat and parameters of the air-spring and the shock-absorber. At last, the model is validated by comparing the simulation results and the test results, considering the seat acceleration PSD and RMS value.

In this paper, a new computational method is provided to identify the uncertain parameters of Load Sensing Proportional Valve (LSPV) in a heavy truck brake system by using the polynomial chaos theory. The simulation model of LSPV is built in the software AMESim depending on structure of the valve, and the estimation process is implemented relying on the experimental measurements by pneumatic bench test. With the polynomial chaos expansion carried out by collocation method, the output observation function of the nonlinear pneumatic model can be transformed into a linear and time-invariant form, and the general recursive functions based on Newton method can therefore be reformulated to fit for the computer programming and calculation. To improve the estimation accuracy, the Newton method is modified with reference to Simulated Annealing algorithm by introducing the Metropolis Principle to control the fluctuation during the estimation process and escape from the local minima.

This paper investigates a hierarchical optimization procedure for the optimum synthesis of a double-axle steering mechanism by considering the dynamic load of a vehicle which is seldom discussed in the previous literature. Firstly, a multi-body model of double-axle steering is presented by characterizing the detailed leaf spring effect. Accordingly, the influences of dynamic load including the motion interference of steering linkage resulted from the elastic deformation of leaf spring, and the effects of wheel slip angle and the position discrepancy of wheel speed rotation centers are explored systematically. And then, a hierarchical optimization method based on target cascading methodology is proposed to classify the design variables of double-axle steering mechanism into four levels. At last, a double-axle steering mechanism of a heavy-duty truck is utilized to demonstrate the validity of this method.

Hydraulic power steering system, which can reduce the steering hand force by applying the output from a hydraulic actuator, has been widely used in vehicles. In this paper, a detailed steer model including steering column, steering trapezium, and detailed hydraulic power steering system which is consisting of steering cylinder, relief valve, rotary valve, pump and hydraulic lines were established, and a multi-body model of a heavy truck was established to connect with the hydraulic power steering system. Modelica simulation language, which can be efficiently used to investigate multi-domain problems, was used to in the modeling and simulation of the power steering system and the vehicle. The simulation was carried out to identify the effects of design variables on the lateral stability of the vehicle. The application of Modelica for investigating multi-domain problems is also demonstrated.

Three constitutive models which capture the amplitude and frequency dependency of filled elastomers are implemented for the conventional engine mounts of automotive powertrain mounting system (PMS). Firstly, a multibody dynamic model of a light duty truck is proposed, which includes 6 degrees of freedom (DOFs) for the PMS. Secondly, Three constitutive models for filled elastomers are implemented for the engine mounts of the PMS, including: (1) Model 1: Kelvin-Voigt model; (2) Model 2: Fractional derivative Kelvin-Voigt model combined with Berg’s friction; (3) Model 3: Generalized elastic viscoelastic elastoplastic model. The nonlinear behaviors of dynamic stiffness and damping of the mounts are investigated. Thirdly, simulations of engine vibration dynamics are presented and compared with these models and the differences between common Kelvin-Voigt model and other constitutive models are observed and analyzed.

Steering returnability is an important index for evaluating vehicle handling performance. A systematic method is presented in this paper to reduce the high yaw rate residue and the steering response time for a light duty truck in the steering return test. The vehicle multibody model is established in ADAMS, which takes into consideration of the frictional loss torque and hydraulically assisted steering property in the steering mechanism, since the friction, which exists in steering column, spherical joint, steering universal joint, and steering gear, plays an important role in vehicle returnability performance. The accuracy of the vehicle model is validated by road test and the key parameters are determined by executing the sensitivity analysis, which shows the effect of each design parameter upon returnability performance.

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.

As there are a variety of uncertainty contained in dynamic systems, this paper presents a method to identify the uncertain parameters of Load Sensing Proportional Valve in a heavy truck brake system. This method is derived from polynomial chaos theory and uses the maximum likelihood approach to estimate the most likely value of uncertain parameters, such as equivalent bearing area diameter of the diaphragm, preload of return spring and so on. The maximum likelihood estimates are obtained through minimizing the cost function derived from the prior probability for the measurement noise. Direct stochastic collocation has been shown to be more efficient than Galerkin approach in the simulation of systems with large number of uncertain parameters. The simulation model of Load Sensing Proportional Valve is built in software AMESim based on logic structure of the valve. The uncertain parameters are estimated through the simulation results which are treated as measurements.

To provide a greater weight capacity, the tandem axle which is a group of two or more axles situated close together has been used on most heavy truck. In general, the reaction moments during braking cause a change in load distribution among both axles of the tandem suspension. Since load transfer among axles of a tandem suspension can lead to premature wheel lockup, tandem-axle geometry and the brake force distribution among individual axles of a tandem suspension have a pronounced effect on braking efficiency. The braking efficiency has directly influence on the vehicle brake distance and vehicle travelling direction stability in any road condition, so how to improve the braking efficiency is researched in this paper. The load transfer among individual axles is not only determined by vehicle deceleration but also by the actual brake force of each axle for tandem axle suspension, which increases the difficulty of braking efficiency improving.

The air brake system has been widely used since its great superiority over many other kinds of brake systems, but the capacity and the stability of air brake system are determined by many factors which are always uncertain and difficult to be evaluated accurately. So it is necessary to improve the robustness of this kind of brake system. In this paper, a physical model of air brake control system is made by a multi-domain physical modeling software-AMESim and the robust design for air brake system is carried out. Firstly, the key design parameters that will greatly affect on the delay time and pressure that leads to the shaking problem are obtained by using the method of design of experiment (DOE). Then, the regress of the response surface based on results of DOE and the robust design using the tolerance design are carried out. The value for those key parameters that can lead to the best performance and robustness of the air brake system are finally determined.

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.

Abrasion of the Electromechanical brake (EMB) brake pad during the braking process leads to an increase in brake gap, which adversely affects braking performance. Therefore, it is imperative to promptly detect brake pad abrasion and adjust the brake gap accordingly. However, the addition of extra gap adjustment or sensor detection devices will bring extra size and cost to the brake system. In this study, we propose an innovative EMB gap active adjustment strategy by employing modeling and analysis of the braking process. This strategy involves identifying the contact and separation points of the braking process based on the differential current signal. Theoretical analysis and simulation results demonstrate that this gap adjustment strategy can effectively regulate the brake gap, mitigate the adverse effects of brake disk abrasion, and notably reduce the response time of the braking force output. Monitoring is critical to accurately control EMB clamping force.

Intelligent vehicle-to-everything connectivity is an important development trend in the automotive industry. Among various active safety systems, Autonomous Emergency Braking (AEB) has garnered widespread attention due to its outstanding performance in reducing traffic accidents. AEB effectively avoids or mitigates vehicle collisions through automatic braking, making it a crucial technology in autonomous driving. However, the majority of current AEB safety models exhibit limitations in braking modes and fail to fully consider the overall vehicle stability during braking. To address these issues, this paper proposes an improved AEB control system based on a risk factor (AERF). The upper-level controller introduces the risk factor (RF) and proposes a multi-stage warning/braking control strategy based on preceding vehicle dynamic characteristics, while also calculating the desired acceleration.

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.