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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.

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.

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.

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.

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.

This paper deals with the robust design of the Load Sensing Proportional Valve (LSPV). To find out the parameters which have main effect on the performance of the LSPV, the DOE based on orthogonal experiment is carried out utilizing the LSPV model built in AMESim environment. In order to save computation expense, the RSM technique is used to approximate the optimal objectives and constraints. Then a robust design methodology using multi-objective evolutionary algorithm (MOEA) is performed and a set of non-dominated solutions are therefore obtained. With specified assessments, feasible solutions can therefore be selected from the entire field of the Pareto optimal solutions. The validation is made by Monte Carlo Simulation Technique in terms of the robustness of the feasible solutions.

As is known to all, there are some contradictions between the handling and ride performance during the design process of vehicles. Sometimes owing to serious collisions of each criterion in the high-dimensional solution space, the common method to deal with the contradiction is to transform into a single target according to weights of each objective, which may not obtain a desired result. A multi-criteria approach is therefore adopted to optimize both properties and the result of a multi-criteria design is not a unique one but a series of balanced solutions. This paper is focused on the robust design of a simplified vehicle model in terms of not only ride comfort but also handling and stability using a multi-objective evolutionary algorithm (MOEA) method. Using the proposed method, the conflicting performance requirements can be better traded off. One of the most important indexes to characterize the vertical ride comfort is the acceleration of the sprung mass.

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 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.

The vehicle ride comfort behavior is closely associated with the vibration isolation system such as the primary suspension system, the engine mounting system, the cab suspension system and the seat suspension system. Air spring is widely used in the cab suspension system for its low vibration transmissibility, variable spring rate and inexpensive automatic leveling. The mathematical model of the air spring is presented. The amplitude and frequency dependency of the air spring's stiffness characteristic is highlighted. The air spring dynamic model is validated by comparing the results of the experiment and the simulation. The co-simulation method of ADAMS and AMESim is applied to integrate the air spring mathematical model into the cab multi-body dynamic model. The simulation and ride comfort test results under random excitation are compared.

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.