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This paper presents the dynamic and analysis models of a typical synchronizer, which are mainly used to analyze the sensitivity of parameters of synchronizer on the gear shift performance. Because there are so many parameters namely coefficient of friction, cone angle, mean radius, blocker angle, etc, affected the synchronizer performance, which the times of experience will increase in a geometrical ratio if tested them one by one, it is almost impossible to evaluate all parameters by experience alone. Due to virtual prototype technology, the synchronizer parameterized virtual models can be built for the synchronizer studies. The parameterized virtual models of the typical synchronizers are developed with ADAMS. Then the gear shift process is simulated and analyzed for the given input parameters respectively. The models also predict the shift time and the peak of the shift force, and the model is validated by the good correlation between simulation results and test data.

Vehicle systems often operate with some degree of uncertainty. This study applies the Chebyshev interval method to model vehicle dynamic systems operating in the presence of interval parameters. A full vehicle model is used as the numerical model and the methodology is illustrated on the steering wheel angle pulse input test. In the numerical simulation, suspension stiffness coefficients and suspension damping coefficients are chosen as interval parameters and lateral acceleration and yaw rate are chosen to capture vehicle dynamic characteristics. System responses in time domain are validated against Monte Carlo simulations and against the scanning approach. Results indicate that the Chebyshev interval method is more efficient than Monte Carlo simulations. The results of scanning method are similar to the ones obtained with the Chebyshev interval method.

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.

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.

There are many uncertain parameters in shock absorbers, which are induced by the manufacturing error, the wear of components and the aging of materials in real vehicle environment. These uncertainties often cause some deterioration of vehicle performance. To optimize the ride characteristic of a vehicle when the shock absorber includes uncertain parameters, the robust design method is used. In this paper, a Twin Tube shock absorber fluid system model has established on the multi-domain modeling environment. This model not only includes the commonly used parameters of the shock absorber but also takes into account the structure parameters of various valves in the shock absorber, which is more detailed and accurate than those models in the past literature. The robust design of the shock absorber parameters is successfully approached using the co-simulation technique, and the ride comfort performance of the vehicle is also improved.

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.

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.

Elastomeric bushings are widely used in the passenger cars to make the cars have an ideal vehicle Noise, Vibration and Harshness (NVH) performance. However, elastomeric bushings also influence on the vehicle handling, ride and the durability performance of each component in the vehicle suspension system. It is relatively easy and cost effective to change the compliance of the bushing components compared with other method because they are made of elastomeric materials. The design of an elastomeric bushing is really a big challenge. One of the main difficulties comes from the different target compliance is wanted according to the handling, ride and durability demand at each different orientation (indicated by X Y Z) of the bushing. In this paper the following procedure was used for optimization of suspension elastomeric bushing compliance. Firstly, a detailed multi-body model was built including the nonlinear bushing effects and lower control arm flexibility.

To solve the dynamic response problem that contains uncertain parameters needs, the stochastic differential equations needs to be calculated. Interval analysis has been widely used to solve engineering problems which contain many uncertain parameters usually. But the numerical solution method for stochastic differential equations based on the interval analysis method was seldom investigated. In this study a new numerical interval method for the stochastic differential equations based on the Euler's method is presented, which can be used to solve the linear system effectively and efficiently. The probabilistic and interval dynamics analysis of a two-degree-of-freedom bike car model with uncertain parameters are presented.

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.

Hydraulic systems are popular on vehicles, such as power steering, shock absorbers, brakes, etc. Many previously works have been done on the modeling and simulation of the hydraulic systems. However, these models and parameters are usually established on the basis of plans, drawings, measurements, observations, experiences, expert knowledge and standards, and so on. In general, certain information and precise values do not exist. Uncertainty may result, e.g., from human mistakes and errors in the manufacture, from the use and maintenance of constructions, from expert evaluations, and from a lack of information. Actually, many uncertain factors will lead to great errors, and may have great effect on the hydraulic system, so the research on the hydraulic system under uncertainties is very necessary. In this paper, fuzzy algorithm is introduced to analysis the response of the hydraulic system with uncertain parameters.

A Special Analytical Target Cascading (SATC) process is developed for design problem which is difficult to ascertain the targets cascaded from upper level to lower level. The methodology is applied to achieve improving Handling Performance and Ride Quality (HPRQ) of a passenger car. A bi-level hierarchical structure with target-transforming process is established based on conceptual suspension model and multi-body models. DOE, RSM and a combined optimization method of simulated annealing and Programming Quadratic Line search is applied to execute the optimization process. The result shows that HPRQ is improved through special ATC based on CSM and multi-body modeling technique.

To design and optimize the vehicle driveline is necessary to decrease the fuel consumption and improve dynamic performance. This paper describes a methodology to optimize the driveline design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A new and flexible tool for modeling multi-domain systems, Modelica, is used to carry out the modeling and analysis of a vehicle, and the multi-domain model is developed to determine the optimum design in terms of fuel economy, with determinability. Secondly, a robust optimization is carried out to find the optimum design considering uncertainty. The results indicate that the fuel economy and dynamic performance are improved greatly.

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.

Clutch actuation systems are complex systems where hydraulic, pneumatic, mechanical and electrical components are coupled. This paper presents a detailed clutch actuation model composed of components from multi-domains like mechanical and pneumatic actuation system, hydraulic boosting system, etc. Various components and subsystem models, such as the driver, engine, gear pairs, clutches, etc., are integrated into an overall vehicle system model according to the transmission power flow and control logic. The model is implemented using the Modelica programming language. The simulation of the clutch actuation system was carried out for the analysis of drivability, shift quality and vehicle overall performance.

A robust design procedure is applied to achieve improved vehicle handling performance as an integral part of simulation-based vehicle design. This paper presents a hybrid robust design method, the robust design process strategy (RDPS), which makes full use of the intense complementary action of characteristics between the Response Surface Methodology (RSM) and the Taguchi method, to get the robust design of the vehicle handling performance. The vehicle multi-body dynamic model is built in the platform that is constructed by the software of iSIGHT, ADAMS/CAR, and MATLAB. The design-of-experiment method of the Latin Hypercube (LHC) is used to obtain the approximate area values, and then the RDPS is utilized to achieve improved vehicle handling performance results. The validation is made by the Monte Carlo Simulation Technique (MCST) in terms of the effectiveness of the RDPS in solving robust design problems.

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.