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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.

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.

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.

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 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.

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.

Due to the influence of non-linear dynamic characteristic of clutch, time-delays, external disturbance and parameter uncertainty, it is difficult to control the automated clutch precisely during the engaging process of the automated clutch for automatic mechanical transmission (AMT) vehicles. Here, an enhanced fuzzy sliding mode controller (EFSMC) has been proposed to control the automated clutch. To meet the real-time requirement of the automated clutch, the region-wise linear technology is adapted to reduce the fuzzy rules of the EFSMC. The simulation results have shown that the proposed controller can achieve a higher performance with minimum reaching time and smooth control actions. In addition, it shows that the controller is effective and robust to the parametric variation and external disturbance.

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.