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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.

A method to simulate digital human running using an optimization-based approach is presented. The digital human is considered as a mechanical system that includes link lengths, mass moments of inertia, joint torques, and external forces. The problem is formulated as an optimization problem to determine the joint angle profiles. The kinematics analysis of the model is carried out using the Denavit-Hartenberg method. The B-spline approximation is used for discretization of the joint angle profiles, and the recursive formulation is used for the dynamic equilibrium analysis. The equations of motion thus obtained are treated as equality constraints in the optimization process. With this formulation, a method for the integration of constrained equations of motion is not required. This is a unique feature of the present formulation and has advantages for the numerical solution process.

Our previous formulation for optimization-based dynamic motion simulation of a serial-link human upper body (from waist to right hand) is extended to predict the motion of a tree-structured human model that includes the torso, right arm, and left arm, with various applied external loads. The dynamics of tree-structured systems is formulated and implemented. The equations of motion for the tree structures must be derived carefully when dealing with the connection link. The optimum solution results show realistic dual-arm human motions and the required joint actuator torques. In the second part of this paper, a new method is introduced in which the constraint forces and moments at the joints are calculated along with the motion and muscle-induced actuator torques. A set of fictitious joints are modeled in addition to the real joints.

As predictive capabilities advance and human-model fidelity increases, so must validation of such predictions and models. However, subjective validation is sufficient only as an initial indicator; thorough, systematic studies must be conducted as well. Thus, the purpose of this paper is to validate postures that are determined using single-objective optimization (SOO) and multi-objective optimization (MOO), as applied to the virtual human Santos™. In addition, a general methodology and tools for posture-prediction validation are presented. We find that using MOO provides improvement over SOO, and the results are realistic from both a subjective and objective perspective.

This paper presents newly developed capabilities for the virtual human Santos™. Santos is an avatar that has extensive modeling and simulation features. It is a digital human with 109 degrees of freedom (DOF), an optimization-based method, predictive dynamics, and realistic human appearance. The new capabilities include (1) significant progress in predictive dynamics (walking and running), (2) advanced clothing modeling and simulation, (3) muscle wrapping and sliding, and (4) hand biomechanics. With these newly developed functionalities, Santos can simulate various dynamic tasks such as walking and running, investigate clothing restrictions to motion such as joint limits and torques, simulate the musculoskeletal system in real time, predict hand injury by monitoring the joint torques, and facilitate vehicle interior design. Finally, additional on-going projects are summarized.

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.

The objective of this paper is to present our method of predicting and simulating visually realistic and dynamically consistent human stair-climbing motion. The digital human is modeled as a 55-degrees of freedom branched mechanical system with associated human anthropometry-based link lengths, mass moments of inertia, and centers of gravity. The joint angle profiles are determined using a B-spline-based parametric optimization technique subject to different physics-based, task-based, and environment-based constraints. The formulation offers the ability to study effects of the magnitude and location of external forces on the resulting joint angle profiles and joint torque profiles. Several virtual experiments are conducted using this optimization-based approach and results are presented.

This paper presents a novel approach to determining the joint motion coupling relationship for the human shoulder complex. The human shoulder complex is the most sophisticated part in terms of degrees of freedom and motion. In the literature, different human shoulder biomechanical models have been developed for various purposes. Also, researchers have realized that there are constant movement relationships among the shoulder bones: the clavicle, scapula, and humerus. This is due to muscles and tendons that are involved in skeletal motions. These relationships, which are also called shoulder rhythm, entail joint motion coupling and joint limit coupling. However, the scope of this work is to determine the joint motion coupling relationship. This relationship is available in the literature, but it is an Euler-angle-based relationship. In the virtual human modeling environment, we cannot directly use this Euler-angle-based relationship.

The human shoulder plays an important role in human posture and motion, especially in scenarios in which humans need achieve tasks with external loads. The shoulder complex model is critical in digital human modeling and simulation because a fidelity model is the basis for realistic posture and motion predictions for digital humans. The complexity of the shoulder mechanism makes it difficult to model a shoulder complex realistically. Although many researchers have attempted to model the human shoulder complex, there has not been a survey of these models and their benefits and limitations. This paper attempts to review various biomechanical models proposed and summarize the pros and cons. It focuses mainly on the human modeling domain, although some of these models were originally from the robotics field. The models are divided into two major categories: open-loop chain models and closed-loop chain models.

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.

Over the past several years, significant advances have been made in the area of posture prediction. However, to make simulations more useful for vehicle design, additional unique tools are needed. This research focuses on the development of one such tool, called zone differentiation. This new tool allows user to visualize not only the complete reach envelope but also the interior comfort levels of the envelope. It uses a color map to display the relative values of various performance measures (i.e. comfort) at points surrounding an avatar. This is done by leveraging an optimization-based approach to posture prediction. Using this tool, a vehicle designer can visually display the impact that the placement of a control (switch, button, etc.) has on a driver's postural comfort. The comfort values are displayed in a manner similar to how a finite element analysis (FEA) programs display stress and strain results. The development of this tool requires two main components.

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.

Significant attention in recent years has been given towards obtaining a better understanding of human joint ranges, measurement, and functionality, especially in conjunction with commands issued by the central nervous system. Studies of those commands often include computer algorithms to describe path trajectories. These are typically in “open-form” with specific descriptions of motions, but not “closed form” mathematical solutions of the full range of possibilities. This paper proposes a rigorous “closed form” kinematic formulation to model human limbs, understand their workspace (also called the reach envelope), and delineate barriers therein where a path becomes difficult or impossible owing to physical constraints. The novel ability to visualize barriers in the workspace emphasizes the power of these closed form equations.

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.

This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks.