Search Results

Lightweight design is a key factor in general engineering design practice, however, it often conflicts with fatigue durability. This paper presents a way for improving the effectiveness of fatigue performance dominated optimization, demonstrated through a case study on suspension brackets for heavy-duty vehicles. This case study is based on random load data collected from fatigue durability tests in proving grounds, and fatigue failures of the heavy-duty vehicle suspension brackets were observed and recorded during the tests. Multi-objective fatigue optimization was introduced by employing multiaxial time-domain fatigue analysis under random loads combined with the non-dominated sorting genetic algorithm II with archives.

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.

In recent years, study on the ride comfort of vehicles has attracted wide attention. The vibration caused by the road is transmitted to the human body through the tire, suspension, vehicle body, and the seat. Since the human body is in contact with the seat and the vibration is transmitted directly to the human body through the seat, the seat pan angle plays an important role on the vibration response of the human body. Previous studies have explored the effects of different backrest designs on human vibration response, but ignored the effects of different seat pan angles. Therefore, this paper will use a human biodynamic model combined with a 6-DOF seat model to study the effect of seat pan angles and feet-floor interaction on human vibration response. Three cases are proposed: Case 1 has a seat pan angle 8°, Case 2 has a seat pan angle 13°, and Case 3 has a seat pan angle 17°.

In this paper, based on our previously preliminary out-of-plane tire model, a complete out-of-plane flexible tire model is further developed by considering the variation of dimension and parameter values among different slices of the tire model. This tire model is validated via various MSC ADAMS® FTire virtual cleat tests. Especially, the cleat tests with non-zero tire camber angles and non-symmetric cleat shapes, which can better capture the out-of-plane tire properties, are included. By comparing the predicted results of the proposed tire model with FTire for various cleat tests, it shows that the complete out-of-plane flexible ring tire model is better at fully representing the actual tire properties for some complicated cleat testing scenarios.

In this paper, a detailed three dimensional (3D) flexible ring tire model is first proposed which includes a rigid rim with thickness, different layers of discretized belt points and a number of massless tread blocks attached on the belt. The parameters of the proposed 3D tire model can be divided into in-plane parameters and out-of-plane parameters. In this paper, the relationship of the in-plane parameters between the 3D tire model and the 2D tire model is determined according to the connections among the tire components. Based on the determined relationship, it is shown that the 3D tire model can produce almost the same prediction results as the 2D tire model for the in-plane tire behaviors.

Nowadays, studying the human body response in a seated position has attracted a lot of attention as environmental vibrations are transferred to the human body through floor and seat. This research has constructed a multi-body biodynamic human model with 17 degrees of freedom (DOF), including the backrest support and the interaction between feet and ground. Three types of human biodynamic models are taken into consideration: the first model doesn't include the interaction between the feet and floor, the second considers the feet and floor interaction by using a high stiffness spring, the third one includes the interaction by using a soft spring. Based on the whole vehicle model, the excitation to human body through feet and back can be obtained by ride simulation. The simulation results indicate that the interaction between feet and ground exerts non-negligible effect upon the performance of the whole body vibration by comparing the three cases.

Vehicle tire performance is an important consideration for vehicle handling, stability, mobility, and ride comfort as well as durability. Significant efforts have been dedicated to tire modeling in the past, but there is still room to improve its accuracy. In this study, a detailed in-plane flexible ring tire model is proposed, where the tire belt is discretized, and each discrete belt segment is considered as a rigid body attached to a number of parallel tread blocks. The mass of each belt segment is accumulated at its geometric center. To test the proposed in-plane tire model, a full-vehicle model is integrated with the tire model for simulation under a special driving scenario: acceleration from rest for a few seconds, then deceleration for a few seconds on a flat-level road, and finally constant velocity on a rough road. The simulation results indicate that the tire model is able to generate tire/road contact patch forces that yield reasonable vehicle dynamic responses.

A new recursive method is presented for real-time estimating the inertia parameters of a vehicle using the well-known Two-Degree-of- Freedom (2DOF) bicycle car model. The parameter estimation is built on the framework of polynomial chaos theory and maximum likelihood estimation. Then the most likely value of both the mass and yaw mass moment of inertia can be obtained based on the numerical simulations of yaw velocity by Newton method. To improve the estimation accuracy, the Newton method is modified by employing the acceptance probability to escape from the local minima during the estimation process. The results of the simulation study suggest that the proposed method can provide quick convergence speed and accurate outputs together with less sensitivity to tuning the initial values of the unidentified parameters.

A tire may be one of the most critical and complex components in vehicle dynamics and road loads analyses because it serves as the only interface between the road surface and the vehicle. Extensive research and development activities about vehicle dynamics and tire models have been published in the past decades, but it is still not clear about the applications and parameter identification associated with all of these tire models. In this literature review study, various published tire models used for vehicle dynamics and road loads analyses are compared in terms of their modeling approaches, applications and parameters identification process and methodologies. It is hoped that the summary of this literature review work can help clarify and guide the future research and development direction about tire modeling.

In vehicle driving environment, the driver is subjected to the vibrations in horizontal, vertical, and fore-aft directions. The human body is very much sensitive to whole body vibration and this vibration transmission to the body depends upon various factors including road irregularities, vehicle suspension, vehicle dynamics, tires, seat design and the human body's properties. The seat design plays a vital role in the vibration isolation as it is directly in contact with human body. Vibration isolation properties of a seat depend upon its dynamic parameters which include spring stiffness and damping of seat suspension and cushion. In this paper, an optimization-based method is used to determine the optimal seat dynamic parameters for seat suspension, and cushion based on minimizing occupant's body fatigue (occupant body absorbed power). A 14-degree of freedom (DOF) multibody biodynamic human model in 2D is selected from literature to assess three types of seat arrangements.

A valid human biodynamic model is very useful for studying the human body's response to whole body vibration. Whole body vibration is one of the important factors in the study of vehicle ride comfort. The environmental vibrations are transferred to the human body through floor and seat. Seated posture is the most commonly used position in automobiles. Therefore, studying the human body response in a seated position has attracted a lot of attention. Because the human body is in direct contact with the seat, its design plays a very important role in vibration transmission. In seat design, two important components are seat suspension and cushion. The mechanical properties of these components are stiffness, damping and mass. These properties can be changed by adjusting cushion material and seat suspension linkages. In this paper, three types of seat models are used. The first one is a hard seat.

Human body size, shape, stature, joint range of motion, joint strength, and other factors vary from one person to another. Even for a single person, anthropometric data, such as weights and joint strengths, change with time. Due to this variability, different people adapt different postures to perform the same reach task within a vehicle. Even for the same person and reach task, postures will vary with time. Therefore, it is important to consider the reliability of achieving a reach task within a vehicle to create a better design for vehicle controls, enhance driver safety, and increase the level of accommodation for all types of drivers. In this study, we will present a reliability/probability approach to gain insights into driver reach tasks with uncertainty. Sensitivity levels are found to determine the importance of each joint to the reach tasks. A digital human upper body model with 21 degrees of freedom (DOFs) is introduced to demonstrate the probability approach.

Seated posture inside a vehicle influences driver performance and control of a vehicle. Many vehicles do not properly allow for a natural seated posture for all drivers. Some vehicles are difficult to drive due to the fact that the driver is inadequately accommodated in the driver seat. For people of extreme stature, tall or short, and for people of extreme width, obese or pregnant populations, it can be difficult to safely operate a vehicle if there is not enough room in the cab or if some controls cannot be reached. This paper employs digital human models to study the effect of obesity on seated posture inside a vehicle. Eight digital human models, four non-obese and four obese, are subjected to reach tests inside a virtual vehicle cab. These tests are used to determine how obesity affects the clearance between the steering wheel and driver body and whether additional factors contribute to discomfort associated with obese people seated inside a vehicle.

Digital human modeling and posture prediction can only be used as a design tool if the predicted postures are realistic. To date, the most realistic postures have been realized by simultaneously optimizing human performance measures (HPMs). These HPMs currently consist of joint discomfort, delta potential energy, and visual displacement. However these HPMs only consider the kinematics of human posture. Dynamic aspects of human posture such as external loads and mass of limbs have not yet been considered in conjunction with the current HPMs. This paper gives the formulation for a new human performance measure combination including the use of joint torque to account for the dynamics of human posture. Postures are then predicted using multi-objective optimization (MOO) techniques to optimize the combination of the new HPM and the current. The predicted postures are then compared with the benchmark postures which are those obtained from using the current HPMs only.

Digital human modeling and simulation allows a designer to test a product early in the design process. Accounting for variability in the human population which the product is intended for is difficult without developing physical prototypes and conducting population testing. Digital human modeling allows a designer to test a product without a physical prototype in a simulated environment using digital humans. Using digital humans, or manikins, of various sizes, a designer can test for variability in the human population before any physical prototype is needed. This paper proposes an optimization-based approach to determine the seat adjustment range in the interior cab design of a vehicle. Previous methods of cab design include population sampling and stochastic posture prediction. This paper places boundary anthropometric digital human models, a 95% male and a 5% female, in a 3D test environment.

Comfort assessment of respirator fit plays an important role in the respirator design process and standard development. To reduce the cost and design time of respirators, the design, fit, and evaluation process can be performed in a virtual environment. Literature shows that respirator-induced discomfort relates to stress, area, and region of the face covered. In this work, we investigate the relationship between the strap tensions and the stress and deformation distribution on the interface between the respirator and the headform. This is the first step towards a comprehensive understanding of the contribution of contact stress to the mathematical comfort fit model. The 3D digital models for respirators and headforms have been developed based on 3D scanning point-cloud using a Cyberware® 3D digitizer. Five digital headform models have been generated: small, medium, large, long and short.

As the need for more advanced human modeling tools has grown, so has the focus on research and development with posture-prediction capabilities for the design and analysis of products, and for the study of human behavior. Virtual humans have grown from digital mannequins with limited fidelity, to realistic avatars with predictive capabilities. Now, one of the frontiers with posture prediction is the incorporation of external loads and joint torques. Although advancements have been made with dynamic motion prediction, relatively little work has been conducted with external load-based posture prediction. Drawing on past success with optimization-based kinematic posture prediction implemented with the virtual human Santos™, we present a new method for considering external loads. A pilot study is conducted whereby equations for static equilibrium are incorporated in the optimization formulation.

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.

In this study, an optimization-based approach for simulating the lifting motion of a three dimensional digital human model is presented. Lifting motion is generated by minimizing a performance measure subjected to basic physical and kinematical constraints. Two performance measures are investigated: one is the dynamic effort; the other is the compression and shear forces on the lumbar joint. The lifting strategies are predicted with different performance measures. The joint strength (torque limit) and the compression and shear force on lumbar joint are also addressed in this study to avoid injury during lifting motion.

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.