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This paper describes the simulation model of a backhoe excavator. The model uses a prescribed motion cycle and the objective of the program is to determine the power requirements for each of the cylinders as well as the total engine power requirement. Most computer simulations are developed by expressing the differential equations of motion for the system being studied. The known force inputs to the system are applied and the time response of the system is then obtained by numerically integrating the governing differential equations. This paper on the other hand develops the reverse of this. Utilizing a prescribed geometry and trajectory cycle for a linkage system as the input, the program solves for the types of force inputs that are required to achieve that trajectory. With the time dependence of the trajectory known, the total power required and the power required of each cylinder is also evaluated. A typical excavator linkage is shown in Fig. 1.

High fidelity mathematical vehicle models that can accurately capture the dynamics of car suspension system are critical in vehicle dynamics studies. System identification techniques can be employed to determine model type, order and parameters. Such techniques are well developed and usually used on linear models. Unfortunately, shock absorbers have nonlinear characteristics that are non-negligible, especially with regard the vehicle's vertical dynamics. In order to effectively employ system identification techniques on a vehicle, a nonlinear mathematical shock absorber model must be developed and then coupled to the linear vehicle model. Such an approach addresses the nonlinear nature of the shock absorber for system identification purposes. This paper presents an approach to integrate the nonlinear shock absorber model into the vehicle model for system identification.

Analytical models (math or computer simulation models) are typically built on the basis of many assumptions and simplifications and hence model prediction could be inaccurate in intended applications. Model validation is thus critical to quantify and improve the degree of accuracy of these models. So far, little work considers model validation for various design configurations so that model prediction is accurate in the intended design space. Furthermore, there is a lack of effective approaches that can be used to quantify model accuracy considering different number of experimental data. To overcome these limitations, objective of this paper is to develop a model validation approach for various design configurations with a reference metric for model accuracy check considering different number of experimental data.

Particle swarm optimization (PSO) is a relatively new stochastic optimization algorithm and has gained much attention in recent years because of its fast convergence speed and strong optimization ability. However, PSO suffers from premature convergence problem for quick losing of diversity. That is to say, if no particle discovers a new superiority position than its previous best location, PSO algorithm will fall into stagnation and output local optimum result. In order to improve the diversity of basic PSO, design of experiment technique is used to initialize the particle swarm in consideration of its space-filling property which guarantees covering the design space comprehensively. And the optimization procedure of PSO is divided into two stages, optimization stage and improving stage. In the optimization stage, the basic PSO initialized by Optimal Latin hypercube technique is conducted.

In this paper, a novel driver model is proposed to track vehicle speed in MIL (Model-in-the-Loop) test system, which has structural consistency with HIL (Hardware-in-the-Loop) test system. First, the MIL test system which contains models of driver, vehicle and test bench is established. Second, according to the connections of the established models in Matlab/Simulink environment, the vehicle speed is calculated in vehicle model. Emphatically, through the deviation between driving cycle speed and calculated vehicle speed, PI controller in driver model adjusts the vehicle speed to ideal point through sending the torque command to drive motor, the ILC (Iterative Learning Control) controller modifies and stores P value of PI controller. Then, in order to obtain the better modification of PI controller, iterative learning control algorithm is deeply researched in term of types and parameters.

The study of vehicle coupling state estimation accuracy especially in observer-based vehicle chassis control for improving road handling and ride comfort is a challenging task for vehicle industry under various driving conditions. Due to a large amount of life safety arising from vehicle roll behavior, how to precisely acquire vehicle roll state and rapidly provide for the vehicle control system are of great concern. Simultaneously, uncertainty is unavoidable for various aspects of a vehicle system, e.g., varying sprung mass, moment of inertia and position of the center of gravity. To deal with the above issues, a novel dual observer approach, which combines adaptive Unscented Kalman Filter (AUKF) and Takagi-Sugeno (T-S), is proposed in this paper. A full-car nonlinear model is first established to describe vehicle lateral and vertical coupling roll behavior under various road excitation.

With the development of advanced ABE fermentation technology, the volumetric percentage of acetone, butanol and ethanol in the bio-solvents can be precisely controlled. To seek for an optimized volumetric ratio for ABE-diesel blends, the previous work in our team has experimentally investigated and analyzed the combustion features of ABE-diesel blends with different volumetric ratio (A: B: E: 6:3:1; 3:6:1; 0:10:0, vol. %) in a constant volume chamber. It was found that an increased amount of acetone would lead to a significant advancement of combustion phasing whereas butanol would compensate the advancing effect. Both spray dynamic and chemistry reaction dynamic are of great importance in explaining the unique combustion characteristic of ABE-diesel blend. In this study, a semi-detailed chemical mechanism is constructed and used to model ABE-diesel spray combustion in a constant volume chamber.

The non-physiological motions of human cervical vertebrae were analyzed in volunteer tests for rear-end impacts and were considered to be an important parameter for neck injuries. The objectives of this study are to improve the Marko de Jager neck model using volunteer test data and to analyze the influence of horizontal and vertical accelerations on cervical vertebral motion. In the beginning of this study, a neck model was positioned based on X-ray cineradiography of a volunteer. Motions of each vertebra were compared with those of volunteer test data for low speed rear-end impacts (4, 6, 8km/h). In these comparisons, the differences of vertebrae motions between the neck model and the volunteer tests were found. To improve the validity of the neck model, the connection properties and the bending properties of the upper and lower vertebrae of the model were modified to increase rigidity.

Virtual reality is an emerging technology with the potential for many engineering applications including machinery simulation. In this paper the writers describe the hardware and software components of a virtual reality system that simulates machinery. They detail the flow of information that occurs in this system and discuss the functioning of an existing system at the National Center for Supercomputing Applications (NCSA) located at the University of Illinois at Urbana-Champaign. Finally, they describe potential uses of virtual reality in product design, manufacturing, training and marketing.

This paper describes a uniform Hardware-In-the-Loop (HiL) test rig for the different types of Electronic Braking System (EBS). It is applied to both modular testing and integrated testing. This test rig includes a vehicle dynamic model, a real-time simulation platform, an actual brake circuit and the EBS system under test. Firstly, the vehicle dynamic model is a highly parameterized commercial vehicle model. So it can simulate different types of commercial vehicle by different parameter configurations. Secondly, multi-types of brake circuit are modeled using brake components simulation library. So, it can test the EBS control unit independently without the influence of any real electro-pneumatic components. And a software EBS controller is also modeled. So it can test the algorithm of EBS offline. Thirdly, all real electro-pneumatic components without real gas inputted are connected to the real-time test platform through independent program-controlled relay-switches.

When the EFI system is used in a specific engine, lots of experiments are needed to optimize the control data (MAP). This work is time and financial consuming. This paper aims to develop a computer-based simulation and test system, which can produce the initial control MAP with good accuracy, and calibrate the ECU on-line. So the experiments are reduced and calibration is accelerated. In order to improve the accuracy of the initial control data, the mathematical models are built not only based on theoretical equations, but also on the control data of typical operation points, which is obtained by the on- line calibration of specific engines. This system can also perform some special calibrations, like "constant pulse width" and "square wave modulation."

Low aspect ratio wings are used extensively on open-wheeled race cars to generate aerodynamic downforce. Consequently, a great deal of effort is invested in obtaining wing profiles that provide high values of lift coefficient. If the wings are designed using 2-D methods, then it is necessary to take into account the change in operating angle of a typical airfoil section that occurs when it operates in the downwash generated by the wing. Accounting for this change during the design phase will ensure that the airfoil sections are optimized for their intended operating conditions. The addition of endplates to the wing serves to counteract the magnitude of the change in operating angle by effectively producing an increase in wing aspect ratio. During the design process at UIUC, an empirical method was used to provide an estimate of the effective aspect ratio of the wing and endplate combination.

In this work, an efficient and unified combustion model is introduced to simulate the flame propagation, diffusion-controlled combustion, and chemically-driven ignition in both SI and CI engine operation. The unified model is constructed upon a G-equation model which addresses the premixed flame propagation. The concept of the Livengood-Wu integral is used with tabulated ignition delay data to account for the chemical kinetics which is responsible for the spontaneous ignition of fuel-air mixture. A set of rigorously defined operations are used to couple the evolution of the G scalar field and the Livengood-Wu integral. The diffusion-controlled combustion is simulated equivalent to applying the Burke-Schumann limit. The combined model is tested in the simulation of the premixed SI combustion in a constant volume chamber, as well as the CI combustion in a conventional small bore diesel engine.

The helical spring is one of fundamental mechanical elements used in various industrial applications such as valves, suspension mechanisms, shock and vibration absorbers, hand levers, etc. In high speed applications, for instance in the internal combustion engine or in reciprocating compressor valves, helical springs are subjected to dynamic and impact loading, which can result in a phenomenon called “surge”. Hence, proper design and selection of helical springs should consider modeling the dynamic and impact response. In order to correctly characterize the physics of a helical spring and its response to dynamic excitations, a comprehensive model of spring elasticity for various spring coil and wire geometries, spring inertial effects as well as contacts between the windings leading to a non-linear spring force behavior is required. In practical applications, such models are utilized in parametric design and optimization studies.

Model validation is a process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. In reliability based design, the intended use of the model is to identify an optimal design with the minimum cost function while satisfying all reliability constraints. It is pivotal that computational models should be validated before conducting the reliability based design. This paper presents an ensemble approach for model bias prediction in order to correct predictions of computational models. The basic idea is to first characterize the model bias of computational models, then correct the model prediction by adding the characterized model bias. The ensemble approach is composed of two prediction mechanisms: 1) response surface of model bias, and 2) Copula modeling of a series of relationships between design variables and the model bias, between model prediction and the model bias.

ROPS-TEST is a newly developed, interactive, graphics program that may be used to simulate testing of roll bars. Cross-sections that it currently supports include solid rectangular, rectangular tubing, and circular tubing. ROPS-TEST can be used to simulate testing for crush, rear and side loading. Output from ROPS-TEST includes load-deflection and strain energy-deflection plots. ROPS-TEST does not replace actual testing of prototype roll bars. Rather it serves as a design tool to select the best design options for a particular application prior to actual testing of the prototype roll bars.

The control valve is the most important implementation part of a high pressure common rail system, and its flow characteristics have a great influence on the performance of an injector. In this paper, based on the structure and the working principle of an electromagnetic injector in a high pressure common rail system, a simulation model of the injector is established by AMESim software. Some key parameters of the control valve, including the volume of the control chamber, the diameter of the orifice Z (feeding orifice), the diameter of the orifice A (discharge orifice) and the hole diameter of the fuel diffusion hole are studied by using this model. The results show that these key structural parameters of the control valve have a great influence on the establishment of the control chamber pressure and the action of the needle valve.

A numerical study of micro-explosion in multi-component droplets is presented. The homogeneous nucleation theory is used in describing the bubble generation process. A modified Rayleigh equation is then used to calculate the bubble growth rate. The breakup criterion is then determined by applying a linear stability analysis on the bubble-droplet system. After the explosion/breakup, the atomization characteristics, including Sauter mean radius and averaged velocity of the secondary droplets, are calculated from conservation equations. Micro-explosion can be enhanced by introducing biodiesel into the fuel blends of ethanol and tetradecane. Micro-explosion is more likely to occur at high ambient pressure. However, increasing the ambient temperature does not have a significant effect on micro-explosion. There exists an optimal composition in the liquid mixture for micro-explosion.

A benchmark study was conducted to assess the capability of an open source CFD based process to accurately simulate the physics of the flow field around various vehicle types. The ICON FOAMpro process was used to simulate the flow field of four baseline geometries of a Truck, CD-Car, B-Car and an SUV. Further studies were carried out to assess the effects of geometry variations on the predicted aerodynamic lift and drag. A Detached-Eddy Simulation (DES) approach was chosen for the benchmarks. In addition to aerodynamic lift and drag values, the results for surface pressure data, surface and wake flow fields were calculated. These results were compared with values obtained using Ford's existing CFD processes.

The purpose this paper is to delineate why there exists a trade-off between biomechanical realism and algorithmic efficiency for human motion simulation models, and to illustrate how empirical human movement data and findings can be integrated with novel modeling techniques to overcome such a realism-efficiency tradeoff. We first review three major classes of biomechanical models for human motion simulation. The review of these models is woven together by a common fundamental problem of redundancy—kinematic and/or muscle redundancy. We describe how this problem is resolved in each class of models, and unveil how the trade-off arises, that is, how the computational demand associated with solving the problem is amplified as a model evolves from small scale to large scale, or from less realism to more realism.