Search Results

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.

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."

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.

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 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.

This paper first discusses the principles of how to identify whether a time series has chaotic characteristics, and explores a method of finding out the embedding dimension of a time series. Then Grassberger-Procaccia (G-P) algorithm is adopted to calculate correlative dimension. After the validity of G-P algorithm is confirmed using several traditional strange attractors, it is applied to calculate the fractal dimension of some vibration signals of an automotive transmission. This article presents how to apply chaos and fractal theories to diagnose the wearing of ball bearings in automotive transmissions based on the analysis of the transmission acceleration vibration signals. The results show that the vibration signals of automotive transmissions have fractal nature. There are certain correlations between a bearing's condition and the fractal dimension of its vibration signal.

In this paper, thermal stress analysis for powertrain component is carried out using two in-house developed elasto-viscoplastic models (i.e. Chaboche model and Sehitoglu model) that are implemented into ABAQUS via its user subroutine UMAT. The model parameters are obtained from isothermal cyclic tests performed on standard samples under various combinations of strain rates and temperatures. Models' validity is verified by comparing to independent non-isothermal tests conducted on similar samples. Both models are applied to the numerical analysis of exhaust manifold subject to temperature cycling as a result of vehicle operation. Due to complexity, only four thermal cycles of heating-up and cooling-down are simulated. Results using the two material models are compared in terms of accuracy and computational efficiency. It is found that the implemented Chaboche model is generally more computationally efficient than Sehitoglu model, though they are almost identical in regard to accuracy.

The computer-aided engineering (CAE) automation study requires a large disk space and a premium processor. If all finite element (FE) models run locally, it may crash the local machine, and if the FE model runs on high-performance computing (HPC), transferring data from the server to the local machine to do the optimization may cause latency issues. This automation study provides a unique road map to optimize the design by working efficiently using the initial setup on the local machine, running an analysis of a large number of FE models on HPC, and performing optimization on the server. CAE Automation process has been demonstrated using a case study on a driveline component, crush spacer. Crush spacer is a very critical engineering design because, first, it provides the minimum required preload to the bearing inner races to keep them in position and, second, it endures a number of duty cycles.

The control parameter of the semi-active suspension system varies with road profile; therefore, in this study a new algorithm based on cuckoo search (CS) optimization method and road estimation was proposed to investigate the characteristics of the nonlinear parameters and at the same time improve the riding comfort. Based on this, a seven degree of freedom full vehicle model was developed with nonlinear damper and spring. The sprung mass acceleration, pitch acceleration, and tire deflection could be selected as the objective functions, and the control current of semi active suspension was selected as optimization variable. A multi-object CS algorithm was utilized to obtain the optimal parameters under different road profiles, and a road estimation algorithm was used to identify the road level. Then the control parameters could be adjusted adaptively according to the level of the road.

A flexible multi-body system dynamics model of crank system is established based on MSC/ADAMS with the purpose of modeling the crank in internal-combustion engine accurately. The film hydrodynamics model is built up through linking ADAMS and elasticity hydrodynamics subroutines. Coupling analysis between multi-flexible body system dynamics and hydrodynamic lubrication of crank system is processed. Results between the model with the function of film and without the function are compared. Then the journal center loci are given. The effects of different factors such as pressure, temperature, rotating speed and load on the journal center loci are also analyzed.

A new method for driving the hydraulic free piston engine is proposed. This method achieves the compression stroke automatically rather than special recovery system. Principle of hydraulic differential drive free-piston engine is analyzed and the control strategy of this novel hydraulic driving engine is also introduced. Then energy balance method is used to design the main parameters of the novel engine. High pressure and secondary high pressure of the hydraulic system are constrained by the combustion parameters and therefore parameters are analyzed. In order to verify the effectiveness of energy balance method, the mathematical model is established based on the piston force analysis and engine working principle. The transient results of dynamics are obtained through simulation. In addition, the effectiveness of the simulation is proofed by dimensionless analysis. It indicates that energy balance method realizes the basic performance of hydraulic free piston engine.

An impact test procedure with a legform addressing lower limb injuries in car-pedestrian accidents has been proposed by EEVC/WG17. Although a high frequency of lower limb fractures is observed in recent accident data, this test procedure assesses knee injuries with a focus on trauma to the ligamentous structures. The goal of this study is to establish a methodology to understand injury mechanisms of both ligamentous damages and bone fractures in car-pedestrian accidents. A finite element (FE) model of the human lower limb was developed using PAM-CRASH™. The commercially available H-Dummy™ lower limb model developed by Nihon ESI for a seated position was modified to represent the standing posture of pedestrians. Mechanical properties for both bony structures and knee ligaments were determined from our extensive literature survey, and were carefully implemented in the model considering their strain rate dependency in order to simulate the dynamic response of the lower limb accurately.