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Model validation is a process to assess the validity and predictive capabilities of a computer model by comparing simulation results with test data for its intended use of the model. One of the key difficulties for model validation is to evaluate the quality of a computer model at different test configurations in design space, and interpolate or extrapolate the evaluation results to untested new design configurations. In this paper, an integrated model interpolation and extrapolation framework based on Bayesian inference and Response Surface Models (RSM) is proposed to validate the designs both within and outside of the original design space. Bayesian inference is first applied to quantify the distributions' hyper-parameters of the bias between test and CAE data in the validation domain. Then, the hyper-parameters are extrapolated from the design configurations to untested new design. They are then followed by the prediction interval of responses at the new design points.

Within the hydraulic shifting circuit of power-shift steering transmission, the performance of filter is generally characterized by the theoretical filtration ratio. However in practical work, the actual filtration ratio is far less than the theoretical ratio. On the basis of investigation on the structural characteristics, the oil flowing distribution and the filter mechanisms, the re-filtering rate ω and recontaminative rate θ are defined to simulate the actual filtering process. Therefore, the dynamic filtration ratio is modelled and simulated in MATLAB/Simulink to investigate that how the filtering rate ω and θ influence the dynamic filtration ratio and the deviation between the dynamic ratio and theoretical ratio. Afterwards, the variation of dynamic filtration ratio is tested through a filtration experiment under the circumstances of various flow rate, temperature and pressure.

Hydrogen is a promising energy carrier because it is characterized by a fast combustion velocity, a wide range of sources, and clean combustion products. A hydrogen internal combustion engine (H2ICE) with a turbocharger has been used to solve the contradiction of power density and control NOx. However, the selection of a H2ICE compressor with a turbocharger is very different from traditional engines because of gas fuel. Hydrogen as a gas fuel has the same volume as its cylinder and thus increases pressure and reduces the mass flow rate of air in cylinder for a port fuel injection-H2ICE (PFI-H2ICE). In this study, a general method involving a H2ICE with a turbocharger is proposed by considering the effect of hydrogen on cylinders. Using this method, we can calculate the turbocharged pressure ratio and mass flow rate of air based on the target power and general parameters. This method also provides a series of intake temperatures of air before calculation to improve accuracy.

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.

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.

This paper summarizes a systematic approach to control of nonlinear automotive systems exposed to fast transients. This approach is based on a combined application of hardware characterization, which inverts nonlinearities, and conventional Proportional-plus-Integral-plus-Derivative (PID) control. The approach renders the closed-loop system dynamics more transparent and simplifies the controller design and calibration for applications in automotive industry. The authors have found this approach effective in presenting and teaching PID controller design and calibration guidelines to automotive engineering audience, who at times may not have formal training in controls but need to understand the development and calibration process of simple controllers.

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.

In order to meet the need of high pressure common rail diesel engine, calibration for injection quantity and basic MAP of electronic-controlled injector are made. Combining with testing data, influencing factors for consistency and identity of injecting fuel in electronic-controlled injector are analyzed, in the condition of small quantity, controlled-pressure undulation quantity and injecting pulse revising are presented to achieve the respective demand. Primary basic map for common rail pressure and injecting fuel are fixed with alterable step method, and calibration of fuel quantity MAP is made on bench test. Finally test of electronic-controlled injector equipped in diesel engine is finished, testing result showed that calibration process and method are reasonable.

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."

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.

An oil-lubricated wet clutch has a direct impact on the drivability and fuel economy of a vehicle equipped with an automatic transmission system. However, a reliable analysis of clutch behavior still remains a challenge. The purpose of this study is to advance the state-of the-art in CFD methodology for modeling transient clutch behavior. First, a new iterative scheme is developed, in combination with commercial CFD software, which is capable of simulating the squeeze film process in a wet clutch. The numerical results are then validated using analytical solutions of the Reynolds equation for simplified clutch geometry and various boundary conditions. It is found that the choice of boundary conditions has a strong influence on squeeze film simulation. The iterative scheme is further validated by comparison to clutch engagement experiments.

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.

The combustion characteristics of hydrogen-air mixtures have significance significant impact on the performance and control of hydrogen-fueled internal combustion engines and the combustion velocity is an important parameter in characterizing the combustion characteristics of the mixture. A four-cylinder hydrogen internal combustion engine was used to study hydrogen combustion; the combustion characteristics of a hydrogen mixture were experimentally studied in a constant-volume incendiary bomb, and the turbulent premixed combustion characteristics of hydrogen were calculated and analyzed. Turbulent hydrogen combustion comes under the folded laminar flame model. The turbulent combustion velocity in lean hydrogen combustion is related not only to the turbulent velocity and the laminar burning velocity, but also to the additional turbulence term caused by the instability of the flame.

This paper investigates series plug-in hybrid electric vehicle (PHEV) behavior during one-day with synthesized representative one-day missions. The amounts of electric energy and fuel consumption are predicted to assess the PHEV impact on the grid with respect to the driving distance and different charging scenarios: (1) charging overnight, (2) charging whenever possible. The representative cycles are synthesized using the extracted information from the real-world driving data in Southeast Michigan gathered through the Field Operational Tests (FOT) conducted by the University of Michigan Transportation Research Institute (UMTRI). The real-world driving data include 4,409 trips covering 830 independent days and temporal distributions of departure and arrival times. The sample size is large enough to represent real-world driving.

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.

Based on MATLAB/Simulink, the ECU application software components library for diesel engine has been designed in this paper. The hierarchic and modularized components library is an open research platform for the model-based control software development. Using the components technology, the requirements of the diesel engine ECU application software have been analyzed, upon which the detailed components partition and the components library design have been accomplished. Besides, based on this components library, a control prototype for the diesel engine has been established quickly and verified through the Hardware-in-the-Loop test. The ECU software design and test process based on the components library show a good flexibility of the library, and it can improve the configurability and reusability of the software and increase the efficiency of the control software development.

The electronic control of direct injection fuel system, which could improve engine fuel efficiency, dynamics and engine emission performance through good atomization, precise control of fuel injection time and improvement of fuel-gas mixture, is the key technology to achieve the stratified combustion and lean combustion. In this paper, a direct injection injector that based on voice coil motor was designed aiming at the technical characteristics of one 800cc two-stroke cam-less engine. Prior to a one - dimensional simulation model of injector was established by AMEsim and the maximal fuel injection demand was met via the optimization of the main parameters of the injector, the structure of the voice coil motor was optimized by magnetic equivalent circuit method. After that, the maximal flow rate of the injector was verified by the injector bench test while the atomization characteristic of the injector was verified by using a high-speed camera.