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Existing gasoline DI injection equipment has been modified to generate single hole pulsed gas jets. Injection experiments have been performed at combinations of 3 different pressure ratios (2 of which supercritical) respectively 3 different hole geometries (i.e. length to diameter ratios). Injection was into a pressure chamber with optical access. Injection pressures and injector hole geometry were selected to be representative of current and near-future DI natural gas engines. Each injector hole design has been characterized by measuring its discharge coefficient for different Re-levels. Transient jets produced by these injectors have been visualized using planar laser sheet Mie scattering (PLMS). For this the injected gas was seeded with small oil droplets. The corresponding flow field was measured using particle image velocimetry (PIV) laser diagnostics.

This paper discusses the development and subsequent validation process of generic multi-body models for commercial vehicle combinations. The model is intended for performance assessment and improving of current and future combinations for the European road network. A second goal is to employ the model for the development of driver support systems and active steering strategies for both low speed manoeuvrability and high speed stability. The model is developed in SimMechanics, which is part of the MATLAB/Simulink software. Due to its modularity, one can quickly modify the model to the desired configuration and dimensions; therefore various multi articulation vehicle models can be created. The paper further illustrates the simplified and generic modelling methods used to build particular components such as chassis, tyres or suspension in the multibody domain.

The energy management strategies (EMS) for hybrid electric vehicles (HEV) have a great impact on the fuel economy (FE). The Pontryagin's minimum principle (PMP) has been proved to be a viable control strategy for HEV. The optimal costate of the PMP control can be determined by the given information of the driving conditions. Since the full knowledge of future driving conditions is not available, this paper proposed a dynamic optimization method for PMP costate without the prediction of the driving cycle. It is known that the lower fuel consumption the method yields, the more efficiently the engine works. The selection of costate is designed to make the engine work in the high efficiency range. Compared with the rule-based control, the proposed method by the principle of Hamiltonian, can make engine working points have more opportunities locating in the middle of high efficiency range, instead of on the boundary of high efficiency range.

Accuracy of heat flux models is critical to clutch design in case of excessive temperatures due to large amounts of friction heat generated in the narrow space. Pressure distribution on the clutch friction interface is an important factor affecting heat flux distribution, thus affecting temperature distribution. In this paper, an experiment is conducted to obtain the pressure distribution for one typical dry clutch equipped with a set of diaphragm spring. Considering that the frictional interface is in contact, this study makes use of pressure sensitive film and acquires data based on image processing techniques. Then a polynomial mathematical model with dimensionless parameters is developed to fit the pressure distribution on the friction disc. After that, the proposed pressure model is applied to a thermal model based on finite element method. In addition, two conventional thermal models (i.e., uniform heat flux model and uniform pressure model), are implemented for comparison.

The vehicle chassis integrated control system can improve the stability of vehicles under extreme conditions using tire force allocation algorithm, in which, the nonlinearity and uncertainty of tire-road contact condition need to be taken into consideration. Thus, An MPC (Model Predictive Control) controller is designed to obtain the additional steering angle and the additional yaw moment. By using a robust optimal allocation algorithm, the additional yaw moment is allocated to the slip ratios of four wheels. An SMC (Sliding-Mode Control) controller is designed to maintain the desired slip ratio of each wheel. Finally, the control performance is verified in MATLAB-CarSim co-simulation environment with open-loop manoeuvers.

The internal combustion engine (ICE) is a typical complex multidisciplinary system which requires the support of precision design and manufacturing. To achieve a better performance of ICEs, tolerance assignment, or tolerance design, plays an important role. A novel multi-disciplinary tolerance design optimization problem considering two important disciplines of ICEs, the compression ratio and friction loss, is proposed and solved in this work, which provides a systematic procedure for the optimal determination of tolerances and overcomes the disadvantages of the traditional experience-based tolerance design. A bi-disciplinary analysis model is developed in this work to assist the problem solving, within which a model between the friction loss and tolerance is built based on the Gaussian Process using the corresponding simulation and experimental data.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

The interaction of fuel sprays and in-cylinder flow in direct-injection engines is expected to alter kinetic energy and integral length scales at least during some portions of the engine cycle. High-speed particle image velocimetry was implemented in an optical four-valve, pent-roof spark-ignition direct-injection single-cylinder engine to quantify this effect. Non-firing motored engine tests were performed at 1300 RPM with and without fuel injection. Two fuel injection timings were investigated: injection in early intake stroke represents quasi-homogenous engine condition; and injection in mid compression stroke mimics the stratified combustion strategy. Two-dimensional crank angle resolved velocity fields were measured to examine the kinetic energy and integral length scale through critical portions of the engine cycle. Reynolds decomposition was applied on the obtained engine flow fields to extract the fluctuations as an indicator for the turbulent flow.

Because of rising complexity during the automotive product development process, the number of disciplines to be concerned has been significantly increased. Multidisciplinary design optimization (MDO) methodology, which provides an opportunity to integrate each discipline and conduct compromise searching process, is investigated and introduced to achieve the best compromise solution for the automotive industry. To make a better application of MDO, the suitable coupling strategy of different disciplines and efficient optimization techniques for automotive design are studied in this article. Firstly, considering the characteristics of automotive load cases which include many shared variables but rare coupling variables, a multilevel MDO coupling strategy based on enhanced collaborative optimization (ECO) is studied to improve the computational efficiency of MDO problems.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

In the current work, unidirectional (UD) carbon fiber composite hatsection component with two different layups are studied under dynamic three-point bending loading. The experiments are performed at various impact velocities, and the effects of impactor velocity and layup on acceleration histories are compared. A macro model is established with LS-DYNA for a more detailed study. The simulation results show that the delamination plays an important role during dynamic three-point bending test. Based on the analysis with a high-speed camera, the sidewall of hatsection shows significant buckling rather than failure. Without considering the delamination, the current material model cannot capture the post-failure phenomenon correctly. The sidewall delamination is modeled by assumption of larger failure strain together with slim parameters, and the simulation results of different impact velocities and layups match the experimental results reasonably well.

Diesel spray mixture formation is investigated at target conditions using multiple diagnostics and laboratories. High-speed Particle Image Velocimetry (PIV) is used to measure the velocity field inside and outside the jet simultaneously with a new frame straddling synchronization scheme. The PIV measurements are carried out in the Engine Combustion Network Spray A target conditions, enabling direct comparisons with mixture fraction measurements previously performed in the same conditions, and forming a unique database at diesel conditions. A 1D spray model, based upon mass and momentum exchange between axial control volumes and near-Gaussian velocity and mixture fraction profiles is evaluated against the data.

Flash boiling is considered a useful method in enhancing the liquid fuel jet break-up and spray atomization process for internal combustion engine applications. Spray atomization efficiency plays a vital role in the combustion process. Although some researches have demonstrated that flash boiling has the potential to improve the combustion efficiency and optimize emission-related issues, the effect of flash boiling spray characteristics on the combustion process has not been fully investigated. In this paper, spray characteristics and its related combustion process were studied via various non-intrusive diagnostics methods. The spray and combustion process under different test conditions were studied using an optical engine. It was found that by using flash boiling atomization, the combustion duration was reduced and IMEP enhanced significantly. Experimental results have built the relationship between flash boiling spray characteristics and the combustion performance in the engine.

It is well known that engine downsizing is still the main energy-saving technology for spark-ignition direct-injection (SIDI) engine. However, with the continuous increase of the boosting ratio, the gasoline engine is often accompanied by the occurrence of knocking, which has the drawback to run the engine at retarded combustion phasing. Besides, in order to protect the turbine blades from being sintered by high exhaust temperature, the strategies of fuel enrichment are often taken to reduce the combustion temperature, which ultimately leads to a high level of particulate number emission. Therefore, to address the issues discussed above, the port water injection (PWI) techniques on a 1.2-L turbocharged, three-cylinder, SIDI engine were investigated. Measurements indicate that the optimization of spark timing has a significant impact on its performance.

A computationally efficient engine model is developed based on an extended NO emission model and state-of-the-art soot model. The model predicts exhaust NO and soot emission for both conventional and advanced, high-EGR (up to 50 %), heavy-duty DI diesel combustion. Modeling activities have aimed at limiting the computational effort while maintaining a sound physical/chemical basis. The main inputs to the model are the fuel injection rate profile, in-cylinder pressure data and trapped in-cylinder conditions together with basic fuel spray information. Obtaining accurate values for these inputs is part of the model validation process which is thoroughly described. Modeling results are compared with single-cylinder as well as multi-cylinder heavy-duty diesel engine data. NO and soot level predictions show good agreement with measurement data for conventional and high-EGR combustion with conventional timing.

Sampling-based methods are general but time consuming for solving a Reliability-Based Design Optimization (RBDO) problem. In order to alleviate the computation burden, score function together with the Monte Carlo method was used to compute the stochastic sensitivities of reliability functions. In literature, re-weighting schemes were shown to converge faster than the regular Monte Carlo method. In this paper, a reweighting scheme together with score function is employed to perform sampling-based stochastic sensitivity analysis to improve the computational efficiency and accuracy. An analytical example is used to show the advantages of the proposed method. Comparisons to the conventional methods are made and discussed. Two RBDO problems are solved to demonstrate the use of the proposed method.

At Eindhoven University of Technology an active suspension system has been developed [1]. This system is superior to other active suspension in terms of bandwidth and power consumption. This active suspension system was tested on a quarter car setup and showed improvements of up to 48% in comfort [2]. In order to implement this suspension in a test vehicle with the same improvements, a non-linear full-car model is developed in this paper which is used to simulate and design various controllers. The non-linear model incorporates non-linear damping, bump stops, actuator saturation and actuator friction. To model the friction in the actuator a combination of Coulomb and viscous friction is used. To model the MacPherson suspension strut, two methods are described and compared. Also the implications of using acceleration sensors which are placed in line with the MacPherson strut are discussed.

Using highly efficient powertrain is one of the most important and effective approaches to increase the driving distance of electric vehicles (EVs). In this paper, a novel two-speed dual-clutch transmission (DCT) is proposed. The transmission is comprised of two traditional friction clutches and two-stage planetary gear sets. One clutch connects the input sun gear and the other connects the input carrier. The Simulink models including an electric motor and two-speed DCT are established. Gearshift schedule based on fuzzy logic which reflects the driver’s intensions is adopted to improve the dynamic and economic performance of the novel transmission. The simulation model is built using MATLAB/Simulink® to validate the effectiveness of the proposed gearshift schedule compared with the conventional two-parameter gearshift schedule. Simulation results show that both the dynamic and economic performance of the novel DCT for EVs are improved with the proposed fuzzy logic gearshift schedule.

Stringent particulate emission regulations are applied to spark-ignition direct-injection (SIDI) engines, calling for a significant in-cylinder reduction of soot particles. To enhance fundamental knowledge of the soot formation and oxidation process inside the cylinder of the engine, a new in-flame particle sampling system has been developed and implemented in a working optical SIDI engine with a side-mounted, wall-guided injection system. Using the sampling probes installed on the piston top, the soot particles are directly sampled from the petrol flame for detailed analysis of particle size distribution, structure, and shape. At the probe tip, a transmission electron microscope (TEM) grid is stored for the soot collection via thermophoresis, which is imaged and post-processed for statistical analysis. Simultaneously, the flame development was recorded using two high-speed cameras to evidence the direct exposure of the sampling grids to the soot-laden diffusion flames and pool fires.

Port water injection is considered as a promising strategy to further improve the combustion performance of internal combustion engines for its benefit in knock resistance by reducing the cylinder temperature. A thorough investigation of the port water injection technique is required to fully understand its effects on the engine combustion process. This study explores the potential of the port water injection technique in improving the performance of a turbo charged Gasoline Direct Injection engine. A 3D computational fluid dynamics model is applied to simulate the in-cylinder mixing and combustion for this engine both with and without water injection. Different water injection timings are investigated and it is found that the injection timing greatly effects the mass of water which enters the combustion chamber, both in liquid and vapor form.