Search Results

The continuous improvement of spark-ignition direct-injection (SIDI) engines is largely attributed to the enhanced understanding of air-fuel mixing and combustion processes. The intricate interaction between transient spray behavior and the ambient flow field is important to unveil the airflow dynamics during the spray injection process. This study investigates the fuel-spray boundary interactions under different superheated conditions by analyzing the ambient flow field pattern with constraint-based modeling (CBM). In the experimental setup, superheated conditions are facilitated by adjusting different fuel temperatures and ambient pressures. By adding the tracer particles containing Rhodamine 6G to the ambient air, the combined diagnostic of fluorescent particle image velocimetry (FPIV) and Mie-scattering is implemented to measure the velocity distribution and flow trajectory of the air surrounding the spray formation and propagation.

Aiming at the problem of weak communication, strong interference, cross-domain, and large-scale environment, it is difficult to achieve efficient decision-making and planning in the collaborative operation of intelligent groups. Based on the SOM algorithm, this paper proposes a dual-selection allocation and distributed vectorized trajectory planning. Form a collaborative planning algorithm that can be updated with high frequency and a rational decision-making mechanism. Provide technical support for collaborative search and detection of intelligent groups. At the same time, based on the principle of minimum consistency, this paper proposes a clock synchronization model under spatial coordination and conducts simulation experiments to verify it. The result proves the efficiency and practicability of the collaborative intelligent decision-making plan proposed in this paper.

Ammonia has attracted the attention of a growing number of researchers in recent years. However, some properties of ammonia (e.g., low laminar burning velocity, high ignition energy, etc.) inhibit its direct application in engines. Several routes have been proposed to overcome these problems, such as oxygen enrichment, partial fuel cracking strategy and co-combustion with more reactive fuels. Improving the reactivity of ammonia from the oxidizer side is also practical. Ozone is a highly reactive oxidizer which can be easily and rapidly generated through electrical plasma and is an effective promoter applicable for a variety of fuels. The dissociation reaction of ozone increases the concentration of reactive radicals and promotes chain-propagating reactions. Thus, obtaining accurate rate constants of reactions related to ozone is necessary, especially at elevated to high pressure range which is closer to engine-relevant conditions.

In order to meet increasingly stringent emission regulations, it is significance to establish a control- oriented transient NOx and PM emission prediction model and improve the accuracy and real-time performance. In this study, the prediction model of transient PM emissions based on Transformer is established. In terms of model accuracy and real-time performance, Transformer emission prediction model is compared with Multilayer perceptron (MLP) neural network and Long-Short Term Memory (LSTM) emission prediction model. The results show that the performance of Transformer transient emission prediction model is superior to other model structures, it can be used for real-time prediction.

Visual Place Recognition (VPR) excels at providing a good location prior for autonomous vehicles to initialize the map-based visual SLAM system, especially when the environment changes after a long term. Condition change and viewpoint change, which influences features extracted from images, are two of the major challenges in recognizing a visited place. Existing VPR methods focus on developing the robustness of global feature to address them but ignore the benefits that local feature can auxiliarily offer. Therefore, we introduce a novel hierarchical place recognition method with both global and local features deriving from homologous VLAD to improve the VPR performance. Our model is weak supervised by GPS label and we design a fine-tuning strategy with a coupled triplet loss to make the model more suitable for extracting local features.

To alleviate the shortage of petroleum resources and the air pollution caused by the burning of fossil fuels, the development of renewable fuels has attracted widespread attention. Among the various renewable fuels, ethanol can be produced from biomass and does not require much modification when applied to practical engines, so it has been widely used. However, ethanol fuel has a higher heat of vaporization than gasoline, it is difficult to evaporate and atomize under cold start conditions. Besides, the catalyst has not reached the conversion temperature at this time, resulting in lower conversion efficiency. These factors all lead to higher pollutant emission levels in ethanol-gasoline blends. To solve the above problems, this research used visualization techniques to compare the effects of flash boiling and high-energy ignition technologies on the in-cylinder combustion process and pollutant emission of ethanol-gasoline blends fuel.

With the development of economic globalization, the speed of development of container terminals is also very rapid. Under the pressure brought by the surge in throughput, the unmanned and intelligent terminals will become the future development direction of terminals. As the cornerstone of the unmanned terminal, the positioning technology provides the most basic position information for system scheduling, path planning, real-time correction, and loading and unloading. Therefore, this paper is aimed to design a low-cost, high-precision, and easy-to-maintain unmanned dock positioning system in order to better solve the problem of unmanned dock positioning. The main research content of this paper is to design a positioning algorithm for unmanned terminal Automated Guided Vehicle (AGV) based on single-line lidar, including point cloud data acquisition, background filtering, point cloud clustering, vehicle position extraction, and result optimization.

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.

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.

With the rapid development of series-parallel hybrid electric vehicles (SPHEVs), mode transition from pure electrical drive to hybrid drive has attracted considerable attention. The presence of time delay due to response capacity of actuators and signal transmission of communication may cause decrease of speed tracking accuracy, even instable dynamics. Consequently, drivability of the SPHEV is unacceptable, and durability of the components is reduced. So far, plenty of control strategies have been proposed for mode transition, however, no previous research has been reported to deal with the time delay during mode transition. In this paper, a dynamic model with time delay of hybrid electric system is established. Next, a mode transition time-delay controller is proposed based on a two degree of freedom internal model controller (2-DOF-IMC).

Ignition performance is critical for the implementation of diluted combustion for spark-ignition engines. The short circuit and restrike phenomena can influence the initial ignition volume and discharge duration which are important for the stable ignition processes. In this study, the short circuits and restrikes of spark channels are studied with various flow velocities, spark plug gaps and discharge energies. The development of the spark channels is captured by using the direct imaging technique with a CMOS camera equipped with an image intensifier. A multi-coil ignition system is designed to enable flexible control of discharge energies. The results show that the spark plug gap size is a critical parameter to suppress the phenomena of short circuits and restrikes. With the enlargement of spark plug gap, the maximum and average lengths of the spark channel effectively increase.

In partially automated and conditionally automated vehicles, a part of the work of human drivers is replaced by the system, and the main source of safety risks is no longer system failures, but non-failure risks caused by insufficient system function design. The absence of unreasonable risk due to hazards resulting from functional insufficiencies of the intended functionality or by reasonably foreseeable misuse by persons, is referred to as the Safety Of The Intended Functionality. Drivers have the responsibility to supervise the automated driving system. When they don't agree with the operation behavior of the system, they will interfere with the instructions. However, this may lead to potential risks.

Injection pressure plays a vital role in spray break-up and atomization. High spray injection pressure is usually adopted to optimize the spray atomization in gasoline direct injection fuel system. However, higher injection pressure also leads to engine emission problem related to wall wetting. To solve this problem, researchers are trying to use flash boiling method to control the spray atomization process under lower injection test conditions. However, the effect of injection pressure on the spray atomization under flash boiling test condition has not been adequately investigated yet. In this study, quantitative study of internal flow and near nozzle spray breakup were carried out based on a two-dimensional transparent nozzle via microscopic imaging and phase Doppler interferometery. N-hexane was chosen as test fluid with different injection pressure conditions. Fuel temperature varied from 112°C to 148°C, which covered a wide range of superheated conditions.

Flash boiling spray has been proven to be a useful method in providing finer fuel droplet and stronger evaporation in favor of creating a homogeneous fuel-air mixture. Combustion characteristics of flash boiling spray are thus valuable to be investigated systematically for aiding the development of efficient internal combustion system. An experimental study of flash boiling spray combustion in a SIDI optical engine under early injection has been conducted. The fuel, Iso-octane, was used across all tests. Three fuel spray conditions experimented in the study: normal liquid, transitional flash boiling and flare flash boiling sprays, within each case that Pa/Ps ratio was set in (>1), (0.3~1), and (<0.3) respectively. A small quartz insert on the piston enables optical access for observing combustion process; non-intrusive measurements on flame radicals has been carried out using a high-speed color camera.

Owing to the stochastic nature of engine knock, determination of the knock limited spark angle (KLSA) is difficult in engine cycle simulation. Therefore, the state-of-the-art knock modeling is mostly limited to either merely predicting knock onset (i.e. auto-ignition of end gas) or combining a simple unburned mass fraction (UMF) model representative of knock intensity (KI). In this study, a newly developed KLSA model, which takes both predictions of knock onset and intensity into account, is firstly introduced. Multiple variables including the excess air ratio, EGR ratio, cylinder pressure and the end gas temperature are included in the knock onset model. Based on the auto-ignition theory of hot spots in end gas, both the energy density and heat release rate in hot spots are taken into consideration in the KI model.

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.

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.

Nozzle length has been proven influencing fuel spray characteristics, and subsequently fuel-air mixing and combustion processes. However, almost all existing related studies are conducted when fuel is subcooled, of which fuel evaporation is extremely weak, especially at the near nozzle region. In addition, injector tip can be heated to very high temperature in SIDI engines, which would trigger flash boiling fuel spray. Therefore, in this study, effect of nozzle length on spray characteristics is investigated under superheated conditions. Three single-hole injectors with different nozzle length were studied. High speed backlit imaging technique was applied to acquire magnified near nozzle spray images based on an optical accessible constant volume chamber. Fuel pressure was maintained at 15 MPa, and n-hexane was chosen as test fuel.

Electric vehicles (EVs) have become a hot research topic due to the petroleum crisis and air pollution issues, and Hybrid EVs (HEVs) equipped with engines and motors are popular nowadays due to their advantage over Pure EVs. The energy distribution between the engine and the motor is the major task of the control strategy or energy management for HEVs. Rule-based and optimization-based approaches are developed in this area, but not much work has been done for large-size super-capacitor (SC) equipped HEVs, like Hybrid buses. In this paper, a new optimization-based control strategy for a hybrid bus equipped with SCs as the energy regeneration system is presented. Considering the driving patterns of a bus that is of frequent accelerations and decelerations, it is proposed to characterize each time instant by its speed and acceleration, and the energy distribution is optimized based on these two state variables.

Rotating flow inside an internal combustion engine cylinder is deliberately engineered for improved fuel-air mixing and combustion. The details of the rotating flow structure vary temporally over an engine cycle as well as cyclically at the same engine phase. Algorithms in the literature to identify these structural details of the rotating flow invariably focus on locating its center and, on occasion, measuring its rotational strength and spatial extent. In this paper, these flow structure parameters are evaluated by means of complex moments, which have been adapted from image (scalar field) recognition applications to two-dimensional flow pattern (vector field) analysis. Several additional detailed characteristics of the rotating flow pattern - the type and extent of its deviation from the ideal circular pattern, its rotational and reflectional symmetry (if exists), and thus its orientation - are also shown to be related to the first few low-order complex moments of the flow pattern.