Search Results

The combustion of dual-fuel engines usually uses a pilot flame to burn out a background fuel inside a cylinder under high compression. The background fuel can be either a gaseous fuel or a volatile liquid fuel, commonly with low reactivity to prevent premature combustion and engine knocking; whereas the pilot flame is normally set off with the direct injection of a liquid fuel with adequate reactivity that is suitable for deterministic auto-ignition with a high compression ratio. In this work, directly injected butanol is used to generate the pilot flame, while intake port injected ethanol or butanol is employed as the background fuel. Compared with the conventional diesel-only combustion, dual-fuel operations not only broaden the fuel applicability, but also enhance the potential for clean combustion, in high efficiency engines. The amount of background fuel and the scheduling of pilot flame are investigated through extensive laboratory experiments.

This empirical work investigates the impacts of thermodynamic parameters, such as pressure and temperature, and fuel properties, such as fuel Cetane number and aromatic contents on ignition delay in diesel engines. Systematic tests are conducted on a single-cylinder research engine to evaluate the ignition delay changes due to the fuel property differences at low, medium and high engine loads under different EGR dilution ratios. The test fuels offer a range of Cetane numbers from 28 to 54.2 and aromatic contents volume ratios from 19.4% to 46.6%. The experimental results of ignition delays are used to derive an ignition delay model modified from Arrhenius’ expression. Following the same format of Arrhenius’ equation, the model incorporates the pressure and temperature effects, and further includes the impacts of intake oxygen concentration, fuel Cetane number and aromatic contents volume ratio on the ignition delay.

In recent years, with the increase of traffic accidents and traffic jams, lane change, as one of the most important and commonly automatic driving operations for autonomous vehicles, is receiving attention in academia. It is considered to be one of the important solutions that play an important role in improving road traffic safety and efficiency. However, most existing lane-changing models are rule-based lane-changing models. These models only assume a one-direction impact of surrounding vehicles on the lane-changing vehicle. In fact, lane change is a process of mutual interaction between vehicles due to the complexity and uncertainty of the traffic environment. Moreover, the safety and efficiency of existing lane-changing decision algorithms need to be improved. In this paper, we proposed a multivehicle cooperative control approach with a distributed control structure to control the model.

Percussive riveting is a widely used way of fastening in the field of aircraft assembly, which used to be done manually. Nowadays, replacing the traditional percussive riveting with automated percussive riveting becomes a trend worldwide, which improves the quality of riveting significantly. For the automated riveting system used in aircraft assembly, reliability is of great importance, deserving to be deeply researched and fully enhanced. In this paper, a high reliable automated percussive riveting system integrated into a dual robot drilling and riveting system is proposed. The riveting system consists of the hammer part and the bucking bar part. And both parts have been optimized to enhance the reliability. In the hammer side, proximity switches are fully used to detect the state of rivet insertion.

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.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

The prediction of agents' future trajectory is a crucial task in supporting advanced driver-assistance systems (ADAS) and plays a vital role in ensuring safe decisions for autonomous driving (AD). Currently, prevailing trajectory prediction methods heavily rely on high-definition maps (HD maps) as a source of prior knowledge. While HD maps enhance the accuracy of trajectory prediction by providing information about the surrounding environment, their widespread use is limited due to their high cost and legal restrictions. Furthermore, due to object occlusion, limited field of view, and other factors, the historical trajectory of the target agent is often incomplete This limitation significantly reduces the accuracy of trajectory prediction. Therefore, this paper proposes ETSA-Pred, a mapless trajectory prediction model that incorporates enhanced temporal modeling and spatial self-attention.

Precise trajectory prediction of surrounding vehicles is critical for decision-making of autonomous vehicles, and learning-based approaches are well recognized for the robustness. However, state-of-the-art learning-based methods ignore (1) the feasibility of the vehicle’s multimodal state information for prediction and (2) the mutually exclusive relationship between the global traffic scene receptive fields and the local position resolution when modeling vehicles’ interactions, which may influence prediction accuracy. Therefore, we propose a “vehicle descriptor”-based long short-term memory (LSTM) model with the dilated convolutional social pooling (VD+DCS-LSTM) to cope with the above issues.

The development of a collision severity model can serve as an important tool in understanding the requirements for devising countermeasures to improve occupant safety and traffic safety. Collision type, weather conditions, and driver intoxication are some of the factors that may influence motor vehicle collisions. The objective of this study is to use artificial neural networks (ANNs) to identify the major determinants or contributors to fatal collisions based on various driver, vehicle, and environment characteristics obtained from collision data from Transport Canada. The developed model will have the capability to predict similar collision outcomes based on the variables analyzed in this study. A multilayer perceptron (MLP) neural network model with feed-forward back-propagation architecture is used to develop a generalized model for predicting collision severity. The model output, collision severity, is divided into three categories - fatal, injury, and property damage only.

Accurate and fast positioning of large aircraft component is of great importance for Automated Alignment System. The Ball joint is a widely-used mechanical device connecting the aircraft component and positioners. However, there are some shortcomings for the device in man-machine engineering, such as the entry state of the ball-head still needs to be confirmed by the workers and then switched to the locking state manually. To solve above problems, a new positioning mechanism is present in this paper, which consists of a ball-head and a ball-socket. The new device is equipped with a monocular vision system, in which a calibrated industrial camera is used to collect the images of the ball-head. And then, the 3-D coordinate of the ball-head center is calculated by a designed algorithm, guiding the positioner to capture the ball-head. Once the ball-head gets into the ball-socket, the pneumatic system will drive the pistons to move to the specified location.

Due to high torque and power density, permanent magnet synchronous motor (PMSM) has become the most viable candidate for electric vehicle (EV) traction application. However, to obtain such high torque and power density within a compact motor structure can cause a significant temperature rise within the motor while operating. As a result of high temperature rise, permanent magnet demagnetization may even occur within the motor. Thus, PMSM is susceptible to thermal instability. Therefore, to ensure thermal stability during varying operating conditions, thermal analysis is a mandatory procedure in addition to electromagnetic analysis during the design phase of the motor. In this paper, a computationally efficient numerical finite element analysis (FEA) process has been proposed for thermal analysis of PMSM.

Sound quality of vehicle interior noise affects passenger comfort. In order to improve the sound quality of a micro commercial vehicle, the vehicle interior noise under different conditions such as idle, constant speeds and accelerating is recorded by using artificial head with dual microphones. The sound quality of recorded noise is evaluated in both objective and subjective ways. Physical parameters of interior noise are calculated objectively, and annoyance score is analyzed subjectively using paired-comparison method. According to the regression analyzing of the annoyance score and the physical parameters, an objective evaluation parameter of the sound quality is employed. To analyze the vehicle body panel contribution to interior noise sound quality, the location and spectrum characteristics of major panel emission noise sources are identified based on partial singular valued decomposition (PSVD) method.

A semi-empirical turbulent flame growth model has been developed based on thermodynamic equilibrium calculations and experiments in a 125-mm cubical combustion chamber. It covers the main flame growth period from spark kernel formation until flame wall contact, including the effects of laminar flame speed, root mean square turbulence intensity, turbulent eddy size, and flame size. As expected, the combustion rate increases with increasing laminar flame speed and/or turbulence intensity. The effect of turbulent eddy scale is less obvious. For a given turbulence intensity, smaller scales produce higher instantaneous flame speed. However, turbulence of a smaller scale also decays more rapidly. Thus, for a given laminar flame speed and turbulence intensity at the time of ignition, there is an optimum turbulent eddy size which leads to the fastest combustion rate over the period considered.

The ever-growing demand to meet the stringent exhaust emission regulations have driven the development of modern gasoline engines towards lean combustion strategies and downsizing to achieve the reduction of exhaust emission and fuel consumption. Currently, the inductive ignition system is still the dominant ignition system applied in Spark Ignited (SI) engines. It is popular due to its simple design, low cost and robust performance. The new development in spark ignition engines demands higher spark energy to be delivered by the inductive ignition system to overcome the unfavorable ignition conditions caused by the increased and diluted in-cylinder charge. To meet this challenge, better understanding of the inductive ignition system is required. The development of a first principle model for simulation can help in understanding the working mechanism of the system in a better way.

Advanced combustion engines, as power sources, dominate all aspects of the transportation sector. Stringent emission and fuel efficiency standards have promoted the research interest in advanced combustion strategies and alternative fuels. Owing to the comparable energy density to the existing fossil fuels and renewable production, alcohol and ether fuels may be a suitable replacement, or an additive to the gasoline/diesel fuels to meet the future emission standards with minimal modification to current engine geometry. Furthermore, lean and diluted combustion are well-researched pathways for efficiency improvement and reduction of engine-out emissions of modern engines. However, lean-burn or EGR dilution can introduce combustion inefficiencies in the form of excessive hydrocarbon, carbonyl species and carbon monoxide emissions.

Multi-spark discharge (MSD) ignition is widely used in high-speed internal combustion engines such as racing cars, motorcycles and outboard motors in attempts to achieve multiple sparks during each ignition. In contrast to transistor coil ignition (TCI) system, MSD system can be greatly shortened the charging time in a very short time. However, when the engine speed becomes higher, the ignition will be faster, electrical energy stored in the ignition system will certainly become less, especially for MSD system. Once the energy released into the spark plug gap can’t be guaranteed sufficiently, ignition will become more difficult, and it will get worse in some harsh environment such as strong turbulence or lean fuel conditions. With these circumstances, the risks of misfire and partial combustion will increase, which can deteriorate the power outputs and exhaust emissions of internal combustion engine.

Diesel fueling and exhaust flow strategies are investigated to control the substrate temperatures of diesel aftertreatment systems. The fueling control includes the common-rail post injection and the external supplemental fuel injection. The post injection pulses are further specified at the early, mid, or late stages of the engine expansion stroke. In comparison, the external fueling rates are moderated under various engine loads to evaluate the thermal impact. Additionally, the active-flow control schemes are implemented to improve the overall energy efficiency of the system. In parallel with the empirical work, the dynamic temperature characteristics of the exhaust system are simulated one-dimensionally with in-house and external codes. The dynamic thermal control, measurement, and modeling of this research intend to improve the performance of diesel particulate filters and diesel NOx absorbers.

This study describes a zero-dimensional algorithm for tracking the intake dilution in real-time. The inputs to the model are the oxygen concentration from the exhaust oxygen sensor, the manifold air pressure and temperature (MAP/MAT), the mass air flow (MAF) and the estimated fuel injected per cycle from the engine control module. The intake manifold, the exhaust manifold and EGR system are discretized into 3 volumes and the detailed concentrations of the gas species comprising the exhaust, EGR and intake streams are tracked at each time step (on a cycle-by-cycle basis). The model does not need the EGR ratio to be known in advance and is also applicable to oxygenated fuels such as ethanol. The model response is tuned to a multi-cylinder engine and the model output is empirically validated against a wide range of engine operations including load and EGR transients.

A vehicle undergoing longitudinal or lateral accelerations experiences load transfer, dynamically changing the normal load carried by each tire. Conventional braking systems are designed only to work adequately over a large range of conditions, but often ignore the dynamic state of the tire's normal load. Fortunately, new developments in braking system hardware give designers more control over the application of braking pressures. By identifying the tires that carry increased normal load, and biasing the braking system toward those tires, total braking force can be increased. The purpose of this research is to investigate advantages of open-loop load transfer based active brake pressure distribution. By estimating the tractive ability of the tires as a function of measurable vehicle conditions, brake pressure can be applied in proportions appropriate for the current dynamic state of the vehicle, referred to as Active Brake Proportioning (ABP).

In this study the capabilities of a semi-active suspension and an active roll suspension are evaluated for comparison with a passive suspension. The vehicle used is a utility truck modeled as a multi-body system in ADAMS/Car while the ECU (electronic control unit) is built in Matlab/Simulink. Cosimulation is used in linking the vehicle model with the controller by exchanging the input and output values of each sub-system with one another. For the simulation models considered, results indicate that for a fish-hook cornering maneuver the semi-active suspension is limited in increasing vehicle performance while the active roll suspension significantly improves it. Further analysis is needed to confirm these findings.