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The tripod constant velocity joint (CVJ) has been widely used in mechanical systems due to its strong load-bearing capacity, high efficiency, and reliability. It has become the most commonly used plunging-type CVJ in automotive drive-shaft. A generated axial force (GAF) with a third-order characteristic of driven shaft speed is caused by the internal friction and motion characteristics in a tripod joint. The large GAF has a negative impact on the NVH (Noise, Vibration, and Harshness) characteristics of automobiles, and this issue is particularly prominent in new energy vehicles. A multi-body dynamic model of the Adjustable Angular Roller (AAR) tripod CVJ is developed to calculate and analyze the GAF. To describe the internal motion of the AAR tripod CVJ, the contact interactions between the roller and the track or the trunnion were modeled using non-linear equivalent spring-damping models for contact collision forces and modified Coulomb friction model for friction.

Nowadays, the rapid growth of civil aviation transportation demand has led to more frequent flight delays. The major problem of flight delays is restricting the development of municipal airports. To further improve passenger satisfaction, and reduce economic losses caused by flight delays, environmental pollution and many other adverse consequences, three machine learning algorithms are constructed in current study: random forest (RF), gradient boosting decision tree (GBDT) and BP neural network (BPNN). The departure flight delay prediction model uses the actual data set of domestic flights in the United States to simulate and verify the performance and accuracy of the three models. This model combines the visual analysis system to show the density of departure flight delays between different airports. Firstly, the data set is reprocessed, and the main factors leading to flight delays are selected as sample attributes by principal component analysis.

Transporting baggage is critical in airport ground support services to ensure smooth flight operations. However, the scheduling of baggage transport vehicles faces challenges related to low efficiency and high costs. A multi-objective optimization vehicle scheduling model is proposed to address these issues, considering time and space costs, vehicle utilization, and passenger waiting time. An improved genetic algorithm (IGA) based on the large-scale neighborhood search algorithm is proposed to solve this model. The simulation experiment is conducted using actual flight data from an international airport. The IGA algorithm is compared with the standard genetic algorithm (SGA) based on experimental results, revealing that the former achieves convergence in a significantly shorter time. Moreover, the scheduling paths of baggage cars that violate flight service time window requirements are significantly lower in the final scheduling scheme under the IGA algorithm than in SGA.

Accurate sensing of road conditions is one of the necessary technologies for safe driving of intelligent vehicles. Compared with the structured road, the unstructured road has complex road conditions, and the response characteristics of vehicles under different road conditions are also different. Therefore, accurately identifying the road categories in front of the vehicle in advance can effectively help the intelligent vehicle timely adjust relevant control strategies for different road conditions and improve the driving comfort and safety of the vehicle. However, traditional road identification methods based on vehicle kinematics or dynamics are difficult to accurately identify the road conditions ahead of the vehicle in advance. Therefore, this paper proposes an unstructured road region detection and road classification algorithm based on machine vision to obtain the road conditions ahead.

Hybrid powertrain has been proven to be an effective fuel-saving technology in commercial vehicles, but many hybrid commercial vehicles still use conventional diesel engines, resulting in limited fuel savings. The main purpose of this study is to enhance the thermal efficiency of a dedicated hybrid diesel engine focusing on the characteristic operating conditions. Via fundamental thermodynamics process analysis of internal combustion engine, steel piston with high compression ratio, air system involving two-stage turbocharger(2TC) with an intercooler, and late intake valve closing(IVC) timing are proposed to improve the thermal efficiency of the engine. Experimental results show that high compression ratio and lower thermal conductivity of the combustion chamber surface lead to lower heat release rates, requiring optimization of piston profile to accelerate the mixing rate. Besides, high compression ratio also leads to higher mechanical losses.

High-speed vehicle is prone to instability under bad road conditions, causing many safety accidents such as tail-flicking and overturning. Stability control could assist vehicle to drive safely and stably by adjusting the additional yaw moment. However, most of the existing stability control strategies directly invoke the information of the sideslip angle of the centroid that is difficult to obtain on the vehicle, and carry out complex controller design, which deviates from the actual application. In order to achieve a complete set of stability control architecture oriented to practical applications, this paper designs a hierarchical vehicle stability control strategy based on differential braking and state estimation technology.

Pumping Mean Effective Pressure (PMEP) is the main factor limiting the improvement of thermal efficiency in a spark-ignition (SI) engine under low load. One of the ways to reduce the pumping loss under low load is to use Cylinder DeActivation (CDA). The CDA aims at reducing the firing density (FD) of the SI engine under low load operation and increasing the mass of air-fuel mixture within one cycle in one cylinder to reduce the throttling effect and further reducing the PMEP. The multi-stroke cycles can also reduce the firing density of the SI engine after some certain reasonable design, which is feasible to improve the thermal efficiency of the engine under low load in theory. The research was carried out on a calibrated four-cylinder SI engine simulation platform. The thermal efficiency improvements of the 6-stroke cycle and 8-stroke cycle to the engine performance were studied compared with the traditional 4-stroke cycle under low load conditions.

Bio-derived butanol is a potential CO2 neutral alternative fuel to be applied in internal combustion engines. However, the physical and combustion characteristics have to be fully understood before it can be used efficiently in engines. This work investigates the viscosity and the combustion characteristics of n-butanol/diesel fuel blends, with a particular focus on the combustion property at low load performance. N-butanol was mixed with diesel from 20 vol% up to 80 vol% blend ratio. Tests were performed in a combustion research unit (constant volume) at fixed chamber pressure that mimic a low load condition. The effects of various chamber temperatures and ambient oxygen concentrations (21%, 13%, and 11%) are evaluated. As expected, the viscosity of n-butanol/diesel fuel blends decreases at high temperature. The decrease is non-linear with the blend ratio.

In order to study the problem of short-term traffic prediction more effectively, experts and scholars have put forward various car-following models. Among data-driven algorithms, k-nearest neighbor algorithm is the most widely used due to its simplicity, flexibility and high accuracy. In this paper, the three-dimensional model based on improved knn algorithm is constructed. It transforms the input vector of basic knn algorithm into a three-row matrix. Data of three dimensions are considered, including only the previous moment data, short period of history data and long period of history data. Three-dimensional matrixes are constructed for prediction and similarity is measured by sum of 2-norm of 3 row vectors. Besides, weighted distance calculation method based on temporal distance is introduced to differentiate impacts data of different dimensions have on the results.

In Intelligent and Connected Transportation Systems (ICTS), vehicles, infrastructure, pedestrians exchange information through two-way telecommunication network. The system collects and uses multi-source data sufficiently so that control measures can be implemented in real-time. However, few studies have discussed how to achieve fairness based on dynamic priority. In this paper, the Platoon Dynamic Dispatching Model (PDDM), based on Vehicle-Intersection Coordination Scheme (VICS), is proposed to control vehicles. The first stage establishes the trajectory model and defines the conflict zones at the intersection. Platoons forms at the upstream, then the conflict risk indicator model is applied to predict the collision risk of the platoons. The dynamic priority dispatching model is applied to change the passing order of platoons at an intersection from all directions in real-time according to their status at the upstream. Finally, PDDM is solved by the wolf pack algorithm.

This work numerically investigates the detailed combustion kinetics of partially premixed combustion (PPC) in a diesel engine under three different premixed ratio fuel conditions. A reduced Primary Reference Fuel (PRF) chemical kinetics mechanism was coupled with CONVERGE-SAGE CFD model to predict PPC combustion under various operating conditions. The experimental results showed that the increase of premixed ratio (PR) fuel resulted in advanced combustion phasing. To provide insight into the effects of PR on ignition delay time and key reaction pathways, a post-process tool was used. The ignition delay time is related to the formation of hydroxyl (OH). Thus, the validated Converge CFD code with the PRF chemistry and the post-process tool was applied to investigate how PR change the formation of OH during the low-to high-temperature reaction transition. The reaction pathway analyses of the formations of OH before ignition time were investigated.

OH, soot and temperature distributions of wall-impinging diesel fuel spray were investigated in a high-temperature high-pressure constant volume combustion vessel. The ambient temperature (Ta) was set as 773 K, and the wall temperature (Tw) was set as 523 K, 673 K, 773 K, respectively. Three different injection pressures (Pi) of 60 MPa, 100 MPa, 160 MPa, and the ambient pressures (Pa) of 4 MPa were applied. The OH spatial distributions of wall-impinging spray were measured by the method of OH chemiluminescence imaging. Two-color pyrometry was applied to evaluate the spatial distributions of KL factor and flame temperature of wall-impinging spray. The results reveal that, OH chemiluminescence is observed in the region near the impingement point firstly. The regions of high OH chemiluminescence intensity and high KL factor appear in the location near the wall surface along the whole combustion process.

In order to improve the electric vehicle endurance mileage and output characteristics of motor, the optimization of inverter loss and motor current ripple reduction are considered. Aiming at high inverter loss of traditional SVPWM and high current ripple of DPWM, an adjustable discontinuous pulse width modulation(ADPWM) is proposed, whose clamping angle α and clamping phase angle θ are variable. In order to accurately calculate the inverter loss, a switching instantaneous inverter loss model is proposed, and the ADPWM inverter loss and current total harmonic distortion(THD) was studied based on Simulink modeling and simulation. The simulation and experiment results show that the experiment can be accurately reflected by Simulink model; The inverter loss can be reduced by 15%-25% by introducing ADPWM while the current distortion rate is low. With the clamping angle α increasing, the inverter loss decreased significantly.

Liquefied natural gas (LNG) engine could provide both reduced operating cost and reduction of greenhouse gas (GHG) emissions. Stoichiometric operation with EGR and the three-way catalyst has become a potential approach for commercial LNG engines to meet the Euro VI emissions legislation. In the current study, numerical investigations on the knocking tendency of several combustion chambers with different geometries and corresponding performances were conducted using CONVERGE CFD code with G-equation flame propagation model coupled with a reduced natural gas chemical kinetic mechanism. The results showed that the CFD modeling approach could predict the knock phenomenon in LNG engines reasonably well under different thermodynamic and flow field conditions.

The application of oxygen-enriched or oxy-fuel combustion coupled with carbon capture and storage technology has zero carbon dioxide emission potential in the boiler and gas turbine of the power plant. However, the oxygen-enriched combustion with high oxygen level has few studies in internal combustion engines. The fundamental issues and challenges of high oxygen level are the great differences in the physical properties and chemical effects compared with the combustion in air condition. As a consequence, the diesel spray combustion characteristics at high oxygen level were investigated in an optical constant volume vessel. The oxygen volume fraction of tested gas was from 21% to 70%, buffered with argon. The high-speed color camera was used to record the natural flame luminosity.

In order to achieve high-efficiency and clean combustion in HCCI engines, combustion must be controlled reasonably. A great variety of species with various reactivities can be produced through low temperature oxidation of fuels, which offers possible solutions to the problem of controlling in-cylinder mixture reactivity to accommodate changes in the operating conditions. In this work, in-cylinder combustion characteristics with low temperature reforming (LTR) were investigated in an optical engine fueled with low octane number fuel. LTR was achieved through low temperature oxidation of fuels in a reformer (flow reactor), and then LTR products (oxidation products) were fed into the engine to alter the charge reactivity. Primary Reference Fuels (blended fuel of n-heptane and iso-octane, PRFs) are often used to investigate the effects of octane number on combustion characteristics in engines.

Gasoline partially premixed combustion shows the potential to achieve clean and high-efficiency combustion. Injection strategies show great influence on in-cylinder air flow and in-cylinder fuel distribution before auto-ignition, which can significantly affect the combustion characteristics and emissions. This study explored the effects of various injection strategies, including port fuel injection (PFI), single direct injection (DIm), double direct injection (DIp+DIm) and port fuel injection coupled with a direct injection (PFI+DIm) on the combustion characteristics and emissions in a modified single cylinder heavy-duty diesel engine fueled with 92# gasoline at low load. The investigation consists of two parts. Firstly, the comparison among PFI, PFI+DIm, and DIp+DIm strategies was conducted at a fixed CA50 to explore the effects of PFI+DIm and DIp+DIm strategies on the thermal efficiency and combustion stability.

The flame structure and combustion characteristics of wall-impinging diesel fuel spray were investigated in a high-temperature high-pressure constant volume combustion vessel. The ambient temperature (Ta) was set to 773 K. The wall temperatures (Tw) were set to 523 K, 673 K and 773 K respectively. Three different injection pressures (Pi) of 600 bar, 1000bar and 1600bar, two ambient pressures (Pa) of 2 MPa and 4 MPa were applied. The flame development process of wall-impinging spray was measured by high-speed photography, which was utilized to quantify the flame luminosity intensity, ignition delay and flame geometrical parameters. The results reveal that, as the wall temperature increases, the flame luminosity intensity increases and the ignition delay decreases.

The dual-fuel Reactivity Controlled Compression Ignition (RCCI) combustion could achieve high efficiency and low emissions over a wide range of operating conditions. However, further high load extension is limited by the excessive pressure rise rate and soot emission. Polyoxymethylene dimethyl ethers (PODE), a novel diesel alternative fuel, has the capability to achieve stoichiometric smoke-free RCCI combustion due to its high oxygen content and unique molecule structure. In this study, experimental investigations on high load extension of gasoline/PODE RCCI operation were conducted using late intake valve closing (LIVC) strategy and intake boosting in a single-cylinder, heavy-duty diesel engine. The experimental results show that the upper load can be effectively extended through boosting and LIVC with gasoline/PODE stoichiometric operation.

In this work the gasoline compression ignition (GCI) combustion characterized by both premixed gasoline port injection and gasoline direct injection in a single-cylinder diesel engine was investigated experimentally and computationally. In the experiment, the premixed ratio (PR), injection timing and exhaust gas recirculation (EGR) rate were varied with the pressure rise rate below 10 bar/crank angle. The experimental results showed that higher PR and earlier injection timing resulted in advanced combustion phasing and improved thermal efficiency, while the pressure rise rates and NOx emissions increased. Besides, a lowest ISFC of 176 g/kWh (corresponding to IMEP =7.24 bar) was obtained, and the soot emissions could be controlled below 0.6 FSN. Despite that NOx emission was effectively reduced with the increase of EGR, HC and CO emissions were high. However, it showed that GCI combustion of this work was sensitive to EGR, which may restrict its future practical application.