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A three-dimensional simulation was carried out for investigating effects of negative valve overlap (NVO) on gas exchange and fuel-air mixing processes in a diesel homogeneous charge compression ignition (HCCI) engine with early fuel injection. It was found that the case with longer NVO produced a stronger swirl motion and a more significant vortex below the intake valve due to the high annular jet flow through the valve curtain area during the intake stroke. However, there was not much difference in the values of swirl ratio, tumble ratio and turbulence intensity between different NVOs at the end of compression stroke. It was also seen that enlarged NVO not just increased in-cylinder temperature but also improved the temperature homogeneity. With increased NVO, there is a bigger spray shape and more droplets exist in gaps of sprays. This demonstrates that stronger turbulence intensity and higher temperature homogeneity with higher NVO improve fuel vaporization and air-fuel mixing.

Generally, noise will occur during steering with the hydraulic power steering system (hereinafter HPS). The noise producing in the rotary valve takes up a big proportion of the total one. To study the noise in the control valve, 2-D meshes of the flow field between the sleeve and the rotor were set up and a general CFD code-Fluent was used to analyze the flow inside the valve. The areas where the noise may be occurred were shown and some suggestions to silence the noise were given.

The fracture of the retainer leads to the failure of the needle rolling bearings in a planetary gear train of a planetary gearbox. In order to solve this engineering problem, the kinematics and kinetics of the failed needle rolling bearings is analyzed with the analytical model and the numerical model. A simple mathematical model is pointed out to analyze the dynamic load of a needle rolling element in the failed bearings. The assembling position of the small sun gear is also found to influence the performance of the needle rolling bearings significantly and therefore a best scheme for modifying the structure of the planetary gearbox is pointed out based on the multi-object optimization theory to reduce the bearing load heavily. Based on the calculated work, a systematic method of choosing the proper bearings for planetary gearbox can be concluded.

Hydraulic system is very important for the performance of AT. The dynamic characteristics of automatic transmission hydraulic system are studied in this paper. Because the valves in the hydraulic system are not standard parts, ITI-SimulationX, the multi-domain physics simulation software from ITI GmbH, is used to build the dynamic model of the hydraulic system based on the basic elements in the library of SimulationX. And then the dynamic characteristics of the system are simulated. The simulation results and the test results from the test bench are compared to confirm the simulation model. The results show that the simulation model can couple with the real system very well and the simulation model can be confirmed. Based on the confirmed simulation model, the effects of different parameters of the hydraulic system on the characteristics of the system are analyzed.

High-speed rotating gears are generally lubricated by spray lubrication. Lubricating oil is driven by high-speed rotating gear, and some lubricating oil will be excited into oil mist, so that the gears are in the gas-liquid mixed environment. In this paper, the computational fluid dynamics model of the spray lubrication cooling process is established based on the gear heat transfer behavior under the spray lubrication condition. The influence of different spray parameters on the liquid-solid two-phase convective heat transfer coefficient is obtained. On this basis, the accurate boundary conditions of gear temperature field calculation are analyzed by studying the heat transfer behavior of high speed gear spray lubrication. The calculation model of gear temperature based on spray lubrication is established, and the temperature field distribution of gear is obtained.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

The development of intelligent and networked vehicles has enhanced the demand for precise road information perception. Detailed and accurate road surface information is essential to intelligent driving decisions and annotation of road surface semantics in high-precision maps. As one of the key parameters of road information, road roughness significantly impacts vehicle driving safety and comfort for passengers. To reach a rapid and accurate estimation of road roughness, in this study, we develop a neural network model based on vehicle response data by optimizing a long-short term memory (LSTM) network through the particle swarm algorithm (PSO), which fits non-linear systems and predicts the output of time series data such as road roughness precisely. We establish a feature dataset based on the vehicle response time domain data that can be easily obtained, such as the vehicle wheel center acceleration and pitch rate.

The limitation of drivers' attention and perception may bring collision dangers, Autonomous Emergency Braking (AEB) can help drivers to avoid the potential collisions through active braking. Since the positive effect of it, motor corporations have begun to equip their vehicles with the system, and regulatory agencies in various countries have introduced test standards. At this stage, the actuator of AEB usually adopts Electronic Stability Program (ESP), but it poor performance of continuous working period and active pressure built-up for all wheels limits its implements. Electromechanical brake booster can realize power assisted brake without relying on the vacuum source and a variety of specific power curves. Moreover it can achieve the active braking with a rapid response, which make it can fulfill requirements of automotive electric and intelligent development.

Traffic light detection has great significant for unmanned vehicle and driver assistance system. Meanwhile many detection algorithms have been proposed in recent years. However, traffic light detection still cannot achieve a desirable result under complicated illumination, bad weather condition and complex road environment. Besides, it is difficult to detect multi-scale traffic lights by embedded devices simultaneously, especially the tiny ones. To solve these problems, this paper presents a robust vision-based method to detect traffic light, the method contains main two stages: the region proposal stage and the traffic light recognition stage. On region proposal stage, we utilize lane detection to remove partial background from the original image. Then, we apply adaptive canny edge detection to highlight region proposal in Cr color channel, where red or green color proposals can be separated easily. Finally, extract the enlarged traffic light RoI (Region of Interest) to classify.

Ice protection is important for aero-engine induction system, such as the inlet vanes. For the ice protection of such parts manufactured with low thermal conductivity polymer-based composite material, the combined heating method using interior jet impingement and exterior ejection film has certain advantages. The simulation model coupling CFD with solid heat conduction was developed and solved with the anisotropic thermal conductivities model to investigate the heat transfer enhancement in the stagnation region of aero-engine inlet vanes due to ejection slot and anisotropic heat conduction, which is related to the curved geometry, ejection slots and anisotropic heat conduction. The temperature distribution and heat flux ratio between the stagnation region on outside surface and the impingement region inside were calculated and analyzed for the configuration with different ejection angle and different materials.

The main objective of this work is to investigate, by means of numerical simulations, the performance of the engine nacelle ventilation cooling system of a helicopter under hover and forward flight conditions, and to propose a simplified method of evaluating the performance based on rotor downwash flow by taking the synthetical effect of engine nacelle, exhaust ejector and external flow of a helicopter into account. For the engine nacelle of a helicopter, an integrated model of the nacelle and exhaust ejector was set up including the domain of external flow. The unstructured grid and finite volume method were applied for domains and control equations discreteness, and the standard k-ε model was applied for solving turbulent control equations. Using the business CFD software, the flow field and the temperature field in the nacelle were calculated for single inlet scheme and double inlets scheme, total up to 9 schemes. The performance of the exhaust ejector was computed.

Due to the lack of masking effect from the engine, noise and vibration from the drivetrain system have become a critical issue in electric vehicles. To address this problem, this study aims at proposing a comprehensive optimization method with respect to multiple internal excitation sources to reduce the noise and vibration of the electric drivetrain system (EDS). A rigid-flexible coupling dynamic (RFCD) model is first proposed by incorporating the elements of electric motors, gear pairs, bearings, shafts, and housing. Based on the proposed model, optimizations concerning multiple internal excitations are carried out by designing the notch width of the stator core and optimizing the modification parameters of the tooth surface along the flank and lead direction. Meanwhile, multiple operating conditions are considered in the optimization of the tooth surface to cover a complete working condition of the EDS.

When automobiles are at the threat of collisions, steering usually needs shorter longitudinal distance than braking for collision avoidance, especially under the condition of high speed or low adhesion. Thus, more collision accidents can be avoided in the same situation. The steering assistance is in need since the operation is hard for drivers. And considering the dynamic characteristics of vehicles in those maneuvers, the real-time and the accuracy of the assisted algorithms is essential. In view of the above problems, this paper first takes lateral acceleration of the vehicle as the constraint, aiming at the collision avoidance situation of the straight lane and the stable driving inside the curve, and trajectory of the collision avoidance is derived by a quintic polynomial.

Recognizing road conditions using onboard sensors is significant for the performance of intelligent vehicles, and the road profile is a widely accepted representation both in the temporal and frequency domains, greatly influencing driving quality. In this paper, a recurrent neural network embedded with attention mechanisms is proposed to reconstruct the road profile sequence. Firstly, the road and vehicle sensor signals are obtained in a simulated environment by modeling the road, tire, and vehicle dynamic system. After that, the models under different working conditions are trained and tested using the collected data, and the attention weights of the trained model are then visualized to optimize the input channels. Finally, field experiments on the real vehicle are conducted to collect real road profile data, combined with vehicle system simulation, to verify the performance of the proposed method.