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The current automotive industry has a growing demand for real-time transmission to support reliable communication and for key technologies. The Time-Sensitive Networking (TSN) working group introduced standards for reliable communication in time-critical systems, including shaping mechanisms for bounded transmission latency. Among these shaping mechanisms, Cyclic Queuing and Forwarding (CQF) and frame preemption provide deterministic guarantees for frame transmission. However, despite some current studies on the performance analysis of CQF and frame preemption, they also need to consider the potential effects of their combined usage on frame transmission. Furthermore, there is a need for more research that addresses the impact of parameter configuration on frame transmission under different situations and shaping mechanisms, especially in the case of mechanism combination.

The noise tests of electric motor systems serve as the foundation for studying their acoustic issues. However, there is currently a lack of corresponding method for identifying key noise characteristics, such as the noise frequency range that needs to be considered, the significant noise order, and the resonance band worth paying attention to, based on experimental test data under actual operating conditions. This article proposes a method for identifying the noise characteristics of an electric motor system based on tests conducted under distinct operating conditions, which consists of three parts: identifying the primary frequency range, the significant order, and the important resonance band. Firstly, in order to extract noise with the primary energy, the concept of noise contribution is introduced. The primary frequency range and the significant order under a specific operating condition can be obtained after extraction.

In the process of automobile industrialization, integrated electric drive systems turn to be the mainstream transmission system of electric vehicles gradually. The main sources of noise and vibration in the chassis are from the gear reducer and motor system, as a replacement of engine. For improving the electric vehicles NVH performance, effective identification and quantitative analysis of the main noise sources are a significant basis. Based on the rotating hub test platform in the semi-anechoic chamber, in this experiment, an electric vehicle equipped with a three-in-one electric drive system is taken as the research object. As well the noise and vibration signals in the interior vehicle and the near field of the electric drive system are collected under the operating conditions of uniform speed, acceleration speed, and coasting with gears under different loads, and the test results are processed and analyzed by using the spectral analysis and order analysis theories.

In recent years, with the development of computing infrastructure and methods, the potential of numerical methods to reasonably predict aerodynamic noise in turbocharger compressors of heavy-duty diesel engines has increased. However, aerodynamic acoustic modeling of complex geometries and flow systems is currently immature, mainly due to the greater challenges in accurately characterizing turbulent viscous flows. Therefore, recent advances in aerodynamic noise calculations for automotive turbocharger compressors were reviewed and a quantitative study of the effects for turbulence models (Shear-Stress Transport (SST) and Detached Eddy Simulation (DES)) and time-steps (2° and 4°) in numerical simulations on the performance and acoustic prediction of a compressor under various conditions were investigated.

A DMS500 engine exhaust particle size spectrometer was employed to characterize the effects of injection strategies on particulate emissions from a turbocharged gasoline direct injection (GDI) engine. The effects of operating parameters (injection pressure, secondary injection ratio and secondary injection end time) on particle diameter distribution and particle number density of emission were investigated. The experimental result indicates that the split injection can suppress the knocking tendency at higher engine loads. The combustion is improved, and the fuel consumption is significantly reduced, avoiding the increase in fuel pump energy consumption caused by the 50 MPa fuel injection system, but the delayed injection increases particulate matter emissions.

Lightweight design is a key factor in general engineering design practice, however, it often conflicts with fatigue durability. This paper presents a way for improving the effectiveness of fatigue performance dominated optimization, demonstrated through a case study on suspension brackets for heavy-duty vehicles. This case study is based on random load data collected from fatigue durability tests in proving grounds, and fatigue failures of the heavy-duty vehicle suspension brackets were observed and recorded during the tests. Multi-objective fatigue optimization was introduced by employing multiaxial time-domain fatigue analysis under random loads combined with the non-dominated sorting genetic algorithm II with archives.

Accurate prediction temperature variation of electric drive transmission (EDT) can effectively monitor its abnormal temperature rise that may occur under high speed and heavy load working conditions, so as to ensure the vehicles’ safe operation. In this paper, combined with real temperature and input/output characteristic data collected from EDT test platform under different working conditions, a spatio-temporal relationship dynamic graph convolution neural network based on least square method (OLS-DRGCN) for temperature prediction is proposed. Firstly, OLS is used to estimate the EDT’s internal temperature based on partial sensor information as the input of OLS-DRGCN. Secondly, the spatial dependence relationship of each temperature node is dynamically learned through node embedding and the dynamic thermal network topology of EDT is constructed. Meanwhile, the timing rule of each temperature node is obtained through the gated recurrent unit.

Both ammonia and hydrogen, as zero-carbon fuels for internal combustion engines, are received growing attention. However, ammonia faces a challenge of low flame propagation velocity. Through injecting hydrogen into active pre-chamber, its jet flame ignition can accelerate the flame propagation velocity of ammonia. The influence of different pre-chamber structures on engine combustion characteristics is significant. In this paper, numerical studies were conducted to assess the impact of various pre-chamber structures and hydrogen injection strategy on the combustion characteristics of ammonia/hydrogen engines while maintaining the equivalent ratio of 1.0. The results indicate that the jet angle significantly affects the position of jet flame and the followed main combustion. The in-cylinder combustion pressure peaks at jet angle of 150°. Meanwhile, the combustion duration of 150° is shortened by 74.3% compared with that of 60°.

The passive pre-chamber (PC) is valued for its jet ignition (JI) and is suitable for wide use in the field of gasoline direct injection (GDI) for small passenger cars, which can improve the performance of lean combustion. However, the intake, exhaust, and ignition combustion stability of the engine at low speed is a shortcoming that has not been overcome. Changing the structural design to increase the fluidity of the main chamber (MC) and pre-chamber (PC) may reduce jet ignition performance, affecting engine dynamics. This investigation is based on non-uniformly nozzles distributed passive pre-chamber, which is adjusted according to the working medium exchange between PC and MC. The advantages and disadvantages of the ignition mode of PC and SI in the target engine speed range are compared through optical experiments on a small single-cylinder GDI engine.

Ultra-lean combustion of GDI engine could achieve higher thermal efficiency and lower NOx emissions, but it also faces challenges such as ignition difficulties and low-speed flame propagation. In this paper, the sparked-spray is proposed as a novel ignition method, which employs the spark to ignite the fuel spray by the cooperative timing control of in-cylinder fuel injection and spark ignition and form a jet flame. Then the jet flame fronts propagate in the ultra-lean premixed mixture in the cylinder. This combustion mode is named Sparked-Spray Induced Combustion (SSIC) in this paper. Based on a 3-cylinder 1.0L GDI engine, a 3D simulation model is established in the CONVERGE to study the effects of ignition strategy, compression ratio, and injection timing on SSIC with a global equivalence ratio of 0.50. The results show it is easier to form the jet flame when sparking at the spray front because the fuel has better atomization and lower turbulent kinetic energy at the spray front.

As a novel ignition technology, pre-chamber ignition can enhance ignition energy, promote flame propagation, and augment turbulence. However, this technology undoubtedly faces challenges, particularly in the context of emission regulations. Of this study, the transient characteristics of combustion and emissions in a hybrid electric vehicle (HEV) gasoline engine with active pre-chamber ignition (PCI) under the first combustion cycle of quick start are focused. The results demonstrate that the PCI engine is available on the first cycle for lean combustion, such as lambda 1.6 to 2.0, and exhibit particle number (PN) below 7×107 N/mL at the first cycle. These particles are predominantly composed of nucleation mode (NM, <50 nm) particles, with minimal accumulation mode (AM, >50 nm) particles.

The functions of modern intelligent connected vehicles are becoming increasingly complex and diverse, and software plays an important role in these advanced features. In order to decouple the software and the hardware and improve the portability and reusability of code, Service-Oriented Architecture (SOA) has been introduced into the automotive industry. Data Distribution Service (DDS) is a widely used communication middleware which provides APIs for service-oriented Remote Procedure Call (RPC) and Service-Oriented Communications (SOC). By using DDS, application developers can flexibly define the data format according to their needs and transfer them more conveniently by publishing and subscribing to the corresponding topic. However, current open source DDS protocols all use unicast communication during the transmission of user data. When there are multiple data readers subscribing to the same topic, the data writer needs to send a unicast message to each data reader individually.

Based on the basic structure and operation function of engine throttle, according to the actual structure of a throttle, a 3-dimensional simulation of the transient airflow during the rotation of the throttle from the closed position to the fully open position is realized by using CFD together with the moving mesh technology and the user-defined program. The influence of the throttle movement on the airflow process is studied. The velocity field, pressure field, and flow noise field are analyzed at different angles of throttle rotation. The numerical simulation results show that at the beginning period of the throttle rotation, the vortex appears in the flow field behind the throttle, and the drop of the air pressure between the upstream and downstream position of the throttle is sharp.

The design of engine intake system affects the intake uniformity of each cylinder of the engine, which in turn has an important impact on the engine performance, the uniform distribution of EGR exhaust gas and the combustion process of each cylinder. In this paper, the constant-pressure supercharged diesel engine intake pipe is used as the research model to study the intake air flow unevenness of the intake pipe of the supercharged diesel engine. The pressure boundary condition at the outlet of each intake manifold is set as the dynamic pressure change condition. The three-dimensional numerical simulation of the transient flow process in the intake manifold of diesel engine is simulated and analyzed by using numerical method, and the change of the Intake air flow field in the intake manifold under different working conditions during the intake overlapping period is discussed.

Exhaust gas recirculation technology is one of the main methods to reduce engine emissions. The pressure of the intake pipe of turbocharged direct-injection diesel engine is high, and it is difficult to realize EGR technology. The application of Venturi tube can easily solve this problem. In this paper, the working principle of guide-injection Venturi tube is introduced, the EGR system and structure of a turbocharged diesel engine using the guide-injection Venturi tube are studied. According to the working principle of EGR system of turbocharged diesel engine, the model of guide-injection Venturi tube is established, the calculation grid is divided, and it is carried out by using Computational Fluid Dynamics method that the three-dimensional numerical simulation of the internal flow of Venturi tube under different EGR rates injection.

The problem of keeping the stable starting performance of diesel engine under high altitude and low temperature conditions has been done a lot of research in the field of diesel engine, but there is a lack of research on extreme conditions such as above 2000 meters above sea level and below 0°C. Aiming at solving the cold start problem of diesel engine in extreme environment, a set of chamber system of cold start environment diesel engine was constructed to simulate environment of 3000m altitude and -20°C. A series of experimental research was conducted on cold start efficiency optimization strategy of a certain type of diesel engine at 3000m altitude and -20°C. In parallel, a diesel engine model was constructed through Chemkin to explore the influence of the three parameters of compression ratio, stroke length, and fuel injection advance angle on the first cold start cycle of diesel engine at 4000m altitude and -20°C.

Argon power cycle hydrogen engine is an internal combustion engine that employs argon instead of nitrogen of air as the working fluid, oxygen as the oxidizer, and hydrogen as the fuel. Since argon has a higher specific heat ratio than air, argon power cycle hydrogen engines have theoretically higher indicated thermal efficiencies according to the Otto cycle efficiency formula. However, argon makes the end mixture more susceptible to spontaneous combustion and thus is accompanied by a stronger knock at a lower compression ratio, thus limiting the improvement of thermal efficiency in engine operation. In order to suppress the limitation of knock on the thermal efficiency, this paper adopts a combination of experimental and simulation methods to investigate the effects of port water injection on the knock suppression and combustion characteristics of an argon power cycle hydrogen engine.

In order to scrutinize the timing variables impacting the combustion performance and emissions of the Port Fuel Injection hydrogen engine (PFI-H2ICE), a model of a four-cylinder hydrogen engine is meticulously built utilizing the 1D software GT-POWER. The effect of excess air coefficients and timing strategies (including the intake valve opening timing (IVO), the start of injection timing (SOI), and ignition timing) is analyzed in this study. The main conclusions are as follows: The hydrogen engine remold from the Isuzu JE4N28 nature gas engine manifests a lean combustion threshold ranging between 2.0 and 2.5. Notably, advancing intake valve opening timing by 20°CA has proven beneficial to the brake thermal efficiency (BTE) of the hydrogen engine while reducing the NOx emissions by a substantial margin, and advancing intake valve opening timing bears the virtue of strengthen the positive influence of the start of injection timing upon the engine's combustion performance.

Recently, several datasets have become available for occupant monitoring algorithm development, including real and synthetic datasets. However, real data acquisition is expensive and labeling is complex, while virtual data may not accurately reflect actual human physiology. To address these issues and obtain high-fidelity data for training intelligent driving monitoring systems, we have constructed a hybrid dataset that combines real driving image data with corresponding virtual data generated from 3D driving scenarios. We have also taken into account individual anthropometric measures and driving postures. Our approach not only greatly enriches the dataset by using virtual data to augment the sample size, but it also saves the need for extensive annotation efforts. Besides, we can enhance the authenticity of the virtual data by applying ergonomics techniques based on RAMSIS, which is crucial in dataset construction.

Multiple actuators equipped in electric vehicles, such as four- wheel steering (4WS) and four-wheel drive (4WD), provide more degrees of freedom for chassis motion control. However, developing independent control strategies for distinct actuator types could result in control conflicts, potentially degrading the vehicle's motion performance. To address this issue, a model predictive control (MPC) based steering-drive cooperated control strategy for enhanced agility and stability of electric vehicles with 4WD and 4WS is proposed in this paper. By designing the control constraints within the MPC framework, the strategy enables single-drive control, single-steering control, and steering-drive cooperative control. In the upper control layer, a linear time-varying MPC (LTV-MPC) is designed to generate optimal additional yaw moment and additional steering angles of front and rear wheels to enhance vehicle agility and lateral stability.