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Highly autonomous vehicles have drawn the interests of many researchers in recent years. For highly autonomous vehicles, a high-definition (HD) map is crucial since it provides accurate information for autonomous driving. However, due to the possible fast-changing environment, the performance of HD maps will deteriorate over time if timely updates are not ensured. Therefore, this paper studies the updating of lightweight HD maps in closed areas. Firstly, a novel two-layer map model called a lightweight HD map is introduced to support autonomous driving in a flexible and efficient way. Secondly, typical updating of scenarios in closed areas with non-paved roads is abstracted into operations including area border expansion, road addition, and road deletion. Meanwhile, a map updating framework is proposed to address the issue of map updating in closed areas. Finally, an experiment is conducted to demonstrate the feasibility and effectiveness of the proposed map updating approach.

Early injection timing is an effective measure of pre-mixture formation for diesel low-temperature combustion. Three algebraic subgrid models (Smagorinsky model, dynamic Smagorinsky model and WALE model) and one-equation kinetic energy turbulent model using modified TAB breakup model (MTAB model) have been implemented into KIVA3V code to make a detailed large eddy simulation of the atomization and evaporation processes of early injection timing in a constant volume chamber and a Ford high-speed direct-injection diesel engine. The results show that the predictive vapor mass fraction and liquid penetration using LES is in good agreement with the experiment results. In combustion chamber, the sub-grid turbulent kinetic energy and viscosity using LES are less than with the RANS models, and following the increasing time, the sub-grid turbulent kinetic energy and viscosity also increase and are concentrated on the spray area.

The ethanol has potential to be a renewable alternative fuel for internal combustion engines and contributes to lower global CO2 emission. In this study, vegetable methyl ester is added in the ethanol-diesel fuel to prevent separation of the ethanol from diesel, thus the ethanol blend ratio can be set up to 30% in volume. This work pays more attention on its spray, effects of the ethanol percentage on the detailed PM components. To investigate the spray behavior of ethanol, diesel and their blends, experiments in a constant volume chamber were carried out combining numerical simulation. Properties of the ethanol-diesel blended fuels were obtained through some measurements and empirical calculations. The breakup sub-model, Wave-KH model considering the blend fuel properties were adopted in an engine simulation code KIVA-3V. The simulation had a good agreement with experiments.

A quasi-dimensional multi-zone model for diesel spray combustion has been developed. The model contains most of the physical processes of diesel spray combustion, and is simplified and economical. The zone formation is based on the fuel injection parameters. For the wall jet penetration velocity, a new equation is used based on the effect of the impinging free jet on the wall jet. For the fuel evaporation, an approximate solution of the instantaneous variations of droplet diameter is given in the simple algebraic equations based on the individual effect of the evaporation and the heat transfer from ambient gas. The soot emission sub-model calculates the soot concentration. This model has been applied for a direct injection diesel engine. The calculated results have shown a reasonable agreement with the experimental results. A parametric study has been carried out.

Diesel particulate filter (DPF) is indispensable for diesel engines to meet the increasingly stringent emission regulations. Both the peak temperature and the maximum temperature gradient of the DPF during active regeneration should be well controlled in order to enhance the reliability and durability of the filter. In this paper, the temperature field of the DPF during active regeneration with hydrocarbon (HC) injection was investigated with engine bench tests and numerical simulation. For the experimental study, 24 thermocouples were inserted into the DPF channels to measure the inner temperature of the filter to capture its temperature field, and the circumferential, axial and radial distribution of the filter temperature was analyzed to understand the DPF temperature field behavior during active regeneration.

Diesel particulate filter (DPF) is necessary for diesel engines to meet the increasingly stringent emission regulations. Many studies have demonstrated that the lubricant derived ash has a significant effect on DPF pressure drop and engine fuel economy, and this effect becomes more and more severe with the increasing of operating hours of the DPF because the ash accumulated in the DPF cannot be removed by regeneration. It is reported that most of the DPFs operated with more ash than soot in the filter for more than three quarters of the time during its lifetime [1]. In order to mitigate this problem, the original engine manufacturers (OEM) tend to use an oversized DPF for the engine. However, it will increase the costs of the DPF and reduce the compactness of the engine aftertreatment system.

Urea-based selective catalytic reduction (SCR) of nitric oxides (NOx) is a key technology for heavy-duty diesel engines to achieve the increasingly stringent NOx emission standards. The aqueous urea injection control is critical for urea-SCR systems in order to achieve high NOx conversion efficiency while restricting the tailpipe ammonia (NH3) slip. For Euro VI emission regulation, an advanced control strategy is essential for SCR systems since its NOx emission limits are tighter and test procedure are more stringent compared to Euro IV and Euro V. The complex chemical kinetics of the SCR process has motivated model-based control design approaches. However, the model is too complex to allow real-time implementation. Therefore, it is very important to have a reduced order model for SCR control system.

Recent research has shown that butanol, instead of ethanol, has the potential of introducing a more suitable blend in diesel engines. This is because butanol has properties similar to current transportation fuels in comparison to ethanol. However, the main downside is the high cost of the butanol production process. Acetone-butanol-ethanol (ABE) is an intermediate product of the fermentation process of butanol production. By eliminating the separation and purification processes, using ABE directly in diesel blends has the potential of greatly decreasing the overall cost for fuel production. This could lead to a vast commercial use of ABE-diesel blends on the market. Much research has been done in the past five years concerning spray and combustion processes of both neat ABE and ABE-diesel mixtures. Additionally, different compositions of ABE mixtures had been characterized with a similar experimental approach.

The earth's fossil energy is not limitless, and we should be taking advantage of the highly developed fields of science and technology to utilize it more efficiently and to create a fully environmentally friendly life. Considering the prodigious amount of vehicles in the world today, even a small improvement in their energy-saving performance could have a significant impact. In this paper, a new type of electro-hydraulic power steering (EHPS) system is described. It has two main advantages. First, it can significantly decrease the demand on the motor so that it can be used for a wider range of vehicles. Second, its pressure-flow characteristic can be programmed and is more flexible than hydraulic power steering (HPS) system. A prototype with a 500 W motor was applied to a truck with a front load of 2,700 kg, and static steer sweep tests were conducted to validate its feasibility.

This study investigates the performance of a diesel engine fueled with naphtha under different load by varying injection parameters and exhaust gas recirculation (EGR) rate. The experiments were conducted on a 1.9-liter common rail diesel engine with a compression ratio of 17.5. Naphtha with a research octane number of 60.5 was tested. Three multi-injection strategies were designed. Each injection strategy, aided with EGR, conducts a characteristic combustion mode. Multi-injection strategies and single-injection strategy were tested and compared at one operating point under different main injection timing and EGR conditions. Results indicate that the well-designed multi-injection strategy has advantages over the single injection strategy in lowering noise, emissions and improving combustion efficiency. Among the three strategies, the strategy with 15-degree pilot timing and 2mg/cycle pilot injection could achieve both low NOx and PM emissions without sacrificing much fuel efficiency.

The electromagnetic regenerative suspension has attracted much attention recently due to its potential to improve ride comfort and handling stability, at the same time recover kinetic energy which is typically dissipated in traditional shock absorbers. The key components of a ball-screw regenerative suspension system are a motor, a ball screw and a nut. For this kind of regenerative suspension, its damping character is determined by the motor's torque-speed capacity, which is different from the damping character of the traditional shock absorber. Therefore, it is necessary to establish a systematic approach for the parameter matching of ball-screw regenerative suspension, so that the damping character provided by it can ensure ride comfort and handling stability. In this paper, a 2-DOF quarter vehicle simulation model with regenerative suspension is constructed. The effects of the inertia force on ride comfort and handling stability are analyzed.

According to the statistics of National Highway Traffic Safety Administration, driver’s cognitive distraction, which is usually caused by drivers using mobile phones, has become one of the main causes of traffic accidents. To solve this problem and guarantee the safety of man-vehicle-road system, the most critical work is to improve the accuracy of driver’s cognitive state detection. In this paper, a novel driver’s cognitive state detecting method based on LightGBM (Light Gradient Boosting Machine) is proposed. Firstly, cognitive distraction experiments of making calls are carried out on a driving simulator to collect vehicle states, eye tracking and EEG (electron encephalogram) data simultaneously and feature extraction is conducted. Then a classifier considering road and individual characteristics used for detecting cognitive states is trained based on LightGBM algorithm, with 3 predefined cognitive states including concentration, ordinary distraction and extreme distraction.

This work presents a multi-objective adaptive cruise control (ACC) system via deep reinforcement learning (DRL). During the control period, it quantitatively considers three indexes: tracking accuracy, riding comfort, and fuel economy. The system balances contradictions between different indexes to achieve the best overall control results. First, a hierarchical control architecture is utilized, where the upper level controller is synthesized under DRL framework to give out the vehicle desired acceleration. The lower level controller executes the command and compensates vehicle dynamics. Then, four state variables that can comprehensively determine the car-following states are selected for better convergence. Multi-objective reward function is quantitatively designed referring to the evaluation indexes, in which safety constraints are considered by adding violation penalty. Thereafter, the training environment which excludes the disturbance of preceding car acceleration is built.

The diesel particulate filter (DPF) is an effective technology for particulate matter (PM) and particle number (PN) reduction. On heavy-duty diesel engines, the passive regeneration by Diesel Oxidation catalysts (DOC) and catalyzed DPFs (CDPF) is widely used for its simplicity and low cost, which is generally combined with the active regeneration of exhaust fuel injection. This study investigated a DOC-CDPF system with exhaust fuel injection upstream of the DOC. The system was integrated with a 7-liter diesel engine whose engine-out PM emission was below the Euro IV level and tested on an engine dynamometer. PM and PN concentrations were measured based on the Particle Measurement Programme (PMP), and the number/size spectrum for particles was obtained by a Differential Mobility Spectrometer (DMS). The filtration efficiency of DPF on PN was higher than 99% in ESC test, while the efficiency on PM was only 58%.

Internal combustion engines, as the dominant power source in the transportation sector and the primary contributor to carbon emissions, face both significant challenges and opportunities in the context of achieving carbon neutral goal. Biofuels, such as biodiesel produced from biomass, and zero-carbon fuel ammonia, can serve as alternative fuels for achieving cleaner combustion in internal combustion engines. The dual-fuel combustion of ammonia-biodiesel not only effectively reduces carbon emissions but also exhibits promising combustion performance, offering a favorable avenue for future applications. However, challenges arise in the form of unburned ammonia (NH3) and N2O emissions. This study, based on a ammonia-biodiesel duel-fuel engine modified from a heavy-duty diesel engine, delves into the impact of adjustments in the two-stage injection strategy on the combustion and emission characteristics.

With the rapid advancement in intelligent vehicle technologies, comprehensive environmental perception has become crucial for achieving higher levels of autonomous driving. Among various perception tasks, monitoring road types and evenness is particularly significant. Different road categories imply varied surface adhesion coefficients, and the evenness of the road reflects distinct physical properties of the road surface. This paper introduces a two-stage road perception framework. Initially, the framework undergoes pre-training on a large annotated drivable area dataset, acquiring a set of pre-trained parameters with robust generalization capabilities, thereby endowing the model with the ability to locate road areas in complex regions.

Ammonia (NH3), a zero-carbon fuel, has great potential for internal combustion engine development. However, its high ignition energy, low laminar burning velocity, narrow range of flammability limits, and high latent heat of vaporization are not conducive for engine application. This paper numerically investigates the feasibility of utilizing ammonia in a heavy-duty diesel engine, specifically through low-pressure direct injection (LP-DI) of hydrogen to ignite ammonia combustion. Due to the lack of a well-corresponding mechanism for the operating conditions of ammonia-hydrogen engines, this study serves only as a trend-oriented prediction. The paper compares the engine's combustion and emission performance by optimizing four critical parameters: excess air ratio, hydrogen energy ratio, ignition timing, and hydrogen injection timing. The results reveal that excessively high hydrogen energy ratios lead to an advanced combustion phase, reducing indicated thermal efficiency.