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The fusion of multi-modal perception in autonomous driving plays a pivotal role in vehicle behavior decision-making. However, much of the previous research has predominantly focused on the fusion of Lidar and cameras. Although Lidar offers an ample supply of point cloud data, its high cost and the substantial volume of point cloud data can lead to computational delays. Consequently, investigating perception fusion under the context of 4D millimeter-wave radar is of paramount importance for cost reduction and enhanced safety. Nevertheless, 4D millimeter-wave radar faces challenges including sparse point clouds, limited information content, and a lack of fusion strategies. In this paper, we introduce, for the first time, an approach that leverages Graph Neural Networks to assist in expressing features from 4D millimeter-wave radar point clouds. This approach effectively extracts unstructured point cloud features, addressing the loss of object detection due to sparsity.

To reduce the energy consumption level of electric vehicles, the working range of the regenerative braking system will gradually expand to the high state of charge of the battery. The time delay in the control signal transmission path of the high state of charge regenerative braking control process will affect the regenerative braking. At the same time, regenerative braking under a high state of charge puts forward higher requirements for the control accuracy of regenerative current. In the research of this paper, the motor model, battery model, and vehicle dynamics model are firstly established by using MATLAB/Simulink, and the dynamic relationship between regenerative current and regenerative braking torque is analyzed at the same time. Considering the system time delay, this paper proposes a high-charge regenerative braking control strategy (SPPC) that combines Smith prediction and prescribed performance control.

Gear rattle noise is one of the important characteristics of manual and dual-clutch transmission，it is generated by the impact of unloaded meshing gear pairs in the transmission due to engine torsional vibration. Based on a front-drive manual transmission and a five dynos drivetrain NVH test bench with high-speed sine wave generator function, this paper designs an experimental program suitable for transmission rattle noise. By driving dynamometer to simulate the torque fluctuation of real engine, the main research is to study the characteristics of the transmission rattle noise under different excitation amplitudes and different excitation frequencies, and the sensitivity of rattle noise under different gears, different oil temperatures, different excitation amplitudes and excitation frequencies is analyzed. Finally, the transmission maps of rattle noise in different gears can be obtained.

Due to the poor ability of millimeter wave radar in recognizing distant static objects, target loss and incomplete information will occur when it recognizes the static target in front, thus increasing the false alarm rate and missing alarm rate of the radar-dependent driving assistant system, which will reduce the driving safety and the acceptability of the assistant system. Aiming at the radar's poor ability to recognize static targets, this paper uses a model based on machine learning algorithm to recognize and track targets. The radar signals are collected and processed in different conditions, and the results show that the radar has a poor recognition effect when the distance is more than 100 meters and the speed is more than 19m/s.

The deformation of injector components cannot be disregarded as the pressure of the system increases. Deformation directly affects the characteristics of needle movement and injection quantity. In this study, structural deformation of the nozzle, the needle and the control plunger under different pressures is calculated by a simulation model. The value of the deformation of injector components is calculated and the maximum deformation location is also determined. Furthermore, the calculated results indicates that the deformation of the control plunger increases the control chamber volume and the cross-section area between the needle and the needle seat. A MATLAB model is established to The influence of structural deformation on needle movement characteristics and injection quantity is investigate by a numerical model. The results show that the characteristic points of needle movement are delayed and injection quantity increases due to the deformation.

HTL is a kind of biodiesel converted from wet biowaste via hydrothermal liquefaction (HTL), which has drawn increasing attention in recent years due to its wide range of raw materials (algae, swine manure, and food processing waste). However, from the previous experiments done in a constant volume chamber, it was observed that the presence of 20% of HTL in the blend produced as much soot as pure diesel at in chamber environment oxygen ratio of 21%, and even more soot at low oxygen ratios. It was also observed that n-butanol addition could reduce the soot emission of diesel significantly under all tested conditions. In this work, the spray and combustion characteristics of HTL and diesel blends with n-butanol added were investigated in a constant volume chamber. The in-chamber temperature and oxygen ranged from 800 to 1200 K and 21% to 13%, respectively, covering both conventional and low-temperature combustion (LTC) regimes.

Flash boiling has drawn much attention recently for its ability to enhance spray atomization and vaporization, while providing better fuel/air mixing for gasoline direct injection engines. However, the behaviors of flash boiling spray with multi-component fuels have not been fully discovered. In this study, isooctane, ethanol and the mixtures of the two with three blend ratios were chosen as the fuels. Measurements were performed with constant fuel temperature while ambient pressures were varied to adjust the superheated degree. Macroscopic and microscopic characteristics of flash boiling spray were investigated using Diffused Back-Illumination (DBI) imaging and Phase Doppler Anemometry (PDA). Comparisons between flash boiling sprays with single component and binary fuel mixtures were performed to study the effect of fuel properties on spray structure as well as atomization and vaporization processes.

The spray structure and vaporization processes of flash-boiling sprays in a constant volume chamber under a wide range of superheated conditions were experimentally investigated by a high speed imaging technique. The Engine Combustion Network’s Spray G injector was used. Four fuels including gasoline, ethanol, and gasoline-ethanol blends E30 and E50 were investigated. Spray penetration length and spray width were correlated to the degree of the superheated degree, which is the ratio of the ambient pressure to saturated vapor pressure (pa/ps). It is found that parameter pa/ps is critical in describing the spray transformation under flash-boiling conditions. Three distinct stages namely the slight flash-boiling, the transition flash-boiling, and the flare flash-boiling are identified to describe the transformation of spray structures.

There are a few different ways in which biofuels can be sourced, with the most popular coming from agricultural sources. An alternative approach is to utilize biowaste. An estimated 20 million dry tons of volatile organic compounds, or biowaste, is annually deposited in US municipal wastewaters. Most of this biowaste energy content is not recovered and, as a result, the biowaste could be a massive potential source of renewable energy. Biocrude diesel is converted from wet biowaste via hydrothermal liquefaction (HTL). Three types of feedstocks (algae, swine manure, and food processing waste) were converted into biocrude oil via HTL. From the previous experiments done in an AVL 5402 single-cylinder diesel engine, it was observed that the presence of 20% of HTL in the blend performed similarly during combustion to pure diesel. By studying these mixtures in a constant volume chamber, these observations could be compared to the results in the diesel engine.

The study of vehicle coupling state estimation accuracy especially in observer-based vehicle chassis control for improving road handling and ride comfort is a challenging task for vehicle industry under various driving conditions. Due to a large amount of life safety arising from vehicle roll behavior, how to precisely acquire vehicle roll state and rapidly provide for the vehicle control system are of great concern. Simultaneously, uncertainty is unavoidable for various aspects of a vehicle system, e.g., varying sprung mass, moment of inertia and position of the center of gravity. To deal with the above issues, a novel dual observer approach, which combines adaptive Unscented Kalman Filter (AUKF) and Takagi-Sugeno (T-S), is proposed in this paper. A full-car nonlinear model is first established to describe vehicle lateral and vertical coupling roll behavior under various road excitation.

A three-dimensional model of a diesel engine intake port was established and was verified by steady-flow test. Based on this model, the influence of intake valve lift on the flow capacity of intake port was studied and a design method of maximum valve lift was put forward. The results show that, under different intake pressure and relative pressure difference conditions, the discharge coefficient increases first and then converges with the increase of valve lift. Under the same valve lift condition, with the increase of relative pressure difference, the discharge coefficient decreases slightly in subsonic state and decreases sharply from subsonic state to supersonic state, but the mass flow rate increases slightly. The optimum ratio of valve lift and valve seat diameter is related to relative pressure difference, it increases first and then keeps constant with the increase of relative pressure difference.

This research examined the focused design, elastic design, energy decoupling, and torque roll axis (TRA) decoupling methods for mount optimization design. Requiring some assumptions, these methods are invalid for some load conditions and constraints. The linearity assumption is advantageous and simplifies both design and optimization analysis, facilitating engineering applications. However, the linearity is rarely seen in real-world applications, and there is no practical method to directly measure the reaction forces in the three locally orthogonal directions, preventing validation of existing methods by experimental results. For nonlinear system identification, there are additional challenges such as unobservable internal variables and the uncertainty of measured data.

This paper presents a road classifier based on the system response with consideration of the tire enveloping. The aim is to provide an easily applicable yet accurate road classification approach for automotive engineers. For this purpose, tire enveloping effect is firstly modeled based on the flexible roller contact (FRC) theory, then transfer functions between road input and commonly used suspension responses i.e. the sprung mass acceleration, unsprung mass acceleration, and rattle space, are calculated for a quarter vehicle model. The influence of parameter variations, vehicle velocity, and measurement noise on transfer functions are comprehensively analyzed to derive the most suitable system response thereafter. In addition, this paper proposes a vehicle speed correction mechanism to further improve the classification accuracy under complex driving conditions.

The control parameter of the semi-active suspension system varies with road profile; therefore, in this study a new algorithm based on cuckoo search (CS) optimization method and road estimation was proposed to investigate the characteristics of the nonlinear parameters and at the same time improve the riding comfort. Based on this, a seven degree of freedom full vehicle model was developed with nonlinear damper and spring. The sprung mass acceleration, pitch acceleration, and tire deflection could be selected as the objective functions, and the control current of semi active suspension was selected as optimization variable. A multi-object CS algorithm was utilized to obtain the optimal parameters under different road profiles, and a road estimation algorithm was used to identify the road level. Then the control parameters could be adjusted adaptively according to the level of the road.

The electric vehicles and the intelligent vehicles put forward to new requirements for the brake system, such as the vacuum-independent braking, automatic or active braking, and regenerative braking, which are the key link for the vehicle’s safety and economy. However, the traditional vacuum brake booster is no longer able to meet these requirements. In this article, a novel integrated power-assisted actuator of brake system is proposed to satisfy the brake system requirements of the electric vehicles and intelligent vehicles. The electronic brake booster system is designed to achieve the function of boosting pedal force of driver, being independent on vacuum source, supplying autonomous or active braking. It is mainly composed of a permanent magnet synchronous motor (PMSM), a two-stage reduction transmission (gears and a ball screw), a servo body, and a reaction disk. The scheme design and power-assisted braking control are the key for the electronic actuator.

More and more stringent emission regulations and the desire to reduce fuel consumption lead to an increasing demand for precise and close-loop combustion control of diesel engines. Cylinder pressure-based combustion control is gradually used for diesel engines in order to enhance emission robustness and reduce fuel consumption. However, it increases the cost. In this paper, a new prediction method of combustion parameters is presented for diesel engines. The experiment was carried out on a test bench to obtain the ECU (Electronic Control Unit) signals of a heavy-duty diesel engine by calibration software. The combustion parameters was measured by a combustion analyzer, such as maximum cylinder pressure (MCP), maximum combustion temperature (MCT), and combustion center of gravity (CA50). A combustion model using genetic programming (GP) is built. The input parameters are chosen from the ECU signals, such as engine speed, engine load, injection quantities, inlet air flow rate.

The electronic unit pump system, which is widely applied to the heavy-duty diesel engine, belongs to the pulsating high-pressure fuel injection system, and the fuel pressure fluctuations have an essential influence on the spray and combustion in the internal combustion engine. Besides, pressure fluctuations are always aroused by the motion of actuators, such as the injector or other control valves, so it is also an advantage for fault diagnosis and feedback control to ascertain the relationship between the pressure fluctuation and the motion of the actuator. In this study, experiments and 1D-simulation were carried on to investigate the fuel pressure fluctuation characteristics and their correlations with the transient motion of the needle valve in the injector.

The diesel low temperature combustion (LTC) can keep high efficiency and produce low emission. Which has been widely studied at home and abroad in recent years. The combustion control parameters, such as injection pressure, injection timing, intake oxygen concentration, intake pressure, intake temperature and so on, have an important influence on the combustion and emission of diesel LTC. Therefore, to realize different combustion modes and combustion mode switch of diesel engine, it is necessary to accurately control the injection parameters and intake parameters of diesel engine. In this work, experimental study has been carried out to analyze the effect of intake oxygen concentration, intake pressure and intake temperature in combustion and emission characteristics of diesel LTC, such as in-cylinder pressure, temperature, heat release rate, NOx and soot emission.

The acquisition of more authentic cylinder pressure data is the basis of engine combustion analysis. Due to the multiple advantages, quartz piezoelectric pressure transducers are generally applied to the measurement of the cylinder pressure. However, these transducers can only produce dynamic cylinder pressure data which may be significantly different from the actual values. Thus, the cylinder pressure data need to be corrected through a certain method, while different cylinder pressure correction methods will cause result divergences of the combustion analysis. This paper aims to acquire a proper cylinder pressure correction method by carrying out theoretical analysis based on the polytropic process in the compression stroke as well as the experimental research of the cylinder pressure of a turbocharged eight-cylinder diesel engine.

Bio-butanol has been considered as a promising alternative fuel for internal combustion engines due to its advantageous physicochemical properties. However, the further development of bio-butanol is inhibited by its high recovery cost and low production efficiency. Hence, the goal of this study is to evaluate two upstream products from different fermentation processes of bio-butanol, namely acetone-butanol-ethanol (ABE) and isopropanol-butanol-ethanol (IBE), as alternative fuels for diesel. The experimental comparison is conducted on a single-cylinder and common-rail diesel engine under various main injection timings (MIT) and equivalent engine load (EEL) conditions. The experimental results show that ABE and IBE significantly affect the combustion phasing. The start of combustion (SOC) is retarded when ABE and IBE are mixed with diesel. Furthermore, the ABE/IBE-diesel blends are more sensitive to the changes in MIT compared with that of pure diesel.