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Aiming at the problem of poor robustness after the combination of lateral kinematics control and lateral dynamics control when an autonomous vehicle decelerates and changes lanes to overtake at a certain distance. This paper proposes a trajectory determination and tracking control method based on a PI-MPC dual algorithm controller. To describe the longitudinal deceleration that satisfies the lateral acceleration limit during a certain distance of lane change, firstly, a fifth-order polynomial and a uniform deceleration motion formula are established to express the lateral and longitudinal displacements, and a model prediction controller (MPC) is used to output the front wheel rotation angle. Through the dynamic formula and the speed proportional-integral (PI) controller to control and adjust the brake pressure.

As a major power source, diesel engines are being widely used in a variety of fields. However, because of complex structure, some faults which cannot be detected by direct signals would occur on engines and even lead to accidents. Among all kinds of indirect signals, vibration signal is the most common choice for faults detection without disassemble because of its convenience and stability. This paper proposed a novel approach for detecting multiple engine faults based on block vibration signals using variational mode decomposition (VMD) and echo state network (ESN). Since the quadratic penalty has a great influence on adaptable VMD that may make expected component signals cannot be extracted exactly, this paper proposed a dynamic quadratic penalty value, which will change with decomposing level. This paper selected a best dynamic quadratic penalty value by analyzing a large amount of data and results showed that this approach can decompose signals more exactly.

Transparent materials such as Plexiglas and glass are applied in airplane and boat widely as the windows and hatches. There are three type stresses in the structure made of Plexiglas or glass, which are residual stresses from the casting, residual stresses due to manufacturing process involving sheet forming structure and the stresses from serving period. In the paper the stresses are studied by laser scattered Photoelasticy method. Phase shift method is presented to recognize scattered light patterns automatically. The residual stresses in Plexiglas plate and shell were analyzed by thin plate-shell theory. Stresses in the Plexiglas and shell were tested by laser scattered Photoelastic method.

The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.

Wall temperature in GDI engine is influenced by both water jacket and gas heat source. In turn, wall temperature affects evaporation and mixing characteristics of impingement spray as well as combustion process and emissions. Therefore, in order to accurately simulate combustion process, accurate wall temperature is essential, which can be obtained by conjugate heat transfer (CHT) and piston heat transfer (PHT) models based on mapping combustion results. This CHT model considers temporal interaction between solid parts and cooling water. This paper presents an integrated methodology to reliably predict in-cylinder combustion process and temperature field of a 2.0L GDI engine which includes engine head/block/gasket and water jacket components. A two-way coupling numerical procedure on the basis of this integrated methodology is as follows.

The evolution of surface functional groups (SFGs) and the graphitization degree of soot generated in premixed methane flames are studied and the correlation between them is discussed. Test soot samples were obtained from an optimized thermophoretic sampling system and probe sampling system. The SFGs of soot were determined by Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) after removing the soluble impurities from the soot samples, while the graphitization degree of soot was characterized by Raman spectrum and electron energy loss spectroscopy (EELS). The results reveal that the number of aliphatic C-H groups and C=O groups shows an initial increase and then decrease in the sooting history. The large amount of aliphatic C-H groups and small amount of aromatic C-H groups in the early stage of the soot mass growth process indicate that aliphatic C-H groups make a major contribution to the early stage of soot mass growth.

In order to ensure braking efficiency and improve the comfort of drivers and passengers, a two-stage braking grading control system was proposed. In the upper controller, the enhanced time-to-collision model under different working conditions was designed, and the braking threshold was determined considering the comfort of braking drivers and passengers, and the driver’s braking behavior was analyzed to determine the vehicle braking deceleration. The vehicle longitudinal dynamic model was built in the lower layer, the PID controller was used to reduce the model deviation. This paper improves the test standard on the basis of China-New Car Assessment Program. The results show that the remaining relative distance between the two vehicles was in the safe range. The control strategy can achieve collision avoidance of vehicle emergency braking.

This paper proposed a path coordination strategy for autonomous parking based on independently designed parking lot topological map. The strategy merges two types of paths at the three stages of path planning, to determinate mode switching timing between low-speed automated driving and automated parking. Firstly, based on the principle that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information. Secondly, the direction and lateral distance of the parking space to the last node of global path are used to decide parking type and direction at parking planning stage. Finally, the parking space node is used to connect global path and parking path at path coordination stage.

With the development of science and technology, breakthroughs have been made in the fields of intelligent algorithms, environmental perception, chip embedding, scene analysis, and multi-information fusion, which together prompted the wide attention of society, manufacturers and owners of autonomous vehicles. As one of the key issues in the research of autonomous vehicles, the research of vehicle lane change algorithm is of great significance to the safety of vehicle driving. This paper focuses on the conflict of interest between the lane-changing vehicle and the target lane vehicle in the fully autonomous driving environment, and proposes the method of coupling kinematics and game theory and reinforcement learning based optimization, so that when the vehicle is in the process of lane changing game, the lane-changing vehicle and the target lane vehicle can make decisions that are beneficial to the balance of interests of both sides.

Motor thermal management of electric vehicles (EVs) is becoming more significant due to its close relations to vehicle aerodynamic performance and power consumption, while computer aided engineering (CAE) plays an important role in its development. A 1D-3D coupled model is established to characterize transient thermal performance of the motor in an electric vehicle on a high performance computer (HPC) platform. The 1D motor thermal management model is integrated with the 1D powertrain model, and a 3D thermal model is established for the motor, while online data exchange is realized between the 1D and 3D models. The 1D model gives boundaries such as inlet coolant temperature, mass flowrate and motor heat generation to the 3D model, while the 3D model gives back boundaries such as heat transfer to coolant simultaneously. Transient simulations are performed for the 140kph(20°C) driving cycle, and the model is calibrated with experimental data.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

As a critical power source, the diesel engine is widely used in various situations. Diesel engine failure may lead to serious property losses and even accidents. Fault detection can improve the safety of diesel engines and reduce economic loss. Surface vibration signal is often used in non-disassembly fault diagnosis because of its convenient measurement and stability. This paper proposed a novel method for engine fault detection based on vibration signals using variational mode decomposition (VMD), K-means, and genetic algorithm. The mode number of VMD dramatically affects the accuracy of extracting signal components. Therefore, a method based on spectral energy distribution is proposed to determine the parameter, and the quadratic penalty term is optimized according to SNR. The results show that the optimized VMD can adaptively extract the vibration signal components of the diesel engine. In the actual fault diagnosis case, it is difficult to obtain the data with labels.

Forward Collision Warning System is an important part of vehicle active safety system, it can reduce the occurrence of rear-end collision accidents with high fatality rate and improve the safety of driving. At present, there are still some outstanding issues to be addressed among the existing forward collision warning systems, such as the high cost of information acquisition based on LiDAR and other high-definition sensors, and the poor real-time performance of target detection based on vision. In view of the aforementioned issues and in order to improve the detection accuracy and real-time requirements of the target detection function of the early warning system, this paper proposes an enhanced deep learning model-based vehicle target detection method, and improves the key techniques of target detection, ranging and speed measurement and early warning strategy in the warning system.

The vehicle axle gear whine noise and vibration are key issues for the automotive industry to design a quiet, reliable driveline system. The main source of excitation for this vibration energy comes from hypoid gear transmission error (TE). The vibration transmits through the flexible axle components, then radiates off from the surface of the housing structure. Thus, the design of hypoid gear pair with minimization of TE is one way to control the dynamic behavior of the vehicle axle system. In this paper, an approach to obtain minimum TE and improved dynamic response with optimal tooth profile modification parameters is discussed. A neural network algorithm, named Back Propagation (BP) algorithm, with improved Particle Swarm Optimization (PSO) is used to predict the TE if some tooth profile modification parameters are given to train the model.

High-pressure common rail (HPCR) fuel injection system is the most widely used fuel system in diesel engines. However, when multiple injection strategy is used, the pressure wave fluctuation is un-avoided due to the opening and closing of the needle valve which will affect the subsequent fuel injection and combustion characteristics. In this paper, several parameters: injection pressure, injection intervals, the main injection pulse widths are investigated on a common rail fuel injection test rig with two injection pulses to explore their effect on the fuel injection rate and fuel quantity. The result showed that the longer injection interval between the pilot and main injections will lead to a rail pressure drop at the beginning of the main injection so that a smaller fuel quantity will be delivered. The main injection pulse width also influences fuel injection rate and the main fuel quantity.

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.

A pump-end control technology for pump-nozzle fuel supply unit, in which the pump is driven and controlled electrically for pressurizing and metering the fuel fed into an engine, is studied. The unit is composed of a solenoid driven plunger pump, a high-pressure fuel tube, and an auto-open nozzle, and only the pump is propelled by PWM power from an ECU. To achieve a higher metering accuracy, a metering theory deciding the fuel discharging rate was developed by studying the system using a physical-mathematical model. The developed so called T3 theory makes the fuel supply unit with excellent metering consistency under various conditions, which can meet the requirement of fuel supply unit application to small engine management system. The study reveals that an electrically characterized variable, T3, which is associated with the net output energy, can directly results in a mass discharge.

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.

Nowadays the strong knocking combustion involving destructive pressure wave or shock wave has become the main bottleneck for highly boosted engines when pursuing high thermal efficiency. However, its fundamental mechanism is still not fully understood. In this study, synchronization measurements through simultaneous pressure acquisition and high-speed direct photography were performed to comparatively investigate the strong knocking combustion of iso-octane and propane in a rapid compression machine with flat piston design. The pressure characteristics and visualized images of autoignition and reaction wave propagation were compared, and the correlations between thermodynamic trajectories and mixture reactivity progress were analyzed. The results show that iso-octane behaves a greater propensity to strong knocking combustion than propane at similar target pressures.

Ensuring lower emissions and better economy (fuel economy and after-treatment economy) simultaneously is the pursuit of future engines. An EGR-LNT synergetic control system was applied to a modified lean-burn CA3GA2 gasoline engine. Results showed that the synergetic control system can achieve a better NOx reduction than sole EGR and sole LNT within a proper range of upstream EGR rate and without the penalty in fuel consumption. It also has the potential to save costly noble metals in LNT, but excessive or deficient upstream EGR would make the synergetic control system inefficiency. In order to guarantee the objectivity of the effect of EGR-LNT synergetic control system on NOx reduction, another modified lean-burn CA4GA5 gasoline engine was additionally tested.