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Vehicles equipped with one or several functions of Advanced Driver Assistant System (ADAS) and autonomous driving (AD) technology are more mature and prevalent nowadays. Vehicles being smarter and driving being easier is an unstoppable trend. In the near future, intelligent vehicles will be mass produced and running on the road. However, before the mass-production of intelligent vehicles, a lot of experimental tests and validations need to be carried out to insure the safety and reliability of ADAS and AD technology. Although the road test of real vehicles is the most reliable and accurate test method, it cannot meet the need of rapid development of technology research due to high time and financial cost. Therefore, a high-efficient design and evaluation methodology for ADAS and AD development and test is a must. In this paper, a virtual co-simulation platform based on MATLAB/Simulink, OpenModelica and Unity 3D game engine (MOMU) is proposed.

High-speed vehicles in low illumination environments severely blur the images used in object detectors, which poses a potential threat to object detector-based advanced driver assistance systems (ADAS) and autonomous driving systems. Augmenting the training images for object detectors is an efficient way to mitigate the threat from motion blur. However, little attention has been paid to the motion of the vehicle and the position of objects in the traffic scene, which limits the consistence between the resulting augmented images and traffic scenes. In this paper, we present a vehicle kinematics-based image augmentation algorithm by modeling and analyzing the traffic scenes to generate more realistic augmented images and achieve higher robustness improvement on object detectors against motion blur. Firstly, we propose a traffic scene model considering vehicle motion and the relationship between the vehicle and the object in the traffic scene.

In order to avoid the influence of the change of the camera pitch angle and the variation of the height of the ground on the ranging accuracy, improve the real-time performance of the algorithm by substituting the current widely-used monocular vision ranging algorithm which builds the optical model based on the shadow of the vehicle floor and the lane line, as well as avoid the classification of vehicle detection, a vehicle distance measurement algorithm based on monocular vision and license plate width is established. Firstly, the target image acquisition and preprocessing are studied. Then the paper studies the license plate image location segmentation method based on accelerated template matching. On this basis, the algorithm for obtaining the ratio of license plate width to image width is studied, and the function of vehicle distance and license plate ratio width is established.

Carbon fiber reinforced plastic (CFRP) composite materials have gained particular interests due to their high specific modulus, high strength, lightweight and perfect corrosion resistance. However, in reality, CFRP composite materials cannot be used alone in some critical places such as positions of joints with hinges, locks. Therefore, metal reinforcements are usually necessary in local positions to prevent structure damage. Besides, if uncertainties present, obtained optimal structures may experience in failures as the optimization usually pushes solutions to the boundaries of constraints and has no room for tolerance and uncertainties, so robust optimization should be considered to accommodate the uncertainties in practice. This paper proposes a mixed topology method to optimize metal and carbon fiber reinforced plastic composite materials simultaneously under nondeterministic load with random magnitude and direction.

As one of the most crucial components in electric vehicles, power batteries generate abundant heat during charging and discharging processes. Thermal management system (TMS), which is designed to keep the battery cells within an optimum temperature range and to maintain an even temperature distribution from cell to cell, is vital for the high efficiency, long calendar life and reliable safety of these power batteries. With the desirable features of low system complexity, light weight, high energy efficiency and good battery thermal uniformity, thermal management using composite phase change materials (PCMs) has drawn great attention in the past fifteen years. In the hope of supplying helpful guidelines for the design of the PCM-based TMSs, this work begins with the summarization of the most commonly applied heat transfer enhancement methods (i.e., the use of thermally conductive particles, metal fin, expanded graphite matrix and metal foam) for PCMs by different researchers.

The exhaust aftertreatment strategy is one of the most fundamental aspects of spark ignition engine technologies. For various types of engines (e.g., carburetor engine, PFI engine and GDI engine), measuring, purifying, modeling, and control strategies regarding the exhaust aftertreatment systems vary significantly. The primary goal of exhaust aftetreatment systems is to reduce the exhaust emission levels of NOx, HC and CO as well as to lower combustion soot. In general, there is a tradeoff among different engine performance aspects. The exhaust catalytic systems, such as the three way catalyst (TWC) and lean NOx trap (LNT) converters, can be applied together with the development of other engine technologies (e.g., variable valve timing, cold start). With respect to engine soot, some advanced diagnosing techniques are essential to obtain thorough investigation of exhaust emission mechanisms.

The cab is an essential part of a light truck, and its fatigue durability performance plays an important role in the design and development stage. Accelerated fatigue bench test has been widely applied to product development of carmakers for its low cost and short development cycle. However, in reality, interference exists generally in torsional conditions for the light truck cab when tested on the 4-post vehicle road simulation system. To solve this problem and minimize the lateral force applied on the hydraulic cylinders, the direction and size combinations of displacement release about front and rear suspensions were discussed based on multi-body dynamics simulation and fixture design theory in this paper. Through comparative study, the optimum design and layout scheme of fixtures was determined to conduct the next test procedure. The weak positions of the light truck cab were firstly predicted by utilizing finite element method (FEM) and fatigue analysis theory.

Centrifugal Pendulum Vibration Absorber (CPVA for short) is used to absorb torsional vibrations caused by the shifting motion of the engine. It is increasingly used in modern powertrains. In the research of the dynamic characteristics of the CPVA, it is necessary to obtain the real motion of the pendulum to compensate the fitting performance of mathematical model. The usual method is to install an angle sensor to measure the movement of the pendulum. On the one hand, the installation of the sensor will affect its movement to a certain extent, so that the measurement results do not match the actual motion. On the other hand, the motion of the pendulum is not only the rotational motion around the rotational axis of the CPVA rotor, but also has translation relative to it. As a result, it is difficult to obtain accurate motion only by the angle sensor. We proposed a non-contact centrifugal pendulum motion measurement method.

During the launch of a car, severe torsional vibration sometimes may occur in its driveline due to somewhat the slipping of the clutch, its intuitive sense for an occupant is the longitudinal vibration of the vehicle, referred to as the launch shudder whose characteristic frequency is from 5 to 25 Hz generally. As the main vibration sources of the driveline and its crucial nonlinear components, the variable stiffness and backlash of the gear meshing are considered, their impacts on the launch shudder are analyzed in this paper. Conformal mapping, finite element method and regression method etc. are the main approaches to calculate the variable meshing stiffness of a gear pair. If this stiffness is get, it can usually be substituted for its approximate analytical expression, just with finite harmonic terms, in Fourier Series form into Ordinary Differential Equations(ODEs) to calculate the vehicle responses with its nonlinearity considered.

Emissions of diesel engine have been received much more attention since the Volkswagen Emission Scandal. The Euro VI emission standard has already included cold start emissions in the legislative emission driving cycles which is one of the hardest part of emission control. High altitude performance is also considered in the latest regulations which will be stricter in the future. Heating the coolant is one of the most common method to improve the cold start performance. But researches focus on the emission of a diesel engine in different coolant temperature at high altitude which up to 4500m have not been seen. The present research investigated the effect of coolant temperature on performance and exhaust emissions (gaseous and particulate emissions) during the cold start of a diesel engine. A plateau simulation system controlled the inlet and exhaust pressure to create altitude environments from 0m to 4500m, and the coolant temperature was controlled from 20°C to 60°C.

In order to explore approaches for improving object detection accuracy in intelligent vehicle system, we exploit super-resolution techniques. A novel method is proposed to confirm the conjecture whether some popular super-resolution networks used for environmental perception of intelligent vehicles and robots can indeed improve the detection accuracy. COCO dataset which contains images from complex ordinary environment is utilized for the verification experiment, due to it can adequately verify the generalization of each algorithm and the consistency of experimental results. Using two representative object detection networks to produce the detection results, namely Faster R-CNN and YOLOv3, we devise to reduce the impact of resizing operation. The two networks allow us to compare the performance of object detection between using original and super-resolved images. We quantify the effect of each super-resolution techniques as well.

The foundation of both advanced driving assistance system(ADAS) and automated driving (AD) is an accurate environment perception system(EPS). However, evaluation and test method of EPS are seldom studied. In this paper, naturalistic driving environment was studied and test scenarios for EPS under rear-end collision risk were proposed accordingly. To describe driving environment, a new concept named environment perception element(EPE) was first proposed in this paper, which refers to all the objects that the EPS must perceive during driving. Typical environment perception elements include weather and light conditions, road features, road markings, traffic signs, traffic lights, other vehicles, pedal cyclists and pedestrians and others. Driving behaviors collected in Shanghai, China were classified and rear-end collision risk scenarios were obtained and described using EPEs. Probability distribution of EPEs was therefore obtained.

In this study, the real-world NOx and particle emissions of buses burning pure diesel fuel (D100), biodiesel fuel with 20% blend ratio (B20) and liquefied natural gas (LNG) were measured with portable emission measurement system (PEMS). The measurement conducted at 6 constant speed, which ranged from 10km/h to 60 km/h at 10km/h intervals, and a period of free driving condition. The relationship between vehicle specific power (VSP) and NOx/particle emissions of each bus were analyzed. The results show that the change rules of NOx, PN and PM emission factors with the increase of VSP were basically the same for the same bus, but for the bus using different fuel, the change rules may change. In VSP bin 0, the vehicles were mostly in idle condition and the emission factors of NOx, PN and PM of three buses were all in a relatively high level. In low VSP interval, which ranged from bin 0 to bin 4, the emissions of three buses first decreased and then increased with the growth of VSP.

The present work proposed to implement oxy-fuel combustion mode into a homogeneous charge compression ignition engine to reduce complexity in engine emissions after-treatment and lower carbon dioxide emission. The combination of oxy-fuel combustion mode with homogeneous charge compression ignition engine can be further optimized by the utilization of direct high temperature and pressure water injection to improve cycle performance. A retrofitted conventional diesel engine coupled with port fuel injection and direct water injection is utilized in this study. A self-designed oxygen and carbon dioxide mixture intake system with flexible oxygen fraction adjustment ability is implemented in the test bench to simulate the adoption of exhaust gas recirculation. Water injection system is directly installed in the combustion chamber with a modified high speed solenoid diesel injector.

The rapid development of the automobile industry has brought energy and environmental issues that scholars are increasingly concerning about. Improving efficiency and reducing emissions are currently two hot topics in the internal combustion engine industry. Direct water injection technology (DWI) can effectively reduce the cylinder temperature, which is due to the absorption of the heat by the injecting liquid water. In addition, lower temperature in the cylinder will reduce the formation of NO. In this paper, a CFD simulation of DWI application in a lean-burning single-cylinder engine with pre-chamber jet ignition was carried out. And the engine was experimentally tested for the simulation model validation. And then the effect of DWI strategy with different injecting water mass on the combustion and emissions characteristics are analyzed. Physically, injected water not only absorbs heat but also provides heat insulation.

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.

Compared with ordinary gasoline, using ethanol gasoline blends as fuel of Internal Combustion Engine is beneficial for the performance of power, economy and emission of engine. However, the fuel ethanol blended in ethanol gasoline blends currently is usually anhydrous ethanol, which requires dewatering implementer in production process, and the cost is high. Therefore, the production cost can be significantly reduced by replacement of anhydrous ethanol with hydrous ethanol while exerting the advantage of ethanol gasoline blends. In this study, computation fluid dynamics (CFD) software CONVERGE is employed to establish a simulation model of an actual gasoline direct injection (GDI) engine, and investigate the effect of burning hydrous ethanol gasoline blends and different injection strategy on combustion process and emission, and the validity of the model was validated by experiments.

The diesel particulate filter (DPF) is an effective device for reducing particulate emissions from diesel engines, while its durability and reliability after long-term use are causes for concern. Usually, particulates are considered to be uniformly deposited in DPF channels to form a cake or end plug, however, recent studies have found that a “middle channel deposit” phenomenon of particulates can form a bridge near the middle of the DPF channel. This phenomenon has serious adverse effects on the durability and reliability of the DPF, including abnormally increased pressure drop and frequent regeneration. Since the width of the DPF channel is only about 1-2 millimeters, conventional methods cannot observe the particulate deposition process inside the DPF.

Based on the working model of a diesel engine, the influence of 2 Miller cycle strategies-Early Intake Valve Closure (EIVC) and Late Intake Valve Closure (LIVC) on the combustion and emissions of diesel engine was analyzed. Then the working condition of each Miller cycle strategies on the engine under the rated speed was optimized through the adjust of the valve timing, boost pressure and the injection timing. The research found that both delaying and advancing the closure timing of the intake valve can decrease the pressure and temperature during compression stroke, prolonging the ignition delay. However, due to the decrease of the working media inside the cylinder, the average in-cylinder temperature and soot emissions will increase, which can be alleviated by raising the boost pressure and the resulting compensation of the intake loss.

The camera-based advanced driver assistance systems (ADAS) like lane departure warning system (LDWS) and lane keeping assist (LKA) can make vehicles safer and driving easier. Lane detection is indispensable for these lane-based systems for achieving vehicle local localization and behavior prediction. Since the vision is vulnerable to the variable environment conditions such as bad weather, occlusions and illumination, the robustness is important. In this paper, a robust algorithm for detecting and tracking multiple lanes with arbitrary shape is proposed. We extend the previously lane detection and tracking process from the space domain to the temporal-spatial domain by using a more robust and general multi-lane model. First, new slice images containing temporal information are generated from image sequences. Instead of binarization process, we use a more general detector for extracting the lane marker candidates with prior knowledge to generate the binary slice image.