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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.

Recently, electro-hydraulic brake systems (EHB) has been developed to take place of the vacuum booster, having the advantage of faster pressure build-up and continuous pressure regulation. In contrast to the vacuum booster, the pressure estimation for EHB is worth to be studied due to its abundant resource (i.e. electric motor) and cost-effective benefit. This work improves an interconnected pressure estimation algorithm (IPEA) based on actuator characteristics by introducing the vehicle dynamics and validates it via vehicle tests. Considering the previous IPEA as the prior pressure estimation, the wheel speed feedback is used for modification via a proportional-integral (PI) observer. Superior to the IPEA based on actuator characteristics, the proposed PEA improves the accuracy by more than 20% under the mismatch of pressure-position relation.

In the autonomous driving perception task, the accuracy of target detection is an essential evaluation, especially for small targets. In this work, we propose a multi-sensor fusion neural network that combines radar and image data to improve the confidence level of the camera when detecting targets and the accuracy of the prediction box regression. The fusion network is based on the basic structure of single-shot multi-box detection (SSD). Inspired by the attention mechanism in image processing, our work incorporates the a priori knowledge of radar detection in the convolutional block attention module (CBAM), which forms a new attention mechanism module called radar convolutional block attention module (RCBAM). We add the RCBAM into the SSD target detection network to build a deep neural network fusing millimeter-wave radar and camera.

Water content estimation is a key problem for studying the PEM fuel cell. When several hundred fuel cells are connected in serial and their active surface area is enlarged for sufficient power, the difference between cells becomes significant with respect to voltage and water content. The voltage of each cell is measurable by the cell voltage monitor (CVM) while it is difficult to estimate water content of the individual. Resistance of the polymer electrolyte membrane is monotonically related to its water content, so that the new online high frequency resistance (HFR) measurement technique is investigated to identify the uniformity of water content between cells and analyze its sensitivity to operating conditions in this paper. Firstly, the accuracy of the proposed technique is experimentally validated to be comparable to that of a commercialized electrochemical impedance spectroscopy (EIS) measurement equipment.

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.

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.

Smart electric vehicles need more accurate and more timely information as well as control than traditional vehicles, which depends on great environmental sensors such as millimeter-wave radar. In this way, the electromagnetic compatibility of whole vehicle would confront more serious challenges because of its high frequency range. Thus, this paper studies the electromagnetic distribution and electromagnetic interference suppression of smart electric vehicles with the followings. Firstly, the millimeter wave radar is modeled and optimized. Micro strip patch antenna, with small size, light mass and low cost, is used as array element of antenna. Millimeter wave radar is modeled and simulated step by step from array element to line array to planar matrix. Then the Cross Shape - Uniplanar Compact - Electromagnetic Band Gap (CS-UC-EBG) structure is deployed to optimize its electromagnetic characteristics, based on finite time domain difference model theory.

Electromechanical Braking System (EMB) stops the wheel by motor and related enforce mechanism to drive braking pads to clamp the friction plate. It is compact in sized as well as faster in response, which solves the issue of potential leakage and slows response of traditional hydraulic brake system. The institutions at home and abroad have put forward all kinds of new structural schemes of EMB. At present, there are various EMB structural schemes, but the analysis and evaluation of these schemes are relatively few. In this paper, on the basis of a large number of research, the EMB actuator is modular decomposed according to function ,then the parametric 3D model library of each function module is established. According to brake requirements of the target vehicle, a development platform is set up to match EMB actuator structure scheme quickly.

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.

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.

Faced with intricate traffic conditions, the single sensor has been unable to meet the safety requirements of Advanced Driver Assistance Systems (ADAS) and autonomous driving. In the field of multi-target tracking, the number of targets detected by vision sensor is sometimes less than the current tracks while the number of targets detected by millimeter wave radar is more than the current tracks. Hence, a multi-sensor information fusion algorithm is presented by utilizing advantage of both vision sensor and millimeter wave radar. The multi-sensor fusion algorithm is based on centralized fusion strategy that the fusion center takes a unified track management. At First, vision sensor and radar are used to detect the target and to measure the range and the azimuth angle of the target. Then, the detections data from vision sensor and radar is transferred to fusion center to join the multi-target tracking with the prediction of current tracks.

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.