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Vehicle sideslip angle estimation is of great importance to the vehicle stability control as it could not be measured directly by ordinary vehicle-mounted sensors. As a result, researchers worldwide have carried out comprehensive research in estimating the vehicle sideslip angle. First, as the attitude would affect the acceleration information measured by the IMU directly, different kinds of vehicle attitude estimation methods with multi-sensor fusion are presented. Then, the estimation algorithms of the vehicle sideslip angle are classified into the following three aspects: kinematic model based method, dynamic model based method, and fusion method. The characteristics of different estimation algorithms are also discussed. Finally, the conclusion and development trend of the sideslip angle estimation are prospected.

Fuel cell electric vehicles (FCEVs) require multiple components to operate properly, and the fuel cell stack—the source of power—is one of the most important components. While the number of enterprises manufacturing and selling fuel cell stacks is increasing globaly year after year, the residual challenges of core components and technologies still need to be resolved in order to keep pace with the development of lithium-ion batteries (i.e., its primary competitor). Additionally, many production and distribution standards are seen as unsettled. These barriers make large-scale commercialization an issue. Use of Proton-exchange Membrane Fuel Cells in Ground Vehicles explores the opportunities and challenges within the PEMFC industry. With the help of expert contributors, a critical overview of fuel cells and the FCEV industry is presented, and core technology, applications, costs, and trends are analyzed.

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.

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.

The catalyzed diesel particulate filter with Pt and Pd noble metals as the main loaded active components are widely used in the field of automobile engines, but the high cost makes it face huge challenges. Rare earth element doping can improve the soot oxidation performance of the catalyzed diesel particulate filter and provide a new way to reduce its cost. In this paper, thermogravimetric tests and chemical reaction kinetic calculations were used to explore the effect of Pt-Pd catalysts doped Ce, and La rare earth elements on the oxidation properties of soot. The results shown that, among Pt-Pd-5%Ce, Pt-Pd-5%La, and Pt-Pd-5%Ce-5%La catalysts, Pt-Pd-5%La catalyst has the highest soot conversion, the highest low-temperature oxidation speed, and the activation energy is the smallest. Compared with soot, this catalyst reduced T10 and T20 by 82% and 26%, respectively, meaning the catalytic activity of Pt-Pd-5%La catalyst was the best.

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.

Intelligent and connected vehicle (ICV) and new energy vehicle (NEV) will be two important directions of the automotive technology in the future, and the coordinated development of these two directions reflects relevantly the higher requirements put forward by nowadays society and people. Through the use of intelligent and connected technology (ICT), NEVs can exchange various traffic information data with the outside world (e.g. other running vehicles, road infrastructure, internet, etc.) in real time, which is so-called Vehicle to Everything (V2X). Based on the further analysis of the mutual traffic information, the vehicles can identify the current driving conditions and predict the future driving conditions effectively, which can realize the real time optimization of the energy management strategies (EMSs) of vehicles’ powertrain system, so as to meet the driving requirements of vehicles under different driving conditions.

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.

Deep neural network models have been widely used for environment perception of intelligent vehicles. However, due to models’ innate probabilistic property, the lack of transparency, and sensitivity to data, perception results have inevitable uncertainties. To compensate for the weakness of probabilistic models, many pieces of research have been proposed to analyze and quantify such uncertainties. For safety-critical intelligent vehicles, the uncertainty analysis of data and models for environment perception is especially important. Uncertainty estimation can be a way to quantify the risk of environment perception. In this regard, it is essential to deliver a comprehensive survey. This work presents a comprehensive overview of uncertainty estimation in deep neural networks for environment perception of intelligent vehicles.

Regulated gaseous and particulate matter (PM) emissions in the exhaust from a heavy duty diesel engine with biodiesel fuel were studied, and the emission characteristics of PM and polycyclic aromatic hydrocarbons (PAHs) emissions in PM were highlighted. In the experiment, pure diesel fuel and B10 (a blend of diesel and biodiesel fuels with the volume ratio of 9 to 1) fuel were chosen. The study shows that, compared to the pure diesel, the emissions of PM, soluble organic fractions (SOF) and PAHs from the heavy duty diesel engine decrease when the engine burns B10 fuel, and the nitrogen oxides (NOx) emission slightly increases, while the unburned hydrocarbon (HC) and carbon monoxide (CO) emissions also decline. Among the detected 12 kinds of PAHs, emission concentrations of 10 kinds of PAHs from the engine with B10 descend. Especially Benzo(a)pyrene equivalent toxicity (BEQ) analysis results show that the BEQ of B10 fuel decreases by 15.2% compared to pure diesel.

A biodiesel fuel, obtained from Jatropha seed in China, was tested in a direct injection, high pressure common-rail diesel engine for passenger cars. Effects of biodiesel on particle number and size distribution of the diesel engine are studied using an Engine Exhaust Particle Sizer (EEPS). Base petroleum diesel fuel, 10% and 20% v/v biodiesel blends with the base petroleum diesel fuel, the biodiesel fuel (B0, B10, B20 and B100 fuels) were tested without engine modification. For all test fuels, the particle number and size distribution show unimodal or bimodal log-normal distribution, with a nucleation mode peak value in 6.04nm to 10.8nm particle diameter, and with an accumulation mode peak value in 39.2nm to 60.4nm particle diameter.

Startup from subzero temperature is one of the major challenges for polymer electrolyte membrane fuel cell (PEMFC) to realize commercialization. Below the freezing point (0°C), water will freeze easily, which blocks the reactant gases into the reaction sites, thus leading to the start failure and material degradation. Therefore, for PEMFC in vehicle application, finding suitable ways to reach successful startup from subfreezing environment is a prerequisite. As it’s difficult and complex for experimental studies to measure the internal quantities, mathematical models are the effective ways to study the detailed transport process and physical phenomenon, which make it possible to achieve detailed prediction of the inner life of the cell. However, review papers only on cold start numerical models are not available. In this study, an extensive review on cold start models is summarized featuring the states and phase changes of water, heat and mass transfer.

Ammonia is employed as the carbon-free fuel in the future engine, which is consistent with the requirements of the current national dual-carbon policy. However, the great amount of NOx and unburned NH3/H2 in the exhaust emissions is produced from combustion of ammonia and is one kind of the most strictly controlled pollutants in the emission regulation. This paper aims to investigate the NOx and unburned NH3/H2 generative process and emission characteristics by CFD simulation during the engine combustion. The results show that the unburned ammonia and hydrogen emissions increase with an increase of equivalence ratio and hydrogen blending ratio. In contrast, the emission concentrations of NOx, NO, and NO2 decrease with the increasing of equivalence ratio, but increase with hydrogen blending ratio rising. The emission concentration of N2O is highly sensitive to the O/H group and temperature, and it is precisely opposite to that of NO and NO2.

Lightweight automobile has an important role in saving the energy, improving the fuel economy and reducing the exhaust emission. However, reducing the mass of the automobile need to meet the structural and NVH (Noise, Vibration and Harshness) performance requirements. With the rapid development of Computer Aided Engineering (CAE) technology, more and more people tend to research the complex engineering application problem by computer simulation. An important challenge in today's simulation is the Multidisciplinary Design Optimization (MDO) of an automobile, including mass, stiffness and modal etc. This paper presents a MDO study in a minicar hatchback.

The main challenge for future autonomous vehicles is to identify their location and body pose in real time during driving, that is, “where am I? and how will I go?”. We address the problems of pose estimation and scene perception from continuous visual frames in intelligent vehicle. Recent advanced technology in the domain of deep learning proposes to train some learning models for vehicle’s series detection tasks in a supervised or unsupervised manner, which has numerous advances over traditional approaches, mainly reflected in the absence of manual calibration and synchronization of the camera and IMU. In the paper, we propose a novel approach for pose estimation and scene recognition with a deep fusion of multi-modal neural features in the manner of unsupervised. Firstly, low-cost camera and IMU are used to extract original visual and inertial data, then the visual and inertial encoders are utilized to encoder the feature of the two modes.