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Positioning system is a key module of autonomous driving. As for LiDAR SLAM system, it faces great challenges in scenarios where there are repetitive and sparse features. Without loop closure or measurements from other sensors, odometry match errors or accumulated errors cannot be corrected. This paper proposes a construction method of LiDAR anchor constraints to improve the robustness of the SLAM system in the above challenging environment. We propose a robust anchor extraction method that adaptively extracts suitable cylindrical anchors in the environment, such as tree trunks, light poles, etc. Skewed tree trunks are detected by feature differences between laser lines. Boundary points on cylinders are removed to avoid misleading. After the appropriate anchors are detected, a factor graph-based anchor constraint construction method is designed. Where direct scans are made to anchor, direct constraints are constructed.

Image corruptions due to noise, blur, contrast change, etc., could lead to a significant performance decline of Deep Neural Networks (DNN), which poses a potential threat to DNN-based autonomous vehicles. Previous works attempted to explain corruption from a Fourier perspective. By comparing the absolute Fourier spectrum difference between corrupted images and clean images in the RGB color space, they regard the noise from some corruptions (Gaussian noise, defocus blur, etc.) as concentrating on the high-frequency components while others (contrast, fog, etc.) concentrate on the low-frequency components. In this work, we present a new perspective that unifies corruptions as noise from high frequency and thus propose an image augmentation algorithm to achieve a more robust performance against common corruptions. First, we notice the 1/fα statistical rule of the natural image's spectrum and the channels-wise differential sensitivity on the YCbCr color space of the Human Visual System.

With the growing prosperity of the long-distance freight and urban logistics industry, the demand for cargo trucks is gradually increasing. The connecting bracket is the critical connecting part of the truck chassis, which bears the load transmitted by the road excitation and reduces the damage to the frame caused by the load. However, the occurrence of rough road conditions is inevitable in heavy-duty transportation. In this paper, road durability tests and fatigue life analysis are carried out on the original structure to ensure the safety of the vehicle. Based on the known boundary and load constraints, a lightweight and high-performance structure is obtained through size optimization, as the original structure cannot meet the performance requirements. Firstly, the road test was conducted on the truck where the original bracket structure is located.

This paper constructs the Accident Crash Scenarios(ACSs) classification system based on the traffic accident data collected by the traffic management department in a Chinses city from 2013 to 2015. The classification system selects four influenced variables on the basis of Critical Driving Scenarios(CDSs) in Naturalistic Driving Data. The proportions of each variable are analyzed, and all ACSs are divided into 48 scenarios. The highest proportion of nine ACSs are extracted from all 10596 ACSs, and the result shows the ACSs involved Car-Pedalcyclist occupy the top four scenarios, and the scenarios involved intersection situations are worth attention. Pedalcyclists include bicyclists, motorcyclists, tri-cyclists and electric bicyclists. Multivariate Logistic Regression(MLR) analysis is then used to study the ACSs involved the type of Car-Pedalcyclist.

LiDAR and camera fusion have emerged as a promising approach for improving place recognition in robotics and autonomous vehicles. However, most existing approaches often treat sensors separately, overlooking the potential benefits of correlation between them. In this paper, we propose a Cross- Modality Module (CMM) to leverage the potential correlation of LiDAR and camera features for place recognition. Besides, to fully exploit potential of each modality, we propose a Local-Global Fusion Module to supplement global coarse-grained features with local fine-grained features. The experiment results on public datasets demonstrate that our approach effectively improves the average recall by 2.3%, reaching 98.7%, compared with simply stacking of LiDAR and camera.

In this paper, it was researched the degradation characteristics of catalytic performance of three kinds of DPFs (C1, C2 and C3, with precious metal concentrations being 15, 25 and 35 g/ft3 respectively) after diesel truck aging. It is found out that the crystallinity of three kinds of DPF samples (Used) in full vehicle aging was higher than that of fresh samples (Fresh) and aged samples (Aged) in the laboratory. Compared with Fresh samples, the concentration of Pt atom in precious metal on the surface of Aged and Used samples tends to decrease in most cases. Activities to CO and C3H8 of Aged and Used samples of three kinds of DPFs had all been degraded, and activity degradation showed a substantial correlation with concentration reduction rate of precious metal on the carrier surface. NO2 productivity of Used samples all rose. Crystallinity of DPF samples after full vehicle aging in Inlet, Middle and Outlet areas successively increased.

A specially designed generator has been developed to produce poly-disperse droplet streams: A liquid fuel (n-heptane) is metered to an ultrasonic atomizer to produce droplets, which are then carried and accelerated vertically upwards through a nozzle tube by carrier-air flow. Conditions of the streams at the nozzle exit are modulated by varying the length of nozzle tubes, the fuel and carrier-air flow rate. Optical measurement techniques such as direct photography method, schlieren photography and particle image velocimetry (PIV) are employed to characterize its performance characteristics. Effects of the nozzle tube length, the carrier-air and fuel flow rate are investigated to evaluate the performance of the generator. Longer nozzle tubes provide a better flow guidance for the carrier-air, and tend to generate streams with less and smaller droplets due to the transporting losses.

Battery state estimation is one of the most important decision parameters for lithium battery energy management. It plays an important role in improving battery energy utilization, ensuring battery safety and enhancing system reliability. This paper is proposed to provide a dynamic correction of SOC in the full working condition, including static condition and dynamic condition. Based on the Coulomb-counting method, the current SOC value of the battery is calculated. Under the static conditions, the open circuit voltage of the battery is used to directly collect the initial SOC. Under the dynamic working conditions, the open circuit voltage of the battery is estimated by the sliding mode observer. Based on the deviation between the calculated and estimated values of the open circuit voltage, the current coefficient of the Coulomb-counting method is dynamically corrected by PI strategy.

Durability performance prediction is a critical issue in fuel cell research. During the demonstration operation of fuel cell commercial vehicles in China, this issue has attracted more attention. In this article, the long short-term memory neural network (LSTMNN), which is an improved recurrent neural network (RNN), and the demonstration operation data are used to establish the prediction model to predict the durability performance of the fuel cell stack. Then, a model based on a back-propagation neural network (BPNN) is established to be a control group. The demonstration operation data is divided into training group and validation group. The former is used to train the prediction model, and the latter is used to verify the validity and accuracy of the prediction model. The outputs of the prediction model, as the durability performance evaluation indexes of the fuel cell, are the polarization curve (current-voltage curve) and the voltage decay curve (time-voltage curve).

The port structure consisting of spur pile, vertical pile and beam is subjected to impact loads, so its internal stress state of each point will rapidly change over time. Dynamic photoelastic method is used to study the dynamic stress and stress wave propagation. With epoxy resin and other materials, a photoelastic model of beam to column connection structure is processed and product. The dynamic response of the model under the impact load by the free fall is researched by the dynamic photoelastic method, and recorded by the new digital dynamic photoelastic system with a laser source and high-speed photography system. The internal dynamic stress propagation and distribution, the maximum shear stress and the dynamic stress concentration problems can be obtained by analyzing the dynamic response.

There are a large number of uncertainties in engineering design, and the accumulated uncertainties will enlarge the overall failure probability of the structure system. Therefore, structural design considering uncertainties has good guiding significance for improving the reliability of engineering structures. To address this issue, the dynamic-static structural topology optimization is established and reliability-based topology optimization with decoupling format is conducted in this study. The design point which satisfying the constraint of the target reliability indicator is obtained according to the reliability indicators of the first-order reliability method, and the uncertain design variables are modified into a deterministic variable according to the sensitivity information.

In this study, the effect of volatile fractions from engine lubricating oil on diesel particle emissions were studied experimentally. One commercial CF lubricating oil was used and distilled to subtract the different volatile fractions with boiling temperature of 220 °C, 260 °C and 300 °C, respectively. Oils derived from this distillation process were applied as the lubricating oil and following engine experiments were conducted. Diesel primary particles were sampled with a costume designed thermophoretic system. A fast response particulate spectrum equipment was employed to study the size distribution and number concentration of particles in the exhaust. Transmission electron microscopy was used to characterize the size distribution of the primary diesel particles relates to different oil volatile fractions.

As one of the pollutants that cannot be ignored, soot has a great impact on human health, environment, and energy conversion. In this investigation, the effect of residence time (25ms, 35ms, and 45ms) and ammonia on morphology and nanostructure of soot in laminar ethylene flames has been studied under atmospheric conditions and different flame heights (15 mm and 30 mm). The transmission electron microscopy (TEM) and high-resolution transmission electron microscope (HRTEM) are used to obtain morphology of aggregates and nanostructure of primary particles, respectively. In addition, to analyze the nanostructure of the particles, an analysis program is built based on MATLAB software, which is able to obtain the fringe separation distance, fringe length, and fringe tortuosity parameters of primary particles, and has been verified by the multilayer graphene interlayer distance.

External rear view mirror is attached at the side of the vehicle which is to permit clear vision for the driver to the rear of the vehicle. When the vehicle is running, the flow field around external rear view mirror is highly three-dimensional, unsteady, separated and turbulent which is known to be a significant source of aerodynamic noise and a contributor to the total drag force on the vehicle. While among all the researches on the flow field around external rear view mirror, different installation environment were employed. The external rear view mirror is mounted on a production car in most researches which presents the real condition and it can also be mounted on the ground of a wind tunnel, a specially designed table, or a generic vehicle model based on the SAE model. While, the relationship between the flow field around external rear view mirror and the installation environment is not very clear.

In order to satisfy design requirements of Lane Keeping Assistance System (LKAS), a Driver Steering Override (DSO) strategy is necessary for driver’s interaction with the assistance system. The assistance system can be overridden by the strategy in case of lane change, obstacle avoidance and other emergency situations. However, evaluation and optimization of the DSO strategy for LKAS cannot easily be completed quantitatively considering driver’s acceptability. In this research, firstly subjective and objective evaluation experiment is designed. Secondly, correlations between the subjective and the objective evaluation results are established by using regression analysis. Finally, based on the correlations established previously, the optimal performance of DSO strategy is obtained by setting the desired comprehensive evaluation ratings as the optimized goal.

Proton exchange membrane fuel cell (PEMFC) system is considered as one of the most popular power sources because of its high energy density, fast dynamic response and zero pollution. However, the start-up at low temperature (e.g. - 30 °C) is still a major challenge for its wide application due to water freezing in Membrane Electrode Assembly (MEA). In this paper, a cold start test process in an environment cabin with auxiliary heat was carried out for a full power automotive PEMFC system, including normal operation, shutdown purge and cold start processes analysis from -30°C. Rated power of this stack is 100kW at the current density of 1.4A/cm2 and relevant maximum output power can reach to 120kW. In order to reduce the damage of high potential to MEA, on-load purge with a current of 30A is conducted to removing extra water in stack for improving cold start ability. Based on corresponding control strategy, cold start was realized successfully within 110s.

This paper reports an experimental investigation of the wake flow behind a 1/12 scale notchback MIRA model at Re = UL/ν = 6.9×105 (where U is free-stream velocity, L the length of the model and ν viscosity). Focus is placed on the flow asymmetry over the backlight and decklid. Forty pressure taps are used to map the surface pressure distribution on the backlight and decklid, while the wake topology is investigated by means of 2D Particle Image Velocimetry. The analysis of the instantaneous pressure signals over the notch configuration clearly shows that the pressure presents a bi-stable behavior in the spanwise direction, characterized by the switches between two preferred values, which is not found in the vertical direction.

In this study, effects of altitude on free diesel spray morphology, macroscopic spray characteristics and air-fuel mixing process were investigated. The diesel spray visualization experiment using high-speed photography was performed in a constant volume chamber which reproduced the injection diesel-like thermodynamic conditions of a heavy-duty turbocharged diesel engine operating at sea level and 1000 m, 2000 m, 3000 m and 4500 m above sea level. The results showed that the spray morphology became narrower and longer at higher altitude, and small vortex-like structures were observed on the downstream spray periphery. Spray penetration increased and spray angle decreased with increasing altitude. At altitudes of 0 m, 1000 m, 2000 m, 3000 m and 4500 m, the spray penetration at 1.45 ms after start of injection (ASOI) were 79.54 mm, 80.51 mm, 81.49 mm, 83.29 mm and 88.92 mm respectively, and the spray angle were 10.9°, 10.8°, 10.7°, 10.4°and 9.8° respectively.

Sealing system is an important subsystem of modern high-performance engine. Sealing system reliability directly affects the engine operating conditions. Cylinder head gaskets(CHG) sealing system is of the most importance to the engine sealing system, which is not only responsible for sealing chamber, the cooling fluid and lubricating oil passage, for preventing gas leakage, water leakage and oil leakage, but also responsible for force transferring between cylinder head and cylinder body. Basing on nonlinear solution method, the sealing performance of multi-layer-steel cylinder head gaskets to a gasoline engine is studied with the finite element software ABAQUS. The deformations of the cylinder liners and engine block are also considered.

The scenario-based test method is now drawing more and more attention in the field of the test for autonomous vehicles. The predefined scenarios are used in the safety verification and performance evaluation of autonomous vehicles. However, the traditional generation method for predefined scenarios is parameterized and open-looped, which makes it challenging to generate diverse and complex scenarios. It is critical when testing high-level autonomous vehicles to verify their reliability in multiple behavior transitions. In this paper, a generation method for the continuous scenario is proposed to realize a function-driven iteration of scenarios for autonomous driving systems (ADS). The method consists of a functional model of ADS and a formal description of abstract scenario.