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With the popularity of automated vehicles, the future mixed traffic flow contains automated vehicles with different degrees of intelligence developed by other manufacturers. Therefore, simulating the interaction behavior of automated vehicles with varying levels of intelligence is crucial for testing and evaluating autonomous driving systems. Since the algorithm of traffic vehicles with various intelligence levels is difficult to obtain, it leads to hardships in quantitatively characterizing their interaction behaviors. Therefore, this paper designs a new automated vehicle test platform to solve the problem. The intelligent vehicle testbed with multiple personalized in-vehicle control units in the loop consists of three parts: 1. Multiple controllers in the loop to simulate the behavior of traffic vehicles；2. The central console applies digital twin technology to share the same traffic scenario between the tested vehicle and the traffic vehicle, creating a mixed traffic flow. 3.

With increasing pressure from environment problem for reduction in CO2 emissions and stricter fuel targets from road vehicles, new transmission technologies are gaining more attention in different main market. To get suitable road load data for transmission durability development is becoming increasingly important and can shorten the development time of new transmission. This paper presents the procedure and methods of road load data development for durability design of transmission product and optimization based on the real road data measurement, statistical characteristics evaluation and fatigue damage equivalency. Apply this road load data method procedure on 3 type of vehicle which represent conventional vehicle, BEV and HEV.

A rapid path-planning algorithm that generates drivable paths for an autonomous vehicle operating in structural road is proposed in this paper. Cubic B-spline curve is adopted to generating smooth path for continuous curvature and, more, parametric basic points of the spline is adjusted to controlling the curvature extremum for kinematic constraints on vehicle. Other than previous approaches such as inverse kinematics, model-based prediction postprocess approach or closed-loop forward simulation, using the kinematics model in each iteration of path for smoothing and controlling curvature leading to time consumption increasing, our method characterized the vehicle curvature constraint by the minimum length of segment line, which synchronously realized constraint and smooth for generating path. And Differ from the path of robot escaping from a maze, the intelligent vehicle traveling on road in structured environments needs to meet the traffic rules.

Parallel-connected modules have been widely used in battery packs for electric vehicles nowadays. Unlike series-connected modules, the direct state inconsistency caused by parameter inconsistency in parallel modules is current and temperature non-uniformity, thus resulting in the inconsistency in the speed of aging among cells. Consequently, the evolution pattern of parameter inconsistency is different from that of series-connected modules. Since it’s practically impossible to monitor each cell’s current and temperature information in battery packs, considering cost and energy efficiency, it’s necessary to study how the parameter inconsistency evolves in parallel modules considering the initial parameter distribution, topology design and working condition. In this study, we assigned cells of 18650 format into several groups regarding the degree of capacity and resistance inconsistency. Then all groups are cycled under different environmental temperature and current profile.

To promote the development of automated vehicles (AVs), large scale of field operational tests (FOTs) were carried out around the world. Applications of naturalistic driving data should base on correlative scenarios. However, most of the existing scenario typologies, aiming at advanced driving assistance system (ADAS) and extracting discontinuous fragments from driving process, are not suitable for AVs, which need to complete continuous driving tasks. In this paper, a systematic scenario-typology consisting of four layers (from top to bottom: trip, cluster, segment and process) was first proposed. A trip refers to the whole duration from starting at initial parking space to parking at final one. The basic units ‘Process’, during which the vehicle fulfils only one driving task, are classified into parking process, long-, middle- and short-time-driving-processes. A segment consists of two neighboring long-time-driving processes and a middle or/and short one between them.

The adhesion control is the basic technology of active safety for the four-wheel driven EV. In this paper, a novel adhesion control method based on fuzzy logic control is proposed. The control system can maximize the adhesion force without road condition information and vehicle speed signal. Also, the regulation torque to prevent wheel slip is smooth and the vehicle driving comfort is greatly improved. For implementation, only the rotating speed of the driving wheel and the motor driving torque signals are needed, while the derived information of the wheel acceleration and the skid status are used. The simulation and road test results have shown that the adhesion control method is effective for preventing slip and lock on the slippery road condition.

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.

A 2 DOF nonlinear dynamic model of the automotive wiper system is established. Complex eigenvalues are calculated based on the complex modal theory, and the system stability as well as its dependence on wiping velocity is analyzed. Bifurcation characteristics of frictional self-excited vibration and stick-slip vibration relative to wiping velocity are studied through numerical analysis. Research of nonlinear vibration characteristics under various wiping velocities is conducted by means of phase trajectories, Poincaré map and frequency spectrum. The pervasive stick-slip vibration during wiping is confirmed, and its temporal and spatial distributions are analyzed by way of time history and contour map. Duty ratio of stick vibration and statistics of scraping residual are introduced as quantitative indexes for wiping effect evaluation. Results indicate that the negative slop of frictional-velocity characteristic is the root cause of system instability.

In this study, the vibroacoustic characteristics and torque fluctuation of switched reluctance motors (SRMs) with different phases and poles have been analyzed in detail. Also, the common four SRMs, i.e., three-phase 6/4 SRM, four-phase 8/6 SRM, five-phase 10/8 SRM, and six-phase 12/10 SRM, have been selected. First, the spatial-temporal distribution characteristics of radial force in SRMs were revealed by virtue of the analytical derivation, which was validated by the 2D Fourier decomposition based on the finite-element results of radial force. Second, a multiphysics model, which was composed of an electromagnetic field, a mechanical field, and an acoustic field, was established to predict the noise behaviors of SRMs with different phases and poles. Third, the relationship between the torque fluctuation and the phases / poles of SRMs, and the relationship between the noise and the radial force / phases / poles are all analyzed.

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.

Due to the advantages of low weight, low emissions and good fuel economy, downsized turbocharged gasoline direct injection (GDI) engines are widely-applied nowadays. However, Low-Speed Pre-Ignition (LSPI) phenomenon observed in these engines restricts their improvement of performance. Some researchers have shown that auto-ignition of lubricant in the combustion chamber has a great effect on the LSPI frequency. To study the auto-ignition characteristics of lubricant, an innovative single droplet auto-ignition test system for lubricant and its mixture is designed and developed, with better accuracy and effectiveness. The experiments are carried out by hanging lubricant droplets on the thermocouple node under active thermo-atmosphere provided by a small “Dibble burner”. The auto-ignition process of lubricant droplets is recorded by a high-speed camera.

In this paper, characteristics of gas emission and particle size distribution are investigated in a common rail diesel engine fueled with biodiesel blends. Gas emission and particle size distribution are measured by AVL FTIR - SESAM and SMPS respectively. The results show that although biodiesel blends would result in higher NOx emissions, characteristics of NOx emissions were also dependent on the engine load for waste cooking oil methyl ester. Higher blend concentration results in higher NO2 emission after two diesel oxidation catalyst s (DOC). A higher blend concentration leads to lower CO and SO2 emissions. No significant difference of Alkene emission is found among biodiesel blends. The particle size distributions of diesel exhaust aerosol consist of a nucleation mode (NM) with a peak below 50N• m and an accumulation mode with a peak above 50N • m. B100 will result in lower particulates with the absence of NM.

As a novel ignition technology, pre-chamber ignition can enhance ignition energy, promote flame propagation, and augment turbulence. However, this technology undoubtedly faces challenges, particularly in the context of emission regulations. Of this study, the transient characteristics of combustion and emissions in a hybrid electric vehicle (HEV) gasoline engine with active pre-chamber ignition (PCI) under the first combustion cycle of quick start are focused. The results demonstrate that the PCI engine is available on the first cycle for lean combustion, such as lambda 1.6 to 2.0, and exhibit particle number (PN) below 7×107 N/mL at the first cycle. These particles are predominantly composed of nucleation mode (NM, <50 nm) particles, with minimal accumulation mode (AM, >50 nm) particles.

With the extension of intelligent vehicles from individual intelligence to group intelligence, intelligent vehicle platoons on intercity highways are important for saving transportation costs, improving transportation efficiency and road utilization, ensuring traffic safety, and utilizing local traffic intelligence [1]. However, there are several problems associated with vehicle platoons including complicated vehicle driving conditions in or between platoon columns, a high degree of mutual influence, dynamic optimization of the platoon, and difficulty in the cooperative control of lane change. Aiming at the dual-column intelligent vehicle platoon control (where “dual-column” refers to the vehicle platoon driving mode formed by multiple vehicles traveling in parallel on two adjacent lanes), a multi-agent model as well as a cooperative control method for lane change based on null space behavior (NSB) for unmanned platoon vehicles are established in this paper.

The operation management of electric Taxi fleets requires cooperative optimization of Charging and Dispatching. The challenge is to make real-time decisions about which is the optimal charging station or passenger for each vehicle in the fleet. With the rapid advancement of Vehicle Internet of Things (VIOT) technologies, the aforementioned challenge can be readily addressed by leveraging big data analytics and machine learning algorithms, thereby contributing to smarter transportation systems. This study focuses on optimizing real-time decision-making for charging and dispatching in large-scale electric taxi fleets to improve their long-term benefits. To achieve this goal, a spatiotemporal decision framework using Bi-level optimization is proposed. Initially, a deep reinforcement learning-based model is built to estimate the value of charging and order dispatching under uncertainty.

Due to the differences in traffic situations and traffic safety laws, standards for extraction of critical driving scenarios (CDSs) vary from different countries and areas around the world. To maintain the characteristic variables under the Chinese typical CDSs, this paper uses the three-layer detection method to extract and detect CDSs in the Natural Driving Data from China-FOT project which executing under the real traffic situation in China. The first layer of detection is mainly based on the feature distributions which deviate from normal driving situations. These distributions associated with speed and longitudinal acceleration/lateral acceleration/yaw rate also quantify the critical levels classification.

With the increasing development in automotive industry, finite element (FE) analysis with model bias prediction has been used more and more widely in the fields of chassis design, body weight reduction optimization and some components development, which reduced the development cycles and enhanced analysis accuracy significantly. However, in the simulation process of plastic fuel tank system, there is few study of model validation or verification, which results that non-risky design decisions cannot be enhanced due to too much consuming time. In this study, to correct the discrepancy and uncertainty of the simulated finite element model, Bayesian inference-based method is employed, to quantify model uncertainty and evaluate the simulated results based on collected data from real mechanical tests of plastic fuel tanks and FE simulations under the same boundary conditions.

As is known to all, the structure of the chassis has been greatly simplified as the application of in-wheel motor in electric vehicle (EV) and distributed control is allowed. The micro EV can alleviate traffic jams, reduce the demand for motor and battery capacity due to its small size and light weight and accordingly solve the problem that in-wheel motor is limited by inner space of the wheel hub. As a result, this type of micro EV is easier to be recognized by the market. In the micro EV above, two seats are side by side and the battery is placed in the middle of the chassis. Besides, in-wheel motors are mounted on the rear axle and only front axle retains traditional hydraulic braking system. Based on this driving/braking system, distribution of braking torque, system reliability and braking intensity is analyzed in this paper.

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.

The active components, such as OH and their concentrations in the coflow, have a strong effect on the combustion process of diesel fuel spray flames in the Controllable Active Thermo-Atmosphere (CATA), which then will affect the soot incandescence of the spray flames. CO2 and H2O2, the additives which have contrary effect on the concentration of the active components, were mixed separately into the thermo-atmosphere before the jet spray were issued into the coflow, which changed the boundary condition around the central jet and influenced the combustion characteristics and soot incandescence. The combustion characteristics such as ignition delay and flame liftoff height of the central spray flames are measured and the linkage between these two parameters is investigated at different coflow temperatures.