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This paper investigates the utilization of Low Earth Orbit (LEO) satellites for vehicle localization and conducts a comparative analysis with traditional Global Navigation Satellite Systems (GNSS)-based methods. With the rise of LEO satellite constellations, such as Starlink, LEO-based vehicle localization may offer solutions to GNSS-related challenges. With a large number of satellites and short communication distance, the LEO-based method has great potential to improve accuracy, reduce warm-up time, and provide a robust localization solution for vehicle applications. In this paper, a dedicated LEO satellite simulator is presented, adaptable to various LEO constellations, making it relevant for evolving technologies beyond older LEO systems like Orbcomm or Iridium. The simulator includes satellite trajectory generation, observable satellite identification, and vehicle localization.

Over the past decade, significant progress has been made in developing algorithms and improving hardware for automated driving. However, conducting research and deploying advanced algorithms on automated vehicles for testing and validation remains costly, especially for academia. This paper presents the efforts of our research team to integrate the newest version of the open-source Autoware software with the commercially available DataSpeed Drive-by-Wire (DBW) system, resulting in the creation of a versatile and robust automated vehicle research platform. Autoware, an open-source software stack based on the 2nd generation Robot Operating System (ROS2), has gained prominence in the automated vehicle research community for its comprehensive suite of perception, planning, and control modules. The DataSpeed DBW system directly communicates with the vehicle's CAN bus and provides precise vehicle control capabilities.

To characterize the stress flow behavior of engineering plastic glass fiber reinforced polypropylene (PPGF) commonly used in automotive interior and exterior components, mechanical property is measured using a universal material testing machine and a servo-hydraulic tensile testing machine under quasi-static, high temperature, and high strain rate conditions. Stress versus strain curves of materials under different conditions are obtained. Based on the measured results, a new parameter identification method of the Johnson-Cook (J-C) constitutive model is proposed by considering the adiabatic temperature rise effect. Firstly, a material-level experiment method is carried out for glass fiber reinforced polypropylene (PPGF) materials, and the influence of wide strain rate range, and large temperature span on the material properties is studied from a macroscopic perspective.

Rubber isolators are widely used under random vibrations. In order to predict their fatigue life, a study on the fatigue analysis methodology for rubber isolators is carried out in this paper. Firstly, taking a mount used for isolating air conditioning compressor vibrations as studying example, accelerations versus time of rubber isolator at both sides are acquired for a car under different running conditions. The acceleration in time domain is transformed to frequency domain using the Fourier transform, and the acceleration power spectral density (PSD) is the obtained. Using the PSD as input, fatigue test is carried for the rubber isolator in different temperature and constant humidity conditions. A finite element model of the rubber isolator using ABAQUS is established for estimating fatigue life, and model validity is verified through static characteristic testing. Dynamic responses of the rubber isolator at frequency domain are calculated if a unit load is applied.

The fatigue prediction model of an air spring based on the crack initiation method is established in this study. Taking a rolling lobe air spring with an aluminum casing as the studying example, a finite element model for analyzing force versus displacement is developed. The static stiffness and dimensional parameters of limit positions are calculated and analyzed. The influence of different modeling methods of air springs bellow are compared and analyzed. Static stiffness measurement of an air spring is conducted, and the calculation results and the measured results of the static stiffness are compared. It is shown that the relative error of the measured stiffness and calculated stiffness is within 1%. The Abaqus post-processing stage is redeveloped in Python language.

Data-driven driving safety assessment is crucial in understanding the insights of traffic accidents caused by dangerous driving behaviors. Meanwhile, quantifying driving safety through well-defined metrics in real-world naturalistic driving data is also an important step for the operational safety assessment of automated vehicles (AV). However, the lack of flexible data acquisition methods and fine-grained datasets has hindered progress in this critical area. In response to this challenge, we propose a novel dataset for driving safety metrics analysis specifically tailored to car-following situations. Leveraging state-of-the-art Artificial Intelligence (AI) technology, we employ drones to capture high-resolution video data at 12 traffic scenes in the Phoenix metropolitan area. After that, we developed advanced computer vision algorithms and semantically annotated maps to extract precise vehicle trajectories and leader-follower relations among vehicles.

The ball joint with cross groove offers both angular and plunging motion. When transmitting the same torque, the cross groove ball joint is lighter than other plunging Constant Velocity Joints (CVJs). It is crucial for the design of the joint and enhancing the contact fatigue life of the raceway to accurately estimate component loads of the ball joints with cross groove. In this study, the transmission efficiency of the joint and the peak value of contact force between ball and the track are used as evaluation indexes for characterizing dynamic performance of the joint. A multibody dynamic model of the joint is established to calculate its dynamic performance. In the model, the contact properties and friction characteristics of the internal structures were modeled, and a nonlinear equivalent spring and damping model was adopted for estimating the contact force. The transmission efficiency loss of the cross groove joint was measured and compared with the calculated values.

Tortuosity, viscous characteristic length and thermal characteristic length are three important parameters for estimating the acoustic performance of porous materials, and it is usually measured by ultrasonic measurement technology, which is costly. In this paper, a method for identifying the tortuosity, viscous characteristic length and thermal characteristic length for the porous fiber materials mixed with kapok fiber and two kinds of other fiber materials is proposed. The tortuosity is calculated by using the porosity and high-frequency normal sound absorption coefficient of porous materials. According to the normal sound absorption coefficient curve of porous materials under plane wave incidence, viscous characteristic length and thermal characteristic length are identified through the Johnson-Champoux-Allard-Lafarge (JCAL) model and genetic algorithm by using the measured parameters, the calculated tortuosity and static thermal permeability.

To reduce the noise in the frequency range of 100Hz~1000Hz, a metamaterial structure composed of lightweight frame, hard membrane-like material and added mass is proposed in this paper. The advantage of this structure is that it is lightweight and the membrane-like material does not need to be stressed in advance. Finite element method (FEM) and experiment are used to investigate the sound transmission loss (STL) performance of the metamaterial structure. The results show that the peak STL is caused by the local resonance of the added mass and the membrane-like material. The valley versus frequency results from the resonance frequencies of metamaterial structure, and it is divided into three resonance frequencies: resonance frequencies from added mass, membrane-like material and frame.

As an important vibration damping element in automobile, the rubber mount can effectively reduce the vibration transmitted from the engine to the frame. In this study, a method of parameters identification of Mooney-Rivlin model by using surrogate model was proposed to more accurately describe the mechanical behavior of mount. Firstly, taking the rubber mount as the research object, the stiffness measurement was carried out. And then the calculation model of the rubber mount was established with Mooney-Rivlin model. Latin hypercube sampling was used to obtain the force and displacement calculation data in different directions. Then, the parameters of the Mooney-Rivlin model were taken as the design variables. And the error of the measured force-displacement curve and the calculated force-displacement curve was taken as the system response. Two surrogate models, the response surface model and the back-propagation neural network, were established.

As an important vibration damping element in automobile industries, the vibration transmitted from the engine to the frame can be reduced effectively because of rubber mount. The influence of preload on the static characteristics of rubber mount and the constitutive parameters identification of Mooney-Rivlin model under preload were studied. Firstly, a test rig for stiffness measurement of rubber mount under preload was designed and the influence of preload on the force versus displacement of mount was studied. Then, the model for estimating force versus displacement of rubber mount was established. The response surface model for parameters identification was established. And the identification method for estimating parameters of Mooney-Rivlin model of rubber mount was proposed with the crow search algorithm. Taking the rubber mount as the research object and taking the parameters of Mooney-Rivlin model as the variables.

The operational safety of Automated Driving System (ADS)-Operated Vehicles (AVs) are a rising concern with the deployment of AVs as prototypes being tested and also in commercial deployment. The robustness of safety evaluation systems is essential in determining the operational safety of AVs as they interact with human-driven vehicles. Extending upon earlier works of the Institute of Automated Mobility (IAM) that have explored the Operational Safety Assessment (OSA) metrics and infrastructure-based safety monitoring systems, in this work, we compare the performance of an infrastructure-based Light Detection And Ranging (LIDAR) system to an onboard vehicle-based LIDAR system in testing at the Maricopa County Department of Transportation SMARTDrive testbed in Anthem, Arizona. The sensor modalities are located in infrastructure and onboard the test vehicles, including LIDAR, cameras, a real-time differential GPS, and a drone with a camera.

Welding deformation of aluminum alloy is an urgent problem to be solved, it affects the performance and service life of welding products. In this research, in order to compute welding deformation and residual stress, a finite element model of 6061-T6 aluminum alloy was established. The efficiency and the accuracy of the welding residual stress calculation and the welding deformation were significantly improved. By comparing the temperature field and the displacement field of simulation and experiment, the finite element model was validated. Through finite element analysis, Heat input and welding times have important effects on welding deformation and residual stress was found. The welding deformation law and the residual stress distribution law were proposed, after cooling of the welding seams, the plates collapsed to the other side of the heat source along the vertical direction, the welding deformation tendency was heightened by double-sided welding.

Electric vehicle battery thermal management based on liquid cooling is the mainstream form of cooling for new energy vehicles. According to energy consumption, the system is divided into active cooling system and passive cooling system. The cooling of battery modules in these two cooling systems is carried out by liquid-cooled plate, which is connected in series in the cooling system. Therefore, the design of the liquid-cooled plate has a great impact on the effect of battery heat dissipation. In this paper, considering the advantages of existing liquid-cooled plates, the author proposed a series-parallel hybrid dc channel liquid-cooled plate structure, taking square lithium iron phosphate battery pack as the research object. Finally, the effects of different inlet flows and temperatures of the liquid-cooled plate on the thermal performance of the liquid-cooled plate were investigated by using single factor analysis.

In the manufacturing of battery boxes using the aluminum extruded process, poor consistency of products and a short life of the die for making aluminum structural sections are usually observed. A new method of producing battery boxes is proposed that combines steel stamped and aluminum extruded process. This paper first describes the design requirements for a battery box using a new process, and several important issues such as weld seam arrangement and error proofing in the manufacturing process are discussed. To address the issue of weld seam arrangement, the following three principles should be considered in the design: These principles include that the profile lap angle should be above 90°, three or more beams should not be lapped too closely together, and multiple brackets in close proximity should be designed as one unit.

As the power of electric vehicles (EVs), lithium-ion batteries (LIBs) are subjected to a variety of mechanical loads during electrochemical operation. Under this operating environment, lithium-ion batteries are at risk of internal short circuit, thermal runaway and even fire, threatening the safety of electric vehicles. The purpose of this paper is to investigate the mechanical behaviors and failure mechanisms of the battery separator to improve the safety of lithium-ion batteries under mechanical loads. In this study, uniaxial tensile, through-thickness compression and biaxial punch tests were performed to characterize two types of separators, dry-processed polypropylene (PP) separators and wet-processed ceramic-coated separators, and to analyze and compare their mechanical properties and failure modes. The comprehensive mechanical tests show that the failure modes of the different separator types are different, with the more anisotropic separator having more complex failure modes.

Because the power unit of electric vehicle has large torque, the rubber mount of electric vehicle is fully compressed under the condition of full throttle acceleration. When designing the mount of electric vehicle, the dynamic-to-static stiffness ratio of mount under the case should be as low as possible to improve the vibration isolation rate of the mount. In this paper, a method for calculating the high frequency dynamic characteristics of rubber isolators under different preloads is presented. Firstly, the dynamic characteristics of rubber specimens under various shear pre-strains were tested. The test results show that the dynamic stiffness of specimen decreases at first and then increases with the increase of shear strain. The viscoelastic parameters of rubber in frequency domain under different pre-strain were identified according to the experimental data. Secondly, a finite element modeling method was proposed.

The successful deployment of automated vehicles (AVs) has recently coincided with the use of off-board sensors for assessments of operational safety. Many intersections and roadways have monocular cameras used primarily for traffic monitoring; however, monocular cameras may not be sufficient to allow for useful AV operational safety assessments to be made in all operational design domains (ODDs) such as low ambient light and inclement weather conditions. Additional sensor modalities such as Light Detecting and Ranging (LiDAR) sensors allow for a wider range of scenarios to be accommodated and may also provide improved measurements of the Operational Safety Assessment (OSA) metrics previously introduced by the Institute of Automated Mobility (IAM).

The vehicle will produce certain shock and vibration during the braking process, which will affect the driving experience of the driver. Aiming at the problems of pitch vibration, longitudinal vibration and shock during the braking process, this paper proposes a planning and following control method for target longitudinal acceleration in post-braking phase, and designs control trigger strategies. Target longitudinal acceleration planning takes minimizing longitudinal shock as the design goal. The following control takes the brake pressure as the control object, and adopts the “feedforward +PID feedback” method to follow the target longitudinal acceleration. Besides, considering the safety of braking process, the trigger condition of control is designed which utilizes BP neural network method to judge whether the control has to be triggered. Based on Simulink software, the simulation model of straight-line braking is established.

The thermal management system, which is used to improve driving safety and thermal comfort, is one of the most important systems in electric vehicles. In recent years, researchers have coupled the heat pump system and the battery cooling system to effectively improve the heating COP (Coefficient of Performance). Therefore an accurate dynamic model of thermal management system plays a key role in investigating system performance and optimal control strategies. In this paper, an electric vehicle thermal management system based on four-way valve heat pump system is designed. The moving boundary method is improved by considering the unsteady flow of the external fluid, and then a 13-order dynamic model of the thermal management system is established. Firstly, the control equations of evaporator, condenser and chiller are derived according to the principle of conservation, and then a dynamic model of thermal management system is established in Simulink.