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The software installed in Electronic Control Units (ECUs) has witnessed a significant scale expansion as the functionality of Intelligent Connected Vehicles (ICVs) has become more sophisticated. To seek convenient long-term functional maintenance, stakeholders want to access ECUs data or update software from anywhere via diagnostic. Accordingly, as one of the external interfaces, Diagnostics over Internet Protocol (DoIP) is inevitably prone to malicious attacks. It is essential to note that cybersecurity threats not only arise from inherent protocol defects but also consider software implementation vulnerabilities. When implementing a specification, developers have considerable freedom to decide how to proceed. Differences between protocol specifications and implementations are often unavoidable, which can result in security vulnerabilities and potential attacks exploiting them.

Based on the durability cycle test of fuel cell stack and the characteristics of cyclic working conditions, this paper defines the characteristic current point and studies the attenuation rule of the fuel cell stack voltage over time under the characteristic current point. The results show that the voltage of the fuel cell stack appears to be linear downward under the characteristic current point. and the voltage attenuation rate of the fuel cell stack increases quadratically with the increase of the current density in addition to the open-circuit voltage point. Then the coefficient of variation is introduced in statistics as the index to characterize the voltage consistency attenuation of the fuel cell stack, and its variation rule is explored. The results show that the voltage consistency of vehicle fuel cell stack decreases seriously with the increase of running time under the condition of durable cycling.

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.

Experimental schemes, frequency characteristics, subjective and objective sound quality evaluation and sound quality prediction model establishment of a certain mass-production SUV (Sport Utility Vehicle, SUV) manual transmission gear rattle phenomenon were analyzed in this paper. Firstly, vehicle experiments, including experiment conditions, vibration acceleration sensor and microphone arrangements and especial considerations in experiments, were described in detail. Secondly, through time-frequency analysis, broadband characteristics of manual transmission gear rattle noise were identified and vibro-impact of gear rattle occurs in the frequency range of 450~4000Hz on the vehicle idle condition and the creeping condition. Thirdly, based on bandwidth filtering processing of gear rattle noise, subjective assessment experiments by a paired comparison method were carried out.

Oil pump is a critical part of engine lubrication system. The performance and efficiency of oil pump are greatly affected by vibration and noise, which would lead to the pump service life decreasing and pump body easily wearing. Hence the vibration and noise of oil pump is of great importance to study. In this paper, a FEA model of the variable displacement oil pump(VDOP) was established to carry on the modal and noise analysis, while the geometric structure was optimized with test verification. The modal analysis of VDOP was carried out by ABAQUS software, the 3-D unsteady flow field in VDOP was simulated by Pumplinx software, and the sound field was analyzed by ACTRAN acoustic module. Using a special oil pump test bench combined with B&K PULSE vibration and noise test equipment, the NVH and comprehensive performance experiment of the VDOP were carried out here.

To wheel driven electric vehicle, besides road unevenness excitation, the electric motor torque fluctuation has great effects on the whole body vibration (WBV) according to prior research.[1],[2] To evaluate and further reduce the influence of torque fluctuation on the whole body vibration (WBV), vibration characteristic of rear suspension is analyzed thoroughly and finally optimized in this paper. Firstly, based on an existing eccentrical motor driven electric vehicle, a rear twist beam suspension suitable for high frequency analysis is modeled in Adams/View. Secondly, the vibration characteristic is simulated using Adams/Vibration module and verified with natural modal parameters of system. Finally, the vibration characteristic is optimized by adjusting the parameters of bushings using DOE method and proven to be effective to reduce WBV caused by torque fluctuation.

Powertrain system of series-parallel hybrid vehicle contains multiple excitation sources like engine, motor and generator. The reduction of noise and vibration is quite difficult during multiplex working modes or the switch of modes. Aiming at Series-parallel hybrid powertrain system which contains engine, motor and planetary gear subsystems, this paper considered a typical working condition which is based on the power control strategy and established the torsional vibration mechanical model of hybrid powertrain system. The inherent characteristics and transient vibration response of the electric mode, hybrid mode and parking charging mode were studied and it was discovered that the repetitive frequency of the powertrain system under the three working modes is the same which is only related to inertia and meshing stiffness of planetary gear system. The non-repetitive frequency and corresponding vibration modes under the electric mode and parking charging mode are both close.

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.

Safety is the cornerstone for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Systems (ADS). To assess the safety of a traffic situation, it is essential to predict motion states of traffic participants in the future with mathematic models. Accurate vehicle trajectory prediction is an important prerequisite for reasonable traffic situation risk assessment and appropriate decision making. Vehicle trajectory prediction methods can be generally divided into motion model based methods and maneuver model based methods. Vehicle trajectory prediction based on motion models can be accurate and reliable only in the short term. While vehicle trajectory prediction based on maneuver models present more satisfactory performance in the long term, these maneuver models rely on machine learning methods. Abundant data should be collected to train the maneuver recognition model, which increases complexity and lowers real-time performance.

In this paper, a novel method is proposed to establish the vehicle yaw stability criterion based on the sideslip angle-yaw rate (β-r) phase plane method. First, nonlinear two degrees of freedom vehicle analysis model is established by adopting the Magic Formula of nonlinear tire model. Then, according to the model in the Matlab/Simulink environment, the β-r phase plane is gained. Emphatically, the effects of different driving conditions (front wheels steering angle, road adhesion coefficient and speed) on the stability boundaries of the phase plane are analyzed. Through a large number of simulation analysis, results show that there are two types of phase plane: curve stability region and diamond stability region, and the judgment method of the vehicle stability domain type under different driving conditions is solved.

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.

Vehicle sideslip angle is significant for electronic stability control devices and hard to estimate due to the nonlinear and uncertain vehicle and tire dynamics. In this paper, based on the two track vehicle dynamic model considering the tire pneumatic trail variation, the vehicle sideslip angle estimation method was proposed. First, the extra steering angle of each wheel caused by kinematics and compliance characteristics of the steering system and suspension system was analyzed. The steering angle estimation method was designed. Since the pneumatic trail would vary with different tire slip angle, distances between the center of gravity (COG) and front&rear axle also change with the tire slip angle. Then, based on the dynamic pneumatic trail and estimated steering angle, we modified the traditional two track vehicle dynamic model using a brush tire model. This model matches the vehicle dynamics more accurately.

High-speed vehicles in low illumination environments severely blur the images used in object detectors, which poses a potential threat to object detector-based advanced driver assistance systems (ADAS) and autonomous driving systems. Augmenting the training images for object detectors is an efficient way to mitigate the threat from motion blur. However, little attention has been paid to the motion of the vehicle and the position of objects in the traffic scene, which limits the consistence between the resulting augmented images and traffic scenes. In this paper, we present a vehicle kinematics-based image augmentation algorithm by modeling and analyzing the traffic scenes to generate more realistic augmented images and achieve higher robustness improvement on object detectors against motion blur. Firstly, we propose a traffic scene model considering vehicle motion and the relationship between the vehicle and the object in the traffic scene.

In order to avoid the influence of the change of the camera pitch angle and the variation of the height of the ground on the ranging accuracy, improve the real-time performance of the algorithm by substituting the current widely-used monocular vision ranging algorithm which builds the optical model based on the shadow of the vehicle floor and the lane line, as well as avoid the classification of vehicle detection, a vehicle distance measurement algorithm based on monocular vision and license plate width is established. Firstly, the target image acquisition and preprocessing are studied. Then the paper studies the license plate image location segmentation method based on accelerated template matching. On this basis, the algorithm for obtaining the ratio of license plate width to image width is studied, and the function of vehicle distance and license plate ratio width is established.

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.

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.

An electronic waste-gated turbocharger for automotive application can accurately control the boost pressure and effectively reduce turbo-lag. It can improve the transient responsive performance of engine and the acceleration performance of vehicle, which makes vehicle have a better adaptation to the complex traffic environment. A detailed analysis of aerodynamic working principle of electronic wastegate is the foundation for designing the control strategy of electronic wastegate. Putting turbine with electronic wastegate under unsteady condition that simulates the pulse exhaust gas of engine and studying influences of different valve opening on the performance of turbine has the practical value. This paper sets fixed and periodical unsteady conditions and adopts numerical methods to explore the performance of turbine in twin-entry turbocharger and the flow loss of bypass. Steady simulation structure is given for reference.

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.

The temperature of proton exchange membrane fuel cell (PEMFC) is the key factor restricting fuel cell’s performance. A deep understanding of temperature on stack voltage consistency and transient characteristics is necessary for improving the output performance of fuel cell. In this paper, the variation trend of consistency and transient characteristics of 20kW PEMFC stack at different temperatures is studied by experiment. In consistency, the amplitude of voltage changes and voltage difference (voltage coefficient variation σV) under different thermal loading conditions is examined. In transient characteristics, discussing the trends of transient voltage at different thermal loading. As the result, once the stack temperature increases from 65 °C to 70 °C, the stack performance and dynamic response are significantly improved, which may be caused by the rise in temperature promoting the establishment of the internal quality transmission channel.

Crashworthiness is one of the most important performances of vehicles, and the front rails are the main crash energy absorption parts during the frontal crashing process. In this paper, the front rail was simplified to a thin-walled beam with a cross section of single-hat which was made of steel and aluminum. And the two boards of it were connected by riveting without rivets. In order to optimize its crashworthiness, the thickness (t), radius (R) and the rivet spacing (d) were selected as three design variables, and its specific energy absorption was the objective while the average impact force was the constraint. Considering the error of manufacturing and measurements, the parameters σs and Et of the steel were selected as the uncertainty variables to improve the design reliability. The algorithm IP-GA and the approximate model-RBF (Radial Basis Function) were applied in this nonlinear uncertainty optimization.