The accurate acquisition of tire body deformation has a crucial influence on the simulation accuracy of theoretical model, so the deformation rules and expression accuracy of different cord are studied by beam body model and finite element model. Firstly, a detailed theoretical model considering the flexible deformation characteristics of the beam carcass is established, and the expressions of tire cornering stiffness and driving/braking stiffness are obtained. Secondly, the tire finite element model is established, and the tire rubber and cord material parameters are accurately obtained to complete the comparison between the simulation results and the test data. On this basis, the finite element model of smooth tire with isotropic tread stiffness distribution is established, and the lateral stiffness, torsional stiffness and steadystate glide stiffness are simulated to obtain the lateral deformation of the tire under the action of lateral force and aligning moment, and the superposition principle of lateral deformation of different cord lines is verified. Then, the lateral deformation of different cord lines is fitted according to the established beam matrix model. Finally, the tread stiffness obtained by different cord lines is compared and verified by combining the flexural stiffness and slip stiffness models. The results show that the principle of deformation superposition is satisfied for different tire cord. The beam matrix model has a better expression precision for the lateral deformation of cord. The bending stiffness of cord shows a nonlinear decreasing trend with the increase of load, and the difference is small under large load. The calculation accuracy of tread stiffness obtained by different cord positions is different. The calculation accuracy of crown cord is the lowest at 93.6%, and the calculation accuracy of body 2 cord is the highest at 97.3%. The research position of the beam body model in the theoretical model is clarified in the study, improving the simulation accuracy of the theoretical model, and providing the reference for the study of tire dynamics.

The wirecontrolled braking system has gradually replaced the traditional vacuum booster solution and has become the leading technology in the braking field of new energy vehicles. Among them, the integrated ElectroHydraulic Braking (EHB) system, as a form of wirecontrolled braking, relies mainly on basic hydraulic braking and motor regenerative braking to fulfill the driver's braking intention when its EHB module fails. These two braking methods can provide relatively limited braking power, which is difficult to achieve the deceleration effect expected by the driver, to some extent increasing the risk of traffic accidents. In order to comprehensively enhance the driving safety performance of the vehicle, in this paper the Electronic Parking Brake (EPB) system is incorporated as one of the executing mechanisms for driving brakes. When the power assist function of the integrated EHB system fails, the intelligent braking system can, based on the deceleration requested by the driver, send a braking force or deceleration request signal through the vehicle network communication. This process coordinates the motor regenerative braking and EPB braking to work together to enhance the vehicle's deceleration performance, thereby significantly improving braking efficiency. In addition, by implementing multilevel control strategies for the EPB system, the system can meet the needs for different levels of deceleration, which not only optimizes the driving experience and improves comfort but also effectively reduces the probability of traffic accidents.

The vehicle stability region is an important aspect of research on vehicle stability analysis and control. For the problems of inaccurate description and difficult solution of stability region in existing research, a quadrilateral description and automatic solution method for vehicle stability region is proposed. A nonlinear twodegreeoffreedom vehicle model is established, and the ant colony algorithm is used to solve the equilibrium state of vehicle system. The Lyapunov indirect method is applied to determine the stability of the equilibrium state. Based on the phase plane of the sideslip anglesideslip angle velocity of mass center, several phase trajectory feature points and the phase plane stability region boundary point search method are established to solve the stability region boundary points. According to the different distributions of the vehicle stability region, two types of stability regions are proposed, and corresponding judgment methods, stability region quadrilateral description and its automatic solution methods are established. Based on the proposed method, the stability region of vehicle under common medium speed driving condition is solved. The results are compared with the parallel line method and diamond method, and the correctness of the quadrilateral description is validated by CarSim sine wave simulation results. The results show that the proposed quadrilateral description of the vehicle stability region can better describe the boundary of the stability region than the parallel line method and diamond method, and automatic solution reduces the workload of stability region solution.

In unstructured scenes, there are often obstacles of various sizes, and the path planning process that only considers obstacle avoidance methods such as detours will lead to decrease in vehicle traffic efficiency. For these problems, in this paper an intelligent vehicle path planning method with multiple obstacleavoidance modes is proposed by integrating a layered collision detection strategy into the traditional Hybrid A* algorithm. Firstly, a doublelayer grid map is constructed based on the vehicle chassis height, and a layered collision detection strategy is designed using the body contour and fourwheel contour. Then, through a welldesigned heuristic function and cost function calculation method, the Hybrid A* algorithm can efficiently search for paths in multi obstacle scenes. Finally, the gradient descent method is used to smooth and optimize the path. Simulation and real vehicle experiment results demonstrate the effectiveness of the proposed algorithm in improving path search efficiency and significantly enhancing path smoothness. Moreover, the planned paths consider both crossing and bypassing strategies for obstacle avoidance, enabling vehicles to have better passability in multiobstacle scenarios.

Traditional 3D object detection methods in Cartesian coordinate systems often overlook the symmetry and continuity of the target from different perspectives to some extent during camera image encoding due to the fixed wedgeshaped imaging geometry of invehicle cameras. To address this, in this paper, PolarDet, an innovative endtoend 3D object detection method in polar coordinates based on position and semantic information weighting is proposed. This method generates BEV (Bird's Eye View) position and semantic information in polar coordinates through polar coordinate queries and predefined polar grid, which then interacts with the BEV information from the previous frame to incorporate temporal information. When outputting the final detection results, PolarDet performs a weighted sum of position and semantic information to enhance information utilization efficiency, allowing the network to achieve higher detection accuracy. Extensive experiments on the challenging BEV object detection nuScenes dataset show that the optimal model of PolarDet achieves a mAP (mean average precision) of 0.469 and an NDS (nuScenes detection score) of 0.56, significantly outperforming Cartesian coordinatebased BEV detection methods.

Commercial platoon cruise control is an effective method to improve transportation efficiency, but existing research is mostly based on homogeneous platoon control with one single vehicle following optimization objective, while using a simple architecture to cope with communication time delay, which is not universally applicable in practical scenarios. Therefore, based on heterogeneous electric commercial vehicle fleets, in this paper a distributed model predictive control strategy is proposed to achieve multiobjective control that takes into account of requirements of vehicle following, economy, and comfort. Delay buffers and compensators are designed for delay prediction models, effectively solving the problems of excessive tracking distance error caused by nonideal communication conditions. Matlab/Simulink simulation shows that the proposed control algorithm can achieve multiobjective optimization control of heterogeneous commercial vehicle fleets. Compared with traditional model predictive control (MPC), it significantly reduces the tracking distance error, energy consumption, and jerk, effectively improving performance of the platoon in terms of tracking, economy and comfort and significantly reducing the adverse effect of time delay.

The Active Sound Enhancement (ASE) system in electric vehicles plays a crucial role in constructing diverse sound features and enhancing driving control perception. For the ASE technology for electric vehicles, a variableweight multimodal switching sound synthesis algorithm is proposed in this paper. By constructing a modeswitching factor matrix, it organically combines order synthesis, pitch modulation synthesis, and particle synthesis methods to form a deep sound fusion ASE system to achieve realtime synthesis of multimodal incabin sound profiles aimed at enriching subjective auditory perception, increasing the richness of the ASE system, and making the synthesized sound more threedimensional and saturated, thus enhancing the driving experience. Subsequently, a sound modulation software for electric vehicles is developed using C#, integrating ASE system control and sound modulation function to realize quick and flexible modulation of vehicle sound. Finally, the application of the sound modulation software in the sound modulation of a specific pure electric SUV is demonstrated. Sound tests combined with subjective evaluation results indicate that this software can effectively achieve multimodal sound synthesis goals, offering practical engineering application value.

Based on the research on the combination of vehicle application scenarios and electric drive torque near zero anti-jerk control requirements, in this paper four vehicle anti-jerk control requirements and their software architectures from the perspective of vehicle anti-jerk, including transmission clearance, torque limitation, electric drive torque near zero, and high-frequency de-noising of wheel speed fluctuation. Based on the requirements of anti-jerk control, vehicle anti-jerk algorithm architecture as well as the control strategy with electric motor torque near zero is designed, and the corresponding control process and calculation analysis are provided. Through simulation and real vehicle testing of the designed anti-jerk control strategy, it is proved that the control algorithm architecture and strategy can effectively achieve the anti-jerk function of the vehicle. According to the longitudinal acceleration curve of the real vehicle test and the fluctuation of the electric drive speed, it can be seen that the designed software architecture and control strategy have achieved good results in vehicle drivability.

With the increasingly strict emission standards for automobiles, non-exhaust particulate matter emission, especially brake wear particulate matter emission, is becoming more prominent. In order to investigate the emission characteristics of brake wear particles under different test cycles, in this study a set of drum brakes is selected to conduct research on PM2.5 and PN10 emission under different test cycles(WLTP-Brake、WLTP、C-WTVC and CHTC-LT cycle) on a brake emission testing system modified based on a brake inertia table. The research results show that there are significant differences in the average initial/final braking temperature of the brake drum under different test cycles, and the highest final braking temperature generally occurs in the braking event corresponding to the maximum initial braking speed in the cycle. The PM2.5 emission factor of the test brake drum under WLTP-Brake cycle is 1.67 mg/km/wheel (the Euro 7 vehicle emission limit of 7 mg/km/vehicle), so the particulate matter emission control of the brake drum, like the brake disc, needs our attention. In addition, the initial braking speed of each cycle has a significantly greater impact on brake particle emission than braking characteristic parameters such as average braking deceleration. This study has practical reference value for the development and testing of low emission brakes for brake enterprises.

Transformer-based models have made significant progress in Remaining Useful Life (RUL) prediction. However, existing Transformer models have the following limitation of difficulty in local feature extraction and failure to consider the importance of varying temporal and spatial input features. To solve the problems, in this paper, an enhanced two-stream Transformer model is proposed, which is reinforced by the local feature extraction module and the interaction fusion module. Firstly, the local feature extraction module captures local features from both the temporal and spatial streams to compensate for the Transformer's deficiency in local feature extraction. Then, the two-stream Transformer is used to extract long-term dependencies in the temporal and spatial dimensions, enhancing complementary learning between the two streams. Finally, the interaction fusion module is constructed to capture stream-level interaction using bilinear fusion, further improving prediction performance. Experiments using multiple models on two real-world datasets from a diesel engine manufacturer demonstrate that the evaluation metrics RMSE and Score are reduced by at least 3.23% and 5.89%, respectively.