By summarizing the laws, regulations and standards formulated in China and foreign countries during the development of intelligent and connected vehicles, this paper sorted out the standardization construction system of intelligent and connected vehicles, which included 4 parts: admission, term definition, testing system and accident liability of intelligent and connected vehicles. Through the interpretation of standards, the understanding of the evolution of relevant laws and regulations in the process of the transformation of traditional vehicles to intelligent and connected vehicles was deepened, the technical requirements and social problems faced by the current intelligent and connected vehicle industry were clarified.

A study was conducted on the collision safety of passengers with “zero gravity” seats at different deployment angles. Firstly, a frontal collision model of the vehicle is established, and the seat angles were adjusted to standard posture, zero gravity sitting posture, and the backrest angle was adjusted to three different postures of 120°, 150°, and 180° based on the standard posture. Then, two collision speed curves of 40 km/h and 56 km/h were applied to the model, respectively. Simulation comparison shows that the injury values of the occupant's head, neck, and chest are the smallest in the standard posture. The injury values of the occupant's head and neck are the largest in the zero-gravity posture. The risk of chest injury increases with the increase of posture angle. The chest undergoes compression deformation, and the lungs are most susceptible to contusion, followed by the liver and spleen. The increase in the inclination angle of the passengers increases the risk of severe diving and “secondary collision” of the lower limbs.

Full Width Deformable Barrier (FWDB) finite element model is established according to the standard of EEVC-WG15, calibrated using the Transport Research Laboratory (TRL) trolley experiment method, and the Moving Progressive Deformable Barrier (MPDB) finite element model that has been calibrated and verified is used to build the MPDB and FWDB crash models of cars and SUVs respectively for the frontal collision compatibility study of vehicles. Compatibility evaluation indexes of MPDB and FWDB models are calculated, the analysis results show that the current MPDB conditions have some limitations on the evaluation of structural compatibility of vehicles, and cannot evaluate the role of the primary energy absorbing structure in the vertical and horizontal directions, and need to be combined with the compatibility evaluation indexes of FWDB conditions, VSI and HSI, to conduct an analysis in order to evaluate the frontal collision compatibility of the vehicle in a more comprehensive way.

In view of the trigger control and storage-recording in the process of automatic driving data collection, this paper started from advanced automatic driving data acquisition technology and advanced automatic driving storage technology, firstly investigated the sensor configuration methods of China and foreign automakers, then reviewed the automobile Event Data Recorder (EDR) system, autonomous driving data recording system and general L3 level autonomous vehicle data acquisition and storage schemes, and concluded that the existing data acquisition and storage technology could generate low quality and high noise redundant data. Finally, based on Tesla’s Shadow Mode, the paper introduced a driving data acquisition and storage method for man-machine co-driving mode, and summarized the development trend of advanced autonomous driving data acquisition technology.

This study aims to enhance the lateral stability of distributed drive electric vehicles when traveling on highways and low-adhesion roads by adopting a hierarchical control strategy. The upper level is the torque decision-making layer, which designs a hierarchical Sliding Mode Control (SMC) based on a two-degree-of-freedom dynamic model to optimize the additional yaw moment and introduces Active Rear-wheel Steering (ARS), while simultaneously using PID control to achieve vehicle speed tracking. The lower level is the torque distribution layer, which optimizes the distribution of driving torque among the four wheels based on wheel load and road adhesion coefficient. Through co-simulation using Carsim and Matlab/Simulink, the control effectiveness was verified under double lane change, different adhesion road surface, and slalom conditions. The results indicate that the SMC+ARS control maintains high stability under high-speed double lane change conditions and outperforms SMC under various adhesion conditions, while also reducing energy consumption during turning.

To investigate the impact of full-touch screen infotainment system response speed on car-following safety, this paper conducts human-machine interaction experiments using real car-following videos in an in-vehicle cockpit simulator. Data are collected from 25 participants under 2 vehicle speeds and 3 response speed conditions during both static and dynamic car-following scenarios. The visual distraction data are analyzed to reveal correlations between system response speed and car-following safety risks. Results demonstrate that as response time increases from 0 to 800 ms, the Total Time Spent on Screen (TTS), Glance-to-Screen Count (GSC), and Single Operation Time (SOT) exhibit nonlinear gradually growth with decelerating rates. Specifically, at 80 km/h, when response time increases from 0 to 400 ms, the TTS, GSC, and SOT increase by 17.83%, 19.74%, and 28.72% respectively, while the smaller increments of 10.97%, 12.89%, and 18.06%. When preceding vehicles braked at a 3 s time headway, the minimum following distance decreases by 14.5 m (80 km/h) and 12.78 m (100 km/h) as response time extends from 0 to 800 ms. Simulation results across 3 time headway levels confirm that slower system response significantly increases both collision probability and severity. These findings provide theoretical foundations for designing safer full-touch HMI systems, highlighting the critical role of optimizing response speed in mitigating driving risks.

In order to improve the active safety of three-axle vehicle under special driving conditions, an all-wheel steering control strategy combining feedforward control and feedback control is proposed. Firstly, considering the nonlinear mechanical properties of tires and the difference of vertical stiffness of each axle, a nine-degree-of-freedom three-axle vehicle dynamics model is established, and the tire cornering stiffness in the reference model is dynamically corrected in real time based on Newton interpolation method. On the basis of this model, a zero-centroid sideslip angle proportional feedforward control based on Ackerman principle is proposed to cooperate with the front wheel steering feedback controller based on Nonsingular Fast Terminal Sliding Mode (NFTSM) and the middle and rear wheel steering feedback controller based on Fuzzy PID to form an all-wheel steering control strategy. Finally, the vehicle is simulated and verified under the condition of fish hook and double lane change. The results show that the designed all-wheel steering control system improves the vehicle's trajectory tracking performance by 34% and lateral stability by 26% over the feedforward control strategy.

In order to enhance the vehicle braking energy recovery efficiency and maintain braking stability, this paper proposes a comprehensive energy recovery method that takes the drivers’ styles and road adhesion characteristics into account. Firstly, the driving style feature parameters are extracted from different drivers’ data, and the driving style recognition model is trained based on the Support Vector Machine (SVM). Then, the road images are preprocessed using the U-Net network, and the lightweight network MobileNet V3 is trained to recognize the road surface efficiently. Finally, combined with the recognition results of driving styles and road surfaces, the variable ratio of braking force of the front and rear axles of the vehicle is allocated, and a method is proposed to determine the regenerative braking force considering the weight of driving styles and road adhesion conditions, the braking energy recovery strategy is formulated on this basis. The simulation results show that the braking efficiency and stability are significantly improved for different road surfaces; the SOC of the battery is improved by 2.13 percentage points and 1.02 percentage points in the WLTC and NEDC cycle conditions respectively, further improving the overall braking stability and economy of vehicles.

This paper studies the noise of a Permanent Magnet Synchronous Motor (PMSM) for electric vehicles. Through the analysis of the contribution of different electromagnetic excitations to the noise, the paper identifies key factors such as motor torque ripple and spatial zero-order electromagnetic force, as well as their contributions to the order noise in different speed ranges. Moreover, through the simulation analysis of the noise under the conditions of eccentricity and current harmonics, the changes in the order noise after considering practical factors are obtained. The Kriging method is used to create an electromagnetic surrogate model, which can quickly calculate the electromagnetic force and torque ripple based on the design parameters of the stator and rotor. On the basis of the surrogate model, the genetic algorithm is used for multi-objective optimization. The order noise obtained from the simulation is significantly reduced compared with the original scheme. The good consistency between the simulation and the experiment is verified through the noise test of the optimized prototype on the test bench.

Based on heat pump technology, an integrated thermal management system that fully utilizes the waste heat of the motor has been designed. The system uses heat exchangers to connect the independent circuits and achieve efficient energy utilization. In order to address the difficulty of controlling thermal management systems, this paper proposes two optimization fuzzy control approaches, anti-saturation integral fuzzy control and multi-level fuzzy control. An integrated thermal management system model is built based on AMESim, and Simulink control strategy models for working mode switching and key components are established to jointly simulate and analyze the thermal management control effect of the entire vehicle. The simulation results show that at 0 ℃, the integrated thermal management system reduces the cabin heating time by about 27.8% compared with the independent thermal management systems of each circuit, and the energy efficiency ratio has been increased by an average of about 31.3%, in addition the winter driving range has been increased by about 9.57%. The control effect of optimized fuzzy control is significantly improved with the heating time of the cab in winter shortened by about 18.4%, and the fluctuation and overshoot of the cabin temperature in summer reduced, and the battery cooling time shortened by about 3.6%.