In order to investigate the effect of frontal collision deceleration waveform parameters on dummy chest injury, the method of equating the deceleration waveform to a Bi-Slope Approximation Wave (BSAW) was used to complete the frontal collision simulation using MADYMO. The results show that the dummy damage corresponding to the bilinear deceleration waveform curve with a larger slope in the first stage and a higher peak at the end is smaller under the condition that the vehicle speed and deformation are guaranteed to be constant; the influence of BSAW parameters on the chest deceleration peak along the X-direction is from the first stage peak, the second stage peak, and the first stage peak moment in decreasing order under the condition that speed change remains unchanged.

To predict injury of the occupant in vehicle collision more rapidly and accurately, a training database for deep learning models was established based on frontal 100% overlap rigid barrier real-world collision data, and data preprocessing and features extraction were conducted. Deep learning models were constructed separately based on Long Short-Term Memory (LSTM), Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) neural network, and Temporal Convolutional Networks (TCN) for injury prediction training. The validation results show that the model prediction accuracy reaches 0.8579, 0.8209 and 0.9674, respectively, demonstrating feasibility of the proposed method.

In order to study the seat safety of passenger cars in China, this paper analyzed the casualties of each seat in three collision modes based on China In-Depth Accident Study (CIDAS) (2011~2022) statistical data, calculated the fatal risk of passengers in the front and rear seats using the risk model, and used risk weighting model and geometric average model of the risk to calculate risk of each seat. The results show that the fatal risk coefficient of the front row is 1.18 compared with the back row. Taking the risk of 100% of the driver’s seat position as the reference standard, the risk of the passenger seat, the left rear seat, the right rear seat and the middle rear seat was 79.57%, 105.23%, 93.28% and 191.69%, respectively.

In order to enhance the safety of the battery system in electric vehicles under side pole impact, a finite element model incorporating the battery system was established. The accuracy of this finite element model was validated through vehicle side pole impact tests. Using this model, the deformation status and acceleration response of the battery pack in side rigid pole impact scenarios were analyzed with structural deformation and acceleration impact as the primary evaluation criteria. The results indicate that under side pole impact, both the external framework and internal support structure of the battery pack experience significant deformation, and all positions within the battery system withstand substantial acceleration impacts. Based on this result, the paper proposed safety-specific design for this impact condition when designing power battery pack and vehicle body sill beam structure.

To address the issue of insufficient estimation accuracy of the Hydraulic Control Unit (HCU) wheel cylinder pressure estimation algorithm for an integrated wire controlled hydraulic braking system with eight valve structure, this article proposed wheel cylinder hydraulic pressure estimation algorithm that can replace pressure sensors. The article first proposed a wheel cylinder hydraulic pressure estimation algorithm based on the Bernoulli principle, and then analyzed the basic characteristics of the hydraulic adjustment unit and the Pressure Volume (PV) characteristics of the brake fluid based on hardware in the loop experimental bench testing. Finally, it was verified through actual vehicle experiments. The experimental results show that under basic braking conditions, the root mean square error of the proposed wheel cylinder pressure estimation algorithm is within 0.259 MPa, the root mean square error under active braking conditions is within 0.374 MPa, which is equivalent to the accuracy of the scheme with added pressure sensors.

In order to improve the efficiency of reliability verification of the e-Axle under mechanical load and thermal load environment, this paper, taking the three-in-one e-Axle as the research object, analyzed the failure mechanism and influencing factors of each subsystem by comprehensively considering the actual operating environment and working conditions of the e-Axle, and studied the acceleration process and calculated equivalent test time according to the accelerated failure logic under different test conditions. The results show that the accelerated life endurance test method can support the reliability verification of the e-Axle.

To address the issue of low simulation accuracy, and large test resources investment in the development of acoustic package, this paper proposed a method based on ray tracing to calculate the external sound load of car body. Firstly, the hard wall panel on external surface of vehicle was extracted, and ray tracing solving model was established in VAOne. Secondly, the noise value of the key sound source of the vehicle was tested. Finally, the key noise sources were loaded into the ray tracing model to calculate the external acoustic load of the car body. With an SUV as the research object, the vehicle exterior acoustic load was calculated and compared with the test results. The result shows that the sound load calculated by the ray tracing model is in good agreement with the experimental value, which can improve the simulation accuracy of the acoustic package development.

Based on the experimental method and technical requirements of GB 15086—2013, a finite element analysis model was established to analyze inertial force resistance and optimize plastic tailgate structure. Firstly, the plastic tailgate structure failure motion mode and stress of inertial force resistance was predicted and analyzed based on the structural design feasibility of plastic tailgate by using finite element analysis model simulation; secondly, the issue of structural failure and cracking of plastic tailgate under inertial load were solved by adopting the method of structural optimization scheme through increasing the load transmission path of the tailgate inner plate and strengthening the local material thickness. Finally, the reliability of the optimization scheme of the plastic tailgate and the accuracy of the simulation analysis model were verified by the bench test.