During the charging and discharging process, lithium-ion batteries generate a large amount of heat. If the temperature is too high, it may cause battery failure or safety problems. As one of the most important technologies of battery cooling system, lithiumion battery cold plate cooling technology is significant to ensure battery safety. Firstly, this paper systematically analyzes the relevant methods of cold plate liquid cooling design, and compares the advantages and disadvantages of different methods. The mainstream cooling method for lithium-ion battery thermal management systems is currently liquid cooling, which boasts higher heat dissipation efficiency. With the increase in battery energy density, the future development trend of electric vehicle thermal management systems may move towards hybrid cooling, systematic design, and intelligent management.

Vehicle safety performance is a primary concern for consumers when selecting a new vehicle, where the crash resistance is of utmost. Central to this is the energy absorbing box, which can dissipate impact energy through deformation and crushing mechanisms, thereby maximizing safety of passengers. To optimize the energy absorbing performance of thin-walled structure and enhance the crash protection of vehicle, the performance evaluation indicators and structural types of thin-walled energy absorbing box is analyzed，and the deformation and energy absorbing characteristic are revealed. Finally, strategies and suggestions for the future development of thin-walled energy absorbing box are proposed, aiming to provide insights for research and practice in the field of vehicle safety.

In recent years, with the rapid development of autonomous driving technologies, the demand of intelligent vehicles for environment perception technology is also higher and higher. Due to the high accuracy of LiDAR data that can better obtain the 3D information in the environment, it has become a research hotspot in the field of 3D target detection. In order to provide more accurate environmental information for intelligent vehicles, the main research contents in the field of 3D target detection by LiDAR are summarized. Firstly, the advantages and disadvantages of various environment sensing sensors for self-driving vehicles are analyzed; secondly, according to the different data processing methods in 3D target detection algorithms, the detection algorithms based on point cloud and the detection algorithms fused with image and point cloud are reviewed; then, the mainstream self-driving datasets and their evaluation methods for 3D target detection are sorted out; and finally, the current 3D target detection algorithms for point cloud are summarized and outlooked. The results show the importance of the 2D view method and the multimodal fusion method in the current research for the development of autonomous driving technologies.

In order to fully understand the research methods and current status of deep learning-based trajectory prediction of intelligent vehicles, through the analysis and summary of existing literature, the input representation, output types, and prediction methods of deep learning-based trajectory prediction models are analyzed. The results show that trajectory prediction methods based on deep learning demonstrate outstanding performance in long-term, multi-modal motion and vehicle-road interaction scenarios.

Unstructured road recognition is a challenging problem in unmanned driving, involving the complexity of the road itself, such as unfixed type, irregular shape, uneven surface and blurred borders. In order to have a comprehensive understanding of vision-based unstructured road recognition methods and research status, through the analysis and summary of existing literature, this paper analyzes the existing three mainstream methods, which are road features-based, road model-based and machine learning-based methods, and collates the currently commonly used unstructured road open source data sets. The results show that the method based on road characteristics and road model has high computational complexity and low recognition accuracy, and the method based on machine learning can significantly improve the recognition accuracy, but the problems such as large data demand, long training time and poor interpretation are existed as well.

The development of battery replacement heavy truck has been a main way to promoting new energy heavy trucks in recent years. Battery-swapping stations provide battery-swapping and recharging services for heavy trucks. The operation economy of battery-swapping stations is directly related to whether the battery replacement heavy trucks can be developed on a large scale in future. This paper mainly establishes the economy calculation model and analyzes the operation economy of battery-swapping stations in 5 short transportation scenarios. The operation economy of battery swapping stations is closely related to the annual battery-swapping electricity. In order to ensure the profit of battery-swapping operation enterprises, it is necessary to focus on the scale and monthly mileage of the heavy trucks fleet under the target application scenarios.

The audio system is the core component of the vehicle’s active sound design and active noise reduction. In order to analyze the acoustic characteristics of audio system, it is necessary to use simulation to study its frequency response and the propagation characteristics of the sound field in the vehicle. Due to the wide frequency coverage of the frequency response, full band coverage cannot be achieved using a single simulation method. Traditional sound field simulation can only cover the frequency band below 1 000 Hz by using finite element methods. To solve this problem, Ray-tracing method commonly used in architectural acoustics was introduced into this study. The scope of application of ray-tracing method applicable to the sound field in the vehicle was discussed. Finally, the audio system was modeled and analyzed based on the ray-tracing method, the influencing factors of the results were analyzed. It is pointed out that factors such as high frequency leakage, sound transmission of glass and sound source directivity affect the simulation results.

In order to improve driving safety and driving comfort, the technologies of replacing traditional rear-view mirrors with electronic rear-view mirrors or camera monitor systems are sorted out, and the requirements of relevant domestic and foreign laws and standards on camera and monitor parameter design are analyzed. The research status of the monitor in terms of size, angle and position design is summarized. Moreover, the results of the actual car-following test and the simulated driving test are analyzed, and the evaluation indicators in the test are compared, including the physiological performance of the driver in the process of completing the driving task. Considering the subjective scores of drivers, the evaluation system under different test conditions is analyzed. This thesis provides feasible evaluation methods for camera monitor system application.

To improve the lateral control accuracy of autonomous vehicles in port scenarios, a closed-loop control algorithm with segmented optimal control is proposed, based on the response characteristics of solenoid valve of hydraulic steering system. The function of single axle steering, double axle steering and crab steering is realized. Moreover, the function and performance of the designed control algorithm have been verified by vehicle validation. The results show that the proposed control algorithm can realize fast and stable tracking of the hydraulic steering signal, and can support the lateral control function of the port autonomous vehicle.

Membrane electrode frames are important part of membrane electrodes. With the development of fuel cells, membrane electrode frames have received increasing attention. The materials used in the current frame are summarized, the structures of the membrane electrode frames are classified according to the number of layers of the frames and packaging method of each frame structure is described. The physical properties of different frame materials are compared, the reasons why Polyethylene Naphthalate Two Formic Acid Glycol ester (PEN) materials has become the mainstream are analyzed, and the durability of different adhesive layers of the frames is tested. The test results show that the pressure sensitive adhesive layer has better durability.