Safety analysis is an integral part of the automotive development process, as the complexity of automated driving systems increases, traditional safety analysis methods are facing challenges. Firstly, the advantages and disadvantages of traditional analysis methods, such as Fault Tree Analysis (FTA), Failure Modes and Effect Analysis (FMEA), and Hazard and Operability (HAZOP), are compared with the System Theoretic Process Analysis (STPA), especially the advantages of STPA for the safety analysis of automated driving systems. Secondly, the current status of STPA applications in essential areas, such as Functional Safety, Safety of the Intended Functionality (SOTIF), Cyber Security, and Human Machine Interface (HMI), are discussed in detail. Finally, the application of STPA in automated driving is prospected from the perspectives of expanding the STPA analysis, integration of analysis and verification, and extending application areas.

In order to analyze the current development status and trends of intelligent manufacturing scenarios in automotive industry, a macro analysis of automotive intelligent manufacturing scenarios is conducted based on the selection of automotive companies in the list of “2023 Intelligent Manufacturing Demonstration Factories and Excellent Scenarios”. This study is carried out from 3 dimensions: regional distribution, excellent scenarios, and typical scenarios by analyzing the content of intelligent manufacturing scenarios from 3 aspects: product lifecycle, production process, and supply chain. The development of intelligent manufacturing scenarios in the automotive industry reveals the following trends: In the short term, the focus of intelligent manufacturing in the automotive industry remains on the “production process.” There is a growing demand to explore the implementation of intelligent manufacturing scenarios in the “product lifecycle” and “supply chain”.

The driving environment of intelligent vehicles often has high uncertainty and complexity, which can lead to accidents and injuries to passengers. In order to improve the safety of intelligent vehicles, three major research methods are currently used to evaluate driving risks, including deterministic methods, probabilistic methods, and machine learning methods. Deterministic methods are traditional binary prediction methods, probabilistic methods can model various uncertainty, and machine learning methods can automatically learn driving behavior, making more accurate assessments of the risk of driving. Future research should combine the advantages of the three approaches to develop safer and more reliable autonomous driving systems.

Through the comparative analysis of cell base materials, various cell integration technologies, and lightweight battery housing solutions, the technical paths for battery density enhancement are elaborated. The improvement in energy density of individual battery cells heavily relies on significant breakthroughs in basic material science. In the post-lithium-ion era, cell densities are expected to reach 1200 W·h/kg, while in the short term, semi-solid battery technology with a cell density of 360 W·h/kg is anticipated to be the first to achieve mass production, enabling electric vehicles with longer driving ranges and higher energy efficiency. Another key technology is to improve cell integration efficiency. Innovative solutions such as Cell-to-Pack (CTP), Cell-to-Chassis (CTC), and Cell-to-Body (CTB) are anticipated to increase cell integration rates to 90% and space utilization to 70%, breaking traditional design limitations and significantly enhancing battery pack energy density. The lightweight design of battery housings is also essential. Lightweight housing design like aluminum alloy extruded profiles, aluminum alloy integrated die-casting, ultra-high-strength steel rolling, and carbon fiber composite materials molding can effectively reduce the overall weight of battery while ensuring performance, thus improving energy density.

In order to reduce the influence of driving fatigue on drivers in man-machine co-driving environment, this paper elaborates the mechanism of driving fatigue in man-machine co-driving environment, then analyzes the detection methods of driving fatigue from subjective and objective aspects, and introduces the alleviation methods of driving fatigue from active fatigue and passive fatigue. Finally, the deficiency of current research on driving fatigue detection and alleviation in man-machine co-driving environment is pointed out, and the prospect of research on driving fatigue detection and alleviation in man-machine co-driving environment is presented from the perspective of multi-feature and multi-mode fusion.

The ownership of electric vehicle(EV) is rapidly increasing, and charging issues caused by grid abnormal power are consequently emerging. EV adaptability testing has become a hot technology urgently needed in the industry. Grid adaptability testing technology can be applied to vehicle charging systems or AC charging piles, DC charging piles, in vehicle chargers, and high integration charging assemblies to improve the development quality of charging ecological products. To deeply adapt to the demands for charging of users in different scenarios, the automotive industry needs to comprehensively analyze the differences in global power grid systems, sort out the principles of abnormal power grids, and develop testing plans covering user charging conditions in terms of power grid systems, power grid drop, power grid steep rise, and power grid harmonics. Electric vehicle charging products should be fully validated before launch to avoid potential abnormal charging problems about the power grid.

This paper focuses on the standard essential patents of the national standard of electric vehicle wireless charging system. Firstly, it sorts out the wireless charging standard essential patent declaration, then analyzes the patent strategy and patent layout of Witricity, a key enterprise of the standard essential patent declaration. Finally the declarations involved foreign matter detection, resonance compensation and tuning control standards, conduct standard necessity analysis on the declared patents are combined, and whether the standard essential patents declared by the company actually constitute the patents necessary for the implementation of the standard is clarified.

Chinese automotive companies confront a range of challenges and issues in areas such as ascross-border trade settlement, cross-border supply chain financing, overseas industry financing, overseas consumer finance, and cross-border trade investment supply and demand. In response to these challenges, this paper traces the evolution of the Chinese automotive industry’s international development and its financial models. It examines the Japanese automotive export finance experience through the lenses of government policies, policy-oriented financial institutions, consortia, and companies. This paper concludes with specific recommendations for the export of Chinese automobiles, aiming to facilitate the high-quality internationalization of Chinese automotive industry.

In order to meet the increasing needs of users, it is an important task to build a development system based on the actual driving needs of users for the development of new energy vehicles. This paper analyzes the performance system of the users’ needs from 5 aspects: user performance demand identification, big data development, performance design, performance simulation and performance verification by establishing a vehicle simulation model, big data analysis model and real vehicle verification. The results show that the establishment of a development system considering the driving needs of users can effectively improve the market competitiveness of new energy vehicle products and improve product stickiness. It is believed that it is of great significance for the research and development of new energy vehicles to consider the needs of users in the research and development process and establish a performance development system based on the needs of users in combination with relevant technical methods.

The accelerated evolution of L2 partial automation and the rapid improvement of market penetration are important directions for the current landing application of Intelligent and Connected Vehicle(ICV), and also the focus of attention to Chinese government. However, China currently lacks mandatory policy laws and regulations, and needs to strengthen supervision. Through in-depth study of the relevant policies, regulations and standards of the United States, Europe and Japan on the L2 partial automation of ICV, this paper fully absorbs and adapts useful experience, and systematically analyzes the current situation, technical level and application needs of China’s L2 combined driver assistance market so as to scientifically and effectively provides intellectual support for combined driving assistance supervisory policy.