In the context of carbon peaking and carbon neutrality, integrated electric drive axles have emerged as a key pathway for commercial-vehicle electrification. Firstly, the paper introduces the typical configurations and layouts of integrated e-axles for commercial vehicles. Given the complexity and diversity of vehicle segments, it analyzes the suitability of electric drive axles for passenger cars, light trucks and pickups, as well as medium-and heavy-duty trucks. Next, the paper focuses on the motor, inverter, and transmission, which are the three core components, and summarizes recent advances in the key technologies supporting commercial-vehicle e-axles. Finally, the paper discusses the challenges these technologies still pose and describes their future prospects, providing a reference for the development and broader adoption of integrated electric drive axle systems in commercial vehicles.

The European New Car Assessment Programme (Euro NCAP) is an important reference for consumers choosing vehicles, and a leading indicator for global advances in automotive safety technology. This paper provides an in-depth interpretation of the latest trends in Euro NCAP testing protocols and compares the latest assessment results. Focusing on the segmentation of the safety-protection assessment systems, the paper reviews research progress in safety assessment techniques throughout the entire process, from safe driving and collision avoidance, to crash protection and post-crash safety. It also summarizes the current status of mainstream assessment systems, discusses the performance and characteristics of leading models, and offers practical guidance for improving China's vehicle-safety evaluation system and supporting the overseas expansion strategies of domestic brands.

Automated Valet Parking (AVP) system is a comprehensive platform integrating intelligent driving environment perception, decision planning and motion control technologies. Trajectory planning is directly related to the efficiency, energy consumption, safety and comfort of the valet parking process. To outline the development status of autonomous parking trajectory planning technology, this paper first reviews the development history of parking technology, then investigates trajectory planning during parking, and analyzes the progress in AVP research. Recognizing that the transition from singlevehicle intelligence to multivehicle cooperation reveals greater potential for system optimization, this study subsequently outlines the fundamental methods and current research status of multivehicle cooperative trajectory planning, with a special focus on cooperative planning in parking scenarios. Finally, this paper analyzes existing issues and future development trends in AVP trajectory planning.

In order to study the optimal posture angles and body-pressure distribution for passengers in an automotive zero-gravity seat, 30 subjects were recruited for subjective comfort assessments and static body pressure distribution tests. They adjusted the seat to their most comfortable position based on personal preference. Cameras recorded the resulting posture angles of each subject in the zero-gravity posture. Meanwhile, the pressure-sensing equipment captured the interface pressures between the human body and the seat. Non-parametric statistics was used to examine the influence of gender, stature percentile, and body mass index (BMI) on those posture angles and pressure distributions. The results show that gender significantly influences only the hip angle. Variations in stature percentile significantly affect the hip angle, the knee angle, and the mean pressure at the left shoulder. Changes in BMI significantly alter the mean pressure at the left shoulder region of the backrest, the lower back, and the entire backrest.

The significant reduction in electric vehicle driving range at low temperatures has limited their widespread adoption in extremely cold regions. To address this industry challenge, this paper proposes an indirect heat pump system for light commercial electric vehicles operating in severe cold climates. The five-way valve design used in the system enables a high level of system integration, and satisfies the thermal demands of various vehicle subsystems under low-temperature conditions. A 1-D simulation model of the vehicle thermal management system was established and validated through bench testing. The low-temperature performance of the system was assessed using climate chamber experiments on the actual vehicle. The heating performance and energy consumption of the proposed system were compared with those of the traditional Positive Temperature Coefficient (PTC) heating mode. The results show that the proposed thermal management system can meet the heating demands at low temperatures, with the average foot outlet temperature reaching 32.3 ℃ at an ambient temperature of -5 ℃. Compared with the traditional PTC heating, the heat pump system proves superior energy-saving performance, reducing system energy consumption by more than 50% and extending the driving range by approximately 15%.

The rapid rise of new energy vehicles under the“dual carbon” goals has shifted the focus of vehicle lightweighting from traditional structural and process innovations to the substitution and optimization of materials. Aluminum alloy materials highly match the requirements for materials used in automotive lightweighting, and are currently the most preferred materials. This paper reviews and discusses the research and development, application and new directions of aluminum alloy materials in automobile lightweighting.Firstly, the paper introduces the main brands and the application status of die casting aluminum, which accounts for more than 70% of the aluminum used in automobile drive systems, chassis systems and body structure parts. The focus is placed on analyzing the research status of integrated die casting technology and its necessary non-heat treatment aluminum alloy. The paper summarizes the use of wrought aluminum alloy in the automotive field, including the stamped parts, profiled components and forgings. It also discusses the research status of traditional automotive forged aluminum and high-strength aluminum, guided by the development trend towards high-strength and ductile aluminum alloys. Finally, the existing bottlenecks of aluminum alloy materials in the automotive field are analyzed and prospected.

With the rapid development of the electric vehicle industry, numerous challenges must be addressed in the dose evaluation of electromagnetic radiation inside vehicles. This paper expounded the research progress on this topic. And based on the relevant international and domestic standards for electromagnetic radiation exposure limits, it compared the similarities and differences of the current electromagnetic radiation standards for electric vehicles. Additionally, the paper introduced the simulation method for calculating radiation, and evaluated the human exposure doses in the vehicle through both simulation calculation and measurements. The simulation and evaluation of electromagnetic radiation in electric vehicles, as well as the radiation impact on human health, require further exploration and study.

The rapid development of autonomous driving technology has increased the demand for the authentic and diverse simulation test scenarios. However, traditional methods for constructing autonomous driving simulation scenarios heavily rely on manual editing, which is not only costly but also limited by the combination and complexity of scene elements, making it difficult to meet the comprehensive testing and validation needs of autonomous driving systems. To address this issue, this paper proposes a method for generating autonomous driving simulation test scenarios based on Large Language Models (LLMs). This approach utilizes a pre-trained LLM, enhanced through LoRA fine-tuning, and integrates a scenario language parser to produce a structured interpretive language, which is used to generate scenario files. The generated text is processed by a parser to convert it into usable scenario files, effectively addressing the issues of overly long texts and model hallucinations, while also achieving the specialization of a general model's capabilities.

At present, the vehicle side impact safety evaluations rarely consider the effect of pre-crash braking on occupant posture. In order to study the occupant displacement induced by braking during the pre-crash phase and its impact on occupant kinematics and injury outcomes under side impact conditions, the paper combines volunteer experiments with CAE simulations. Three side impact models, including a standard posture model, a muscle-tensed model, and a muscle-relaxed model, were developed to compare differences in occupant kinematics and key injury indicators across the models. The results show that, during braking, the volunteers experienced greater displacement under the relaxed muscle state, with the maximum displacements of the head and first thoracic vertebra (T1) reaching 225 mm and 145 mm, respectively. This displacement significantly changed the contact between the upper body of the dummy and the side restraint system during the side impact, creating a risk that the dummy's chest could move outside the effective protection zone of side airbag. The peak Y-acceleration of the head was increased by 163.98 m/s²(79.4%), and the maximum abdominal compression was increased by 13.53 mm (64.0%) during the side impact. These results provide valuable insights for the development of advanced restraint systems and integrated safety testing methods.

The rapid development of connected and intelligent vehicles is accelerating the exploration and commercialization of artificial intelligence (AI) technologies. Yet the broader and deeper application of AI in automated driving also brings increasingly prominent safety risks. Thus, developing safety testing and assessment methods for AI-applied automated driving systems is crucial for balancing technological innovation with safety concerns. From a system-safety perspective, this paper proposes a safety assessment method covering three stages: design and development, testing and evaluation, and deployment and operation. The method integrates the life cycle of AI system, safety requirements, verification and validation methods, and continuous risk assessment and safety analysis. Furthermore, the measures for development, design, testing, and optimization to ensure system safety are proposed, providing a reference for future testing and safety assessment of AI-based automated driving systems.