At present, the vast majority of intelligent surface products are made of a single material: plastic, which typically integrated capacitive touch and vibration feedback technologies. In order to meet the needs of users for appearance design and digital experience, various technologies such as capacitive touch, sound feedback, vibration feedback, and pressure sensing are utilized. By covering the surface with 4 materials: plastic, wood, metal and fabric, this paper explores various tactile sensations from vibration sources and surface properties of materials. This exploration aims to enhance the material richness and user experience in intelligent cockpit design.

With the increasing demand for real-time and large capacity data transmission in the in-vehicle network, Time Sensitive Networking (TSN) has become an essential technology in the electronic and electrical architecture with vehicle ethernet as the backbone network. In order to verify the delay effect of TSN protocol on vehicle ethernet, this paper analyzes the technical characteristics and application scenarios of the main TSN protocol family, uses RTaW software modeling, and simulates the traffic of vehicle ethernet under 4 different conditions through the Zonal architecture network. The results show that when the interference traffic accounts for 80% of the main link bandwidth, the worst end-to-end delay of vehicle ethernet using TSN protocol increases by about 0.1 us, which is close to no-interference case delay. Simulation results show that TSN can guarantee the delay of vehicle ethernet transmission queue reliably. TSN will play a greater role in audio and video transmission, high-level automatic driving, security backup and other aspects.

The quality problems of new energy vehicles cover a wide range, involve multiple sectors, and demand high technical standards. In order to prevent direct intervention from related sectors when problems arise and address the problems of unclear specialization in the traditional problem management process, low efficiency in problem-solving, lengthy resolution time, and incomplete problem resolution, a system-level problem management method for new energy vehicles is proposed. It involves problem positioning, problem process control, problem summary and accumulation, and problem recurrence preventing. Moreover, it innovatively introduces digital tools and methods into the problem management process. This research shows that this method can improve the efficiency of problem-solving, enhance the depth of problem management, facilitate effective experience accumulation, and strongly support the rapid iteration and technological upgrading of new energy vehicle products.

Digital intelligent transformation serves as the core driving force for the transformation, upgrading and high-quality development of the automotive industry. To address the issues of insufficient collaboration, low efficiency, lack of data governance, and difficulty in knowledge reuse in the R&D field, FAW actively developes the “FAW Digital Twin” to achieve 100% business digital twinning. Moreover, FAW also actively engages in business digital intelligence transformation, outlining a comprehensive methodology for business digital twinning and independently developing a cloud-native, modularized, and service-oriented designer workbench. The operationalization of the digital twinning in R&D business has significantly improved the research and development efficiency and quality. The platform collaboration efficiency has enhanced one time, the average design change period has been shortened by half, and the average problem resolution period has been reduced by 30.69%.

In order to overcome the difficulties that quite a few patent value evaluation systems exist but difficult to implement and the enterprises are not able to achieve effective hierarchical management, this paper expounds a management scheme based on the actual life cycle of patents, and formulates a hierarchical management strategy of the whole life cycle of patents that is more in line with market demand and enterprise strategy by interpreting the characteristics and influencing factors of high-value patents. Moreover, a 12-digit code is formed through the multi-dimensional evaluation of each patent proposal before, during and after the application. Last but not least, this patent management operation mode is determined according to the coding results, so as to ensure the patents commercial value.

Taking wet clutch as the research object, through theoretical calculation of coupling steel temperature of clutch, the clutch torsional and convective heat transfer coefficients are estimated by establishing the clutch torsional thermodynamic model. The main factors affecting the accuracy of calculation are extracted, and a physical model for dynamic measurement of steel sheet temperature is developed for key factors. Based on the measured results, the distribution law of axial temperature field of different steel plates is analyzed, the cooling oil passage of the clutch is optimized, the maximum temperature difference of different steel plates is reduced by 74.6%, which effectively improves the transmission torque of the clutch. At the same time, the clutch temperature model in-depth calibration under different oil temperature, torque and speed difference is carried out, which realizes the precise torque transfer ability of the transfer case while still secures the function of reliable thermal protection function.

To adapt to new trend of software-defined vehicle development and promote transformation and upgrading of automotive electronic and electrical architecture, this paper delineates the pivotal factors driving software-defined vehicle development and investigates the impending evolution of vehicle electronic and electrical hardware architecture. The paper examines the conceptual framework, hierarchical structure, and deployment strategies of Service-Oriented Architecture (SOA). Building upon these insights, a holistic technical framework for software-defined vehicle is developed, and the study delves into novel development methodologies and potential application domains. This research offers a technical blueprint for the design of future automotive electronic and electrical architectures.

To address the lack of effective monitoring and fault tolerance mechanisms in the service-oriented AUTOSAR Adaptive Platform (AP) and to ensure high stability and safety of the software system in case of faults, this study takes the automotive basic software platform AP as the research object. A complete monitoring and fault tolerance mechanism is designed through the Automated Valet Parking (AVP) software system. By analyzing traditional software architectures, other service-oriented architecture monitoring solutions, and the characteristics of AP, a monitoring scheme for AP is designed to supervise the platform infrastructure (processors, networks, memory) and service states (response times). A data display module developed with Qt, using the LT protocol, implements the collection and display of real-time monitoring data. Furthermore, a service call chain tracing method supporting the SOME/IP protocol is proposed, enabling analysis of complex service call relationships within service-oriented architectures. The results indicate that the scheme can monitor and analyze service failures within the AVP software system and implement fault tolerance mechanisms in case of failures, thus enhancing system reliability.

The strategic objectives of "carbon peaking" and "carbon neutrality" have brought significant challenges for reducing carbon emissions from passenger cars. Therefore, formulating a technical route for carbon reduction in passenger vehicles is a crucial task for the future sustainable development of the automotive industry. Firstly, it involves analyzing data on new passenger car production, stock and scrap rate up to 2060, as well as carbon intensity data of electricity industry. Subsequently, the carbon emission data from various power sources for passenger cars is compiled. An analysis model is then established, along with evaluation dimensions and indicators, to assess passenger cars with different power sources. Finally, the analysis focuses on the sensitivity of individual power technologies in reducing carbon emissions. The findings indicate that pure electric vehicles (EVs), plug-in hybrids (PHEVs), and hybrid electric vehicles (HEVs) play a pivotal role in rapidly reducing carbon emissions to achieve "carbon peaking". Additionally, carbon-neutral fuel power and fuel cell vehicle technologies demonstrate advantages in achieving "carbon neutrality". In conclusion, achieving "carbon peaking" and "carbon neutrality" in powertrains requires a combination of multi-source technology pathways within specific timeframes for implementation. Furthermore, transitioning policies and regulations from "double credit" to"carbon credit" based on technology neutrality is essential to realize the dual-carbon technical route for passenger cars.

Fuel cell vehicle (FCV) is an important direction for the sustainable development of the automotive industry in the future. However, existing test and evaluation standards for FCVs have not thoroughly examined the types of faults and their classification. There is a lack of a unified fault grading classification scheme. To solve this issue, a comprehensive set of grading classification evaluation indicators for FCV faults is proposed to standardize the levels of related faults. The focus is on researching methods for classifying FCV faults in the case of lack of data. Based on factor analysis and fuzzy set theory, a fault mode classification evaluation method for FCVs under data scarcity conditions is proposed, offering guidance for the classification of FCV fault levels.