To support the application and development of basalt fiber composites in the automotive products, this study investigates the mechanical properties including flexural and tensile properties of basalt fiber composites with different thicknesses and areal densities. The effects of fiber diameter and fiber mat areal density on the mechanical properties of basalt fiber composite panels are analyzed. The results indicate that the transverse properties of the boards are superior to their longitudinal properties. Under the same conditions, increasing the area density of the fiber mat and reducing the board thickness can both improve the mechanical properties and reduce the water absorption rate. Furthermore, decreasing the diameter of the basalt fibers can improve the mechanical properties, but has a minor effect on the water absorption rate.

In order to explore the influence of wet Dual Clutch Transmission (DCT) on sliding power at different incline starts, the mathematical models of engine dynamic condition, vehicle driving resistance, clutch friction pair and the power model of automobile transmission system based on MATLAB/Simulink are established by mathematical modeling method. The start of wet DCT is simulated under the slope conditions of 0°, 10° and 20° respectively, and the change of the rotating speed of the main and slave ends and the slip and friction work of the friction pair are obtained under different conditions, so as to analyze the influence of slope change on the start of wet DCT vehicles, and provide certain reference and value for the theoretical research and application exploration of wet DCT.

In response to the complex and variable real-world operating conditions of electric vehicles and the technical prololems of traditional motor systems relying on calibration based on single standard operating conditions leading to low efficiency across the entire operating range, this paper proposes an adaptive optimization method integrating real-time operating condition perception, multi-parameter collaborative control, and thermal management linkage. This method collects multi-dimensional operational data such as motor speed, torque, coolant temperature/flow rate, constructs a three-dimensional feature space (speed-torque-thermal state) with dynamic partitioning, and collaboratively optimizes power device driving parameters (gate resistance, driving voltage), Pulse Width Modulation Switch (PWM) switching frequency, and cooling system operation strategy based on partition characteristics. Compared to the traditional fixed redundancy design for the most severe operating conditions, the proposed method achieves precise loss control across the entire operating range through "hardware-software collaboration+thermal-electric coupling" while satisfying system safety and reliability requirements. Bench test verification shows that this method improves the motor system's CLTC comprehensive cycle efficiency by approximately 0.34~0.67 percentage points, effectively reducing the vehicle's electricity consumption per 100 km and significantly extending its driving range.

To accurately evaluate and optimize the structural performance of the Body-in-White (BIW), this study focuses on a passenger car BIW by conducting equivalent torsional stiffness analysis and structural improvement research. Based on the pre-processing software ANSA and the finite element solver Nastran, a high-precision finite element model of the BIW is established in accordance with finite element theory. The equivalent torsion analysis method is employed to obtain the dynamic response curve of the BIW's equivalent torsional stiffness. Subsequently, structural weak areas are identified, and targeted reinforcement schemes are proposed accordingly. Simulation verification results show that the proposed reinforcement scheme significantly enhances the torsional stiffness of the BIW, and the optimized dynamic curve of equivalent torsional stiffness is markedly improved. The proposed method effectively guides the structural design and optimization of the BIW, providing a reliable theoretical basis and technical support for improving the NVH performance and ride comfort of the vehicle.

To resolve the problems of prominent in-vehicle low-frequency noise, excessive vibration and deteriorated ride comfort of a pure-electric VAN under multiple rotational speed conditions when the air conditioner is turned on, an optimization study on vehicle Noise, Vibration and Harshness (NVH) is carried out. Based on the Transfer-Path-Analysis (TPA) model of"source-path-receiver", the vibration transfer process of the air-conditioning compressor is analyzed, and the modal coupling mechanism between the rigid-body mode of the compressor and the modal of the mounting bracket in the two-stage vibration isolation system is systematically revealed. Aiming at the NVH defects induced by insufficient isolation efficiency of the vibration isolation system, a decoupling method via collaborative optimization of the dynamic stiffness at mounting points and the stiffness of vibration-isolator rubber pads is proposed to effectively reduce interior vibration and noise levels. Vehicle test verification demonstrates that the peak noise at 66 Hz is reduced by 14 dB after optimization, and the subjective evaluation result reaches an acceptable level.

To achieve an excellent brake pedal feeling and support the efficient design of electromechanical brake pedal simulator, this paper takes the brake pedal stiffness characteristics as the core objective. Dynamic models of key components of the electromechanical brake pedal simulator are established on the AMESim simulation platform, and the dynamic performance of the pedal system is analyzed via simulation. Based on the developed models, the paper systematically investigates the influences of the preload force, maximum compressible stroke and spring stiffness of the spring assembly on the brake pedal stiffness characteristics, and clarifies the quantitative mapping relationship between parameters and stiffness performance. A forward parameter decomposition method targeting brake pedal stiffness is proposed, which provides a reference for the design of electromechanical brake pedal simulator.

To address the challenge of balancing technological innovation and safety regulation brought about by the rapid development of Intelligent Connected Vehicle (ICV) technology, the paper deeply explores the regulatory challenges and innovative solutions faced by the development of intelligent connected vehicles. By analyzing the difficulties faced by ICVs and systematically analyzing the domestic and foreign automotive sandbox regulatory experience, the paper proposes regulatory innovation suggestions such as system improvement, data driven, safety assessment and widespread application, providing systematic insights and suggestions for constructing a more efficient intelligent connected vehicle safety regulatory system.

To investigate the development status of intelligent connected heavy truck platooning technology and its policy implementation in Beijing, this study conducts a comprehensive review of domestic and international policies, practical application cases, and the policy practices within the Beijing High-Level Automated Driving Demonstration Zone. The research empirically verifies the actual impacts of platooning technology on transportation efficiency and safety. Furthermore, based on the current state of deployment, it analyzes persistent real-world challenges hindering large-scale adoption and proposes actionable recommendations. The findings indicate that while intelligent connected heavy truck platooning delivers significant economic and social benefits, achieving scalable commercialization and industrial synergy requires expanding high-speed testing scopes and refining relevant policies and regulations.

To achieve the"Dual Carbon"goals in the transportation sector, this study proposes an integrated smart travel management platform architecture that incorporates carbon accounts and a carbon evaluation mechanism. The platform architecture comprises a user terminal, a backend management terminal, and system interfaces, featuring an independent carbon evaluation and trading subsystem. This paper elaborates on the platform's carbon asset management modules, detailing the mechanisms for carbon inventory, as well as the generation, utilization, and alignment with carbon quota trading systems. Furthermore, it analyzes the policy synergy pathways and application prospects by integrating national"Dual Carbon"policies with carbon inclusion initiatives, while also addressing challenges related to technological development, regulatory oversight, and social acceptance. The results indicate that the platform enables the quantitative assessment and visualization of users' travel-related carbon reduction behaviors through personal carbon accounts, facilitating priority recommendations for low-carbon travel modes and carbon incentive mechanisms. Through refined carbon asset management and inventory, the platform supports participation in the national voluntary emission reduction (CCER) trading system, thereby promoting individual engagement in the carbon market. Ultimately, the bidirectional synergy between the platform and carbon inclusion policies effectively enhances the share of green travel among the public, contributing significantly to the reduction of transport-related carbon emissions.

To accurately evaluate the level of vehicle intelligence and guide product iteration, this paper develops an intelligent user evaluation index system based on the Product Leadership Attribute Leading strategy (PALS) framework, covering 3 dimensions including product, technology, and corporate image. It introduces the LACU competitive evaluation strategy and conducts an empirical analysis with 1 521 purchase decision makers assessing a subject vehicle model and 5 competing models. The results show that the subject vehicle achieves an L (Leading) rating in 2 indicators:"leading intelligent interaction technology" and "owning an independent intelligent technology brand," which constitute its differentiated advantages. However, it receives a U (Uncompetitive) rating in 5 indicators, including"leading intelligent driving technology,"indicating notable weaknesses. The study confirms that the LACU evaluation system can effectively quantify a product's competitive position in the field of intelligence, identify strengths and shortcomings, and provide a scientific basis for automakers to define priorities in technological iteration and optimize resource allocation.