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15 May 2026, Volume 51 Issue 9 Previous Issue   
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New Energy Vehicle
Intelligent Connected Vehicle
Design and Research
Process·Materials
Automobile Education
Standards·Regulations·Management
Reviews


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New Energy Vehicle

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Optimization of Hub Motor Dynamic Performance Based on Wavelet Neural Network CHEN Yue1 , CHEN Xing1,2* , ZHANG Guozong1 2026, 51(9): 1-6,18.  DOI: 10.16638/j.cnki.1671-7988.2026.009.001 Abstract ( )   PDF (895KB) ( )   To address the issues of strong nonlinearity, time-varying parameters, and external disturbances in hub motor control systems, traditional proportional-integral-derivative (PID) control exhibits slow dynamic response and poor disturbance resistance. To improve control performance, this study proposes an adaptive control strategy based on a wavelet neural network (WNN). A feedforward neural network structure using wavelet functions as activation functions is designed and integrated with a PID controller to construct a WNN-PID controller. This structure utilizes the timefrequency localization characteristics of wavelet transform to extract system error features online and adaptively adjusts PID parameters through the online learning capability of the neural network, thereby achieving precise control of the motor speed. Simulation results demonstrate that, compared to traditional PID control, the proposed WNN-PID method significantly improves dynamic response speed, load disturbance resistance, and control accuracy. It effectively enhances the overall performance of hub motor under complex working conditions and provides a valuable reference for the development of high-performance motor control systems. References | Related Articles | Metrics

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Analysis of Power up and down Control and Fault Diagnosis Strategy of Electric Forklift Intelligent Vehicle Control Unit FANG Yimao1,2, HUANG Dexiang1,2* , LI Jiacheng1,2 , WU Zhenguo1,2 , LI Zhe1,2 2026, 51(9): 7-12.  DOI: 10.16638/j.cnki.1671-7988.2026.009.002 Abstract ( )   PDF (1372KB) ( )   To ensure the safe and stable operation of electric forklifts and accurate fault diagnosis analysis, this paper focuses on the vehicle control unit (VCU) of electric forklifts and designs a comprehensive power up and down strategy alongside a hierarchical fault diagnosis system. Test results demonstrate that the power up and down strategy ensures stable system operation with control logic meeting requirements, while the fault diagnosis module achieves 100% of the targets in modelin-the-loop (MIL) testing. In real-vehicle tests, the system achieves a fault identification accuracy of over 98% with rapid response. This study effectively enhances the operational safety and maintenance efficiency of electric forklifts, providing a valuable reference for the optimization of industrial vehicle systems. References | Related Articles | Metrics

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The Influence of the Differential Pressure Flow Channel Pressure Variation Zone on the Performance of PEMFC Changzhi Vocational and Technical College 2026, 51(9): 13-18.  DOI: 10.16638/j.cnki.1671-7988.2026.009.003 Abstract ( )   PDF (2019KB) ( )   The differential pressure channel utilizes the pressure variation zone to create different pressures between adjacent channels, promoting convection under the reactant ridges and enhancing the oxygen concentration in the spine area of the membrane electrode. To clarify how the size of the pressure variation zone influences the performance of differential pressure flow channels, this paper investigates the effects of two key dimensional parameters (length and height) on oxygen concentration distribution, inter-channel pressure difference, and power density. The results show that compared with the length factor, the height of the pressure variation zone has a more significant impact on battery performance. Under the condition of output voltage of 0.4 V, pressure variation zone height of 0.05 mm, and length of 1.5 mm, the power density of the differential pressure flow channel is 0.364 8 W/cm 2 . This finding clarifies the dominant role of the pressure variation zone height on the performance of the differential pressure flow channel, providing a key basis for enhancing oxygen convection in the spine area of the membrane electrode assembly and improving fuel cell power density through reasonable design of the pressure variation zone dimensions. References | Related Articles | Metrics

Intelligent Connected Vehicle

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Research, Development, Testing, and Verification Platform for Intelligent Driving Perception Performance Based on a Data Closed Loop QU Yanbao1 , ZHANG Minchao2 , LI Nen2 , ZHAO Wenbo1 , HUANG Yan1 2026, 51(9): 19-25.  DOI: 10.16638/j.cnki.1671-7988.2026.009.004 Abstract ( )   PDF (2362KB) ( )   To address the functional anomalies and deficiencies in autonomous driving systems caused by the performance limitations of onboard sensors such as cameras and radar, this study aims to establish a universal sensor testing and evaluation framework. This framework is intended to provide a basis for OEMs' sensor selection and performance validation. Leveraging practical experience in data-driven closed-loop engineering, a comprehensive theoretical and methodological system is constructed. This system covers the entire process from in-vehicle configuration and data acquisition to data processing and perceptual performance testing, thereby elevating sensor testing from isolated functional verification to systematic and quantifiable performance evaluation. The research resulted in a complete and actionable methodology for sensor testing and evaluation. This framework enables the systematic assessment of key sensor performance indicators, accurately revealing their performance boundaries and limitations. The proposed methodological system provides a universal testing standard for the industry. It can not only effectively guide OEMs in sensor selection decisions and enhance the reliability of autonomous driving systems but also holds significant reference value for advancing the development of environmental perception technology across the sector. References | Related Articles | Metrics

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Reliability Design of Low-Voltage Electrical Systems for Autonomous Driving WANG Wenduo, GUO Xin 2026, 51(9): 26-30,39.  DOI: 10.16638/j.cnki.1671-7988.2026.009.005 Abstract ( )   PDF (857KB) ( )   To establish a comprehensive reliability design theory and implementation scheme for low-voltage electrical systems in autonomous vehicles, addressing the challenges of high system complexity and failure risks to ensure safe and stable operation. Through analyzing the layered architectural characteristics of low-voltage electrical systems, multi-dimensional reliability design methods including power supply redundancy, sensor fault tolerance, electronic control unit (ECU) backup, and actuator protection are adopted to construct a multi-level fault-tolerant system covering perception, network, decision, and execution layers. The system achieves a mean time between failures of 100 000 hours, safety failure rate reduced to 10-8 per hour, dual-processor fault detection time controlled within 10 ms, system switching time not exceeding 50 ms, and voltage stability reaching ±2%. The multi-level reliability design scheme significantly enhances the fault tolerance capability and overall safety of autonomous vehicle low-voltage electrical systems, providing important theoretical support and engineering guidance for the commercialization of autonomous driving technology. References | Related Articles | Metrics

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Research on UAV Collaborative Perception and Path Decision-Making Method for Intelligent Connected Vehicles FENG Min, GU Hongxia, FENG Lifan 2026, 51(9): 31-39.  DOI: 10.16638/j.cnki.1671-7988.2026.009.006 Abstract ( )   PDF (1028KB) ( )   With the rapid implementation of high-level autonomous driving technology, intelligent connected vehicles (ICV) face core pain points in complex urban traffic environments, such as limited perception range of single vehicle, insufficient blind area coverage, weak prediction ability of dynamic traffic risks, and poor robustness of path decision-making in extreme scenarios, which seriously restrict the large-scale application of high-level autonomous driving. Aiming at the above problems, this paper proposes a unmanned aerial vehicle (UAV) collaborative perception and path decision-making method for intelligent connected vehicles. A complete technical system is formed through integrated environment modeling, multi-objective optimization model construction, and two-layer collaborative algorithm design, and the effectiveness of the method is verified through simulation experiments in medium-density and high-density urban traffic scenarios. The results show that in the single vehicle-single UAV collaborative scenario, compared with the traditional A* algorithm, the improved jump point search (JPS) algorithm proposed in this paper can reduce the path decision-making time by up to 28.32%, improve the global perception coverage by 19.64%, and reduce the comprehensive traffic cost by up to 6.15%. The research effectively makes up for the spatial limitation of single vehicle perception of intelligent connected vehicles, realizes the closed-loop optimization of collaborative perception and path decision-making, can provide theoretical support and technical reference for the implementation of air-ground integrated autonomous driving technology, and has important engineering application value for promoting the in-depth integration of low-altitude economy and intelligent transportation system. References | Related Articles | Metrics

Design and Research

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Heat Dissipation Optimization and Analysis of Wheel-End Braking System for FSAE Racing Cars ZENG Junqi, LUO Jiahong, QIU Junqiang, LI Yi, HE Haiyan, WANG Chuang* 2026, 51(9): 40-47.  DOI: 10.16638/j.cnki.1671-7988.2026.009.007 Abstract ( )   PDF (6003KB) ( )   The wheel-end braking system serves as a critical chassis subsystem whose thermal management performance directly governs vehicle handling stability and operational safety. This study implements multidisciplinary co-optimization of wheel-end braking system cooling for the "INNOVATION6" formula society of automotive engineers (FSAE) racing car. Utilizing CATIA for 3D parametric modeling and ANSYS for thermal-fluid coupling simulations, heat dissipation bottlenecks are systematically identified. These analyses are integrated with a VI-Grade-based driver-in-the-loop (DIL) simulation platform to holistically quantify dynamic performance impacts. Post-optimization results confirm a 36% enhancement in heat dissipation efficiency that substantially mitigates brake thermal fade risks, accompanied by a 10% increase in braking efficiency. Closed-loop simulation tests further demonstrate a 3% reduction in lap time. These validated improvements underscore the efficacy of thermal optimization in enhancing wheel-end braking system performance. The proposed methodology provides a robust theoretical foundation and practical design guidelines for developing lightweight, high-efficiency heat dissipation, and reliable design of wheel-end braking systems in FSAE racing applications. References | Related Articles | Metrics

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Research on Hill-Start Aid Control of Heavy-Duty Truck Based on Typical Vehicle Operating Conditions ZHANG Shuaishuai, TIAN Xuewu, LIU Enliang, HOU Shengdong, WANG Lei 2026, 51(9): 48-52，84.  DOI: 10.16638/j.cnki.1671-7988.2026.009.008 Abstract ( )   PDF (2720KB) ( )   When the heavy-duty truck hill-start assist control strategy does not match the road condition characteristics during start-up operation, the vehicle driving experience varies significantly. This paper takes heavy-duty trucks equipped with automated manual transmissions (AMT) as the research object, introduces an adaptive control mechanism for hill-start to identify vehicle states, and proposes a method to accurately estimate vehicle resistance and release the brake at an appropriate timing during hill-start assistance based on typical vehicle operating conditions. Tests have shown that this method meets the operational needs of drivers in practical production work. Through simulation and real-vehicle verification, the heavy-duty truck can release the brake in a timely manner during hill-start, the driving experience during start-up is significantly improved, and the driver's requirements are fully satisfied. References | Related Articles | Metrics

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Research on the Application of Model Updating Technology in Chassis Structure LIU Qian, WU Yan, QI Zhihui, HE Na 2026, 51(9): 53-59.  DOI: 10.16638/j.cnki.1671-7988.2026.009.009 Abstract ( )   PDF (1475KB) ( )   In the modal analysis of vehicle frames using the finite element method, discrepancies between finite element calculation results and experimental test results inevitably arise due to factors such as uncertainty in material properties, simplifications in modeling and boundary conditions. This paper takes a newly developed special-purpose vehicle frame as the research object, establishes a fully parametric model, and employs a combined zero-order and first-order optimization method to update the finite element model of the frame based on experimental data. Taking the sum of frequency errors at each order as the objective function, material density, Young's modulus, and wall thickness are selected as design variables, while model mass error, individual frequency errors at each order, and modal assurance criterion are used as state variables for iterative computation. The results show that the objective function value decreases from 39.68% to 8.33%, the maximum single-order frequency error decreases from 6.03% to 2.13%, and the minimum modal assurance criterion (MAC) value corresponding to each order mode is 0.955. The updated frame model can be used for subsequent dynamic studies. References | Related Articles | Metrics

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Control Strategy and Performance Optimization of Simulated Upshift for CVT MA Zhiyuan 2026, 51(9): 60-64.  DOI: 10.16638/j.cnki.1671-7988.2026.009.010 Abstract ( )   PDF (1225KB) ( )   This paper briefly introduces the working principle of the continuously variable transmission (CVT), optimizes the control strategy of CVT simulated upshift to address noise issues during wide-open-throttle acceleration, clarifies the goals of simulated upshift performance optimization from the perspectives of acceleration performance and drivability, and presents the use of calibration methods and the design for six sigma (DFSS) tool to improve simulated upshift performance. The optimization scheme is determined by increasing the minimum shift speed for simulated upshift while optimizing the rate of speed variation during the acceleration phase. An orthogonal experiment is designed to obtain the optimal solution. The optimization results show that the 0～100 km/h acceleration time decreases by 0.45 s, and the subjective score of upshift drivability increases by 0.50 point. Spot checks on mass-produced vehicles confirm that all optimized indicators meet the development requirements. This method provides a fast, efficient, and low-cost approach to optimizing simulated upshift performance, offering good engineering reference value. References | Related Articles | Metrics

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Study on Energy Absorption Mechanism and Section Chamfer of Crash Boxes Based on LS-DYNA ZHOU Danfeng1 , ZHANG Hongjun1 , WU Zhaoyang2 2026, 51(9): 65-68.  DOI: 10.16638/j.cnki.1671-7988.2026.009.011 Abstract ( )   PDF (1120KB) ( )   Based on the super-folding element theory, finite element models of quadrilateral crosssection energy-absorbing boxes with three kinds of chamfers and five kinds of polygonal cross-section energy-absorbing boxes are established by using LS-DYNA. Under axial crushing conditions, the deformation mode, specific energy absorption, crash force efficiency and other performance indicators are compared and analyzed. The results show that the energy absorption efficiency per unit mass of the chamfered region is four times that of the flat region. Increasing the number of symmetrical chamfers on the cross-section can optimize the structural stiffness distribution, effectively induce stable multi-mode buckling of the structure and reduce the crushing wavelength. On this basis, a cruciform cross-section energy-absorbing box is designed, whose specific energy absorption is increased by approximately 118.86% compared with the CASE1 scheme, and the crash force efficiency remains above 56%. The multi-axis symmetric cross-section enables stable progressive crushing, effectively improves the specific energy absorption and load stability, and contributes greatly to vehicle body lightweight and the improvement of collision maintenance economy. References | Related Articles | Metrics

Process·Materials

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Development and Application of High-Efficiency Cutting Tools for Large-Diameter Deep Holes ZHAO Wenchang, JIA Jupeng, YE Min 2026, 51(9): 69-72.  DOI: 10.16638/j.cnki.1671-7988.2026.009.012 Abstract ( )   PDF (2328KB) ( )   This research aims to address the issues of low machining efficiency, short tool life, and poor hole surface quality in the processing of large-diameter deep holes (diameter D=30~80 mm, aperture L/D=5~12) in automotive transmission housings. Traditional deep hole drills face challenges such as difficult chip evacuation, insufficient cooling, and unstable centering when processing largediameter deep holes. To address the shortcomings of traditional deep hole drills in large-diameter deep hole machining, such as poor chip evacuation, insufficient cooling, and unstable centering, this research proposes a novel and efficient machine-clamped deep hole drill design. Innovatively, the design features a dense arrangement of large and small inserts, combined with a supporting guide strip and a straight flute chip evacuation channel, which significantly enhances tool rigidity and machining stability. Comparative experiments have shown that the new tool, when machining QT400 material, achieves a significant reduction in hole surface roughness, a 1.5-fold increase in tool life, and a 50% improvement in machining efficiency. This study provides an efficient, low-cost, and reliable tool solution for large-diameter deep hole machining, offering significant engineering application value in advancing the manufacturing technology of key automotive components. References | Related Articles | Metrics

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Dimension Engineering Design and Validation of Magnesium Alloy Hydrogen Supply Frames GUO Qi, LI Chenxin, TANG Jinping 2026, 51(9): 73-76.  DOI: 10.16638/j.cnki.1671-7988.2026.009.013 Abstract ( )   PDF (2376KB) ( )   Given the rapid development of hydrogen fuel cell heavy-duty trucks, reducing the weight and implementing lightweight design for hydrogen supply system frames has become particularly crucial. This paper designs and investigates a magnesium alloy hydrogen supply system frame by identifying the three-section cage-type welded structure of the steel hydrogen supply system frame. It adopts a design and assembly approach centered on bolted connections for the magnesium alloy hydrogen supply frame. By applying dimensional engineering analysis methods, it identifies three primary dimensional chains at critical connection joints, determines correct hole diameter values, and establishes a rational assembly sequence and methodology. This provides methods and ideas for the design and assembly of magnesium alloy hydrogen supply frames based on dimensional engineering. References | Related Articles | Metrics

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Practical Exploration of "Zero-Waste Factory" in the Automotive Painting Process LU Mingchao, KONG Dejun, JU Hongyu, YUAN Xiaolin, LI Jingming 2026, 51(9): 77-80,100.  DOI: 10.16638/j.cnki.1671-7988.2026.009.014 Abstract ( )   PDF (989KB) ( )   As a core pollution link in automobile manufacturing where hazardous waste generation accounts for over 90% of the total across the four major processes, the green transformation of the painting process holds strategic significance for achieving the goals of a "zero-waste city". Based on the theoretical framework of a "zero-waste factory", this study systematically analyzes the hazardous waste generation mechanisms in key stages such as pre-treatment, sealing, and spraying. By adopting a collaborative treatment strategy of "source reduction, process control, and end-of-pipe treatment", and implementing measures such as waterborne or solvent-based waste solvent treatment, mask-free sealing, robot-based efficient cleaning, and resource recovery, a 50% reduction in hazardous waste has been achieved, along with a decrease in overall operational costs. This provides a replicable technical pathway and management approach for the green transformation of the automotive industry. References | Related Articles | Metrics

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Effect of Humidity on the Corrosion Behavior of Hot-Rolled Steel Plate in Automobile Corrosion Test ZHANG Bao, CHEN Wei* , GUO Xiaoliang 2026, 51(9): 81-84.  DOI: 10.16638/j.cnki.1671-7988.2026.009.015 Abstract ( )   PDF (1730KB) ( )   This paper studies the effect of humidity variation on the corrosion rate of hot-rolled steel sheets under automotive corrosion test conditions. The micromorphology and phase composition of the corroded surface are analyzed by scanning electron microscope and X-ray diffractometer. The results show that alternating humidity exerts a greater influence on the corrosion rate of hot-rolled steel sheets than continuous high humidity, while the two conditions present a basically consistent trend of corrosion rate change. In the initial acceleration stage within the first 5 days of the test, the corrosion rate of the steel sheet increases continuously, cracks appear on the rust layer surface and Fe2O3 is formed. During 5 to 7 days, the corrosion rate decreases significantly, surface cracks of the rust layer reduce, and Fe2O3 and corrosion-resistant α-FeOOH are generated. At 20 days, the corrosion rate rises continuously with obvious spalling of the rust layer, and the corrosion products mainly include Fe3O4, Fe2O3 and a small amount of α-FeOOH. Alternating humidity significantly promotes the later corrosion development of hot-rolled steel sheets, which provides a reference for the anti-corrosion design of hot-rolled steel sheets for automobiles. References | Related Articles | Metrics

Automobile Education

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AI-Empowered Innovative Teaching Practice in the Course of Automobile Manufacturing Technology YANG Honggang 2026, 51(9): 85-89.  DOI: 10.16638/j.cnki.1671-7988.2026.009.016 Abstract ( )   PDF (1606KB) ( )   With the widespread application of artificial intelligence (AI) technology, knowledge graph empowering higher education has become a new form of educational digitization. Based on the knowledge graph, this article explores the construction and teaching practice of the Automobile Manufacturing Technology course empowered by AI. It focuses on intelligent manufacturing and intelligent quality inspection technology for automobiles, enriches and improves the course content, organizes teaching knowledge points, builds a relational network, provides exercise library resources, and combines AI intelligent teaching assistants. Through the integration of graph-based knowledge points, ideological and political integration points in the course, and online and offline integration points, an AI course system is constructed, which provides intelligent assistance for pre-class preview, intelligent management during class, and intelligent research after class. This system builds an autonomous learning path for students, provides customized learning plans, enhances the effectiveness of course teaching, promotes students' mastery of automobile manufacturing technology, and lays the foundation for cultivating craftsman talents in the new era. References | Related Articles | Metrics

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Personalized Exploration and Practice in Academic Assessment Reform for New Energy Vehicle Students DANG Jinjin 2026, 51(9): 90-94,106.  DOI: 10.16638/j.cnki.1671-7988.2026.009.017 Abstract ( )   PDF (1097KB) ( )   This paper takes the New Energy Vehicle Technology major at Luoyang Vocational and Technical College as a case study. Student learning behavior data are collected via the SuperStar learning platform. Formative and summative assessments are integrated to evaluate classroom performance, project assignments, internships, and competency development. A closed-loop system of "goal setting-process tracking-self-reflection-comprehensive evaluation" is established. Personalized learning pathways and career guidance are provided to students. Practical results indicate:Classroom participation increased from 65.2%±12.1%before the reform to 81.3% ±10.5%, representing a 16.1% improvement. The homework submission rate rose from 78.4%±9.3% before the reform to 92.6%±6.7%, an increase of 14.2 percentage points. The rate of students independently completing practical training projects increased from 60.5%±15.4% to 79.8%±12.2%. The average student score increased from (68.7±8.2) points to (81.5±7.4) points, representing a 12.8 points (an increase of approximately 18.6%). The average satisfaction score for the academic assessment system rose from (3.2±0.6) points to (4.1±0.5) points. Additionally, indicators such as student satisfaction and employer job-fit alignment have shown an upward trend. This model effectively stimulates students' initiative in learning and practical skills, offering valuable insights for vocational automotive institutions to establish intelligent, personalized academic assessment systems. References | Related Articles | Metrics

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Research and Practice on the Path of Collaborative Ideological and Political Education between Schools and Enterprises in Higher Vocational Automotive Repair Major from the Perspective of Industry-Education Integration SUN Huan 2026, 51(9): 95-100.  DOI: 10.16638/j.cnki.1671-7988.2026.009.018 Abstract ( )   PDF (1209KB) ( )   With the rapid development of China's automotive industry, the demand for high-quality technical and skilled talents in the automotive maintenance industry is becoming increasingly urgent. This study focuses on the vocational auto repair major from the perspective of industry education integration, exploring effective paths for school enterprise collaboration in ideological and political education. Through in-depth analysis of the challenges faced by ideological and political education in this major, combined with industry demand and professional characteristics, a system of ideological and political education has been constructed with "integrating morality and technology" as the core, industry education integration as the carrier, and deep cooperation between schools and enterprises. The study proposes a series of innovative measures, including optimizing top-level design, co building curriculum resources, building a dual teacher team, strengthening practical education, and improving evaluation mechanisms. Through empirical research and practical testing, the effectiveness of the proposed path has been confirmed, significantly improving students' ideological and political literacy, professional ethics, and vocational skills, and providing enterprises with a large number of composite talents who understand politics, excel in technology, and are good at innovation. This study has important theoretical value and practical significance for deepening the reform of vocational education teaching, promoting modern apprenticeship system, and achieving high-quality development of vocational education. References | Related Articles | Metrics

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Research and Analysis on the Application of Virtual Simulation Technology in the Teaching of New Energy Vehicles LU Jian, CHENG Lianshe 2026, 51(9): 101-106.  DOI: 10.16638/j.cnki.1671-7988.2026.009.019 Abstract ( )   PDF (1082KB) ( )   With the rapid development and widespread application of new energy vehicles, the major of new energy vehicle technology has been commonly established in automotive programs at vocational colleges. Given the characteristics of new energy vehicles, how to carry out teaching safely and efficiently has become a critical issue facing this major. The rapidly advancing virtual simulation technology in recent years will undoubtedly bring significant benefits to the teaching of this discipline. This paper provides an in-depth analysis of the limitations of traditional teaching methods in the instruction of new energy vehicle technology. Based on the teaching characteristics of this major, a teaching application model using virtual simulation technology is proposed. Through applied research, the paper summarizes the features of virtual simulation technology in the teaching of this major, as well as directions for future optimization. This study provides valuable references for improving the integration of virtual simulation technology with the new energy vehicle technology major, enhancing teaching quality, and better serving professional instruction. References | Related Articles | Metrics

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Research on the Teaching Mode of Battery Management Course Based on AMESim DONG Peiyang, SUN Song, CHENG Xinlong, CHENG Kanghui 2026, 51(9): 107-110.  DOI: 10.16638/j.cnki.1671-7988.2026.009.020 Abstract ( )   PDF (1046KB) ( )   The Battery Management course involves a large number of technical parameters and numerical calculations, making it difficult for students to correlate technical parameters with battery performance during the teaching process. Drawing on the Sino-German Advanced Vocational Education Cooperation Project (SGAVE), simulation technology is introduced into practical teaching to construct a complete knowledge chain and evaluation system of theoretical derivation, simulation verification, and engineering application. The practical results show that simulation technology not only solves the difficulties in practical teaching of the Battery Management course, but also presents the mechanism changes of power batteries in a visual way, stimulating students' interest in learning and enabling them to actively participate in the thinking and exploration of learning problems. References | Related Articles | Metrics

Standards·Regulations·Management

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A Study on the Influencing Factors and Causal Mechanisms of Severe Road Traffic Accidents LIANG Hua1 , ZENG Wu1 , LUO Jiang3 , LIAO Huanwang1 , GAO Jianping1 , LI Yongwei2 2026, 51(9): 111-117.  DOI: 10.16638/j.cnki.1671-7988.2026.009.021 Abstract ( )   PDF (1628KB) ( )   Road traffic accidents represent a major threat to public safety and socio-economic development, with severe accidents causing particularly significant losses of life and property. Based on traffic accident data collected in a specific region from 2017–2020, this study employed random forest sensitivity analysis combined with statistical methods to identify and examine the key factors influencing accident severity. The results indicate that lighting conditions, casualty type, driving experience, intersection type, lane or median configuration, and pavement type are the core variables. Further analysis revealed that severe accidents predominantly occurred during daytime and well-lit nighttime hours, with drivers and passengers of moderate driving experience (5–10 years) exhibiting higher risk profiles. Sections without intersections or Y-shaped intersections demonstrated particularly prominent risks, while the most critical hazards were identified in unseparated two-way lanes. The findings highlight that both roadway design and participant characteristics play decisive roles in accident severity, providing a scientific basis for traffic safety management and risk prevention. References | Related Articles | Metrics

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Research on the Influencing Factors of Autonomous Vehicle Promotion from the Public Perspective LIU Qingkai1 , LÜ Li1 , BAI Guohua1 , GU Zhipeng2 , YANG Junmei2 2026, 51(9): 118-122,129.  DOI: 10.16638/j.cnki.1671-7988.2026.009.022 Abstract ( )   PDF (1270KB) ( )   With the rapid development of intelligence, autonomous driving vehicles have also advanced rapidly. However, the public has doubts about their technology, safety, and legal aspects, and this attitude hinders the development of autonomous driving vehicles. This article first designs relevant questionnaires through the Likert five-point scale method, then uses the statistical package for the social sciences (SPSS) to test the reliability and validity of the collected data, and finally conducts in-depth analysis with the Logit model. The study takes whether one is willing to recommend autonomous driving vehicles as the dependent variable, and age, gender, income, etc. as independent variables. The results show that indicators such as age, income, understanding of autonomous driving, technical maturity, confidence in handling highway conditions, and willingness to accept premium (p<0.05) all have significant impacts on the willingness to recommend. Among them, age is significantly negatively correlated with the willingness to recommend, with younger groups more willing to recommend, while the elderly are the opposite. Income, technical maturity, confidence in handling highway conditions, and willingness to accept premium are positively correlated with the willingness to recommend. Additionally, over 70% of respondents expressed concerns about privacy leaks, reflecting that information security issues are also significant obstacles in the promotion process. References | Related Articles | Metrics

Reviews

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Overview of SOC Estimation Methods for Lithium-Ion Batteries ZHANG Ni, SHENG Guochao* 2026, 51(9): 123-129.  DOI: 10.16638/j.cnki.1671-7988.2026.009.023 Abstract ( )   PDF (1479KB) ( )   Lithium-ion batteries, as one of the core components of new energy vehicles, have become a key research field for new energy vehicles. To pursue more efficient battery management technologies, the estimation method of battery state of charge (SOC) has become a critical research content. At present, mainstream battery SOC estimation methods include data-driven technologies, advanced filtering methods, and machine learning algorithms. Advanced filtering methods and machine learning algorithms exert remarkable effects on improving the accuracy of SOC estimation, and the integration of artificial intelligence and hybrid models also demonstrates favorable performance in enhancing SOC estimation performance. This paper conducts a specific evaluation on battery SOC estimation methods in battery management systems, summarizes and compares existing SOC estimation methods, concludes the advantages and disadvantages of various methods, proposes a system architecture for multi-state joint estimation, and forecasts the development trends of SOC estimation methods, so as to contribute to the safe operation and efficient management of lithium-ion batteries. References | Related Articles | Metrics

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Review of Brake Disc Temperature Estimation Methods DU Mansheng, ZHOU Chenyang 2026, 51(9): 130-137.  DOI: 10.16638/j.cnki.1671-7988.2026.009.024 Abstract ( )   PDF (2327KB) ( )   Accurate estimation of vehicle brake disc temperature is crucial for ensuring braking system safety and preventing thermal fade. This paper reviews key technical methods for brake disc temperature estimation, including sensor measurement (contact and non-contact), physical modeling (lumped parameter model, thermo-mechanical coupled finite element simulation, thermal network, energy balance model), and data-driven methods (multiple regression, machine learning algorithms). Comparative analysis of their principles, accuracy, advantages and limitations shows that sensor measurement serves as calibration basis for physical modeling; physical modeling provides mechanistic constraints for data-driven methods; and data-driven methods boost model adaptability and generalization, forming a "measurement–modeling–data" closed-loop support system together. Finally, this paper further summarizes the challenges of existing methods in extreme operating conditions, real-time performance, and engineering applicability, while outlining future research directions including multi-method integration, sensor technology synergy, dynamic adaptive optimization, and practical engineering implementation. These insights aim to provide references for brake system design and safety monitoring. References | Related Articles | Metrics

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Research Progress on Key Technologies for Collaborative Control of Traffic Flow at Intelligent and Connected Intersections LIN Qilin 2026, 51(9): 138-144.  DOI: 10.16638/j.cnki.1671-7988.2026.009.025 Abstract ( )   PDF (1207KB) ( )   As the core nodes of urban traffic networks, intersections are confronted with the inefficiency of conventional traffic signal control and stop-yield mechanisms in catering to the rapid growth of traffic volume. Such traditional approaches also fail to adapt to the complex mixed-traffic scenarios involving connected and automated vehicles (CAV) and human-driven vehicles (HDV). This paper systematically reviews four key technologies for cooperative control, including vehicleto-everything (V2X) sensing and communication, cooperative control architecture design, mixed traffic flow modeling, and core algorithm optimization. It further conducts an in-depth analysis of the current research challenges, such as time delays in multi-source sensing and the imbalance between cooperative control architecture and algorithm efficiency. Accordingly, the development trends are proposed, including multimodal perception fusion, robust disturbance rejection control, and green low-carbon multi-objective optimization, providing references for further research in this field. References | Related Articles | Metrics