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主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

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    Adaptive Energy Management for New Energy Vehicles
    Powertrain Optimization of Electric Dumping Trucks Based on Driving Cycle
    WU Jinlong1,2 , TIAN Chuan1,2 , XIE Fan1,2, HE Jianjun1,2, HU Yuanbo1,2
    2026, 51(7): 1-7,36.  DOI: 10.16638/j.cnki.1671-7988.2026.007.001
    Abstract ( )   PDF (2411KB) ( )  
    Driven by the "dual carbon" strategic goals, optimizing the energy consumption of electric urban construction muck dump trucks is of great significance for green urban construction. This study develops a dedicated driving cycle for electric muck dump trucks in Chengdu based on the internet of vehicles platform. The cycle shows significant differences from China heavy-duty commercial vehicle test cycle-dumper (CHTC-D): the proportion of the 0–10 km/h low-speed range is 5.3% higher, and the 50–60 km/h medium-high speed range is 7.3% higher, reflecting the unique driving characteristics of urban construction muck scenarios dominated by low-speed idling with suburban high-speed demand. A vehicle simulation model is established based on the cycle to optimize the power transmission system. By optimizing the shifting strategy and reconstructing hardware configuration, the simulated energy consumption is reduced by 6.3 kWh/100 km, providing scientific basis and engineering solutions for improving the economy of electric muck dump trucks.
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    Adaptive Fuel Cell Energy Management Strategy Based on Driving Conditions
    SHI Hongyan, YANG Hao, KANG Wu, LIU Yanhu, QIAO Pengyu
    2026, 51(7): 8-12,30.  DOI: 10.16638/j.cnki.1671-7988.2026.007.002
    Abstract ( )   PDF (1403KB) ( )  
    Common operating scenarios for fuel cell heavy-duty trucks include low-speed operations within yards, medium-speed urban driving, plain national highways, mountainous national highways, and highway operations. Different operating scenarios impose varying requirements on the output power of the fuel cell and the discharge capability of the power battery, presenting challenges in optimizing energy efficiency and durability for fuel cell vehicles under complex and changing conditions. This paper designs a driving condition-adaptive energy management strategy for fuel cell vehicles. Firstly, a machine learning model is constructed based on historical data to predict the future vehicle speed. Secondly, the vehicle's operating state is classified by combining predicted data with real-time data. Subsequently, energy management strategies with optimal energy consumption under different operating conditions are defined based on experimental results to ensure optimal vehicle economy under corresponding conditions. Finally, the output power of the fuel cell is filtered. According to simulation comparative analysis, the condition-adaptive energy management strategy reduces hydrogen consumption by 1.8% compared to the original strategy, while maintaining good vehicle following performance.
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    Brake Energy Recovery Optimization Method for Pure Electric Vehicles Based on Operating Condition Recognition
    DING Lei1 , DONG Zhihui1 , WU Song2 , HAN Lixing1 , CAI Jianjun3
    2026, 51(7): 13-19.  DOI: 10.16638/j.cnki.1671-7988.2026.007.003
    Abstract ( )   PDF (1456KB) ( )  
    Pure electric vehicles face the problem of range anxiety, and how to improve battery energy efficiency has become a research hotspot. In response to the shortcomings of existing pure electric vehicle braking energy recovery strategies in actual operation, this study proposes a pure electric vehicle braking energy recovery control strategy based on condition recognition to optimize the energy recovery effect of pure electric vehicles in actual road driving environments. This method uses K-means clustering algorithm to classify the driving state of the actual vehicle during braking energy recovery, and uses machine learning algorithm to identify and train the driving state with insufficient energy recovery, establishing a vehicle operating condition recognition model. Design improved control strategies for driving conditions with poor recycling efficiency, establish an online execution module, and switch vehicle control strategies in real-time. The results show that this method can accurately identify working conditions with poor braking performance, improve the efficiency of braking energy recovery by switching optimization strategies, and increase the range by 3%~4% compared to the original braking energy recovery scheme.
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    Intelligent Connected Vehicle
    Design of an Intelligent Inspection and Fire-Fighting Vehicle Based on Multi-Source Heterogeneous Data Fusion
    WANG Fengjuan1 , TANG Hao1,2 , FENG Junjie1 , WANG Xingyue1
    2026, 51(7): 20-25.  DOI: 10.16638/j.cnki.1671-7988.2026.007.004
    Abstract ( )   PDF (1157KB) ( )  
    Aiming at the problems of prominent fire safety risks, difficult manual inspection and low emergency response efficiency, this paper designs an intelligent inspection and fire-fighting vehicle. The vehicle takes the STM32 microcontroller as the core, and adopts a closed-loop working mode of fixed-line tracking, fire source detection and disposal, and automatic return to tracking. Stable and accurate driving along the preset path is realized by grayscale tracking technology combined with cascade proportional-integral-derivative (PID) algorithm. A multi-source heterogeneous fire detection system is constructed by flame sensors, comprehensive environmental sensors and YOLOv11 visual recognition, and accurate fire detection and positioning are realized with the Kalman filtering algorithm. Experimental results show that the system stably completes the operations of path tracking, fire source detection and fire extinguishing, and realizes autonomous inspection in a simulated scenario. The system achieves a fire source recognition accuracy of 96.3% and an average fire extinguishing time of less than 6 s, which rapidly handles incipient fires and presents good engineering application value.
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    Research on Lane-changing Trajectory Planning of Intelligent Vehicles Based on Artificial Potential Field
    XIAO Pan, HE Zhizhong
    2026, 51(7): 26-30.  DOI: 10.16638/j.cnki.1671-7988.2026.007.005
    Abstract ( )   PDF (1106KB) ( )  
    Improving the stability and safety of intelligent vehicles during lane changes on freeways is one of the core research directions in the field of intelligent transportation systems. This paper takes the lane-changing condition of intelligent vehicles on freeways as the research object, adopts the artificial potential field (APF) algorithm as the basic algorithm for lane-changing trajectory planning, and focuses on improving the repulsive force range of the traditional artificial potential field algorithm. Based on the minimum safe lane-changing distance model integrated with the elliptical vehicle safety contour, a semi-elliptical repulsive force range of the artificial potential field is constructed, and the functional relationship between this repulsive force range and the relative vehicle speed is determined. To verify the effectiveness of the improved method, simulation experiments are carried out in a joint simulation environment of Simulink/CarSim with a model predictive trajectory tracking controller (MPC). The results show that the improved artificial potential field algorithm can safely and effectively plan the lane-changing trajectory of intelligent vehicles on freeways. During the tracking process of the controller, the vehicle state parameters remain stable, which further verifies the effectiveness of the proposed algorithm.
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    Design and Research
    Research on Power Range of Outer Rotor Brushless DC Motor Used in Air Conditioner Blower of Vehicle
    ZHAO Quanbin
    2026, 51(7): 31-36.  DOI: 10.16638/j.cnki.1671-7988.2026.007.006
    Abstract ( )   PDF (1099KB) ( )  
    In this paper, according to the power supply voltage, the speed span, and the operation condition of the air conditioner blowers of vehicles, the performance advantages of the brushless direct current (DC) motor with fractional-slot concentrated winding outer-rotor applied in this area are analyzed. As for a fractional-slot concentrated winding outer-rotor brushless DC motor with a power supply voltage of 13.5 V and outer diameter of Φ88 mm, the parameters including main dimension, length-to-radius ratio, pole-slot combination, air-gap length, etc. are electromagnetics designed. The 2D finite element model of the motor is established and simplified, which the finite element simulation is carried out to determine the electromagnetic performances of the motor. The simulation results show that the design scheme of the motor can satisfy the demanded performances. Based on the former electromagnetics design, the achievable power range for the motor is obtained by modifying the wire turns, wire diameter, and axial length of the stator core of the motor, with the platform-based design method adopted and the other parameters unchanged. The recommended power distribution of the motor is given by considering the current, current density, loss, winding difficulty and cost of the driver. For the external rotor brushless DC motor of the air conditioner blower with the same power supply voltage and outer diameter, the design can be selected, and the parameters can be adjusted or the performance can be optimized according to the above power range.
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    A Cross-Talk Mitigation Design Method for Coreless Current Sensors Based on Artificial Neural Networks
    DU Enli, HUANG Yaodong* , YU Anbo
    2026, 51(7): 37-40,69.  DOI: 10.16638/j.cnki.1671-7988.2026.007.007
    Abstract ( )   PDF (1537KB) ( )  
    With the increasing power density of motor controllers, more and more extreme size requirements are imposed on current sensors. Although the emerging coreless current sensor solution can decrease the core size of the current sensor in terms of size, the inter-phase crosstalk is a major problem that cannot be ignored. To solve the inter-phase crosstalk problem of coreless current sensors, this paper proposes a rapid optimization design method for inter-phase crosstalk suppression of coreless current sensors based on a back propagation artificial neural network. By constraining the actual application size range of the sensor, the magnetic field simulation is carried out using three-dimensional finite element, and the simulation results are used for neural network training. In practical applications, this method only requires the inter-phase distance of the coreless sensor to be provided to complete the rapid correction of inter-phase crosstalk of the coreless current sensor. Through the comparison of numerical simulation results of different inter-phase distances with neural network results, the rapidity and effectiveness of the rapid optimization method for inter-phase crosstalk suppression based on artificial neural network are verified.
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    Design and Development of Gasoline Engine Test Stands Based on Convenient Positioning Function
    YU Hang, WANG Yakun
    2026, 51(7): 41-45.  DOI: 10.16638/j.cnki.1671-7988.2026.007.008
    Abstract ( )   PDF (1211KB) ( )  
    To address the shortcomings of existing engine test stands in terms of rapid positioning for multiple engine models, ease of operation, and operation duration, this paper has designed a gasoline engine test stand based on a convenient positioning function. By designing a mobile cart structure with a "coarse adjustment+fine adjustment" dual-dimensional adjustment mechanism, 90% of the installation work is transferred to be completed outside the test stand in advance. Meanwhile, compared with the traditional installation method within the test stand, the structure composition, working principle, and performance advantages of this system are systematically analyzed. Experimental verification results show that this test stand has smaller centering deviations for different engine models, shorter installation times, and better bolt torque stability, with overall performance superior to that of traditional test stands. This achievement enables precise positioning and convenient installation of different engines, significantly improving experimental efficiency and teaching quality. It has good application prospects in testing, teaching and other fields.
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    Design of High-Pressure LNG Supply System for Vehicles
    LUO Feng, Yeerdana·Baolatibieke, ZHANG Jie, MA Hongwei
    2026, 51(7): 46-50.  DOI: 10.16638/j.cnki.1671-7988.2026.007.009
    Abstract ( )   PDF (1840KB) ( )  
    All mainstream natural gas engines on the market adopt the technology of pre-mixed intake and spark ignition. At present, a high-pressure direct-injection natural gas engine for vehicles is under research and development, which can improve the power performance of existing natural gas engines. High-pressure direct-injection natural gas engines require high-pressure natural gas at 30 MPa to be injected for combustion and power output. Conventional vehicle liquefied natural gas (LNG) supply systems operate at relatively low pressure, so a pressurization device must be added to meet the high-pressure gas intake requirement. This paper studies the internal pressurization method inside the LNG cylinder, and designs a hydraulically driven cryogenic pump to pressurize and extract LNG liquid. After vaporization, high-pressure gas is formed for engine use. Meanwhile, the gas intake pressure and intake temperature are monitored to achieve more precise control of gas supply. Experimental verification shows that all indicators of the high-pressure LNG supply system meet the design requirements, and the system can provide stable and accurate high-pressure gas supply.
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    NVH Optimization of Electric Drive Assembly for Commercial Vehicle Based on Operational Deflection Shapes Analysis
    ZHAO Xuan, CHEN Xiaoli, WANG Xin, WANG Pengchuan
    2026, 51(7): 51-55106.  DOI: 10.16638/j.cnki.1671-7988.2026.007.010
    Abstract ( )   PDF (2155KB) ( )  
    This paper investigates the central electric drive assembly of a commercial vehicle model. Bench tests involving noise measurements during speed-increasing operations under loading conditions reveales pronounced resonance phenomena across multiple gear positions. To elucidate the resonance mechanism and develop mitigation strategies, a rigid-flexible coupled multi-body dynamics model of the drive assembly is established via Romax Designer. The model enables identification of resonance frequencies and corresponding structural operational deformation patterns. Subsequent local operational deflection shapes (ODS) analysis identifies the cover of shift actuator assembly as the critical resonance-prone component exhibiting maximum deformation amplitude. A noise-reduction solution involving damping material application to the inner surface of the cover is implemented without structural modifications. Comparative experimental results demonstrate significant resonance suppression, achieving a maximum noise reduction of approximately 4.6 dB(A) in the electric drive assembly.
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    Design and Research of Steel-Plastic Hybrid Cross Car Beam
    SUN Zhirui1 , LIU Qiongyu 1 , LI Xing2
    2026, 51(7): 56-61.  DOI: 10.16638/j.cnki.1671-7988.2026.007.011
    Abstract ( )   PDF (1876KB) ( )  
    Against the development trend of replacing steel with plastic in automotive interiors, this paper investigates a new cross car beam structure made of steel-plastic hybrid materials. Through product design optimization, application of lightweight materials and simulation-driven optimization, the hybrid beam meets key performance requirements including steering column modal characteristics, dynamic stiffness at steering column mounting points and dynamic stiffness at air conditioning mounting points. Compared with conventional steel cross car beams, it reduces weight by 20%~30%, cuts the number of parts by 80% and shortens assembly time by 65%. The structure achieves significant improvements in weight reduction and assembly efficiency, demonstrating high engineering application value.
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    Research on Carbon Emission Prediction and Reduction Methods in Transportation
    CHEN Dan1 , CHEN Yang1 , YU Hui2 , RAO Wenming1 , LI Ruiqi1 , REN Pengchao1
    2026, 51(7): 62-69.  DOI: 10.16638/j.cnki.1671-7988.2026.007.012
    Abstract ( )   PDF (1401KB) ( )  
    :In order to achieve the goal of "double carbon", the transportation industry urgently needs to solve the problem of high emissions and promote green, low-carbon and high-quality development. This paper focuses on the research of CO2 emission prediction and reduction methods in transportation. Firstly, a micro-observation model for CO2 emissions in transportation is constructed, and a medium and long-term prediction method for CO2 emissions in transportation based on the dynamic linear growth model is proposed. Then, CO2 emission efficiency measurement models from single-factor and multi-factor perspectives are constructed, and a CO2 emission regional difference analysis method based on K-means clustering is proposed. On this basis, an overall framework and organizational mechanism for transportation emission reduction based on market mechanisms are innovatively proposed, and a regional difference transportation emission reduction model is constructed. The effectiveness of the proposed methods is verified through case analysis. The research shows that under regional difference policies, the average energy conservation rate and emission reduction rate of transportation in various provinces and cities in eastern China can reach 26.34% and 30.95%, respectively, and the average emission efficiency can be improved by 46.44%. Compared with the comparison model, the average emission reduction rate and emission efficiency have been improved by 9.33% and 25.80%, respectively.
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    Testing and Experiment
    Research on the Selection Method for the Inner Panel of Automobile Engine Hoods Based on Multi-Objective Decision-Making
    HU Yuanzhi, SHI Zhengkai
    2026, 51(7): 70-75.  DOI: 10.16638/j.cnki.1671-7988.2026.007.013
    Abstract ( )   PDF (2246KB) ( )  
    To address the conflict between pedestrian head protection and lightweight objectives in automotive hood inner panel design, this paper proposes a multi-objective optimization-based selection methodology. Two candidate structures (component A and component B) are designed using DC04 steel and AL5182 aluminum alloy with different thickness parameters (steel: 0.6~0.9 mm; aluminum alloy: 0.8~1.4 mm), forming 16 design schemes. Finite element simulation is utilized to calculate the head injury criterion (HIC) scores and component mass for each scheme. Pareto frontier analysis is applied to screen the non-dominated solution set, identifying 5 Pareto-optimal solutions. Results demonstrate that AL5182 aluminum alloy schemes dominate the optimal solution set, with mass distribution ranging from 2.84~4.41 kg, effectively balancing lightweight and safety performance. Under identical material and thickness configurations, component A typically exhibits superior crashworthiness performance compared to component B. The study reveals the critical influence of material type, structural design, and thickness parameters on the trade-off relationship between lightweight and pedestrian protection performance in hood inner panels, providing practical basis and decision support for multi-objective optimization design of automotive components.
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    Analysis and Optimization of Rear Suspension Resonance Mechanism on Low-Adhesion Road Surfaces
    RAO Wenming1,2 , LIN Sheng1,2, ZHONG Weiwei1 , LIU Jian1,2 , ZHONG Chengping1,2, XU Gaoxin1,2
    2026, 51(7): 76-80.  DOI: 10.16638/j.cnki.1671-7988.2026.007.014
    Abstract ( )   PDF (1339KB) ( )  
    Based on an engineering case of rear suspension resonance occurring in a rear-drive new energy commercial vehicle operating on low-adhesion road surfaces, this paper investigates the phenomena of driving wheel slippage and periodic resonance. Utilizing vibration transfer path analysis principles and natural frequency identification techniques, the mechanism behind the vibration issue is revealed: it results from the coupling between the drive wheel hop frequency and the modal natural frequency of the rear suspension system, which excites rear suspension system resonance leading to whole-vehicle vibration. A traction control system (TCS) based on the anti-lock braking system (ABS) architecture is proposed. This system integrates the core control logic functions within a central control unit. System validation demonstrates the active intervention characteristics of the TCS during wide-open throttle acceleration, effectively suppressing excessive wheel slip and the resonance phenomenon. The research findings provide a new engineering application case for improving ride comfort and dynamic stability control of new energy commercial vehicles under low-adhesion road conditions.
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    Uncertainty Evaluation of Closed-Cup Flash Point Measurement for Automotive Diesel in Plateau Environment
    SHAO Qiang1,2, Da Zhen1,2 , ZHU Zhehui1,2*
    2026, 51(7): 81-84.  DOI: 10.16638/j.cnki.1671-7988.2026.007.015
    Abstract ( )   PDF (1002KB) ( )  
    To evaluate the measurement uncertainty of the closed-cup flash point of automotive diesel in plateau environments, this study addresses the requirements for detecting the closed-cup flash point of automotive diesel under plateau conditions. Based on experimental equipment using a fully automatic closed-cup flash point apparatus, this paper comprehensively analyzes the components of uncertainty sources during the flash point measurement process, quantifies the degree of influence of each factor on the measurement results, and derives the combined uncertainty and expanded uncertainty values through mathematical modeling. According to the analysis, the closed-cup flash point measurement result for diesel is (63.5±0.4) ℃. The study finds that during the uncertainty evaluation process, the uncertainty component of repeatability measurements is the largest, serving as the primary source affecting flash point determination results in plateau environments. It has a significant impact on the accuracy of measurement results and should be given focused attention during the testing process.
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    Study on Partial Frequency Dynamic Characteristics of Balanced Suspension Commercial Vehicle
    YANG Ruipeng, WANG Dan, CHEN Qifeng, JIAO Yan, WANG Yuan
    2026, 51(7): 85-89131.  DOI: 10.16638/j.cnki.1671-7988.2026.007.016
    Abstract ( )   PDF (1343KB) ( )  
    As the core design parameter of the suspension system, suspension partial frequency directly determines the vibration transmission characteristics during vehicle operation and has a crucial impact on vehicle performance such as vibration. Its design rationality is directly related to riding comfort, component reliability, etc. Aiming at the structural characteristics of commercial vehicles with balanced suspension, this paper identifies key components such as axles, suspension systems, frames, cabs and mounting systems, clarifies the connection relationship and mechanical characteristics of each component, and on this basis, establishes a vehicle 8-degree-of-freedom vibration system model, which provides a reliable simulation basis for the design of suspension partial frequency. In the design process, based on the actual design parameters of the vehicle, the system modal shape analysis is correlated with the spring stiffness parameters to automatically identify the suspension partial frequency. The vibration model established in this paper can ensure that reliable partial frequency results can be obtained quickly and effectively without prototypes in the early stage of design. It not only provides accurate simulation model support for the design of suspension partial frequency, but also can predict the impact of partial frequency design on vehicle vibration in advance, thus providing a basis for subsequent performance design.
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    Process·Materials
    Reliability and Design Guidelines for Acrylic Foam Tape Bonding in Automotive Exterior Applications
    HAN Yuxian1 , ZHU Hao2
    2026, 51(7): 90-95.  DOI: 10.16638/j.cnki.1671-7988.2026.007.017
    Abstract ( )   PDF (1699KB) ( )  
    Various attachment methods are employed for automotive exterior components. Among these, acrylic foam tape (AFT) has gained widespread application due to its superior stress distribution capabilities, excellent vibration damping and noise reduction properties, outstanding sealing performance, and high assembly efficiency. However, in practical engineering scenarios, AFT is susceptible to adhesion failure, which directly compromises the overall reliability of exterior assemblies. This paper provides an in-depth investigation into the critical factors influencing bonding performance, including application temperature, substrate surface finish, wet-out pressure, material selection (tape and primer), and the geometric compatibility between the component and its mating surface. Furthermore, it delineates essential design criteria for AFT integration, such as locating pin dimensions, edge clearance, release liner tab configurations, support rib design, and bonding area requirements. By synthesizing these influencing factors and design parameters, this study offers technical guidance for optimizing the bonding reliability of acrylic foam tapes in automotive exterior applications.
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    The Design of Engine Exhaust Manifold Nut Automatic Tightening Equipment
    LAI Mingcong
    2026, 51(7): 96-101.  DOI: 10.16638/j.cnki.1671-7988.2026.007.018
    Abstract ( )   PDF (2559KB) ( )  
    In order to resolve the pain points of low efficiency and inconsistent torque in manual tightening of exhaust manifold nuts on engine assembly lines, this paper develops a fully automated tightening device integrated with a servo pitch-adjustable mechanism, a jacking mechanism, and a laser-based positioning system. By deploying a six-axis robot to drive dual tightening shafts for collaborative operation, high-precision positioning and synchronous tightening of the nuts are achieved, with a cycle time of 39 s per workstation. This solution fundamentally enhances the automation rate of engine assembly lines and eliminates operator-induced variations, providing a replicable technical pathway for automating similar fastening processes.
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    Production Mode of Low-Cost Heat Treatment for Steel Parts
    HAO Yong1 , SU Shiyi1 , LIU Guoqing1 , WANG Yan1 , LIU Kangping1 , WANG Lanlan2
    2026, 51(7): 102-106.  DOI: 10.16638/j.cnki.1671-7988.2026.007.019
    Abstract ( )   PDF (2265KB) ( )  
    In 2025, electric energy accounts for 30% of industrial terminal energy consumption, and thermal processing is an important part of industrial electricity consumption. Coupled with the factors of technology, equipment and management, the processing cost remains high. In the fierce market competition, energy saving and consumption reduction have become the necessary trend of sustainable development of enterprises. The existing heat treatment process is conservative, the machining allowance is large, the equipment management is backward, and the production plan is discontinuous, which leads to low equipment utilization and serious energy consumption waste. Combined with the present situation, the concept of lean production is introduced into the heat treatment production process, and a low-cost heat treatment production mode is formed through four aspects: reducing machining allowance, equipment transformation, production planning and operation combination.
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    Automobile Education
    Development and Practice of Teaching Resources for Comprehensive Testing of Intelligent Connected Vehicles under the Background of the "Five Pillars" New Infrastructure
    XU Xiaoyu 1 , TIAN Gaohua2
    2026, 51(7): 107-111.  DOI: 10.16638/j.cnki.1671-7988.2026.007.020
    Abstract ( )   PDF (1158KB) ( )  
    In the context of deep integration between "five pillars" new infrastructure, through indepth analysis of the intelligent connected vehicle industry's job demand for high-quality technical professionals, we propose a teaching resource development path centers on moral education. Using the Intelligent Connected Vehicle Comprehensive Testing course as a platform, centers on the learning outcomes of students, this approach "professional aligns with industry chain requirements, course benchmarks against new standards, integrates dual-qualified faculty, matches real-world training scenarios, and ensures dynamic textbook updates". By establishing granular teaching resources characterized by "minimal functional units and maximum reusability value," we continuously explore optimized development pathways. This process breaks down curriculum knowledge, skills, equipment, and scenarios into standardized teaching components, builds concise teaching videos, lesson plans, exercises, and other resources. Utilize platforms like the Xuexitong to display these granular resources. Through granular resource development, we can better meet diverse needs including classroom teaching, "1+X" certification, and corporate social training, thereby cultivating new-generation skilled professionals with both a sense of 'serving the nation through technology' and the 'master craftsman' ethos.
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    Application Methods and Effect Analysis of Deep Learning in Intelligent Transportation System Teaching
    SONG Xianan, SONG Qingmin, FENG Lijuan* , LI Jiangjiang
    2026, 51(7): 112-116.  DOI: 10.16638/j.cnki.1671-7988.2026.007.021
    Abstract ( )   PDF (1108KB) ( )  
    With the rapid development of intelligent transportation systems worldwide, education on intelligent transportation systems, as a critical link in cultivating professional talents, faces challenges such as teaching content lagging behind technological advancements, weak practical components, and insufficient student innovation capabilities. Aiming at the practical challenges in intelligent transportation system education, this paper proposes teaching application strategies based on deep learning. Starting from three aspects, integration methods, specific applications, and teaching effectiveness evaluation, it focuses on exploring specific application methods of deep learning technology in core teaching content such as traffic flow prediction and traffic incident detection. The research adopts a mixed-method approach, combining quantitative data analysis with qualitative case studies to systematically evaluate the practical effectiveness of deep learning in intelligent transportation system education. Experimental results indicate that the introduction of deep learning technology significantly enhances students' technical application ability and problem-solving skills, while simultaneously improving the advanced nature and practicality of the teaching content.
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    Exploration and Practice of Automotive Construction Course Development in the Context of New Engineering
    LEI Xianhua, TAN Jieyu * , LI Yazi, LEI Yuxi
    2026, 51(7): 117-123.  DOI: 10.16638/j.cnki.1671-7988.2026.007.022
    Abstract ( )   PDF (1329KB) ( )  
    Under the background of new engineering, the Automotive Construction course faces challenges in adapting to the rapid iteration of new energy vehicles and intelligent connected vehicle technologies. This paper explores the core issues of curriculum construction from three aspects: first, building a dynamically updated curriculum content system by tracking cutting-edge technological breakthroughs, achieving the organic integration of core foundational knowledge with new energy and intelligent connected technology modules; second, promoting the sharing of practical platforms through the "university alliance" and "enterprise resource pool" models, addressing the shortage of practical resources for teachers and improving cross-regional resource utilization efficiency; third, improving a diversified evaluation system by strengthening indicators such as innovative design, competition performance, and teamwork, shifting the teaching objectives from knowledge transmission to capability cultivation. Practice shows that after the curriculum reform and construction, the synchrony between the curriculum content and industrial technology has significantly increased by about 32%. The practical guidance ability and norms of teachers have improved by about 50%. The engineering practice and innovation abilities of students have been effectively cultivated. The comprehensive participation rate in projects and competitions has increased by approximately 9%, and the comprehensive rate of winning awards and obtaining project approvals has increased by approximately 19%. This exploration can provide practical experience for the construction and reform of similar engineering courses.
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    Research on Talent Cultivation Model by Job Demand Oriented from the Integration of Industry and Education -A Case Study of Automobile Majors in Higher Vocational Colleges
    LI Xiaojing, SHEN Shengli, JIAO Hongxing, HU Wei
    2026, 51(7): 124-128.  DOI: 10.16638/j.cnki.1671-7988.2026.007.023
    Abstract ( )   PDF (2000KB) ( )  
    The automobile major is to adapt to the new changes brought by the development of science and technology in the fields of industry production, construction, management and service. It complies with the new trend of electrification, intelligence, networking and sharing in the automotive industry, and meets the new requirements for positions such as automobile manufacturing, new business forms and new models. There is an urgent need for a large number of professionals. However, the shortage of highly skilled talents in the automobile industry coexists with the difficulty of employment for graduates. This paper analyzes the industry demand, takes the industry demand and student employment as the orientation, and takes the integration of industry and education as the starting point. This paper analyzes the talent training mode of vocational automobile majors, solves the contradiction between "teaching" and "production" of enterprises, explores the integrated development mode of industry and education suitable for the needs of regional automobile industry, and delivers qualified talents to the automobile industry.
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    Based on the "Learning by Doing" Project-Integrated Comprehensive Practice Curriculum Reform -A Case Study of the New Energy Vehicle Engineering Major
    HAN Shaojian, LI Xiaojie, LUO Jia, CHEN Dongdong, ZHANG Rui
    2026, 51(7): 129-134.  DOI: 10.16638/j.cnki.1671-7988.2026.007.024
    Abstract ( )   PDF (2586KB) ( )  
    To address the pressing demand for interdisciplinary engineering talents in the highquality development of the new energy vehicle industry, the new energy vehicle engineering program at North University of China has established an integrated comprehensive practice curriculum system centered on learning by doing. This initiative targets core challenges in traditional practical education including theory-practice disconnect, fragmented knowledge delivery, outdated content, and monotonous methods by employing representative engineering cases to implement full-cycle theory– design–manufacturing–testing training, thereby organically integrating professional knowledge acquisition and practical skill development throughout the four-year undergraduate program. Empirical results confirm that the reform significantly enhances teaching quality, strengthens students' comprehensive mastery of automotive engineering theory and practice, effectively stimulates proactive engagement, and elevates capabilities in scientific research and innovative practical application.
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    A CiteSpace-Based Visualization Analysis of Literature on Ideological and Political Education in Automotive Maintenance Courses
    LIN Xu
    2026, 51(7): 135-139.  DOI: 10.16638/j.cnki.1671-7988.2026.007.025
    Abstract ( )   PDF (2183KB) ( )  
    To clarify the research context, hotspots and development trends of ideological-political education integrated into automobile maintenance courses in China, The article uses the data source of China national knowledge infrastructure (CNKI), relevant literatures from January 2019 to July 2025 are retrieved, and CiteSpace software is used to conduct visual quantitative analysis on 130 valid literatures. The results show that the number of published papers on ideological-political education in automobile maintenance courses presents a trend of steady growth followed by a slight decline. The research forces are mainly secondary vocational colleges and higher vocational colleges, but the cooperation between authors and institutions is sparse and the research structure is scattered.The research hotspots focus on ideological-political education in courses, craftsmanship spirit, teaching reform and information-based teaching. The research has generally shifted from theoretical construction to practical implementation, showing a digital development trend. At present, there are still some problems in the research, such as superficial integration of ideological-political elements, insufficient innovation in teaching modes, and shallow application of information technology. Systematic analysis of the research characteristics in this field is conducive to promoting cross-institutional cooperation, deepening the organic integration of ideological-political education and professional teaching, and boosting the high-quality development of ideological-political education in automobile maintenance courses.
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    Research on the Curriculum Reform of Automotive Vocational Education Based on the Integration of Virtual and Reality -Taking the Course Fundamentals of Automotive Service Engineering as an Example
    LIU Ning
    2026, 51(7): 140-144.  DOI: 10.16638/j.cnki.1671-7988.2026.007.026
    Abstract ( )   PDF (1203KB) ( )  
    Against the backdrop of the rapid development of the automotive service industry and the transformation of vocational undergraduate education, vocational undergraduate automotive service engineering and technology courses face practical problems such as deviation from the professional "practice oriented" training positioning, low matching between content and core job competency requirements, and insufficient adaptability of teaching modes. This article takes the course "Fundamentals of Automotive Service Engineering" as the research object, and proposes a curriculum reform path centered on the "combination of virtual and real" technology by reconstructing the course content system, innovating teaching modes, and optimizing assessment and evaluation mechanisms. Research has shown that this program significantly improves students' learning initiative, with the proportion of students actively speaking up increasing from 21% to 58%. Academic performance has steadily improved, with an average course score increase of 13 points. Improved feedback from students and internship companies. More than 20 outstanding project achievements have been transformed into dynamic teaching resources, forming a closed loop of "learning practice resource regeneration", verifying the systematic and effective nature of the reform. At the same time, this study provides a practical paradigm for the construction of similar courses in vocational undergraduate colleges.
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