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15 September 2026, Volume 51 Issue 17 Previous Issue   
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New Energy Vehicle
Intelligent Connected Vehicle
Design and Research
Testing and Experiment
Automobile Education
Standards·Regulations·Management


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New Energy Vehicle

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A fault diagnosis method for new energy vehicle reducer bearings based on BO-BiGRU-SDAE WANG Linlin1 , JIN Lei1 , ZHU Shanggong1 , RAN Di2 , XIU Lingling1 2026, 51(17): 1-5,45.  DOI: 10.16638/j.cnki.1671-7988.2026.01 001 Abstract ( )   PDF (1478KB) ( )   The reducer is a key power component in new energy vehicles. The built-in rolling bearings are prone to various failures, which can lead to major traffic accidents and seriously threaten driving safety. To address issues in diagnosing reducer bearing faults under strong background noise–such as insufficient anti-interference capability of deep models, limited diagnostic accuracy, and difficulty in tuning deep model parameters. By leveraging the synergistic effect of the strong noise-robust feature extraction capability of stacked denoising autoencoder (SDAE) and the temporal modeling advantages of Bidirectional gated recurrent unit (BiGRU), combined with bayesian optimization (BO) for model parameter tuning to enhance diagnostic performance, this paper proposes a novel fault diagnosis method for new energy vehicle reducer bearings based on the BOBiGRU-SDAE model. Experiments were conducted on common fault states of new energy vehicle reducer bearings. The results showed that the proposed method achieved a diagnostic accuracy as high as 98.75%, significantly higher than other mainstream neural network models. The study confirms that the proposed method demonstrated excellent effectiveness and accuracy. The study can provide an efficient and feasible technical solution for diagnosing new energy vehicle reducer bearing faults. References | Related Articles | Metrics

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Application and development research of 3.0T V6 methanol engine WU Zhanhu, LEI Jiaojiao, JIA Yun, LI Xiaojin 2026, 51(17): 6-12,51.  DOI: 10.16638/j.cnki.1671-7988.2026.017.002 Abstract ( )   PDF (1525KB) ( )   To promote methanol-extended-range new-energy commercial vehicles, targeted optimization design is carried out on the fuel supply, intake-exhaust, ignition, lubrication and other systems of the prototype engine based on a 3.0T V6 gasoline engine body and in combination with the physicochemical properties of methanol fuel. Core technologies including the Atkinson cycle, variable-geometry turbocharger (VGT) and 4-valve variable valve timing (4VVT) are integrated to address key problems of methanol engines such as corrosion, wear, cold start difficulty and seal failure. Bench test results show that the optimized 3.0T V6 M100 methanol engine delivers a net power of 230 kW, a net torque of 510 Nm and a minimum specific methanol consumption of 440 g/(kW·h), with its thermal efficiency reaching 42.7%. The model accuracy of both engine external characteristics and universal characteristics meets design criteria. All performance indicators satisfy the power output requirements of extended-range new-energy commercial vehicles, so this engine can serve as a reliable power matching unit for such vehicles. Compared with conventional retrofitted methanol engines, this engine features high power density, compact size and convenient maintenance. References | Related Articles | Metrics

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Research on lithium battery SOC joint estimation based on VFF-RLS and UKF LIU Yangyang, SHI Wei, ZHANG Zhuohang, HUANG Kailong, LI Mengci 2026, 51(17): 13-22.  DOI: 10.16638/j.cnki.1671-7988.2026.01 003 Abstract ( )   PDF (1655KB) ( )   To address the issue of limited state of charge (SOC) estimation accuracy for lithium-ion batteries under complex dynamic operating conditions, caused by time-varying model parameters, this paper proposes a joint estimation method based on an improved variable forgetting factor recursive least squares (VFF-RLS) algorithm and unscented Kalman filter (UKF). First, a secondorder resistor-capacitor (RC) equivalent circuit model is established, and the VFF-RLS algorithm is employed to identify the model parameters in real time. Then, an adaptive adjustment of the forgetting factor is achieved by constructing a function based on voltage prediction errors, which resolves the trade-off between convergence speed and steady-state fluctuation inherent in traditional fixed-parameter algorithms. Subsequently, the real-time identified parameters are incorporated into the UKF algorithm for SOC estimation, effectively suppressing nonlinear errors. Finally, experimental validation is conducted. The results demonstrate that under the hybrid pulse power characteristic (HPPC) condition, the root mean square error (RMSE) of the model terminal voltage prediction is only 0.001 3 V, confirming the accuracy of the parameter identification. Under the dynamically severe dynamic stress test (DST) condition, the SOC estimation RMSE of the proposed algorithm is 0.744 6%, showing a significant improvement in accuracy compared to the fixed forgetting factor algorithm. Under the complex Urban dynamometer driving schedule (UDDS) condition, the algorithm maintains a high estimation accuracy of 0.791 9% without the need for manual parameter tuning. Comparative experiments confirm that the proposed joint algorithm outperforms the traditional extended Kalman filter (EKF) algorithm in both accuracy and robustness. References | Related Articles | Metrics

Intelligent Connected Vehicle

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Research on steering wheel hands-off detection method based on torque signal LI Penglong, GAO Xinhua, WANG Jinlei, YUAN Li* , ZHANG Jingjia 2026, 51(17): 23-33.  DOI: 10.16638/j.cnki.1671-7988.2026.017.004 Abstract ( )   PDF (1722KB) ( )   In L2-level autonomous driving assistance systems, accurate driver hands-off detection is a critical factor for ensuring driving safety. Among the current mainstream hands-off detection technologies, torque-based steering wheel systems suffer from high false alarm rates, capacitivebased steering wheel systems incur high costs, and visual monitoring approaches have blind spots and degraded performance at night. To address these issues, this paper proposes a hands-off detection method based on multi-feature fusion deep learning. The method extracts multi-dimensional features from raw steering wheel torque signals in the time domain, frequency domain, and combined timefrequency domain. A one-dimensional convolutional neural network (CNN) is employed to process the raw signal branch, while a multi-layer perceptron (MLP) is used to process the handcrafted feature branch. The multi-feature fusion network (MFF-Net) then performs feature fusion and classification, directly outputting a binary classification result indicating whether the driver's hands are on or off the steering wheel. Validation on 108 sets of real-world driving data demonstrates that the proposed method achieves a detection accuracy of 99.07%, which meets the precision requirements of L2-level driving assistance systems for hands-off detection. This work provides an optimized solution for low-cost steering wheel hands-off detection and holds considerable engineering application value. References | Related Articles | Metrics

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With the advancement and widespread adoption of assisted driving and autonomous driving technologies, traffic sign recognition has become a pivotal component of intelligent transportation systems. To achieve precise identification of traffic sign images by vehicles, this paper proposes a two-stage recognition method based on YOLOv8n and Vision Transformer (ViT). During the object detection phase, the YOLOv8n model combined with an anchor-free bounding box mechanism enables rapid localization of target regions. In the recognition phase, the ViT network is employed to extract global self-attention features from candidate regions, enhancing discrimination accuracy for similar signs. Additionally, image enhancement techniques such as MixUp, CutMix, and Albumentations are applied during training to improve the model's robustness under real-world driving conditions including occlusion and lighting variations. Finally, the effectiveness and robustness of the proposed method are validated on the German traffic sign detection benchmark (GTSDB) and the German traffic sign recognition benchmark (GTSRB). YANG Jing, LUO Yuan 2026, 51(17): 34-39.  DOI: 10.16638/j.cnki.1671-7988.2026.017.005 Abstract ( )   PDF (1574KB) ( )   With the advancement and widespread adoption of assisted driving and autonomous driving technologies, traffic sign recognition has become a pivotal component of intelligent transportation systems. To achieve precise identification of traffic sign images by vehicles, this paper proposes a two-stage recognition method based on YOLOv8n and Vision Transformer (ViT). During the object detection phase, the YOLOv8n model combined with an anchor-free bounding box mechanism enables rapid localization of target regions. In the recognition phase, the ViT network is employed to extract global self-attention features from candidate regions, enhancing discrimination accuracy for similar signs. Additionally, image enhancement techniques such as MixUp, CutMix, and Albumentations are applied during training to improve the model's robustness under real-world driving conditions including occlusion and lighting variations. Finally, the effectiveness and robustness of the proposed method are validated on the German traffic sign detection benchmark (GTSDB) and the German traffic sign recognition benchmark (GTSRB). References | Related Articles | Metrics

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Research on driving stability of vehicle lane keeping under autonomous driving mode LIU Zhengsen 2026, 51(17): 40-45.  DOI: 10.16638/j.cnki.1671-7988.2026.017.006 Abstract ( )   PDF (1196KB) ( )   Lane keeping system is a key function of autonomous driving, and its stability is directly related to driving safety. To this end, this paper constructs a vehicle-road coupled dynamics model that takes into account tire nonlinearity, suspension roll, and road adhesion effects, and proposes a fuzzy sliding mode control strategy based on preview deviation compensation. The asymptotic stability of the closed-loop system is proved using Lyapunov theory. The simulation model parameters are selected and calibrated based on real vehicle data of a certain production sedan. The results show that the proposed strategy achieves high trajectory tracking accuracy and lateral stability under different vehicle speeds and road curvatures, with lateral deviation controlled within 0.15 m, meeting the safety requirements of autonomous driving. References | Related Articles | Metrics

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Research on trajectory tracking control based on the MPC algorithm YUAN Liqiu, DUAN Xinyue 2026, 51(17): 46-51.  DOI: 10.16638/j.cnki.1671-7988.2026.017.007 Abstract ( )   PDF (1185KB) ( )   Aiming at the lane-changing trajectory tracking control problem of intelligent vehicles, this paper proposes a trajectory tracking control strategy based on model predictive control (MPC). Firstly, a 2-degree-of-freedom vehicle dynamic model is established, and the state-space expression is adopted to describe the lateral motion characteristics of the vehicle. Secondly, a fifth-order polynomial lane-changing trajectory is designed as the desired path, which features continuous and smooth curvature and heading angle. Then, a trajectory tracking controller is designed based on the MPC algorithm, and the 2-degree-of-freedom vehicle model is discretized. Taking the lateral position deviation and heading angle deviation as state variables and the front-wheel steering angle as the control variable, a cost function containing tracking error and control increment is constructed.Constraint conditions including front-wheel steering angle, steering-angle change rate and lateral acceleration are introduced, and the optimal control problem is transformed into a quadratic programming problem for solution. Finally, the co-simulation of MATLAB/Simulink and CarSim is used to verify the feasibility and effectiveness of the proposed control strategy. Simulation results show that the designed controller achieves favorable tracking performance and high tracking accuracy under different vehicle-speed working conditions. The maximum lateral displacement error is kept within 0.045 m, and the front-wheel steering angle varies smoothly. References | Related Articles | Metrics

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A study on technology and industry development of automotive intelligent driving based on K-means clustering and LDA topic modeling YU Yatao 2026, 51(17): 52-58,84.  DOI: 10.16638/j.cnki.1671-7988.2026.017.008 Abstract ( )   PDF (2935KB) ( )   This study focuses on relevant content in the field of automotive intelligent driving on WeChat public accounts over the past three years, using "automotive intelligent driving" and "automotive industry" as keywords for thematic retrieval. After data cleaning and organisation, 121 high-quality texts were selected as the analysis corpus. The study employs the latent dirichlet allocation (LDA) topic model to train the obtained texts, identifying the core research hotspots in China's intelligent driving technology field, namely computing power, risk, risk level, data models,driver monitoring, assisted driving, sensor fusion, and intelligent vehicles. On this basis, the study further points out that automotive industry practitioners and learners in related fields should pay sufficient attention to eight aspects–computing power research, risk research, risk level research, data model research, driver monitoring research, assisted driving research, sensor fusion research, and intelligent vehicle research–when conducting research in intelligent driving technology in the future. For hotspot theme task identification, the study verifies the effectiveness and practicality of the LDA topic model through K-means clustering. Its analysis results are conducive to researchers and industry personnel quickly grasping frontier developments and research focuses in the field. Additionally, the study's conclusions can provide references for automotive industry policy-making and corporate technology planning, helping the automotive sector form a clearer development path in key intelligent driving technologies. References | Related Articles | Metrics

Design and Research

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Study on comfortable seating position of Chinese vehicle drivers HUA Meng, WEN Bing, CAO Yong, HUO Canjian 2026, 51(17): 59-65.  DOI: 10.16638/j.cnki.1671-7988.2026.017.009 Abstract ( )   PDF (2510KB) ( )   At present, most domestic automakers adopt the society of automotive engineers (SAE) comfort model for designing human seating positions, which is derived from anthropometric data of American populations and tends to cause comfort complaints when applied in China. To investigate the comfortable seating positions of Chinese vehicle drivers, this study establishes a comfort seating position model based on anthropometric data of Chinese drivers. A total of 12 test vehicles are selected, from which the comfortable driving postures are collected, the positional relationship between the driver's H-point and foot pedal point is extracted, and a fitted model of comfortable seating position is obtained. Comparative analysis with the SAE model is conducted to demonstrate the differences in anthropometric dimensions. The effectiveness of the proposed comfort model is further verified via a human-machine bench test. This research provides certain guiding significance for the design of driving comfort tailored to Chinese drivers. References | Related Articles | Metrics

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Design of integrated thrust rods in commercial vehicle chassis suspensions YAN Ge, XU Wenliang 2026, 51(17): 66-70,100.  DOI: 10.16638/j.cnki.1671-7988.2026.017.010 Abstract ( )   PDF (3055KB) ( )   As the core load-transmitting component of a commercial vehicle's chassis suspension system, the torque rod plays a critical role in transmitting longitudinal and lateral forces, suppressing axle displacement, and maintaining wheel alignment parameters. It is responsible for transferring push-pull balance forces and constraining side-bending torque to restrict axle movement, thereby enhancing the overall stability and rigidity of the chassis suspension. Traditional friction-welded torque rods suffer from issues such as excessive connection points, susceptibility to loosening, and heavy weight. To address this, this paper designs an integrated torque rod assembly structure. Under the premise of ensuring strength and reliability, this design reduces stress concentration. Compared with traditional tubular friction-welded structures, it eliminates welding defects between components, resulting in a more uniform stress distribution. This also increases fatigue resistance, improving the vehicle's driving stability, operational safety, and component service life. Through finite elementsimulation and fatigue durability experimental analysis, the stress distribution, modal characteristics, and fatigue life of the integrated torque rod under typical load spectra are simulated and verified. This provides a theoretical basis and engineering reference for the lightweight, high-reliability design of commercial vehicle suspension torque rods. References | Related Articles | Metrics

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Active control of rear-wheel steering based on road adhesion coefficient WU Gang, DONG Yehui* , LIU Kai, HUANG Zhonghai, DUAN Xuyong 2026, 51(17): 71-79.  DOI: 10.16638/j.cnki.1671-7988.2026.017.011 Abstract ( )   PDF (2757KB) ( )   This study aims to address the issues of reduced robustness and insufficient control accuracy in rear-wheel steering (RWS) systems operating on low-adhesion road surfaces. Complex road conditions, such as wet or icy surfaces, can cause abrupt variations in the tire–road friction coefficient, severely impacting the robustness and stability of rear-wheel steering control. To tackle these challenges, this research proposes an active control strategy based on real-time estimation of the dynamic road adhesion coefficient; specifically, it constructs a friction coefficient estimation model using multi-source sensor data and designs an adaptive regulation control strategy for the rear wheel angle to achieve rapid response across various road conditions. Validation through both simulation and physical vehicle testing demonstrates that the proposed control method significantly enhances the lateral stability and handling response of the vehicle under complex and variable road environments, while effectively suppressing the risk of instability. This study provides a theoretical foundation and engineering reference for the adaptive chassis control of intelligent vehicles in complex environments, offering significant practical value for improving the all-weather driving safety capabilities of autonomous driving systems. References | Related Articles | Metrics

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Research on technical renovation of drainage unit in flood control emergency rescue and drainage vehicle MENG Weilai 2026, 51(17): 80-84.  DOI: 10.16638/j.cnki.1671-7988.2026.017.012 Abstract ( )   PDF (1633KB) ( )   Flood-control emergency rescue encounters diverse hazard scenarios, requiring flooddrainage vehicles to combine high-flow and high-lift performances. Due to the rapid iteration of flood drainage vehicles, most vehicles manufactured five to six years ago suffer from insufficient lift capacity and cannot handle deep waterlogging hazards. To address this problem, the layout of onboard cabin equipment is optimized and a high-lift drainage unit is installed without altering the vehicle appearance. This approach overcomes lift-limitation constraints to satisfy deep-waterlogging drainage requirements while taking drainage flow into account, achieving a performance balance between high lift and large flow. It can provide reference ideas for the upgrading and retrofitting of aging flood-drainage equipment as well as the research and development of new-type flood-drainage equipment. References | Related Articles | Metrics

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Application of virtual manufacturing technology in automotive dimensional engineering XU Mian1 , SHI Kai2 , XU Mingyang1 , DUAN Zongyao3 , LI Chengjie1 2026, 51(17): 85-90.  DOI: 10.16638/j.cnki.1671-7988.2026.017.013 Abstract ( )   PDF (2136KB) ( )   As competition in the automotive industry intensifies, vehicle development cycles are continuously shortened, while customers are paying increasing attention to exterior appearance and functional details. Dimensional matching accuracy directly affects vehicle gap and flush quality as well as the realization of related functions, and therefore serves as a critical foundation for ensuring vehicle appearance quality and performance in use. Traditional physical analysis and validation methods can no longer meet these requirements. This paper systematically elaborates the application approach of virtual manufacturing technology in automotive dimensional engineering. From the three levels of single parts, assemblies, and the whole vehicle, a full-process system for dimensional analysis and application based on virtual manufacturing is established. At the single-part level, the rationality of the reference point system (RPS) design is mainly analyzed. At the assembly level, deviations are predicted through full-process simulation of welding, hemming, and other manufacturing processes. At the whole-vehicle level, virtual matching technology is used to identify matching risks in advance. Engineering practice in a vehicle project demonstrates that this system can effectively improve dimensional design quality and on-site ramp-up efficiency, thereby enabling front-loaded control of dimensional quality. References | Related Articles | Metrics

Testing and Experiment

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Simulation analysis of spot welds fatigue in heavy truck cab based on virtual bench LIU Zhilei1 , DU Jian2* 2026, 51(17): 91-95,137.  DOI: 10.16638/j.cnki.1671-7988.2026.017.014 Abstract ( )   PDF (4509KB) ( )   To investigate the influence of force-based and stress-based spot weld modeling methods on cab fatigue behavior, a heavy-duty truck cab is selected as the research object. A rigid-flexible coupled virtual model of the cab is developed in ADAMS, and road load spectrum data are collected from vehicle proving ground tests. The virtual iteration method is applied to reproduce the cab,s load-bearing state under test conditions. Simulation results are correlated with experimental data to validate the accuracy of the virtual test rig model, while dynamic fatigue load spectra at cab interface points are extracted for subsequent analysis. Using the quasi-static method with the decomposed load spectra as input, the accuracy of the force-based and stress-based methods in predicting spot weld fatigue is evaluated. Results indicate that both approaches yield consistent fatigue damage distributions in the cab. However, the stress-based method demonstrates higher accuracy, with simulation outcomes aligning more closely with bench test data, whereas the force-based method offers advantages in modeling efficiency and computational speed. Finally, process improvements are applied to critical weld regions, leading to a 5.89-fold increase in cab fatigue life, thereby verifying the effectiveness of the proposed modifications. References | Related Articles | Metrics

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The practical application of the physical method for direct vision of commercial vehicles based on UN R167.01 ZHANG Xin, CAI Pengfei, TAN Wanli, ZHANG Chaolin 2026, 51(17): 96-100.  DOI: 10.16638/j.cnki.1671-7988.2026.017.015 Abstract ( )   PDF (2831KB) ( )   As the latest technical specification of the United Nations for the direct vision safety of commercial vehicles, Uniform Provisions Concerning the Approval of Motor Vehicles with Regard to Their Direct Vision (UN R167.01) is characterized by complex technical definitions, numerous testing steps, and a lack of commercial testing tools. This article, combining theoretical analysis, systematically elaborates on the core definitions, physical test principles and procedures of UN R167.01, and constructs a test implementation framework that can directly guide engineering practice. Moreover, based on the self-developed testing equipment of this center, it provides a test case for the direct vision of commercial vehicles. After testing, the nearside visible volume of acertain vehicle model is 5.74 m 3 , the front visible volume is 10.17 m 3 , the subsection front visible volume is 3.12 m 3 , the offside visible volume is 10.72 m 3 , and the total visible volume is 26.63 m 3 . The test results show that the direct vision testing equipment for commercial vehicles independently developed by our center can effectively complete the UN R167.01 regulation test, providing testing support for Chinese commercial vehicle products to meet international market access requirements. References | Related Articles | Metrics

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European regional hybrid vehicle fuel economy optimization and empirical research GAO Xiang, HAN Haowei, WANG Guoqiang, TAO Yu, CHENG Junlong 2026, 51(17): 101-108.  DOI: 10.16638/j.cnki.1671-7988.2026.017.016 Abstract ( )   PDF (2126KB) ( )   With the strategy of expanding overseas exports advances, the demand for differentiated performance development for different markets has become increasingly urgent. During the market entry into Europe, the fuel economy of a hybrid sports utility vehicle (SUV) model deteriorated significantly due to considerable differences between local traffic conditions and those in China and the lack of targeted strategy adjustments, resulting in weakened product competitiveness. Based on the driving characteristics of European users, this paper conducts an in-depth analysis from the perspectives of vehicle architecture, engine characteristics and control strategies under typical driving conditions, including a constant high speed of 130 km/h, a high-speed cycle collected in Turkey, and the worldwide harmonized light vehicles test cycle (WLTC). The results show that under high-speed conditions, taking reducing the frequency of secondary energy conversion as the core strategy can effectively lower fuel consumption while maintaining battery state of charge, with fuel consumption improved by 0.14 L/100 km at a constant high speed and 0.2 L/100 km under the Turkey-collected high-speed cycle. For the WLTC cycle, a refined simulation benchmarking optimization method is proposed, which achieves a further fuel consumption reduction of approximately 0.1 L/100 km by re-optimizing the existing start-stop strategy. The core strategies and optimization methods presented in this paper can provide an important reference for the performance development of the company’s overseas models. References | Related Articles | Metrics

Automobile Education

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A "adjust-integrate-evaluate" talent cultivation model for vehicle engineering driven by industry needs LIU Chao1 , WU Na1* , WU Chao1 , XU Zitao2 2026, 51(17): 109-113.  DOI: 10.16638/j.cnki.1671-7988.2026.017.017 Abstract ( )   PDF (1134KB) ( )   To address the disconnection between talent cultivation of Vehicle Engineering and industrial demands in application-oriented universities, this paper proposes and constructs a closedloop education model centered on "adjustment-integration-evaluation". Relying on dynamic adjustment of curriculum systems, in-depth integration of school-enterprise teaching and multi-dimensional evaluation feedback, this model forms a self-iterative improvement mechanism of "demand drivingteaching implementation-effect evaluation-continuous optimization". Taking the Vehicle Engineering program of Tangshan University as an example, practice proves that the model enables precise matching between curriculum content and post competencies. The excellent and good rate of students' engineering practice and innovation capacity rises from 40% to 70%, the average post adaptation period shortens by around 30%, and enterprise satisfaction reaches over 80%. The findings offer replicable and promotable systematic solutions for applied engineering talent cultivation in similar universities. References | Related Articles | Metrics

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Innovation and exploration of project-driven teaching under the new technological paradigm －A case study of the New Energy Vehicle Power Battery Technology course HUANG Lili1 , LIU Xiaobin1* , WANG Song2 , YIN Xinquan1 , LIU Yongtao3 , DU Yao1 2026, 51(17): 114-118.  DOI: 10.16638/j.cnki.1671-7988.2026.017.018 Abstract ( )   PDF (1287KB) ( )   To meet the demand for cultivating comprehensive automotive engineering professionals in response to the transformation of the automotive industry under the new technological paradigm, and to address the current issues such as the singularity of ability cultivation and the lag in course reorganization in automotive-related courses. This study takes the course of New Energy Vehicle Power Battery Technology as the research object, centering on the completion of specific projects, developing projects based on teaching content for the course, and emphasizing practical application based on the actual learning situation of students. It adopts a teaching method of "heuristic, discussion-based, research-oriented, and extended group-based" to assign project tasks at different levels, personalizing student cultivation, and guides students to complete the project contents of the course teaching elements. Students complete the task assessment through self-study, explanation, discussion, and defense activities, thereby fostering their scientific research capabilities and innovative thinking. This forms a teaching innovation model of "knowledge reconstruction-ability advancement-proactive innovation-assessment based on project". According to the assessment results of two consecutive cohorts of students before and after the reform, it is evident that the overall academic performance of students has significantly improved, effectively enhancing the teaching effect, bridging the gap between theoretical teaching and industrial practice, and meeting the needs of automotive enterprises for compound engineering talents. References | Related Articles | Metrics

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Training and practice of computational thinking in electrical and electronic practice of automotive engineering XU Jinhai, ZHANG Lei, ZHAO Yongqiang 2026, 51(17): 119-123.  DOI: 10.16638/j.cnki.1671-7988.2026.017.019 Abstract ( )   PDF (3370KB) ( )   Electrical and Electronic Practice is a public required practical course for the vehicle engineering major, designed to introduce fundamental knowledge and practical skills in electrical and electronic engineering. It typically emphasizes the development of students' engineering practice abilities but often overlooks the cultivation of engineering thinking. This paper integrates computational thinking into Electrical and Electronic Practice, using graphical programming as the practical platform, aiming to guide students in applying computational thinking to address multifaceted and systematic engineering problems. Practice has shown that this approach effectively enhances students' enthusiasm for practice and strengthens their practical capabilities in design, circuit analysis and debugging, and problem solving, providing an effective pathway for cultivating modern vehicle engineering talents with computational thinking and engineering competence. References | Related Articles | Metrics

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Practical research on the digital literacy evaluation model for students in higher vocational automotive major LIU Zongyao, YANG Wenhui, LIU Jun 2026, 51(17): 124-128.  DOI: 10.16638/j.cnki.1671-7988.2026.017.020 Abstract ( )   PDF (1100KB) ( )   To address the new requirements for digital literacy in the automotive industry's digital transformation and explore a digital literacy evaluation path that suits the characteristics of automotive majors in higher vocational colleges, this paper, guided by social constructivist learning theory, adopts an action research method. Data are collected through semi-structured interviews, participatory observation, and document analysis, and are subjected to thematic analysis. The research aims to reveal the cognitive characteristics of digital literacy among automotive major students, the interaction between their cognition and the standardized evaluation framework, and to construct a digital literacy evaluation model with professional specificity based on these findings. The research findings indicate that automotive major students' cognition of digital literacy is characterized by contextualization and pragmatism, with an emphasis on instrumental rationality and practical value orientation. There is a structural tension between individual cognition and the standardized evaluation framework. Students actively adjust the dynamic balance with the evaluation framework through strategies such as cognitive reconstruction of key events in the interaction. The study shows that the formation of digital literacy among automotive major students in higher vocational colleges is a constructive process of continuous negotiation with the evaluation framework in specific professional contexts. References | Related Articles | Metrics

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Interdisciplinary curriculum teaching reform path for cultivating outstanding engineers －A case study of the course Principles of Artificial Intelligence WANG Zhiyuan1 , ZHANG Yangang1* , YIN Guohua2 , CHEN Jianjun2 2026, 51(17): 129-137.  DOI: 10.16638/j.cnki.1671-7988.2026.017.021 Abstract ( )   PDF (2567KB) ( )   As a crucial component of the national strategic talent pool, outstanding engineers serve as key supports for advancing high-level self-reliance and strength in science and technology, building a leading technological nation, and realizing Chinese modernization. Constructing a graduate professional curriculum system aligned with the goal of cultivating outstanding engineers is essential for solidifying their theoretical foundation and professional knowledge. This paper addresses current issues in curriculum structure, implementation, teaching staff allocation, and evaluation methods. It systematically explores a teaching reform path for cultivating exceptional engineers from four dimensions: curriculum system, teaching process, teaching staff, and evaluation mechanism. Taking the course Principles of Artificial Intelligence in the Vehicle Engineering major master's program at North University of China as a practical case, we introduce an engineering demand-driven six-step teaching model along with diversified instructional methods, establish an interdisciplinary teaching team, and build a four-efficacy evaluation system centered on process-based evaluation and holistic assessment. Practice demonstrates that in the course, the proportion of process-based evaluation for students increases to 60%, indicators related to engineering innovation capability improve significantly, teaching satisfaction exceeds 90%, and a replicable, scalable model for curriculum reform initially takes shape. This study provides an actionable pathway reference for cultivating high-level, interdisciplinary engineering master's students. References | Related Articles | Metrics

Standards·Regulations·Management

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Quality gate management application in new product development of commercial vehicle transmissions XIONG Zhao 2026, 51(17): 138-142,148.  DOI: 10.16638/j.cnki.1671-7988.2026.017.022 Abstract ( )   PDF (1221KB) ( )   As commercial vehicle transmissions evolve from mechanical products toward newenergy and intelligent ones, effective R&D process management and new product quality improvement stand out as key tasks for transmission enterprises during transformation. Targeting prominent problems such as frequent defects in R&D trial production and high after-sales failure rates in new product development, this paper adopts quality gate management theory, integrates whole-process quality management and maturity management concepts, and constructs a standardized quality gate management system suitable for Fast Company from the perspectives of quality gate classification, review procedures, node planning and responsibility allocation. After implementation, this system strengthens risk interception capacity at each link, cuts after-sales failure rates, shifts quality management from passive troubleshooting to active prevention, and offers valuable references for peer enterprises in the industry to improve new product development quality. References | Related Articles | Metrics

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Research on regulations and testing methods for automatic emergency braking systems of commercial vehicles exported to the European Union XU She, ZHANG Guoxi 2026, 51(17): 143-148.  DOI: 10.16638/j.cnki.1671-7988.2026.017.023 Abstract ( )   PDF (2021KB) ( )   The global fatality rate of commercial vehicle traffic accidents remains high. The automatic emergency braking system (AEBS) is a key technology to reduce accidents, and the European Union has mandated it for commercial vehicles through UN ECE R131. This paper reviews the formulation and revision process of the regulation, and provides a detailed analysis of the four core test scenarios and their corresponding criteria: stationary target, moving target, failure detection, and false response. Combined with a real vehicle test case of a semi-trailer tractor exported to the European Union, it is verified that all vehicle indicators meet the regulatory requirements. It is also concluded that excessive deceleration during the warning stage and insufficient warning-to-emergency braking time are common causes of test failure, which are rooted in unreasonable design of the vehicle's AEBS control strategy. Finally, it is pointed out that the current regulatory test scenarios have limitations, and it is suggested to improve the standards and enrich test conditions in the future, so as to provide a reference for domestic commercial vehicle export and AEBS technology optimization. References | Related Articles | Metrics