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30 May 2026, Volume 51 Issue 10 Previous Issue   
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System Integration and Intelligent Decision
New Energy Vehicle
Design and Research
Testing and Experiment
Process·Materials
Automobile Education


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System Integration and Intelligent Decision

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Comparative Study of LSTM and TCN Models for Vehicle Thermal Management Performance Prediction LI Guoyun 2026, 51(10): 1-9.  DOI: 10.16638/j.cnki.1671-7988.2026.010.001 Abstract ( )   PDF (1097KB) ( )   The operating characteristics of vehicle thermal management systems are jointly affected by driving conditions, temperature settings and occupant comfort. An accurate performance prediction is critical for system optimization and fault diagnosis. This paper employs dual-layer long short-term memory (LSTM) and temporal convolutional network (TCN) for temperature prediction in electric vehicle thermal management systems, analyzes the mechanism of the two algorithms,verifies key modules through ablation experiments, and discusses the influences of data length, time window and training strategies on prediction performance.Using root mean squared error (RMSE), mean squared error (MSE), mean absolute error (MAE), concordance correlation coefficient (CCC) and training time as evaluation metrics, the models are trained and validated based on real-vehicle coolingdown data. The predicted trends of facevent air temperature and breath temperature are compared with measured data. Results show that the dual-layer LSTM model achieves higher accuracy with a CCC value of 0.94 for facevent air temperature. The TCN model exhibits outstanding advantages in training and inference efficiency: its training time is only 2.2% of the LSTM model, and the prediction speed is nearly 15 times higher, while the accuracy still meets engineering requirements. Ablation experiments demonstrate that the dual-layer structure and Dropout enhance the performance of LSTM, and dilated convolution combined with residual connections constitutes the core of efficient TCN modeling. The 30 s time window, 1 650 s data length and optimized training strategies achieve the best model performance. This study provides valuable references for the application of dual-layer LSTM and TCN in vehicle thermal management systems. References | Related Articles | Metrics

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Whale-Algorithm-Optimized Integral Terminal Sliding-Mode Path-Tracking Control for Autonomous Vehicles HUANG Yudan, ZHONG Yong, CHEN Guichuan 2026, 51(10): 10-19.  DOI: 10.16638/j.cnki.1671-7988.2026.010.002 Abstract ( )   PDF (3477KB) ( )   To address the problems of large steady-state error, obvious chattering,and decreased robustness under complex disturbances that may exist in traditional linear sliding mode control for autonomous driving trajectory tracking, the article proposes an integral adaptive sliding mode control strategy based on the whale optimization algorithm (WOA). By establishing a vehicle dynamics model and a comprehensive error system, an integral sliding mode surface is designed, and an adaptive law is introduced to compensate for system uncertainties and external disturbances. The WOA is used to globally optimize the control law parameters. The asymptotic stability of the system is proven using Lyapunov theory. CarSim/Simulink co-simulation results show that compared with the comparison methods, the proposed scheme significantly improves trajectory tracking accuracy, response speed, and robustness. Under external disturbance conditions, the average lateral error is reduced by 20%～30%, verifying its application value in autonomous driving trajectory tracking. References | Related Articles | Metrics

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SOC Accurate Estimation of Lithium-ion Battery Based on CNN-MLP Dual-Branch Fusion Network SONG Wei 2026, 51(10): 20-26.  DOI: 10.16638/j.cnki.1671-7988.2026.010.003 Abstract ( )   PDF (1442KB) ( )   In the context of the rapid development of new energy and energy storage systems, moment, while a 1D-CNNextracts local temporal features from a sliding window of multivariate sequences. The features from both branches are subsequently concatenated to achieve fused prediction, enabling end-to-end SOC estimation. Experimental results show that the proposed model achieves a root mean square error (RMSE) of 1.48 and a coefficient of determination (R 2 ) of 0.996 on the test set. Compared with single-branch CNN, MLP, and long short-term memory (LSTM) models, the CNN-MLP fusion model demonstrates significant improvements in mean absolute error (MAE), RMSE, and R 2 , validating the effectiveness of the dual-branch decoupling and feature fusion strategy in enhancing the robustness and accuracy of SOC estimation. high-precision estimation of the state of charge (SOC) of lithium-ion batteries is crucial for battery safety and energy management. To address the challenges posed by strong nonlinearity, dynamic hysteresis, and noise interference under complex operating conditions, this paper proposes a SOC estimation method based on a convolutional neural network-multilayer perceptron (CNN-MLP) dual-branch fusion network. The method employs a decoupled modeling approach: a multilayer perceptron captures the nonlinear mapping of current, voltage, and temperature at the present References | Related Articles | Metrics

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Research on a T-BOX Signal Parsing and Decoupling Method for Multi-Vehicle Adaptation DU Cuixia, ZHANG Yan 2026, 51(10): 27-34.  DOI: 10.16638/j.cnki.1671-7988.2026.010.004 Abstract ( )   PDF (1195KB) ( )   To address the core problems of long development cycle, high maintenance cost and low matrices. A parsing tool converts DBC files from different suppliers into standard JavaScript object notation (JSON) configuration files, and assigns a globally unique logical index to each functional signal, so as to realize complete decoupling between the application layer and physical layer signal positions. During T-BOX operation, corresponding configuration files are dynamically loaded according to vehicle identification codes. The parsing engine accurately extracts signal values based on the configurations, and processes and distributes the signals by classification in accordance with three signal models: event, alarm and status. Upper-layer applications only need to subscribe to fixed logical indexes to shield the heterogeneity of underlying CAN protocols. Experimental results show that the proposed scheme reduces the adaptation cycle for new vehicle models from 40 person-days in traditional schemes to 3 person-days, and decreases the central processing unit (CPU) occupancy rate of the signal parsing module by 62.3%. In cross-vehicle switching tests, upper-layer applications operate normally without any modification. The method effectively improves development efficiency, system maintainability and scalability, and provides a feasible solution for the platform-based and standardized development of intelligent connected vehicles. platformization caused by inconsistent controller area network (CAN) communication matrices when intelligent connected vehicle terminals are adapted to different vehicle models, this paper proposes a T-BOX platform design method based on signal ID decoupling and dynamic configuration loading. The core of the method is to construct a signal parsing middleware abstracted from specific CAN References | Related Articles | Metrics

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Analysis and Optimization Methods of CANFD Communication Quality ZHOU Hongying, LIU Xiaoxiang, WANG Min, YIN Shuo 2026, 51(10): 35-39.  DOI: 10.16638/j.cnki.1671-7988.2026.010.005 Abstract ( )   PDF (1127KB) ( )   Aiming at the problem of poor communication signal waveform quality (such as severe smaller number of nodes, shorter CANFD branch lines, configuring weak terminal resistors for non-terminal nodes, and selecting NXPTJA1645 transceivers with ringing suppression, the signal ringing is minimized and the signal quality is improved. Finally, optimization measures are proposed from aspects of topology reconstruction, harness parameter management and control, and hardware configuration upgrading. Vehicle tests verify that these measures can effectively suppress signal reflection and ringing, avoid misjudgment of recessive bits, and significantly improve the communication reliability of the CANFD bus. This research provides a quantitative basis and practical solutions for the design of automotive CANFD networks and the optimization of signal quality. reflection and ringing) in the application of controller area network flexible data rate (CANFD) bus in the automotive field, this paper conducts research on signal quality analysis and optimization by combining the design requirements of CANFD network system solutions and practical application pain points. Firstly, based on the CANFD sampling principle and the requirements for recessive bit reception threshold, an evaluation method of "level assessment in the 50%~100% interval after the recessive bit" is constructed, and the acceptance criteria for signal quality testing are formulated. Secondly, by using the control variable method, comparative tests are carried out on key influencing factors including network topology, number of nodes, harness design, terminal resistor configuration, and transceiver selection. The results show that when using a topology without nested branches, a References | Related Articles | Metrics

New Energy Vehicle

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Analysis of Influence of Uncoordinated Charging of Electric Vehicles on Distribution Transformer CAI Tianyu, ZHANG Jinjiang* , MO Yujie, GE Mengxue, ZHOU Zhiqiang 2026, 51(10): 40-45.  DOI: 10.16638/j.cnki.1671-7988.2026.010.006 Abstract ( )   PDF (1792KB) ( )   With the rapid growth in the number of electric vehicle (EV) in use, the large-scale integration of EVs into the distribution network for charging poses new challenges to the power system. As the core equipment of the distribution network, the operational safety and lifetime loss of distribution transformers are more significantly affected by EV charging loads. Considering residential travel and charging behaviors, this paper establishes an EV load model that takes into account both users' fast-charging probability and charging decisions. It employs the Monte Carlo random simulation method to calculate the charging load characteristics of typical residential areas under different EV penetration rates. In accordance with the IEC 60076-7 standard, a transformer capacity assessment model is built, focusing on analyzing the mechanism by which EV charging impacts the hot-spot temperature, lifetime loss, and failure rate of transformers under two scenarios: uncoordinated charging and load leveling optimization.The results show that: for every 20% increase in EV penetration rate, the daily average lifetime loss of transformers can increase by 1.8 to 2.5 times; under the high penetration scenario of 75%, the peak failure rate of transformers is 62.3% higher than that under the base load scenario; after load leveling optimization, the lifetime loss of transformers can be reduced by 81.2%, and the failure rate drops to the level when no EV are connected to the grid. The research in this paper can provide theoretical support for the assessment of connecting charging piles to distribution transformers in old residential communities and the dispatch of ordered EV charging. References | Related Articles | Metrics

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Analysis of Research Hotspots in Vehicle Stability Control Based on CiteSpace DONG Mingmei, LIU Jia* , WAN Xue, WANG Jun, WANG Lijian 2026, 51(10): 46-52.  DOI: 10.16638/j.cnki.1671-7988.2026.010.007 Abstract ( )   PDF (6029KB) ( )   To fully understand the research status, hotspot evolution and cutting-edge trends in the field of vehicle stability control, this paper employs CiteSpace visual analysis software to conduct indepth mining and analysis of relevant literature on vehicle stability research from 2014 to 2024, which is indexed in the CNKI database and the WOS core collection database. By constructing keyword co-occurrence networks, clusters, timelines and burst maps, it visually presents the research force distribution, core themes, development context and research frontiers in this field. Results show that the core hotspots of vehicle stability research focus on driving stability, handling stability, electric vehicles, co-simulation, model predictive control and other aspects. This study indicates that model predictive control, coordinated control and stability control for distributed drive electric vehicles represent important research frontiers and development directions at present and in the future. References | Related Articles | Metrics

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Exploration on In-Car Whistling Suppression of a Certain Brand of Pure Electric Vehicles Based on Active Noise Control LI Xiangzhen 2026, 51(10): 53-57.  DOI: 10.16638/j.cnki.1671-7988.2026.010.008 Abstract ( )   PDF (916KB) ( )   Amid the accelerated transformation and upgrading of the new energy vehicle industry, the issue of mid-to-high-frequency whine noise inside battery electric passenger vehicles has become increasingly prominent due to the characteristics of their electric drive systems. This noise affects driving comfort and constrains product competitiveness. Therefore, conducting targeted noise control research holds significant industry value. This paper combines experimental analysis to identify the main noise sources as motor electromagnetic noise and gear meshing noise from the reducer. An active interior noise control approach is attempted. The results show that the system operates stably under constant-speed conditions of 40～80 km/h, achieving a noise reduction of up to 14 dB(A) at the target whine frequency and a maximum overall sound pressure level reduction of 2.86 dB(A), providing a practical reference for the performance optimization of battery electric vehicles. References | Related Articles | Metrics

Design and Research

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Practical Application of Vehicle Test Case and Script Generation Based on Large Language Models LIU Hui, ZHAO Lina 2026, 51(10): 58-61，67.  DOI: 10.16638/j.cnki.1671-7988.2026.010.009 Abstract ( )   PDF (964KB) ( )   To enhance the depth of analysis and generation efficiency of vehicle test cases and scripts, and to promote the development of automated testing, this paper focuses on the application and practice of artificial intelligence (AI) technology in vehicle automated testing, mainly covering the generation of automated test cases and the writing of automated test scripts. Specifically, the self-generation method of test cases based on large language models dynamically builds test scenarios with higher coverage by analyzing requirement documents and historical test data. The automated test scripts based on large language models combine reinforcement learning and code generation techniques to achieve the automatic writing and optimization of test scripts, reducing the error rate of manual coding while improving the efficiency of script maintenance. Practical results show that the automated generation system of vehicle test cases and test scripts based on large language models proposed in this paper can effectively increase the coverage of test cases by 18%, improve the efficiency of automated script writing by 50%, and significantly shorten the testing cycle. References | Related Articles | Metrics

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Development and Application of Broadband Noise Attenuation and Specific Frequency Noise Attenuation for a Heavy-Duty Truck Air Intake Pipe SONG Ziyuan, WANG Lei 2026, 51(10): 62-67.  DOI: 10.16638/j.cnki.1671-7988.2026.010.010 Abstract ( )   PDF (2853KB) ( )   With the tightening of commercial vehicle noise regulations, low-frequency noise control in the intake system is one of the measures to improve overall noise, vibration, harshness (NVH) performance. This research addresses the challenge of achieving efficient noise reduction across a wide frequency range in heavy-duty truck intake systems due to spatial constraints and flow resistance limitations in traditional muffler designs through forward engineering. For a specific heavy-duty truck intake system, an innovative integrated high-position air intake tube structure is proposed. By designing internal ribs to create a three-channel cross-sectional transition structure and integrating Helmholtz resonators, the method utilizes acoustic impedance abrupt changes and phase interference theory to achieve broadband noise reduction and targeted frequency attenuation. Simulation analysis and experimental verification demonstrate significant noise control effects in the intake system, with this research providing practical guidance for engineering applications. References | Related Articles | Metrics

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Development and Research of Instrument Control Technology Based on CANoe BIAN Jinxin, WU Bing 2026, 51(10): 68-73,94.  DOI: 10.16638/j.cnki.1671-7988.2026.010.011 Abstract ( )   PDF (2330KB) ( )   In the development of CANoe automated test systems for automotive components, the rapid integration of various instruments serves as a core bottleneck restricting the improvement of test efficiency. Aiming at the problems of poor compatibility and complicated operation existing in current instrument control technologies, this paper presents two control technologies applicable to most scenarios, namely instrument control technology based on CAPL DLL and instrument control technology based on C Library.These technologies can shield underlying logic. Testers only need to make simple calls in test scripts or directly operate system variables to realize the automated control of various instruments by CANoe efficiently, which effectively improves the integration efficiency and usability of the test system. References | Related Articles | Metrics

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Research and Verification on Torsional Vibration Improvement of Range Extender Based on Rotor Bracket of Generator YU Shuhao 2026, 51(10): 74-78.  DOI: 10.16638/j.cnki.1671-7988.2026.010.012 Abstract ( )   PDF (2250KB) ( )   Direct-connected range extender torque ripple of the engine is transmitted to the shaft of the coaxial generator. When the excitation frequency is coupled with the structural mode, the shaft resonance will be excited, obvious abnormal noise is heard. To address this issue, a combined finite element model of the rotor shaft and crankshaft is established using the finite element analysis method. Simulation calculate the modal and vibration mode of the shafting, and lock the problem mode in combination with the modal test; The modal contribution analysis identified a significant contribution from the rotor side. It proposes optimizing parameters such as the spoke angle, spoke thickness, and span of the rotor support bracket to achieve the optimal structure. Compared to the U-shaped structure, the T-shaped structure reduces modal strain energy by up to 50% and decreases the maximum vibration from impact by over 87% in vehicle testing. Subjective ratings improve by 1.5 points. It effectively solves the torsional vibration problem of the shafting caused by the direct connection structure of the range extender, which provides a reference for the design of the shafting structure of the direct connection range extender. References | Related Articles | Metrics

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Research on Vehicle Recognition Algorithm Based on Semantic Feature Enhancement SHANG Yabo, LEI Xinyu 2026, 51(10): 78-83130.  DOI: 10.16638/j.cnki.1671-7988.2026.010.013 Abstract ( )   PDF (1422KB) ( )   Fine-grained visual classification often leads to unstable recognition results due to the significant visual differences among objects within the same sub-class. To address this issue, this paper proposes a novel contrastive fine-grained visual classification network that suppresses intraclass variance by capturing the semantic consistency of visual changes within the same class. Specifically, it first uses spatial attention maps to embed discriminative regions to distinguish different sub-classes, and in this process, combines a feature selection self-attention module to enhance the model's focus on key features and reduce background interference, thereby effectively enhancing feature representation and extracting detailed information. Experimental results show that the proposed model has achieved significant performance improvements in multiple vehicle classification tasks, verifying the effectiveness and universality of the proposed method. References | Related Articles | Metrics

Testing and Experiment

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Optimization Research on Shoulder Force and Upper Chest Injury of Driver in Side Pole Crash LAN Jian, HE Ning, LIU Jiawen* 2026, 51(10): 84-89112.  DOI: 10.16638/j.cnki.1671-7988.2026.010.014 Abstract ( )   PDF (2502KB) ( )   The high chest injury and excessive shoulder force of the front driver in side pole collisions have always been a difficult point in the development of vehicle safety performance. To solve the issues of excessive chest injury and shoulder force on the driver in side pole collisions, it is necessary to study the key constraint system parameters that affect the shoulder force and upper chest injury of driver in the vehicle and provide the optimal constraint system parameter matching scheme. Article uses finite element analysis method and studies the influence of various key factors such as side airbag stiffness, package type, ignition time, and pelvic push block on the chest injury and shoulder force of WorldSID dummy based on the simulation analysis and vehicle test of a new energy vehicle's side pole collision. Optimization method and optimal solutions were proposed to reduce the driver's shoulder force and upper chest injury under side pole conditions. The results show that a reasonable constraint system parameterized matching can effectively reduce the dummy's shoulder force to within 3 kN and the upper chest injury to within 28 mm, providing rational suggestions and guidance for solving the problems of high upper chest injury and excessive shoulder force in the driver under side pole collision conditions. References | Related Articles | Metrics

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Research and Optimization Methods for the Housing Strength of Heavy-Duty Truck AMT Actuators LI Peng, ZHANG Bing 2026, 51(10): 90-94.  DOI: 10.16638/j.cnki.1671-7988.2026.010.015 Abstract ( )   PDF (3068KB) ( )   As a core component of the heavy-duty truck automated mechanical transmission (AMT) assembly, the shift actuator completes the shift commands issued by the transmission control unit (TCU) during the gear shifting process, while also withstanding various active and passive stresses in multiple directions. Addressing the issue of lower housing fracture during the front auxiliary section durability test, this paper proposes a new research approach. First, a strain test is conducted on the actuator fork to obtain the maximum force experienced by the fork. This maximum force is then used as an input for finite element analysis to calculate the maximum stress at the fracture location, enabling targeted improvement of the housing strength. After structural optimization, the stress at the housing fracture is reduced by 60%, and the housing ultimately passes 1.4 million shift durability cycles, validating the effectiveness of the proposed improvement solution. References | Related Articles | Metrics

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Research on Noise Optimization of Oil-Pump Controller in an Active-Suspension System of a Passenger Car LÜ Xiaolong 2026, 51(10): 95-99.  DOI: 10.16638/j.cnki.1671-7988.2026.010.016 Abstract ( )   PDF (1711KB) ( )   Based on the development of the active suspension system for a certain passenger car model, the problem of noise, vibration, harshness (NVH) noise generated by the oil pump controller under static vehicle conditions was encountered. To address the root cause of the problem, we formulated different control strategy plans and conducted verification and testing of the oil-pump controller at different cutoff frequencies. Finally, by combining the response characteristics of the oil-pump controller and the NVH test results, we determined that the optimal control strategy plan is condition 3, where the cutoff frequency of the oil-pump controller in SiC open-tube state is 8 000 Hz. This plan meets the functional development and NVH noise performance indicators of the activesuspension system, thereby enhancing vehicle comfort and handling stability. References | Related Articles | Metrics

Process·Materials

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Research and Design of Transmission Breakage Residue Gasification System for Syngas Production Based on Aspen Plus SHI Zhaozhuo, WANG Xin, PAN Jianbin, DENG Jingzhe, CAI Zilin 2026, 51(10): 100-103.  DOI: 10.16638/j.cnki.1671-7988.2026.010.017 Abstract ( )   PDF (1201KB) ( )   With the advancement of circular economies both domestically and internationally, coupled with the establishment of the “dual carbon” goals, the reuse of waste materials within the manufacturing sector has become a critical issue. Transmission breakage residue, as a typical industrial mixed plastic waste in manufacturing, poses urgent environmental pollution and resource wastage issues that require resolution during its processing. In this study, a gasification system is established using transmission breakage residue as the feedstock, and the effects of oxygen ratio, steam-to-carbon ratio, carbon-to-carbon ratio, and reforming temperature on the composition and yield of syngas are systematically analyzed. The results show that appropriate adjustment of process parameters can significantly increase the H2 and CO yields in the syngas and improve the overall gasification efficiency. This work provides theoretical guidance and data support for the resource utilization of transmission breakage residue and similar solid wastes. References | Related Articles | Metrics

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Study on Zonal Corrosion Damage of Entire Vehicle HUANG Lei, LI Xiang, ZHANG Tao, XIAO Hui 2026, 51(10): 104-107.  DOI: 10.16638/j.cnki.1671-7988.2026.010.018 Abstract ( )   PDF (1877KB) ( )   To accurately identify differences in corrosion damage across various vehicle regions and achieve precise anti-corrosion design with cost optimization, this study systematically collected panel check index (PCI) data from four typical areas–roof, underbody, engine compartment, and passenger compartment-based on accelerated corrosion tests of passenger vehicles. Combined with the equivalent cumulative corrosion environment method, quantitative analysis and comparison of corrosion damage in each region were conducted. The test results show significant differences in corrosion damage across vehicle regions, with the damage level following the descending order: underbody>roof>engine compartment>passenger compartment. Notably, after 60 test cycles, the corrosion damage in the underbody reached 596.55, approximately 224 times that of the passenger compartment. Based on these findings, the paper further proposes a differentiated anti-corrosion design strategy for different zones, along with recommendations for materials, coatings, and structural improvements for high-risk areas. This research provides data support and methodological references for the reverse optimization of vehicle anti-corrosion design, contributing to the efficient allocation of anti-corrosion resources. References | Related Articles | Metrics

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Case Analysis on the Impact of Valve Chamfer on Engine Maintenance CHEN Fei 2026, 51(10): 108-112.  DOI: 10.16638/j.cnki.1671-7988.2026.010.019 Abstract ( )   PDF (1659KB) ( )   Engine maintenance is a precise maintenance process, and the parameters of each component and the coordination parameters between components directly affect the quality and effect of engine repair. This article introduces an important parameter of the automobile engine that is often overlooked during the maintenance process: valve chamfer. By following a maintenance case, from the fault phenomenon to the diagnosis process, test drive process, to the final analysis of the fault cause, it demonstrates the profound impact of the valve chamfer parameter on engine performance. At the same time, it summarizes the practical experience of engine maintenance and also provides a reference for automotive maintenance technicians. References | Related Articles | Metrics

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Design of Shock-Absorbing Bolts for Diesel Engine Cover LI Zhilin 2026, 51(10): 113-118.  DOI: 10.16638/j.cnki.1671-7988.2026.010.020 Abstract ( )   PDF (1971KB) ( )   Aiming at the vibration and noise issues of a diesel engine cover, an improved design scheme for damping bolts is proposed, intended to reduce mechanical vibration transmission through structural optimization and enhance noise, vibration, harshness (NVH) performance. A collaborative design process employing multiple methods is adopted. First, structural innovation design is carried out based on customer requirements, and key parameters are determined through theoretical mechanical calculations. Second, computer-aided engineering (CAE) simulation analysis is conducted to verify the structural design and evaluate leakage risks. Finally, prototypes are manufactured and bench tests are performed to validate the vibration and noise reduction effect of the newly designed damping bolts. Experimental data show that the optimized damping bolts achieve a reduction of 2 dB in the peak frequency-domain noise. The design scheme has passed fatigue life tests, meeting the 240 h durability test requirement. This research forms a complete design methodology from theoretical calculation to experimental verification, providing a standardized process for the development of engine damping components and demonstrating significant engineering application value. References | Related Articles | Metrics

Automobile Education

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Research on Differentiated Teaching of Fundamental Mechanics Course in Vehicle Engineering Major by Digital Intelligence Empowerment QIN Xuan, HAO Qi, WU Shengjun, WANG Guanghui 2026, 51(10): 119-124.  DOI: 10.16638/j.cnki.1671-7988.2026.010.021 Abstract ( )   PDF (1279KB) ( )   This article explores the deep integration of artificial intelligence (AI) technology with education and teaching, with the Fundamental Mechanics course as the core carrier and the vehicle engineering major as the starting point. By establishing a virtual teaching and research room and building a smart teaching system for empirical research, starting from the three core dimensions of teaching goal setting, teaching process implementation, and teaching evaluation, a data-driven, intelligent diagnosis, and personalized differentiated teaching process system empowered by digital intelligence is constructed. The pilot program of differentiated teaching has been carried out, and the results show that compared with traditional teaching, differentiated teaching significantly improves the course overall performance, enhances course satisfaction, and effectively cultivates students' professional identity. References | Related Articles | Metrics

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Reform of Material Mechanics Experiments Based on the Concept of "Two Properties and One Degree" With Practice －Take the Vehicle Engineering Major as an Example QIN Jing, WANG Kedong, CHI Hong, LIU Chao, XING Ying 2026, 51(10): 125-130.  DOI: 10.16638/j.cnki.1671-7988.2026.010.022 Abstract ( )   PDF (1365KB) ( )   To address the lack of systematicity in experimental content, teaching methods, and assessment approaches for the Mechanics of Materials Laboratory course in the vehicle engineering major, and to meet the requirements of "two properties and one degree" (high-level, innovativeness, and challenging degree), an experimental reform proposal was developed based on "two properties and one degree" concept. The reform includes optimizing traditional experiments and adding indepth extension experiments in experimental content; adopting a combination of "flipped classroom" and "project-driven" teaching models to stimulate student initiative; and establishing a diversified evaluation system that covers the entire process, multiple dimensions, and multiple stakeholders. Post-reform data shows significant improvements in student learning interest, experimental operation and analysis skills, and competition participation and award rates, forming a replicable teaching model. This advancement fosters innovative development in discipline-based experimental teaching, enhances industry influence, and strengthens international collaboration. References | Related Articles | Metrics

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Research and Practice of the School-Enterprise Cooperative Teaching Model Based on the Apprenticeship System with Chinese Characteristics LI Haixiang, YE Fang 2026, 51(10): 131-137.  DOI: 10.16638/j.cnki.1671-7988.2026.010.023 Abstract ( )   PDF (1495KB) ( )   This article aims to explore the implementation pathways of a school-enterprise cooperation model for the Automotive Manufacturing and Testing Technology program under the Chinese characteristic apprenticeship system, in order to address issues such as the misalignment between the current training system and industrial demands, as well as the disconnect between theory and practice. By leveraging the strengths of the Chinese characteristic apprenticeship system, a deep schoolenterprise collaborative "dual-subject" organizational model is formed, a "three-field" linked teaching model is established, and a "four-integration" education model is implemented. Through measures such as innovating teaching organization models, optimizing the professional curriculum system, building a high-quality teaching team, and establishing a multi-party evaluation mechanism, this approach effectively promotes the integration of the education chain with the industrial chain, and enhances the adaptability and practical capabilities of talent cultivation. This research provides actionable practical references for deepening vocational education reform, and holds both practical significance and theoretical value for promoting the high-quality development of vocational education. References | Related Articles | Metrics

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Vocational Competence Improvement and Evaluation Strategies for New Energy Vehicle Major Teachers in the Digital Age ZHU Kening 2026, 51(10): 138-142.  DOI: 10.16638/j.cnki.1671-7988.2026.010.024 Abstract ( )   PDF (1047KB) ( )   With the continuous upgrading of the new energy vehicle industry, especially its in-depth integration with digital technology, the industry demands digital and innovative talents. This puts forward higher requirements for the vocational competence system of teachers specializing in new energy vehicles in higher vocational colleges. Based on the context of the digital age, combined with the development characteristics of the new energy vehicle industry, and relying on the "Golden Seed" young teachers project, this article first analyzes the core competence requirements for new energy vehicle major teachers in the digital age. Then, it proposes competence improvement strategies from three dimensions: the construction of a training system, the establishment of a practical platform, and the innovation of teaching models. Furthermore, it constructs an evaluation system with four-dimensional indicators, namely "teaching-profession-industry-scientific research". Finally, it forms a closed-loop mechanism of "competence improvement–dynamic evaluation–continuous improvement". It provides theoretical references and practical paths for the construction of the teaching staff in the new energy vehicle major, and contributes to the digital reform of higher vocational education. References | Related Articles | Metrics

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Innovative Reconstruction of New Energy Vehicle Construction Course Driven by the Dual Engines of New Engineering and Knowledge Graph SONG Xiaoyan, LIU Feifei, LI Yanchao, HE Fa 2026, 51(10): 143-148.  DOI: 10.16638/j.cnki.1671-7988.2026.010.025 Abstract ( )   PDF (1414KB) ( )   Based on the background of new engineering construction, this article responds to the requirements of the Ministry of Education of China to deepen the reform of undergraduate education and optimize the layout of disciplines and majors in universities, focus on the reconstruction path of the New Energy Vehicle Construction course. By combing the knowledge graph and the research status of the New Energy Vehicle Construction course, a course reconstruction framework centered on the four-dimensional system of "objective-knowledge-ability-literacy" is clarified. By reviewing the research status of knowledge graph and new energy vehicle construction courses, a curriculum reconstruction framework centered on the four-dimensional system of "goals knowledge abilities literacy" is clarified. Six core knowledge modules, including new energy vehicle battery system and motor drive system, were constructed. The logical relationships between knowledge points were sorted out and a visualized knowledge graph was formed. The resources of the learning platform were integrated with virtual simulation training scenarios. Finally, various methods such as literature research, investigation research, and action research were adopted to ensure the scientific and practical nature of the course reconstruction. Dynamic updates of teaching resources and personalized delivery of personalized teaching are achieved through the application of knowledge graphs, while issues including the disconnection between traditional courses and industrial technologies, and the lack of targeted learning support for students are addressed. Ultimately, the goal is to improve teaching effectiveness and cultivate applied talents that meet the needs of the new energy vehicle industry. References | Related Articles | Metrics