Automobile Applied Technology

Optimal design and stability control of distributed multi-wheel steering system for wheeled special vehicles

YUAN Jia1,2 , ZHANG Kaidi2 , ZHANG Yunqing2* , TAN Kun1 , ZHONG Ke1

2026, 51(19): 1-11. DOI: 10.16638/j.cnki.1671-7988.2026.019.001

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To meet the special requirements for maneuverability and handling stability of multi-axle heavy-duty wheeled special vehicles under complex working conditions, this paper proposes a distributed multi-wheel steering system based on an improved multi-redundancy and highly integrated corner module structure, and further investigates the hierarchical control strategy for lateral stability on this basis. Firstly, a vehicle dynamic model with proportional feedforward allwheel steering is established. Through a comparative analysis of the angular step steering responses at different vehicle speeds, it is demonstrated that the proposed distributed multi-wheel steering system can achieve a synergistic balance between driving stability and steering responsiveness by operating in the all-wheel steering mode at low speeds and the dual-front-axle steering mode at medium and high speeds. On this basis, a hierarchical control framework for lateral stability is designed. The upper-layer comprehensive feedback controller calculates the additional yaw moment of the vehicle using a fuzzy adaptive proportional-integral-derivative (PID) algorithm. The lowerlayer torque distribution controller takes the minimum tire adhesion utilization rate as the core optimization objective to realize the optimal torque allocation of each wheel. Combined with the longitudinal vehicle speed tracking control, a complete hierarchical optimal control system is constructed. Finally, a co-simulation platform is established based on RecurDyn and MATLAB/ Simulink for comparative simulation verification under different control strategies. The results demonstrate that the distributed multi-wheel steering system designed in this paper can effectively improve the vehicle handling stability and driving safety under the control of the comprehensive feedback hierarchical optimization strategy.

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Front-wheel active steering control strategy based on tire lateral stability margin

DONG Zilong1 , NIE Xiaoshuai1,2*, HU Wei1

2026, 51(19): 12-20. DOI: 10.16638/j.cnki.1671-7988.2026.019.002

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Active steering improves vehicle yaw stability by correcting the front-wheel steering angle. However, existing methods rely on state errors such as yaw rate and sideslip angle to calculate the additional front-wheel steering angle, lacking consideration of the degree of tire force saturation and the available lateral force boundary. This can easily lead to insufficient steering correction or excessive intervention, thereby degrading vehicle handling and stability under large-curvature steering conditions. Therefore, an active steering control method based on tire lateral stability margin is proposed. First, the remaining stability margin is calculated from the front-wheel sideslip angle, and the degree of understeer is constructed to quantify the degree of vehicle instability. Second, the front-wheel correction steering angle is calculated according to the degree of instability, so that the tires are maintained within the range of efficient lateral force utilization. Third, the front-wheel steering angle is constrained according to the vehicle state to avoid excessive additional correction steering angle causing excessive steering intervention, thereby improving vehicle handling stability. Finally, comparisons are conducted with the no-correction control under mild and aggressive circular driving conditions. After applying the correction, under mild conditions, the yaw rate increases by 7% and the front-wheel sideslip angle decreases by 30%; under aggressive conditions, the variation range of the yaw rate decreases by 20%, the peak value decreases by 53%, and the peak front-wheel sideslip angle decreases by 40%, indicating that the control strategy keeps the front wheels away from the sideslip saturation region, optimizes lateral force distribution, and improves handling stability.

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Development and verification of a vehicle-based brake-by-wire system test platform

ZHANG Guoyong1,2 , NIU Chengyong1,2, XU Jianxun1,2 , YANG Zhihao1,2 , WU Yongqiang1,2 , WANG Na3

2026, 51(19): 21-28,100. DOI: 10.16638/j.cnki.1671-7988.2026.019.003

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To address the challenges of accurately replicating real-world scenarios during simulation and bench testing in the development of electronic mechanical braking (EMB) systems, as well as the inefficiencies and insufficient coverage of real-vehicle testing, this paper introduces a comprehensive wire-controlled brake testing platform based on the entire vehicle. This platform facilitates real-time data collection and precise control of all brake system parameters. Utilizing an automotive-grade multi-core master control architecture, coupled with a high-precision sensor array and real-time control software, the platform supports brake performance testing under various operating conditions. It has been validated through basic functional and reliability tests, including conventional braking, braking on special surfaces, and partial failure scenarios. At an initial speed of 100 km/h, the braking distance is reduced by 18.2% compared to traditional systems, with a maximum deviation of less than 0.3 m, indicating good repeatability and stability of the test data. The emergency braking response time can be shortened by approximately 0.2 s, verifying the effectiveness of the platform's pressure control algorithm. The platform functions normally in open road and single/multiple wheel failure tests, with results meeting national standards and test data errors less than 2%. This provides efficient and reliable technical support for the research, development, and validation of wire-controlled brake systems.

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Research on active suspension control strategy based on reinforcement learning SAC algorithm

WANG Zhao, HAN Da, YU Yang, YU Delong, LI Mingwei

2026, 51(19): 29-34. DOI: 10.16638/j.cnki.1671-7988.2026.019.004

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To address the issues of poor adaptability and complex parameter tuning in active suspension control strategies, this paper proposes an active suspension control strategy based on the reinforcement learning soft actor-critic (SAC) algorithm. A dynamic model of the suspension system is established, based on which a policy neural network is constructed. A state-adaptive temperature parameter update mechanism is designed to improve convergence efficiency and control accuracy. Simulation results demonstrate that the proposed control strategy exhibits excellent robustness and adaptability. Compared with passive suspension, proportional-integral-derivative (PID) controlled active suspension, and skyhook algorithm-based semi-active suspension, the ride comfort index is improved by 8.1% to 22.6%, providing an effective solution for intelligent control of active suspensions.

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The design of steer-by-wire actuator for intelligent chassis integrated control

HUANG Jiahui1 , ZHAO Yongqiang1,2* , CAO Dizhang1 , XU Jinhai2

2026, 51(19): 35-42. DOI: 10.16638/j.cnki.1671-7988.2026.019.005

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A steer-by-wire actuator based on an inverted planetary roller screw mechanism is proposed to meet the requirements of high load-carrying capacity, high stiffness, fast response, and compact integration in intelligent chassis systems. Under the constraints of a maximum axial load of 20 kN, a maximum rotational speed of 3 000 r/min, and limited installation space, key parameters including roller number, thread starts, pitch diameter, and effective contact length are determined.The axial load distribution, axial stiffness, and thread tooth strength are then analyzed theoretically. Finite element analysis is conducted to verify the static performance of the mechanism, and the dynamic responses under uniform steering and bump-impact conditions are investigated. The results show that the axial stiffness is approximately 317.5 kN/mm, the maximum von Mises stress is 139.31 MPa, and the safety factor is 3.73. The shear and bending stresses of the thread tooth are 101 MPa and 164 MPa, respectively, both lower than the allowable values. Further considering the effect of alternating loads, the fatigue safety factor is estimated to be 2.74 based on the Goodman criterion, indicating that the fatigue strength requirement of the steer-by-wire actuator is satisfied. Under uniform steering, the stress response remains stable. Under bump impact, transient high contact pressure occurs, but no structural instability is observed.The results indicate that the proposed mechanism can improve load-carrying capacity and transmission stiffness within a limited radial size, providing a reference for the design of compact steer-by-wire actuators.

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Sliding mode control based differential braking for vehicle stability after tire blowout

XIE Baochun1 , LI Xiangguo2 , MEI Zhiqian2 , JIANG Xiaojie1

2026, 51(19): 43-48,122. DOI: 10.16638/j.cnki.1671-7988.2026.019.006

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For the yaw instability problem of vehicles after tire blowout on split-μ road, a sliding mode control strategy based on differential braking is proposed. Based on the difference of adhesion coefficients on split-mu road, a 7-degrees of freedom (7-DOF) vehicle dynamics model with Pacejka tire model is established, and a blowout tire force degradation mechanism is introduced to simulate and control the vehicle after blowout. Taking the yaw rate error as the control variable to construct the sliding mode surface, the controller is designed based on the exponential reaching law, and additional yaw moment is generated through differential braking to gradually maintain vehicle stability. Based on Simulink and CarSim co-simulation platform, front left tire (65 km/h) blowout, rear right tire (65 km/h) blowout, front left tire (100 km/h) blowout under split-μ conditions are validated for sliding mode control method. The simulation results show, without driver control, the vehicle lateral distance with control method can be reduced to less than 0.8 m. And peak yaw rate can be also reduced effectively. The proposed method provides an effective engineering solution for vehicle driving safety control under split-μ road tire blowout conditions, and the implementation of this control strategy is also relatively simple in engineering.

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Vehicle stability control under active steering and differential braking for tire blowout

CHEN Shengbo

2026, 51(19): 49-56. DOI: 10.16638/j.cnki.1671-7988.2026.019.007

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When a vehicle experiences a tire blowout at high speed, it generates a strong lateral disturbance torque, threatening the driving stability. Therefore, this paper proposes a coordinated control strategy of active steering and differential braking. Based on the three-degree-of-freedom vehicle model, a hierarchical yaw rate feedback controller is designed: the upper layer proportionintegral-differential (PID) calculates the total control torque, and the lower layer is allocated to the active steering and differential braking systems. Simulation results show that in the 90 km/h straight-line tire blowout condition, the maximum lateral displacement, yaw rate, and center of gravity camber angle are reduced by 43.7%, 29.2%, and 35.3% respectively; in the 60 km/h curved road tire blowout condition, it effectively suppresses the lateral deviation and yawing divergence. This coordinated control strategy utilizes the complementary advantages of both to significantly improve the vehicle stability under tire blowout conditions.

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Simulation study of electric vehicle brake power system based on PSO-BP optimized fuzzy PID method

DUAN Wenfu1 , FU Qiang1,2 , SU Da1

2026, 51(19): 57-63. DOI: 10.16638/j.cnki.1671-7988.2026.019.008

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To address the nonlinear, time-varying, and strongly coupled characteristics of electric vehicles during ground braking, this paper propsoes a cooperative control strategy integrating particle swarm optimization (PSO)-enhanced back propagation (BP) neural networks with fuzzy proportion-integral-differential (PID) for the intelligent control of anti-lock braking system (ABS)/ air reverse thrust system (ARTS) compsoite braking power systems. This approach utilizes fuzzy PID for rapid response and coarse-tuning of slip rate, while PSO optimizes the BP neural network for fine-tuning gain compensation, effectively suppressing steady-state error and oscillation issues. A five-degree-of- freedom longitudinal dynamic model incorporating the ARTS and ground braking force was established, with a mathematical model for reverse thrust developed based on one-dimensional steady-state isentropic flow theory. Simulation results demonstrate that compared to traditional ABS, the propsoed control strategy reduces braking time by 25.7% and braking distance by 34.7% on high-coefficient-of-adhesion road surfaces. It precisely stabilizes slip rate within the ideal range near 0.2, significantly enhancing braking efficiency and stability. This validates the approach's potential for application in electric vehicle ground braking systems.

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Vehicle roll control method based on front and rear active stabilizer bars

ZHANG Jiale, GAN Jiayue

2026, 51(19): 64-73,115. DOI: 10.16638/j.cnki.1671-7988.2026.019.009

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To enhance the roll stability of vehicles under high-speed cornering conditions, a vehicle roll control method based on front and rear active lateral stabilizer bars is proposed. First, considering the coupling characteristics of vehicle lateral motion, yaw motion, and roll motion, as well as the adjustment effect of active stabilizer bars on the roll stiffness of the front and rear axles, a three- degree-of-freedom vehicle roll dynamics model and state space equations incorporating front and rear active stabilizer bars are established. Second, the lateral-load transfer rate (LTR) is adopted as the roll stability evaluation index, and an adaptive torque distribution strategy for the front and rear active stabilizer bars is designed based on the LTR difference between the front and rear axles. On this basis, a fuzzy proportional-integral-derivative (PID) control method is employed to achieve independent coordinated regulation of the front and rear stabilizer bar torques. Finally, two rollover-prone maneuvers, namely J-Turn and Fishhook, are selected for simulation analysis to systematically verify the adaptability, disturbance rejection capability, and parameter perturbation robustness of the proposed method. The results demonstrate that, compared with the vehicle without stabilizer bars, the proposed method effectively reduces the vehicle roll angle and lateral load transfer rate, with the maximum roll angle reduced by more than 57.1% and the critical rollover speed increased by 61.4%. Moreover, the coordinated control of front and rear stabilizer bar torque achieves superior roll suppression performance compared with single stabilizer bar control, exhibiting strong robustness against varying driving conditions and parameter perturbations.

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Structural optimization and analysis of a modular electric vehicle skateboard chassis

LI Yufeng, ZHANG Deping*

2026, 51(19): 74-79. DOI: 10.16638/j.cnki.1671-7988.2026.019.010

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To address the conflict between structural safety and lightweight design of a modular electric-vehicle skateboard chassis, a full-vehicle finite-element model incorporating the front suspension, rear suspension and central-battery-compartment modules is established. Static analyses under driving condition and bending-moment condition as well as free modal analysis are carried out to examine the strength and stiffness redundancies of the initial structure. A hierarchical lightweight strategy combining frame dimensional optimization and suspension-component topology optimization is adopted. The results show that the total mass of the optimized chassis decreases from 922.5 kg to 443.4 kg, with a weight-reduction rate of 51.9%. The maximum equivalent stress under typical load cases meets the strength requirement, and the first-order bending modal frequency is 48.59 Hz, which effectively avoids the frequency bands of road excitation and motor-order noise. It is demonstrated that the proposed hierarchical optimization method can remarkably improve material-utilization efficiency under the constraints of strength and noise, vibration, harshness (NVH) performance, providing a reference for the platform-oriented development of skateboard chassis.

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Review on state of health prediction techniques for plug-in hybrid electric vehicle batteries

LEI Zhaoyu, DING Binlei, WANG Yujie, WANG Runyu *

2026, 51(19): 80-88. DOI: 10.16638/j.cnki.1671-7988.2026.019.011

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State of health (SOH) serves as a key indicator for assessing the overall condition and remaining capacity of plug-in hybrid electric vehicle (PHEV) batteries. Accurate SOH prediction is of significant value for ensuring safe and reliable vehicle operation, optimizing performance, and extending battery lifespan. This paper systematically reviews the current research status of SOH prediction techniques for PHEVs, categorizing the technical approaches into experimental methods, model-based methods, data-driven methods, and model fusion methods, while summarizing the advantages and limitations of each approach based on current research. Furthermore, the paper synthesizes industry application trends in SOH prediction and management adopted by automotive manufacturers, and identifies challenges in data acquisition and processing, model accuracy and generalization, real-time performance and computational efficiency, as well as personalized modeling and user behavior integration. By elucidating the theoretical framework and practical pathways of SOH prediction techniques for PHEV batteries, this study provides critical theoretical guidance for the industry, facilitating the optimization of battery management systems, enhancement of vehicle safety and reliability, and promotion of high-quality development in the new energy vehicle market.

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Improved road object detection algorithm based on YOLOv12

LI Penglong, HUO Hongming, YUAN Li* , ZHANG Jingjia, YU Shoushan

2026, 51(19): 89-100. DOI: 10.16638/j.cnki.1671-7988.2026.019.012

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Aiming at the problems of missed detection and false detection caused by diverse target scale variations, complex background interference and mutual overlap between targets in complex traffic scenarios, this paper proposes YOLO-PCA, an improved road object detection algorithm based on YOLOv12. First, the poly kernel inception(PKI) module is introduced into the backbone network to construct a multi-scale feature extraction module. Through the combination of convolution kernels of different sizes, features of different scales are extracted, which enhances the feature representation ability of the model for targets of different scales. Second, the channel prior convolutional attention (CPCA) module is introduced to dynamically allocate attention weights in channel and spatial dimensions, which enhances the model's ability to extract detailed target feature under complex backgrounds while reducing computational complexity. Finally, the parallelized patch-aware attention (PPA) module is introduced into the detection head, enabling the model to better focus on key information of small targets and improves the detection accuracy of the model for small targets. Experimental results show that the mean average precision (mAP@0.5) of the improved model on the KITTI dataset reaches 98.7%, which is 0.9 percentage points higher than the baseline YOLOv12 model. Therefore, the improved model effectively improves the detection performance for occluded, truncated targets and small targets, and can better meet the requirements of complex road object detection.

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Research on the correspondence between features and attacks in CAN bus intrusion detection

LIU Zhaoqi

2026, 51(19): 101-106. DOI: 10.16638/j.cnki.1671-7988.2026.019.013

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Aiming at the lack of native security mechanisms in the in-vehicle controller area network (CAN) and the poor explainability of existing intrusion detection methods, this paper investigates "which statistical features can detect specific types of CAN attacks". Seventeen-dimensional statistical features including identifier distribution, data-length code, payload, inter-frame interval and high-frequency identifiers are extracted via sliding windows. Taking linear support vector machine (SVM) as the classifier, a feature-group×attack-type detection matrix is constructed under strict stratified chronological splitting, and permutation importance is adopted to interpret detection mechanisms. On the Car-Hacking dataset, identifier-distribution features achieve recall no less than 99.6% for four injection-type attacks, denial-of-service (DoS), fuzzing, gear spoofing and revolutions per minute spoofing, whereas inter-frame interval features yield only 0.036～0.069 recall for spoofing attacks. Fuzzing attacks are dominated by identifier diversity, while spoofing attacks are governed by Top-1 identifier frequency. Cross-dataset validation on the real ORNL automotive dynamometer (ROAD) shows that masquerade attacks barely perturb identifier distributions; the optimal single feature group yields an receiver operating characteristic-area under curve (ROC-AUC) of only about 0.765, and the combination of all 17 dimensions improves the value to 0.855. The dominant feature migrates from identifier distribution to inter-frame timing, revealing the capability boundary of distribution-based features. The findings provide references for feature reduction and explainable diagnosis of in-vehicle intrusion detection systems.

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Research on hierarchical planning and trajectory optimization for intelligent vehicle lane-changing and obstacle avoidance based on B-spline

HUANG Jiecong1 , CAI Longyu 1 , XIE Jipeng1,2*

2026, 51(19): 107-115. DOI: 10.16638/j.cnki.1671-7988.2026.019.014

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To address the difficulty of simultaneously achieving trajectory smoothness and kinematic feasibility in single-layer planning methods for intelligent vehicle lane-changing scenarios, this paper proposes a hierarchical trajectory planning method based on fourth-order B-splines. The method adopts a hierarchical architecture of "geometric optimization, kinematic correction": first, a smooth reference trajectory is constructed using fourth-order B-spline curves, and the sequential least squares programming (SLSQP) algorithm is employed to optimize the control points, realizing spatial obstacle avoidance and geometric smoothness; subsequently, within the B-spline parameterization framework, multi-disk safety corridor constraints and a two-degree-of-freedom vehicle kinematic model are introduced to optimize the control sequence, ensuring that the trajectory satisfies vehicle kinematic constraints and comfort requirements. Building upon conventional hierarchical planning methods, the proposed approach converts the reference trajectory from the geometric layer into a bounded feasible region through a safety corridor generation mechanism, thereby endowing the motion layer with the ability to autonomously adjust the spatial trajectory within the corridor boundaries. Simulation results demonstrate that, compared with single-layer planning methods, the proposed method achieves superior trajectory smoothness and comfort performance in lane-changing obstacle-avoidance scenarios, while also improving computational efficiency by 61%, providing an effective technical solution for intelligent vehicle lane-changing and obstacle avoidance on structured roads.

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Study on transfer path and multi-stage energy absorption mechanism of vehicle body under impact loads

RONG Zhe

2026, 51(19): 116-122. DOI: 10.16638/j.cnki.1671-7988.2026.019.015

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In response to the increase of the frontal collision speed to 55 km/h and the 21% increase in collision energy in the China-new car assessment program (C-NCAP), based on the principle of conservation of energy, a "sandwich cage style" force transmission path for the front cabin and a step-by-step controllable deformation strategy are proposed in this paper. Simulation analysis is carried out with the aid of computer aided engineering (CAE) technology, and its accuracy can reach more than 95%. Moreover, the analysis results have all passed the verification of real vehicles, achieving the goals of directional folding of collision force and graded energy absorption of "soft front and hard rear". The front fender intrusion is reduced by 19.6%, the peak acceleration of the B-pillar is decreased by 13.2%, and the energy absorption efficiency is increased by 17.8%. The five-star vehicle body safety standard is achieved, providing a basis and solution for the safety design of high-energy collision structures of electric vehicles.

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In-depth research on platform-based development method for left-hand and right-hand drive vehicles

FU Xiaobiao, WANG Fuzhong, LIANG Fusheng

2026, 51(19): 123-128,136. DOI: 10.16638/j.cnki.1671-7988.2026.019.016

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Against the backdrop of the comprehensive acceleration of Chinese automakers’ global expansion, vehicle enterprises need to serve diverse markets with varying global traffic-rule requirements, making overseas business a core growth-driving strategy. Aiming at the pain points of high costs, long lead times and poor compatibility in the conventional phased development of left-hand drive and right-hand drive vehicles, this paper proposes a platform-based development method for left-hand drive and right-hand drive vehicles built on a native modular architecture. A complete development system is constructed from four dimensions: pre-architecture presetting, system modularization, component generalization, and global compliance adaptation. Its application value is verified through practical cases of domestic automakers. Research results indicate that this synchronous left-hand drive and right-hand drive platform-based development mode can shorten time-to-market by approximately 45% and reduce comprehensive R&D costs by around 40%. It can effectively support the global deployment of automakers and provide a referable technical path for vehicle export featuring multi-market, multi-model and multi-powertrain capabilities.

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Exploration of teaching models for automotive professional course clusters in the context of digital-intelligence integration

WANG Danqi, WU Wenguang, ZOU Tiefang, LIU Xin, WANG Fang

2026, 51(19): 129-136. DOI: 10.16638/j.cnki.1671-7988.2026.019.017

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To address the issues of fragmented curriculum systems, insufficient utilization of digital resources, and single-dimensional teaching evaluation in automotive engineering education, this paper, guided by the technical demands of the intelligent new energy vehicle industry and centered on the "digital intelligence+new engineering" education concept, constructs a three-layer progressive digital-intelligence teaching reform framework of content-resources-model". Firstly, the "three-core and four-wing" approach is used to reconstruct the teaching content of the course cluster, forming a four-in-one intelligent graph integrating"knowledge-objectives-problems-ideological political education". Secondly, the "three-modernization and four-nature" strategy is asdopted to upgrade teaching resources, achieving precise mapping of digital resources. Based on these, the "threeintegration and two-drive" digital-intelligence teaching model is established to shift teaching from experience-driven to data-driven approaches. The teaching reform practice shows that after two years of continuous reform, student satisfaction with professional courses increased by 5%, the average score of the reformed class in specialized courses is 14.6% higher than that of the ordinary class, and scores in graduate entrance examination subjects increased by 10.2%. In the past two years, students have won more than 20 national and provincial awards in competitions such as the "Internet+", and the formula racing team has won the national second prize for three consecutive years, with significant improvements in students' innovation ability and awareness. The quantifiable and traceable teaching quality feedback loop formed in this study provides a replicable technical path and practical paradigm for the digital-intelligence transformation of engineering education.

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Exploration of teaching reform of system modeling and simulation course based on heavy vehicles as the carrier under the background of new engineering

WANG Hongwei, XING Dongzhuo, MENG Fanwei

2026, 51(19): 137-144. DOI: 10.16638/j.cnki.1671-7988.2026.019.018

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In response to the new requirements for vehicle engineering talent cultivation brought about by the construction of new engineering disciplines, this study has carried out a systematic teaching reform for the course of System Modeling and Simulation. The course has established a three-in-one teaching model of knowledge map as the guideline, project task-driven, and intelligent technology empowerment, with the typical engineering problem of heavy vehicle system modeling and control as the main line. It has completed the joint simulation from MATLAB/Simulink modeling to TruckSim, and innovatively applied the large model technology to achieve learning process tracking and intelligent evaluation.The teaching practice shows that the average comprehensive satisfaction score of students toward the course has significantly increased from 4.2/5.0 (before the reform) to 4.8/5.0, the reform can effectively enhance students' comprehensive qualities in complex system analysis, design and innovative practice, providing a reference path for the course construction and talent cultivation of the vehicle engineering major in the new engineering field.

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Reform and practice of automotive technical service and marketing professional courses under the integration of "post-course-competition-certificate" －Taking the course of used car appraisal and evaluation as an example

LI Min

2026, 51(19): 145-150. DOI: 10.16638/j.cnki.1671-7988.2026.019.019

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In response to the surging demand for appraisal professionals in China's used car industry and the mismatch between training quality and job requirements, this paper focuses on the Used Car Appraisal and Evaluation curriculum. Based on the concept of "post-course-competition-certificate" integration, it employs research methods and empirical analysis to align course reforms with job competency clusters. The research proposes implementation strategies including current situation analysis, curriculum restructuring, competition-certification integration, and resource coordination, all validated through practical implementation. Results demonstrate significant improvements: students' course performance and vocational skill certification pass rates have surged, with consistent excellence in multi-level skill competitions. Practical capabilities and professional ethics have been enhanced, achieving 100% internship satisfaction rates and markedly improved job adaptability and employment competitiveness. This research provides actionable insights for vocational education in used car appraisal and offers replicable methodologies for core curriculum reform in automotiverelated programs at higher vocational colleges.

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Construction and implementation of specialized and innovative integration characteristic courses in applied research universities －Take the course on vehicle intelligent connected technology as an example

LI Yuan1 , WANG Yubiao2 , XUE Zhian1

2026, 51(19): 151-156. DOI: 10.16638/j.cnki.1671-7988.2026.019.020

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As the automotive industry accelerates its development toward intelligence and connectivity, higher requirements are placed on the engineering practice and innovation capabilities of talents majoring in vehicle engineering. The traditional "PPT+textbook" teaching mode shows deficiencies in training students on complex engineering scenario cognition, system analysis and comprehensive decision making. Taking the course Vehicle Intelligent Connected Technology at Inner Mongolia University of Technology as the research object, this paper explores a curriculum teaching reform path oriented to the integration of specialization and innovation for application oriented universities, supported by the engineering education accreditation of the vehicle engineering program and the featured curriculum construction project for integrating specialty and innovation. A "virtual reality (VR) case action learning method" is constructed and implemented. By reconstructing course objectives and optimizing teaching content arrangement and classroom implementation procedures, real world engineering problems are integrated into the whole teaching process. The results demonstrate that after curriculum implementation, students' comprehensive case analysis scores increase by 15%~25%; their capabilities of system architecture understanding and multiobjective decision making improve by over 18% on average. Classroom participation and task completion rates rise significantly. More than 80% of students believe that this method has enhanced their engineering problem analysis ability, systematic thinking and learning initiative.

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Research on the construction of ideological and political case database for the specialty of new energy vehicle engineering

ZHANG Liping, LI Gang, SHEN Caiying

2026, 51(19): 157-162. DOI: 10.16638/j.cnki.1671-7988.2026.019.021

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As a crucial measure to implement the fundamental task of moral education and talent cultivation, curriculum-based ideological and political education plays a pivotal role in professional teaching across various disciplines. Taking the New Energy Vehicle Engineering major as an example, this study conducts an in-depth exploration of the significance, current status, strategies, and practical effects of constructing a curriculum ideological and political case library. Centering on the core requirement of in-depth integration between ideological and political elements and professional knowledge, the research formulates a profession-specific construction plan for such a case library. The plan is developed through four key steps: clarifying the objectives of case library construction, establishing a multi-dimensional case system integrated with ideological and political elements, innovating diversified case presentation formats, and improving the long-term management and dynamic update mechanism of the library. Results from practical application indicate that the implementation and operation of this case library have achieved remarkable effects. It not only helps students consolidate core professional knowledge and enhance practical application capabilities but also effectively stimulates their patriotic sentiments and sense of social responsibility. Consequently, it provides strong support for high-quality talent cultivation in the New Energy Vehicle Engineering major and offers valuable reference for the development of curriculum ideological and political education in other majors.

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