Automobile Applied Technology

Research on energy recovery algorithm for pure electric commercial vehicle based on acceleration estimation and correction

WANG Pengxiang, GAO Yuxiang, WANG Jiawei, BAI Xiang, WANG Shichao

2026, 51(13): 1-8. DOI: 10.16638/j.cnki.1671-7988.2026.013.001

Abstract ( )

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The range anxiety problem is prominent for pure electric commercial vehicles, and dynamically adjusts the energy recovery intensity according to changes in vehicle speed and acceleration during braking on complex roads. Verified by actual range tests under mountain road conditions of a commercial vehicle enterprise, the economy is improved by 4%, which confirms the effectiveness of the proposed method and provides technical support for improving the range of pure electric commercial vehicles. optimizing energy regeneration is key to improving the driving range. Energy regeneration relies on accurate acceleration information; However, complex road conditions and sensor noise can easily cause data distortion, leading to misjudgment of energy management strategies and reducing economy and safety. Therefore, an energy regeneration algorithm based on fused acceleration information is proposed for pure electric commercial vehicles. Firstly, considering the computing power constraints of the vehicle controller, an acceleration estimation algorithm based on Kalman filtering is proposed to correct and optimize the original sensor data to reduce errors. Secondly, an energy recovery algorithm fused with corrected acceleration information is constructed, which

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Design and verification of power battery for a cetain battery electric light trucks

YE Changsen

2026, 51(13): 9-13. DOI: 10.16638/j.cnki.1671-7988.2026.013.002

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New energy light trucks, as the primary vehicle type for urban distribution, are maintained rapid growth in 2025. However, the current battery electric light trucks are plagued by issues such as short driving range, slow charging speed, and short warranty period, which severely impede their market promotion. Battery electric light-duty trucks equipped with dual-gun charging, high-capacity, liquid cooling and liquid heating systems, and extended warranty periods are key to overcoming the current development bottlenecks. This paper conducts a systematic study on the matching design of key components including the power battery, charging system, and thermal management system. By combining simulation analysis with experimental verification, it is concluded that under normal temperature conditions, dual-gun fast charging can reduce charging time by 50%, and the vehicle can meet the warranty requirement of 6.0×105 km. This solution demonstrates strong innovativeness and practicality.

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Research on integrated vehicle frame and battery bracket technology

YU Jibang, FAN Pingli, GUO Lei, MA Bo

2026, 51(13): 14-19,25. DOI: 10.16638/j.cnki.1671-7988.2026.013.003

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New energy light-duty trucks commonly employ a single-pack battery configuration mounted beneath the chassis frame. In accordance with current design requirements, the chassis must undergo structural reinforcement in the battery installation area to withstand concentrated impact loads. Simultaneously, the battery brackets must fulfill the dual functions of supporting the battery weight and connecting to the chassis, resulting in increased strength requirements for both the chassis assembly and the battery bracket assembly. This leads to elevated component weight and costs. To address this, an integrated design approach for the chassis assembly and battery bracket assembly has been proposed. Through structural design and optimization, a lightweight solution is developed to reduce weight and cost. Computer aided engineering (CAE) analysis confirms that, without compromising assembly stiffness and strength, a lightweight reduction of approximately 10.5% and a cost reduction of about 11.6% have been achieved. Additionally, two upper battery brackets have been eliminated, and production processes have been streamlined. This study provides a novel development strategy for new energy light-duty truck chassis and battery brackets, delivering both energy efficiency benefits and enhanced cargo space for users.

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A Parking slot detection method with uncertainty

YU Meng, FU Ying, HE Qiaojun

2026, 51(13): 20-25. DOI: 10.16638/j.cnki.1671-7988.2026.013.004

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In the process of manually annotating parking slot detection datasets, every effort is made to accurately mark the corner points of parking slot. However, in actual annotation images, some corner points may be blurry or obstructed by obstacles, making precise annotation difficult. This poses challenges for the model when regressing the coordinates of these corner points using the dataset. This article proposes a novel loss function for parking slot corner point offset, which simultaneously learns the corner point offset and localization variance, thereby improving the accuracy of parking space corner point localization with almost no additional computational load. On a self-constructed dataset, the proposed approach achieves higher precision, while significantly reducing both the parking slot corner localization error and the parking slot boundary angle error. Moreover, the standard deviations of these two errors are notably smaller, indicating that the model produces more stable and consistent predictions.

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Research on behavioral decision-making method for tractor-trailer trucks based on markov decision process

XUE Lingling, WANG Yizhe, BO Tao, QU Zhenyu

2026, 51(13): 26-32. DOI: 10.16638/j.cnki.1671-7988.2026.013.005

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In order to improve the safety and comfort of heavy-duty truck intelligent driving decision-making systems, this paper decouples the horizontal and vertical decision-making, and proposes a behavioral decision-making method for hybrid trailers based on finite state machines and Markov decision processes. The horizontal decision-making uses a finite state machine, and the longitudinal decision-making uses a dual-mode Markov decision process with fixed probability and adaptive probability to achieve safe and efficient decision-making in park scenarios. The behavioral decision-making system adopts a hierarchical architecture, which is roughly short-term trajectory prediction-collision detection-horizontal and vertical behavioral decision-making-trajectory planning. This system is code implemented under the ROS1 framework, and is simulated and verified in the park scene in 51simone. The results show that the system can make reasonable and safe decisions in lane keeping, car following and lane changing scenarios.

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A study on the test methodology and robustness of the Euro NCAP emergency lane keeping scenario

ZHANG Xiao, ZHANG Shuai, KONG Lingming, SHEN Liangyi, GENG Dongliang, ZHANG Sen

2026, 51(13): 33-38，86. DOI: 10.16638/j.cnki.1671-7988.2026.013.006

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In response to the high proportion of traffic accidents caused by lane departure and the industry pain point of the lack of standardized and systematic verification methods for the safety performance of intelligent vehicle emergency lane keeping (ELK) system in complex practical scenarios, this study aims to establish a standardized testing process and a scientific robustness evaluation system for ELK system based on the Euro NCAP 2026 version of the Crash Avoidance– Lane Departure Collisions (v1.1), in order to improve the consistency and effectiveness of ELK system testing. The research focuses on the core scenario of overtaking and lane changing collision avoidance between ELK adjacent lane vehicles and motorcycles. The experimental conditions, vehicle preparation, measurement accuracy requirements, and experimental implementation process under this scenario are systematically sorted out; The focus is on analyzing the criteria for dividing robustness levels in the regulations, clarifying core robustness evaluation indicators such as collision position offset and initial position deviation; And a real vehicle verification test is conducted on a pure electric sedan equipped with ELK system, completing the testing and data validity analysis of standard and robustness scenarios. The research results indicate that the ELK system testing method and robustness evaluation system constructed have strong practical feasibility and engineering application value, which can provide theoretical support and practical reference for the development, testing, and optimization of intelligent vehicle ELK system.

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Design and analysis of a lattice-type electro-mechanical brake actuator for vehicles

YU Jiaqi, WANG Kuiyang* , FENG Yijin, AN Ruixuan, XIAO Jianqiang, TANG Jinhua

2026, 51(13): 39-43,91. DOI: 10.16638/j.cnki.1671-7988.2026.013.007

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To meet the high performance requirements of new energy vehicles and high-level autonomous driving for braking systems, this paper proposes a lattice-type electro-mechanical brake (EMB) actuator. The actuator employs an array of 10 independently motor-driven braking units, allowing flexible combination of working modes according to braking force demands. Based on the reference vehicle parameters, the key components are selected. Through CATIA modeling and ANSYS static analysis, it is verified that the stress and deformation of each component are within allowable limits, and the braking torque meets the requirements. The results show that the proposed mechanism offers the advantages of high structural redundancy, precise control, and fast response, providing a feasible solution for a new generation of intelligent braking technology.

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Research on structural improvement-based minimum turning diameter optimization for a certain SUV

LIU Wei1 , WANG Yunping1* , YUE Fuli1 , LIU Liang1 , ZHONG Chengping1,2,3

2026, 51(13): 44-49，96. DOI: 10.16638/j.cnki.1671-7988.2026.013.008

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To address the issue of excessive turning circle in a specific sport utility vehicle (SUV) model, this paper conducts optimization by integrating parameter benchmarking, structural disassembly, computer aided engineering (CAE) simulation, and bench testing. A comparison of parameters between the target vehicle, the base vehicle, and benchmark models of the same class reveals significant gaps in the target vehicle's steering wheel angle and frame dimensions. Further analysis indicates that these gaps stemmed from three factors: first, the steering gear is moved downward to accommodate the layout requirements of the new engine; second, the widened frame restricts the reasonable arrangement of the anti-roll bar; and third, the steering gear's own travel fails to meet the design requirements. Based on this, three collaborative optimization schemes centered on the "steering system-frame structure-suspension components" are proposed. Comparative verification shows that the scheme–featuring a newly developed anti-roll bar, adjustment of the second crossbeam of the frame, increased steering gear travel, and lower control arm avoidance–achieves the best effect: the turning circle is optimized 1 m, reaching the mainstream level of the same class. Meanwhile, the stiffness of the anti-roll bar is improved, the natural frequency of the steering gear is enhanced, the tire clearance meets the design requirements, resulting in high engineering feasibility. This study holds practical significance for improving vehicle handling performance and market competitiveness.

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Multi-parameter optimization design of FSCC racing engine intake system structure based on CFD

LIU Zexu 1 , WANG Binhao2 , YANG Qingbo3 , LIU Erqiang1*

2026, 51(13): 50-56. DOI: 10.16638/j.cnki.1671-7988.2026.013.009

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To address the issue of throttle valve limiting engine power performance under formula student combustion China (FSCC) rules, and considering real vehicle space constraints, this study takes the CBR600rr engine as the object and performs computational fluid dynamics (CFD) simulation based on the k-ε turbulence model. The effects of inlet contraction angle, inlet expansion angle, and the angle between intake main pipe and manifold on intake performance are analyzed, and the optimal design parameters are obtained through parameter optimization. The results show that when the inlet contraction angle is 20°, the inlet expansion angle is 10°, and the intake main pipe-to-manifold angle is 123°, the total flow rate increases by 17.1% compared with the original design, and the unevenness of outlet flow rate of each cylinder decreases to 2.92%. The study reveals the influence mechanism of key structural parameters on engine intake flow, providing a theoretical basis and engineering reference for the design of intake systems for high-power density racing cars.

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Optimization of commercial vehicle front underrun protection structure

SHEN Yaqiang, BAI Haikang, ZHAO Bozhi, FANG Shuai, WANG Weidong

2026, 51(13): 57-61. DOI: 10.16638/j.cnki.1671-7988.2026.013.010

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As a core component of the passive safety system of commercial vehicles, the traditional front underrun protection structure has difficulties and problems such as easy fracture of connecting bolts, limited design space, and structural instability, which urgently need to be optimized. This paper proposes a new front underrun protection structure for commercial vehicles. By optimizing the key connection points of the structure, the load path of the entire structure is changed to prevent the connecting bolts from bearing excessive forces. At the same time, lateral support structures are added on both sides to withstand collision impact forces from multiple directions and improve the stability of the cross member. Additionally, lightweight design is applied to the cross member by using an aluminum alloy structure, which enhances the energy absorption capacity of the cross member and reduces the load on the connecting brackets. Combined with computer-aided engineering (CAE) analysis, the new structure's ability to withstand impact forces from a collision meets regulatory requirements, and the structure does not experience instability.

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Research on AI large model optimization toolchain methodology based on hood stiffness

HE Jinlong

2026, 51(13): 62-66. DOI: 10.16638/j.cnki.1671-7988.2026.013.011

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To address the problems of traditional simulation optimization, such as heavy reliance on manual experience, long iteration cycles, and low process automation, this paper proposes an intelligent optimization toolchain method based on large artificial intelligence (AI) models. Taking the automobile hood as the research object, the full-process automation of "modeling–simulation– data processing–AI optimization–result output" is realized by constructing a parametric model for hood stiffness, designing an automated iterative algorithm, and developing a low-code AI optimization configuration interface. Relying on the data analysis and decision-making capabilities of large AI models, the dependence of traditional optimization on algorithms and engineer experience is eliminated. The iteration cycle is drastically shortened by 90%, fills the domestic gap in the integrated application of AI and automotive structural simulation optimization, and provides a reusable technical solution for the intelligent optimization of key automotive components, which can be directly applied to the actual research and development of automotive engineering.

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Optimization of vehicle understeer based on roll steer characteristics of rear multi-link suspension

ZHOU Yangyu

2026, 51(13): 67-70. DOI: 10.16638/j.cnki.1671-7988.2026.013.012

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To address the problem that the roll steer characteristics of the rear four-link suspension of a vehicle are unfavorable to the understeer of the whole vehicle, this paper combines the K&C characteristic test and simulation analysis results of the rear four-link suspension of the vehicle, establishes an ADAMS suspension model of the rear four-link suspension, and carries out optimization iterations in combination with engineering practice. Finally, the roll steer is optimized without obvious changes in other suspension performances, and the understeer degree of the whole vehicle is improved. This study provides an effective method for the subsequent understeer optimization of vehicles with this suspension. The relevant conclusions are verified by steady-state circular test simulation and have engineering application value.

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Analysis of the influence of clutch disengagement force on AMT control

LI Jiahao, LIU Dan, CHEN Xing, WANG Yu, WANG Hao

2026, 51(13): 71-75. DOI: 10.16638/j.cnki.1671-7988.2026.013.013

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The control accuracy of the clutch directly determines the overall control level of the electronically controlled pneumatic automated mechanical transmission (AMT). This paper focuses on the control accuracy of this system. Firstly, it elaborates on the separation characteristics of the diaphragm spring clutch pressure plate and clarifies its basic impact on control accuracy. Secondly, it obtains the clutch separation force curve through real-vehicle tests and systematically analyzes its variation rules and trends. Finally, using the step separation and engagement control of the clutch target position, it collects target and actual position data in real vehicles, compares the following characteristics of two clutch models, and explores the influence mechanism of separation force curve differences on control accuracy. The results provide theoretical support and basic technical references for the selection and design of electronically controlled pneumatic AMT clutches.

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Smartphone-based automotive acceleration testing and data processing method

ZENG Jia, JIE Tao, YANG Jianfeng, ZHANG Chunling

2026, 51(13): 76-81. DOI: 10.16638/j.cnki.1671-7988.2026.013.014

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Addressing the issues associated with traditional automotive dynamic acceleration performance testing, such as reliance on high-cost professional equipment and complex operations, this paper innovatively proposes a low-cost, high-efficiency testing method and data processing system based on universal smartphones and software. By collaboratively using two smartphones to collect vehicle speed and time data and employing WPS spreadsheets for automated data processing, this approach resolves pain points in traditional testing, including strong equipment dependency and low data processing efficiency. Experiments demonstrate that the deviation rate of this method is less than 2% in key automotive acceleration performance indicators such as 0–100 km/h acceleration time and 0–400 m acceleration time. Moreover, ordinary engineers can master the entire operational process after short-term training. This research provides an economical and efficient alternative solution for automotive dynamic acceleration performance testing.

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Modeling and kinematic analysis of a novel MacPherson suspension

YANG Weiyong, JIANG Dongsheng, FANG Ton

2026, 51(13): 82-86. DOI: 10.16638/j.cnki.1671-7988.2026.013.015

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The accelerated electrification of automobiles raises requirements for overall vehicle performance, placing higher demands on the kinematic characteristics and dynamic response of suspension systems. This paper studies the kinematic properties of the newly optimized MacPherson suspension. Based on multi-body dynamics theory, a virtual prototype model of the suspension is established via the ADAMS/Car platform. Simulation results demonstrate that under wheel travel conditions, the variation trends of toe angle, camber angle, kingpin inclination angle, kingpin caster angle and roll center height of the new suspension are similar to those of the traditional MacPherson suspension, which maintains favorable driving stability. Under steering conditions, the new suspension delivers prominent advantages with larger wheel steering angle, smaller turning diameter and lower steering gear ratio, effectively improving vehicle maneuverability and steering sensitivity. The research findings provide theoretical reference and simulation support for the optimal design of suspension systems for electric vehicles.

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Design and implementation of fault code production management and control tool based on UDS communication

LIU Yu, GENG Xinrui, LU Guoguang, ZHANG Bin, XI Xuelei

2026, 51(13): 87-91. DOI: 10.16638/j.cnki.1671-7988.2026.013.016

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With the continuous development of the automotive industry, the management and control of fault codes before vehicle dispatch during the production phase have become increasingly stringent. How to meet the production cycle time while achieving precise fault code control is a key focus of diagnostic research. To address the pain point that the existing fault code reading and clearing tools used by the vehicle logistics department of a manufacturing base cannot meet the production cycle requirement of 1 min before vehicle dispatch, this paper carries out the design and implementation of a fault code production management and control tool based on unified diagnostic services (UDS) communication. The solution design is carried out through the tool's interface, the software and hardware solutions of the tool are designed, and controller end-of-line (EOL) verification is conducted through simulation and real-vehicle testing. The research results show that the fault code production management and control tool can achieve the functional verification of clearing and reading vehicle fault codes, reducing the time at the original reading and clearing station from 3 min to within 1 min, thereby meeting the production cycle requirement. The annual costsaving benefit for a single base reaches 1.92 million yuan, providing a reference for research in related fields.

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Intelligence visual inspection system based on zero defect zone

YUAN Hongtao1 , CHEN Weihua1 , LIANG Liwen2

2026, 51(13): 92-96. DOI: 10.16638/j.cnki.1671-7988.2026.013.017

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Misfitting and missing installation of waterproof and sealing components in automobile manufacturing easily lead to vehicle water leakage and reduce product reliability. This paper builds a visual inspection system based on programmable logic controller. Combined with the zero-defect concept for automobile production, the system links vehicle identification, body positioning and visual inspection units, optimizes algorithms and camera modes, and captures operators' part picking actions in real time to realize 100% active error prevention during operation. Compared with traditional camera inspection, this system raises the detection accuracy from 94.46% to 99.89%, cuts the response time from 2.9 s to 1.2 s, and reduces the installation and commissioning time from 8 h to 2 h.

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A method for improving the appearance quality of cold-stamped bridge half-shells

Shaanxi Hande Axle Company Limited

2026, 51(13): 97-100. DOI: 10.16638/j.cnki.1671-7988.2026.013.018

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In response to surface defects such as "extrusion ridges" and "strip indentations" observed during the transition from hot stamping to cold stamping for a specific model of axle housing half-shells, this paper thoroughly investigates their root causes, which are attributed to localized material accumulation and instability due to uneven material flow. By introducing an innovative composite mold design featuring a "curved-surface die" and a "variable-radius punch", a novel method for actively controlling material flow paths is established. This approach effectively coordinates flow velocity differences across regions by reconstructing the initial contact state and stress distribution of the blank and eliminating abrupt stress concentration points along the flow paths. Practical results demonstrate that the method completely eliminates the targeted surface defects, resulting in smooth and flat product surfaces, it has been successfully applied in mass production, providing valuable theoretical insights and a practical reference for the precision cold stamping of similar complex structural components.

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Exploration on the teaching reform of artificial intelligence enabling automobile specialty courses －Take the course of engine principles as an example

ZHANG Yixi1 , ZHAO Kun1 , HU Yueqi1 , YUAN Tian1 , SU Xin1 , ZHAO Weiyi2 , WU Yonghui3

2026, 51(13): 101-106,131. DOI: 10.16638/j.cnki.1671-7988.2026.013.019

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Under the background of digital transformation of education and the revolution of automobile industry, it is urgent to carry out teaching reform and innovation in applied undergraduate automobile courses. This study explores the teaching reform path of an artificial intelligence empowerment course using the course engine principles as an example, in view of the problems of abstract course content, insufficient personalized learning support, and a single evaluation method. Guided by the course objectives and combined with the development trend of multi-power source coordination in the automobile industry, the course knowledge system is reconstructed by building a four-dimensional map of "knowledge-problem-ability-ideological and political". The three-level and three-element personalized teaching model is designed, and a three-dimensional evaluation system, including knowledge mastery, ability development, and literacy achievement, is established to promote the precision of teaching implementation and the personalization of learning paths. The teaching practice shows that the reform scheme effectively improves students' classroom participation and knowledge understanding depth, enhances engineering practice ability and innovation thinking, and provides practical experience for the teaching reform of automobile specialty course.

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Research on the role of skill competitions in promoting teaching reform in higher vocational colleges under the background of new quality productive forces －A case study of new energy vehicle technology specialty

WU Kejia1 , LIAO Xiangrong1 , LIN Junxiong2 , WU Jing1

2026, 51(13): 107-112. DOI: 10.16638/j.cnki.1671-7988.2026.013.020

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Against the backdrop of rapid development in new productive forces, the continuous acceleration of technological iteration in the new energy vehicle industry necessitates ongoing updates to talent cultivation quality in vocational colleges. Taking the New Energy Vehicle Technology program as an example, this paper systematically explores the pivotal role of vocational skills competitions in driving teaching reforms, proposing an integrated "Job-Course-CompetitionCertificate-Innovation" five-in-one training model. Through in-depth analysis of competition mechanisms in practical training infrastructure development, faculty competency enhancement, curriculum content updates, and evaluation system optimization, the study establishes a teaching reform pathway characterized by "position-based syllabus design, course foundation establishment, competition-driven skill development, certification-validated effectiveness, and innovation-powered empowerment." Implementing a three-year teaching practice at Fujian Information Vocational and Technical College's New Energy Vehicle Technology program, key initiatives included: integrating curriculum content with competition standards, building dual-qualified faculty teams, developing artificial intelligence (AI)-enhanced virtual-real training platforms, innovating blended learning through "online to offline (O2O)+modular projects," and cultivating both craftsmanship spirit and digital literacy. Practical results demonstrate that this reform model effectively transforms elite competitions into mass courses, forming replicable and scalable systemic solutions while providing theoretical support and practical paradigms for vocational education to adapt to new productive forces demands.

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Research on the cross-disciplinary integration talent training model of applied undergraduate mechanical discipline based on artificial intelligence empowerment

WANG Xin, ZHAO Kun, WU Ling, WANG Peng, YAN Jiao

2026, 51(13): 113-119. DOI: 10.16638/j.cnki.1671-7988.2026.013.021

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With the deepening of a new round of technological revolution and industrial transformation, the field of mechanical engineering is rapidly transforming towards intelligence and integration. However, in the current cultivation of applied undergraduate mechanical talents，there are still obvious disciplinary barriers, a disconnect between the curriculum system and industry demand, and insufficient integration of artificial intelligence technology, which makes it difficult to meet the requirements of talent cultivation in the context of intelligent manufacturing. This article takes the applied undergraduate mechanical discipline as the research object, focusing on the two core dimensions of artificial intelligence empowerment and interdisciplinary integration. By optimizing the structure of professional courses, optimizing the allocation of teaching staff, reconstructing the talent cultivation evaluation system, and exploring innovative interdisciplinary education, this article aims to explore the integration of disciplines. Finally, through the pilot application of the Robotics Engineering and New Energy Vehicle Engineering majors at XIHANG University, this training model effectively breaks the traditional disciplinary boundaries and significantly enhances students' interdisciplinary application ability and intelligent manufacturing practical ability.

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Development and application of work-process systematized loose-leaf textbooks for automotive majors in higher vocational colleges

LIANG Hua1 , WEI Zhiyong2 , DENG Rukui1

2026, 51(13): 120-125. DOI: 10.16638/j.cnki.1671-7988.2026.013.022

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Guided by the theory of work-process systematization, this paper deeply explores the indepth integration paths and practical application values of the theory with new-type loose-leaf textbooks in the teaching of automotive majors in higher vocational colleges. The research shows that the two are highly compatible in task-driven teaching and modular design, providing an innovative carrier for the transformation of the textbook system from "knowledge storage" to "competence generation". In practice, a development path of "post-task-competence" is constructed, and four core application scenarios are derived: hierarchical teaching, project-based courses, integration of "post, course, competition and certificate", and dynamic updating via school-enterprise collaboration, so as to adapt to diversified student sources, serve project-based teaching and meet the demands of industry-education integration. It is concluded that this is not only a reform of textbook form, but also a systematic reconstruction of teaching organization logic, which needs to be supported by reforms in teaching staff, management and evaluation. In the future, it can be integrated with digital technology and develop towards "smart loose-leaf textbooks", providing an effective solution for cultivating high-skilled talents adapted to the transformation of the automotive industry.

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The path and practice for enhancing professional skills in new energy vehicle application and maintenance under the background of the "3+certificate" vocational education college entrance examination

CHI Duwang1 , MAI Jianling1 , HUANG Chunmei2*

2026, 51(13): 126-131. DOI: 10.16638/j.cnki.1671-7988.2026.013.023

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In recent years, the number of students sitting for the vocational college entrance examination at Zhaoqing Science and Technology School keeps rising. To meet students' demands for further education and skill upgrading, especially the requirements for professional skill certificates and undergraduate vocational skill assessments in the vocational college entrance examination, this paper takes the major of new energy vehicle application and maintenance as a research object and explores teaching reforms focusing on major construction and students' technical competence improvement. Special training plans, revised talent training programs, optimized curriculum systems and teaching modes help raise students' learning efficiency of professional skills. Practices demonstrate that the reform delivers satisfying outcomes in students' pass rates in skill certificate examinations and performance in skill competitions. Teachers also gain stronger capabilities in teaching and research, making a historic breakthrough in award levels at municipal teaching competency competitions. This study verifies that systematic teaching reform and curriculum optimization effectively advance major construction and lift talent training quality with remarkable results.

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LSTM-based traffic flow forecasting for urban expressways

HE Jianlin, LI Bingzhang, ZHANG Redong, CAI Zizhuang, WANG Xinyan*

2026, 51(13): 132-136. DOI: 10.16638/j.cnki.1671-7988.2026.013.024

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Urban elevated expressway traffic flows exhibit characteristics such as pronounced nonlinearity, significant temporal correlation, and complex fluctuations. To enable accurate forecasting of short-term traffic conditions, this study proposes a recursive prediction model for future traffic volumes based on the long short-term memory (LSTM) neural network. Taking the Jiaoning Road elevated expressway in Shinan District, Qingdao as the study subject, this paper conducts short-term traffic flow forecasting based on actual traffic flow data obtained from gantry monitoring. The model's predictive performance is comprehensively evaluated using metrics including the coefficient of determination, mean absolute error, mean deviation error, and root mean square error. Comparative analysis between the LSTM reference model and back propagation neural network optimized by genetic algorithm (BP-GA) and convolutional neural network (CNN) prediction models reveals that the LSTM model demonstrates superior predictive accuracy and robust generalisation capability. With a coefficient of determination reaching 0.606 and overall minimal prediction errors, its forecasting performance surpasses the other two models. This approach provides valuable support for predicting traffic flow at future time points.

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The key application of automotive maintenance technology in vehicle performance appraisal

LIU Cijian

2026, 51(13): 137-142. DOI: 10.16638/j.cnki.1671-7988.2026.013.025

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To explore the key role and practical application effectiveness of automobile maintenance technology in the judicial identification of traffic accidents, this paper summarizes daily work experience and combines it with relevant case analyses. It can be verified that automobile maintenance technology is one of the key technologies supporting the judicial identification of road traffic accidents, and it plays a crucial role in both the performance appraisal of accident vehicles and the analysis of accident causes. The findings of this study reveal the fact that judicial identification work is a complex interdisciplinary task, and also indicate the importance and practical significance of strengthening the cultivation of various abilities of judicial identifiers in the judicial identification industry. Meanwhile, it encourages industry competent authorities to increase professional training related to automobile maintenance technology for judicial identifiers engaged in traffic accident identification.

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