The research focuses on the application of the "dual-teacher and three-track" collaborative education mechanism in the double-creativity education of automotive majors in higher vocational colleges, and explains its theoretical connotation and operational logic. This paper focuses on analyzing the collaborative role of university teachers, enterprise mentors and entrepreneurship coaches in course co-construction, project co-research and talent co-cultivation, and explores the practical model of this mechanism in teaching reform and industry-education integration. Through cases of course construction and technological breakthroughs, the achievements of the mechanism in enhancing teachers' capabilities, strengthening students' innovation and entrepreneurship qualities, and integrating professional education are summarized. At the same time, the deficiencies in system connection and resource allocation are pointed out. Research shows that the "dual-teacher and three-track" mechanism is conducive to the deep integration of innovation and entrepreneurship education with automotive professional teaching, and has significant promoting significance for the cultivation of innovative technical talents.

With the rapid development of the new energy vehicle industry, the AC charging system of pure electric vehicles, as a key link in the energy supply of electric vehicles, its stability and safety directly affect the entire new energy vehicle industry. This paper conducts an in-depth analysis of the working logic of the AC charging system for pure electric vehicles, systematically sorts out the technical problems and fault types existing in the current charging system, and proposes corresponding optimization strategies in combination with actual application scenarios.

The problem of high voltage failure to power on BYD Qin EV pure electric new energy vehicles occurs from time to time, which has a significant impact on the normal use of the vehicle. Based on this, this article introduces the high-voltage system structure and control logic of BYD Qin EV, analyzes the types of high-voltage non power on faults, explains the diagnostic process and methods of such faults, and proposes common fault causes, manifestations, and maintenance methods based on practical cases.

This paper expounds the design of a fishbone-shaped water collection and distribution device and its application in a compact modular layout, providing a reference for the optimization of the external pipeline of battery thermal management in electric buses.

To analyze the charging power matching of battery electric vehicles (BEVs) at normal temperature and improve relevant testing methods, this study conducted tests on the charging process of five BEV models under charging piles of different specifications in a normal-temperature experimental environment. Before the test, the vehicles were discharged to 10% State of Charge (SOC) and left to stand for more than 12 hours. Parameters including charging power and vehicle demand power in the SOC 10%~80% (fast-charging range) and SOC 10%~100% (full-charging range) were collected and analyzed, and the power response coefficient k was proposed to comprehensively evaluate the charging adaptability of the models.

With the rapid development of the automotive industry and the increasing demand for road traffic safety, the automotive lighting system has evolved from a simple lighting tool into a key component for ensuring driving safety. Therefore, this paper conducts research on an intelligent automotive lighting control system based on a single-chip microcomputer, aiming to design a solution that is both practical and economical. The system uses the STC89C52 single-chip microcomputer as the control core, perceives ambient light intensity, the distance of obstacles ahead, and the vehicle's steering state through multi-sensor fusion, realizes adaptive adjustment of lights in combination with intelligent control algorithms, and improves the system's stability in the complex electromagnetic environment of automobiles through hardware optimization and software anti-interference design.

With the rapid development of the automobile industry in the direction of intelligence and networking, as the"Neural network" of the vehicle, the structure of the automobile wiring harness is becoming more and more complex, and the types are becoming more and more numerous, which brings new challenges to the warehouse management of wire harness manufacturing enterprises. This paper first expounds the significance of the introduction of intelligent systems, and then systematically proposes a hierarchical overall architecture design scheme, furthermore, a feasible optimization strategy is proposed from the perspective of intelligent scheduling of work flow and system life cycle maintenance, in order to help enterprises in the fierce market competition through the intelligent innovation of internal logistics to build a solid core advantage of supply chain.

Under the guidance of the "dual carbon" goals, the energy consumption driving range performance of electric light trucks have become key areas for technological breakthroughs. This paper employs a coupled approach based on rolling resistance and energy recovery strategies to conduct energy consumption, range tests, and simulation analyses on a prototype electric light truck. The results show that under both 40 km/h constant-speed and complex driving conditions, energy consumption and driving range improved. Low-resistance design significantly enhances driving range, while high-energy recovery intensity, although reducing energy consumption, has a negative impact on driving experience.

This article takes the concept of ideological and political education in courses as the core, combines practical cases from multiple vocational colleges, and explores the specific construction paths of ideological and political education in the courses of the new energy vehicle Technology major from five aspects: overall design of the talent cultivation plan, systematic optimization of the curriculum system, innovation of educational and teaching methods, deepening of collaborative education among government, schools, industries and enterprises, and improvement of the multi-dimensional talent evaluation system. It aims to achieve a deep integration of professional education and ideological and political education, and cultivate compound talents with both technical capabilities and a sense of patriotism.

This paper proposes a machine vision-guided flexible assembly system for industrial robots, focusing on resolving the precision-efficiency conflict in automotive engine docking. By integrating high-resolution industrial cameras with six-dimensional force sensors, and combining YOLOv3 object detection with nine-point calibration algorithms, the system achieves sub-pixel level component positioning and dynamic error compensation. Experimental results demonstrate that the system achieves 0.05mm positioning accuracy in engine crankshaft assembly, completes single-station operations within 8 seconds, and reduces defect rates by 20% compared to traditional processes.

This article mainly analyzes the types and potential risks of common voltage terminals for wires of different diameters in the high-voltage charging base of new energy vehicles. Firstly, this paper focuses on discussing the problem of signal line breakage caused by the significant difference in tensile force values when the signal line and the PE line are co-pressed at high magnification wire diameters. Secondly, it compares and elaborates on the advantages and disadvantages of MW-type crimping and six-sided crimping. Finally, it proposes improvement measures such as optimizing the crimping process, mold design, and wire harness fixation to enhance the connection reliability of the co-pressed terminal, providing a basis for product development and quality control.

The rapid development of new energy vehicles and energy storage industries has imposed higher demands on power battery health management. Accurate prediction of State of Health has become a core challenge in ensuring system safety and economic viability. Current prediction methods face three major bottlenecks: insufficient adaptability to dynamic operating conditions, difficulties in characterizing micro-level degradation mechanisms, and high implementation costs. Therefore, this paper conducts in-depth research on a multi-physics field feature collaborative extraction mechanism and a lightweight deep learning framework. The goal is to establish a novel prediction paradigm that combines real-time responsiveness with industrial-grade accuracy, providing a theoretical breakthrough direction for battery lifecycle management.

With the popularization of electric vehicles, the metering accuracy of DC charging piles has become the key to ensuring user rights and the fairness of services. This paper is based on JJG 1149—2022 "Electric Vehicle Off-Board Charger (Trial)", focusing on the metering error of DC charging pile, analyzing the influence of multiple factors such as ripple, temperature and hardware characteristics on metering accuracy, and proposes an error analysis method based on signal decomposition and neural network, and verifies the effectiveness of the method through experiments. The research results provide technical support for the optimization of metering performance and the implementation of procedures for DC charging piles.

Plug-in Hybrid Electric Vehicle (PHEV) achieves a balance among power performance, economy and environmental protection by integrating the advantages of internal combustion engines and electric motors. As a key technology in PHEV research and development, the matching of power system parameters and the simulation technology of vehicle performance directly determine the comprehensive performance and market competitiveness of its products. This paper systematically expounds the method of power system parameter matching, deeply integrates professional simulation tools such as MATLAB/Simulink and AVL-Cruise, and constructs a multi-dimensional vehicle performance simulation system architecture covering power performance, economy and thermal management. Through empirical analysis of typical engineering cases, the optimization efficiency of parameter matching on vehicle performance is quantitatively verified, and the future development trend of this technology is discussed.

This paper proposes a parallel hybrid vehicle AMT transmission shift control optimization method to dynamically learn and adjust shift positions, to avoid wear on the forks, and to improve the reliability of the transmission assembly. The control optimization process is explained in terms of symptoms, cause analysis, structure layout, and test verification.

This article analyzes the composition and working principle of the side air curtain system, optimizes the selection of gas generators and the design of key parameters, and conducts simulation analysis on the inflation process by using fluid-structure coupling simulation technology. Verify the effectiveness of the optimized design scheme and provide a brand-new idea for improving the safety protection performance of the side air curtain system.

Based on the failure of the automatic start-stop system of Geely Emgrand GL model, this paper sorts out the fault diagnosis process from a practical perspective, focuses on analyzing key links such as line connection, sensor signal, and control module communication, and proposes a line repair plan in combination with typical cases, providing practical maintenance guidance for auto repair personnel.

Against the backdrop of rapid development in the new energy vehicle industry, power batteries have become the core technical component supporting its performance. However, during actual operation, power batteries often face safety hazards such as overheating, short circuits, overcharging, and over-discharging. These issues may not only lead to battery performance degradation but also trigger safety incidents in severe cases. To effectively enhance the safety of power batteries, various advanced monitoring technologies and management solutions have been extensively researched and practically implemented within the industry. By conducting real-time monitoring of key operational parameters such as temperature, voltage, and current, combined with dynamic regulation through the Battery Management System (BMS),potential battery failures can be effectively preempted. The deep integration of intelligent monitoring systems and big data analytics further provides a more precise early warning mechanism for power battery safety, significantly enhancing the overall operational safety and stability of new energy vehicles. Leveraging these technological measures, the safety and reliability of power batteries during use can be notably improved, thereby offering robust support for the sustained and healthy development of the new energy vehicle industry.

With the rapid development of the new energy vehicle industry, the safety issues of power battery modules have become increasingly prominent. Thermal runaway protection and thermal management are key links in ensuring battery safety. This article explores in depth the causes of thermal runaway in power battery modules and the development of protective technologies, with a focus on analyzing the types, properties, and applications of thermal management materials (including thermal conductive materials, thermal barrier materials, and phase change materials). It looks forward to the future development trends of thermal runaway protection and thermal management materials, aiming to provide theoretical support and technical references for the safe design and optimization of power battery modules.

This study analyzes the energy density balancing mechanism of BYD Han EV's blade battery system:Adopting long strip-shaped cell design and module-free integration, volume utilization rate is significantly improved, with first-generation energy density of 140Wh/kg and second-generation reaching 190Wh/kg (lab data 210Wh/kg). Integrated with direct cooling thermal management and BMS active balancing, the temperature difference is controlled below 5℃ ,and cycle life exceeds 3000 times. Experimental data shows 92% range retention at -30℃ and 800V platform enabling 15-minute fast charging to 80%. The research reveals that through structural optimization with intelligent algorithms, the blade battery achieves balance between energy density, safety, and lifespan, providing references for high-energy-density battery design.

This paper explores the adaptive challenges of detecting autonomous vehicles in complex road environments in China, analyzes its impact and potential risks on the development of autonomous driving technology-Based on this, an optimization scheme based on the VOLO algorithm is proposed. This scheme integrates frequency domain enhancement and dynamic sparsity techniques, enhancing the detection performance of vehicles in harsh weather and strengthening the robustness and adaptability of the system.

With the popularization of intelligent driving, the identification of special vehicles has become a key issue. This article conducts research on the recognition challenges of special vehicles in the era of intelligent driving.Firstly, it introduces the vehicle-level system framework based on sound recognition. Then, it elaborates in detail the methods of sound preprocessing and feature extraction using the TorchAudio library. Finally, it combines the ResNet-18 residual network for sound classification. And the effectiveness of this method in the sound recognition of special vehicles is verified through experiments, providing a new approach for the recognition of special vehicles in intelligent driving.

To adapt to the centralized computing electronic and electrical architecture under the trend of "software-defined vehicles", this paper conducts adaptive development and optimization design for the digital key system. First, sort out the evolution logic of automotive electronic and electrical architecture from distributed, domain control to vehicle-cloud integrated centralized (EEA 3.0); Furthermore, the pain points existing in the traditional digital key system under the distributed architecture, such as functional independence, insufficient log storage, and weak data collaboration ability, are analyzed, and an adaptation solution based on the EEA 3.0 architecture is proposed.

The battery cold plate is an important component of the battery thermal management system. The thermal management performance of new energy batteries plays a crucial role in the performance and safety of batteries. Through static load tests on the cold plate, a matching test fixture is designed to study the strength of the cold plate, analyze the deformation of the cold plate, compare the strength differences between the formed cold plate and raw materials, and test the overall air tightness changes of the cold plate before and after the test. At the same time, based on the layout of the cooling space on the large surface of the battery and the actual expansion force load conditions of the battery, fatigue durability research on the cold plate is carried out. The deformation of the cold plate after the alternating load test is analyzed, and the overall air tightness changes of the cold plate before and after the test are tested. Through the results of the static load test and fatigue durability test of the cold plate, data guidance is provided for optimizing the structural design and spatial layout of the cold plate.

In response to the control requirements of intelligent headlights, this paper proposes an intelligent headlight priority control strategy based on an intelligent controller. It focuses on expounding the control logic, priority strategy and specific control system of intelligent headlights: when the vehicle needs to adjust the priority of headlights, the corresponding control module issues a work instruction to enable the intelligent headlights to adjust the priority logic between different lights, so as to adapt to the regulatory requirements of different countries and regions. This strategy provides a reference for solving the priority management problems caused by multi-region regulatory adaptation and function expansion

With the increasing popularity of electric vehicles, liquid lithium batteries in power batteries have the risk of fire caused by thermal runaway in application, and the charging speed is difficult to meet the needs of users for rapid energy replenishment, which restricts the further promotion of electric vehicles and the improvement of user experience. Based on this, this paper discusses the technical characteristics of the new solid-state lithium battery, its compatibility with the existing electric vehicle system, the current application bottleneck and its optimization strategy, from the perspective of material innovation and system integration, a feasible development path is proposed to provide a useful reference for the application optimization of solid-state batteries in electric vehicles.

With the continuous advancement of vehicle electrification and intelligence, traditional low-voltage power distribution technology can no longer meet the complex and variable power demands. This paper proposes a scenario engine-based intelligent low-voltage power distribution technology for vehicles. By real-time sensing of vehicle status, user habits, and environmental information, it dynamically optimizes power distribution strategies to achieve efficient energy allocation. The article elaborates on the technical principles, system architecture, and key technologies of the scenario engine, while analyzing its performance advantages through practical application cases. Research shows that vehicles equipped with this intelligent power distribution technology based on the scenario engine can reduce energy consumption by 15%~30%, significantly improving electric vehicle range and system reliability, providing important references for the future evolution of automotive electrical architectures.

With the rapid development of vehicle engine control technology, original equipment manufacturers (OEMs) have put forward higher requirements for the genuine identification of filter element systems. The article proposes a design scheme for the genuine identification system of automotive filter elements based on digital technology, integrating electronic tags, encryption algorithms and cross-module encryption communication logic, aiming to enhance the real-time performance and reliability of the authenticity judgment of filter elements. This solution can effectively identify the authenticity of filter elements, ensure the secure transmission and storage of data, and provide strong support for the power performance and safety of the engine.

Under the trend of automotive electrification and intelligence, vehicles have higher requirements for dynamic performance and comfort. Shock absorbers, as the core of the suspension system, their performance affects multiple aspects such as vehicle body control. In response to the current widespread problems such as valve system response lag, material failure, and damping decline, this article focuses on the research of dynamic characteristic optimization and material compatibility of hydraulic shock absorbers. Through structural innovation design and the application of high-performance materials, a suspension system solution that combines high response speed and long service life is constructed.

This paper focuses on the faults of power batteries in new energy vehicles. It first analyzes their core characteristics and systematically elaborates on the application logic and operational key points of three key technologies: on-board real-time diagnosis, offline diagnosis, and intelligent diagnosis. Ultimately, a standardized troubleshooting process is constructed, which includes initial screening, in-depth detection, fault repair, and effect verification. The research aims to provide references for improving the efficiency of power battery fault handling and ensuring the safe operation of new energy vehicles.

Aiming at the longitudinal force control problem of pure electric pickup trucks under low-speed creep conditions, in order to improve control accuracy, driving smoothness and anti-disturbance robustness, this paper proposes a dynamic constraint model predictive control strategy integrating real-time slope feedforward. Firstly, establish a discrete state space model of the vehicle's longitudinal dynamics considering multi-source drag coupling; Secondly, a multi-objective cost function is constructed with speed tracking error, torque change rate and energy consumption as the optimization objectives. The core innovation lies in the design of a dynamic constraint adjustment mechanism based on slope feedforward. By estimating the slope resistance in real time and dynamically correcting the motor torque constraint boundary, the robustness of the controller under large slope disturbances and the feasibility of solving optimization problems are enhanced. Finally, a real vehicle test platform was built based on domestic pure electric pickup trucks to complete the verification. The results show that compared with the traditional proportional-integral-differential controller,the proposed MPC controller,reduces the average absolute error of speed tracking by 53.1% and the fluctuation of torque change rate (characterizing driving smoothness) by 52.4%. It shows excellent dynamic response characteristics under both slope and load change conditions, which can significantly improve the comprehensive control quality under creep conditions and has engineering application value.

This paper proposes an intelligent light language system solution that integrates preset and custom functions. This system is composed of a hierarchical architecture, including an interaction layer, a logic processing layer, and a hardware execution layer. It supports multiple application scenarios such as driving, temporary parking,getting on and off the vehicle, and instructions. The interaction layer provides custom functions such as mode selection,hand-drawing, and text input. The logic processing layer issues control instructions in combination with vehicle statussignals, and the hardware execution layer drives LEDs to achieve light language animations. Through design analysis,this system can enhance the personalized expression and information transmission capabilities of automotive lighting.

This article explores the application effect and technical implementation path of automotive LED light efficiency adaptive control technology in intelligent driving environments, and evaluates the impact of multi-mode light efficiency control strategies on driving safety performance under different environmental conditions through on-board experiments. The results show that adaptive light effect control based on environmental perception and driving status can significantly improve the safety performance of night driving and reduce the accident risk rate by approximately 32%.Light efficiency control is positively correlated with visual comfort, and the adaptive mode optimizes the balance between energy consumption and lighting effect, improving the average energy utilization efficiency by approximately 18%. The research provides practical basis and theoretical support for the development of light efficiency control technology in intelligent driving systems.

Electromechanical Braking (EMB) technology is driving a generational shift from hydraulic to brake by-wire systems. Targeting autonomous driving requirements, this study employs theoretical comparison and empirical analysis to reveal EMB’s triple breakthroughs over hydraulic systems.Structural Reconstruction: Electromechanical direct-drive architecture eliminates hydraulic pipelines, reducing components by 40% and mass by 24.1%.Performance Leap: Response time ≤100ms 30% faster), control precision ±0.01MPa (85% higher), reducing collision kinetic energy by 62% in AEB scenarios.Energy Efficiency Innovation: Enhancing endurance by optimizing drag torque. Localization practices confirm feasibility: xxx company curbs torque attenuation at -40℃ (≤8%). The new regulation GB 21670—2025,to be implemented on January 1st, 2026, will accelerate industrial substitution. Future efforts must resolve redundancy costs challenges toward integrated "brake-drive-steer" smart actuators.

With their high power density, efficiency, and excellent dynamic response characteristics, permanent magnet synchronous motors have become the core power unit in new energy vehicle drive systems. This paper investigates their dynamic characteristics at the system level. By constructing a mathematical model in the d-q coordinate system, we analyze the response processes of electromagnetic torque, rotational speed, current, and external disturbances, elucidating the mechanism of torque fluctuations and parameter coupling. The results demonstrate that rational structural design and dynamic control strategies can significantly enhance motor response speed and system stability, providing theoretical and technical support for optimizing the driving performance and energy efficiency of electric vehicles.

As the primary mode of transportation, automobiles may develop electrical system failures during prolonged use that impair the proper functioning of electronic components. These malfunctions manifest in diverse forms with varied root causes, making the selection of appropriate diagnostic techniques and repair methodologies crucial. This article examines common electrical system failures, outlines diagnostic strategies, and proposes practical maintenance solutions to enhance repair efficiency and quality. The study provides actionable frameworks for implementing effective fault diagnosis and repair practices in automotive engineering.

Aiming at the problems that abnormal noise faults of traditional fuel vehicle engines affect driving experience and driving safety, as well as the difficulty in maintenance, this article first classifies and sorts out three common types of abnormal noises related to rotational speed rhythm, load temperature, and local location. Technical difficulties such as low accuracy of reanalysis diagnosis, complex maintenance operations, and limited equipment costs. By establishing a "primary-intermediate-advanced" hierarchical diagnosis system, optimizing the cold knocking cylinder repair and crankshaft main bearing noise treatment technology, and formulating management strategies for lubrication/combustion systems and fasteners, the speed and quality of abnormal noise fault repair can be enhanced. Practice has shown that this scheme can reduce the recurrence rate and occurrence rate of faults, providing support for the maintenance of traditional fuel vehicle engines.

The integration of automotive electronics puts extreme demands on the miniaturization, high-density and extreme working condition reliability of automotive smart connectors. Polybutylene terephthalate has become the core shell material by virtue of its excellent electrical insulation, heat resistance and dimensional stability, but the multi-field coupling of melt flow, heat conduction, pressure transfer and crystallization shrinkage in the injection molding process is prone to inducing non-uniform crystalline orientation and residual stress concentration. Especially in the manufacture of microstructured connectors, the above coupling effect is significantly exacerbated, resulting in defects such as header warpage, terminal coplanarity misalignment, and other defects, which directly threaten the reliability of the on-board electronic system. The existing process optimization lacks the knowledge of systematic coupling mechanism, therefore, this study focuses on the multi-field dynamic coupling mechanism of the injection molding process of PBT-based connectors, and explores the temperature-flow-stress interaction law in depth, with a view to providing a theoretical cornerstone for the manufacturing of high-precision and high-reliability in-vehicle electronic devices.