The structural configuration and characteristics of an automobile engine's fuel injection system have a direct impact on the engine's performance. Computational analysis of the fuel system is a crucial method for improving engine performance. Based on the analysis of the structure and mathematical models of the components of the engine's electronic fuel injection system, a simulation model was established, and the structural parameters of the fuel system were optimized through matching calculations. The research results indicate that a plunger diameter and lift of F23x24, along with a injection hole number and diameter of 7xF0.45, provide superior fuel injection characteristics. Additionally, the flow area of the solenoid valve's drain port, as well as the timing and duration of the electrical activation, significantly influence the fuel injection characteristics of the system. The optimized structural parameters hold important reference value for the design of engine fuel systems.
In modern manufacturing and processing production lines, production equipment is an important part of manufacturing production. The full utilization of equipment has a direct impact on the matching of production needs. This article considers the concept of “man-machine factor,” which is the ratio of the number of operators required per piece of equipment to the number of pieces of equipment. A multi-objective optimization function model considering the production line balance rate, smoothing index and human-machine coefficient was constructed. In order to solve this problem, the improved adaptive NSGA- II algorithm is used to solve the model. The research results show that: ① On the premise of meeting the customer's rhythm requirements, adjusting the human-machine coefficient can improve the production line balance rate, reduce the smoothing index and production costs. ② Through numerical examples, it is verified that compared with the traditional NSGA- II algorithm, the improved adaptive NSGA- II algorithm can find an approximate Pareto solution set with higher quality and wider coverage, providing choices for decision makers. This proves the validity and practicality of this research method. This research provides an effective optimization method for modern manufacturing processing production lines and provides a reference for other similar industries.
Compared with traditional fuel vehicle and pure electric vehicle,the noise,vibration,harshness(NVH)problem of range extender electric vehicle is more complicated because of the influence of range extender control strategy.The unreasonable matching control logic is easy to cause problems such as high acceleration noise,roar,etc.,and the later change cost is large and the cycle is long.In this paper,the theoretical model of the range extender system is simplified and the range extender system is regarded as an integral excitation source.By monitoring the state of the whole vehicle,the performance of the vibration and noise of the key points in the vehicle under different effective torque and crankshaft speed output by the range extender system,and avoiding the poor performance of the NVH strategy points,in the early stage of the project,the matching optimization of the vibration and noise of the key points in the vehicle can be realized,save cost and shorten project development cycle.
To quantitatively analyze the influence of solenoid valve parameters on their dynamic response characteristics, mathematic models are built based on the electromagnetic theory. Research is carried out using mathematical models, whereby the dynamic response process of the solenoid valve driven by constant voltage is simulated. The four parameters, namely: driven voltage, initial air gap distance, spring preload, and the number of coil turns influence the dynamic characteristics of the solenoid valve. The solenoid valve displacement curves under different parameters are obtained. Theoretically determined relationships between the dynamic response characteristics and the structural and control parameters of the solenoid valve, provide the basis for the parameter matching of the solenoid valve, and the optimized design of electronic control fuel systems.
汽柴油双燃料燃烧模式可以降低柴油机中小负荷的氮氧化物和碳烟排放并提高有效效率.文章在一台光学发动机上,采用高速摄影的方法对汽柴油均质混合气引燃(HCII)燃烧进行了解析,针对汽油比例对 HCII 燃烧的影响开展了可视化研究.研究结果表明,HCII 燃烧的过程是火焰首先随着柴油喷束从汽缸中央向四周延展,同时点燃周围的汽油混合气产生蓝色火焰,蓝色火焰逐渐发展至整个燃烧室范围.汽油火焰在多点被同时点燃,火焰面积在极短时间内迅速增加,覆盖几乎所有缸内范围,相对于传统汽油机,HCII燃烧速度明显增加.随着汽油比例的增加,缸内蓝色火焰比例明显增加,火焰亮度降低,从而实现低温燃烧.
For the problem that intelligent vehicles lack the driver's subjective driving operation cognition and the risk cognition of traffic participants,this paper proposed a trajectory planning algorithm based on improved Driver Risk Field(DRF).Firstly,the coordinate transformation from Cartesian coordinate system to Frenet coordinate system was carried out for the position of the vehicle,which visually represented the position information between the vehicle and the road;Secondly,a driver risk field model integrating vehicle stability risk was constructed to perceive the risk of traffic participants from the driver's perspective;Finally,considering the comfort needs of drivers and passengers,obstacle avoidance operations were performed on the perceived risk potential energy high points based on quintic and quartic polynomial trajectories.The simulation and hardware-in-the-loop test results show that the planned trajectory meets both the obstacle avoidance function and the acceleration constraints,ensuring the safety and comfort of driving.
《汽车文摘》(月刊)于1963年7月3日创刊,由国务院国有资产监督管理委员会主管、中国第一汽车集团有限公司主办,为中国汽车工程学会会刊.《汽车文摘》以"览全球汽车技术文献,指中国汽车技术之道"为使命,以打造"中国汽车前沿与创新技术传播与交流的重要平台"为愿景,致力于成为汽车领域最具影响力的综述类期刊. 2022年11月,《汽车文摘》复合影响因子达1.066,首个影响因子突破"1",这反映出《汽车文摘》自2019年启动转型升级以来,期刊学术影响力稳步提升.
For the problem that the autonomous navigation exploration algorithm is easy to fall into the local area,this paper proposed an exploration algorithm combining sampling and deep reinforcement learning.First,the Long-Short-Term Memory(LSTM)network was used locally to obtain the historical pose information of the unmanned vehicle to avoid repeated exploration of the explored area;secondly,the optimal action of the deep reinforcement learning strategy was used to output using deep reinforcement learning and the reward function was designed to encourage the unmanned vehicle to fully explore the unknown area;Finally,the horizontal movement factor of the unmanned vehicle was considered to generate a global exploration path conforming to its current attitude by solving the Asymmetric Travel Salesman Problem(ATSP).In the 2 000 s mine tunnel simulation environment,compared with the Technologies for Autonomous Robot Exploration(TARE)algorithm,the proposed algorithm increased the exploration area by 346.3 m2 and reduced the total driving distance by 209.4 m;in the real scene test,the exploration algorithm completed the exploration of the underground garage with an area of 3 444.3 m2 and returned to the starting point in 1 014 s and built the environment map.
To make autonomous lane change for intelligent vehicles in the situations with no lane or unclear lane,this paper proposed a lane change trajectory planning method based on virtual lane lines.Firstly,a virtual lane was constructed to divide the road into lanes parallel to the vehicle orientation,the best lane was determined according to the minimum heading angle of collision-free lane change.Secondly,the lane change end state was determined according to the average vehicle speed of the current lane and the target lane.The lane change trajectory was generated using the quintic polynomial combined with vehicle kinematics and dynamics.The path planning algorithm proposed was added to the intelligent planning decision-making module of the intelligent vehicle for simulation and hardware-in-loop test.The results show that the method realizes the function of autonomous lane changing in the situations without lane and improve the safety and driving efficiency of the vehicle in complex traffic environment.
To promote the application of core technologies in the autonomous operation system of intelligent and connected vehicles,this article analyzed the development trends,technical architectures and key technologies of future automotive operation systems from the perspectives of vehicle electronic and electrical architectures.At the same time,based on the application needs of vehicle manufacturers,the paper proposed implementation suggestions to accelerate the production and installation of domestic operation systems and ecological construction,in order to help accelerate the industrialization and development of autonomous operation systems for intelligent and connected vehicles.
To ensure the security and privacy of sensitive data in Internet of Vehicle(IoV)environments,this paper proposed a distributed differential privacy data protection scheme combining federated learning and reinforced learning mechanisms.In this scheme,a federated learning architecture was applied to keep data on vehicle nodes or edge devices for learning,enabling data privacy protection,reducing data transmission costs through distributed storage.The Laplace mechanism was employed to achieve differential privacy,the Layer-wise Relevance Propagation(LRP)was used to manage data perturbation,ensuring the privacy and efficiency of model parameter transmissions.Experimental results show that the proposed scheme can achieve approximately 80％global accuracy within 10 rounds of communication,with a maximum of 98％,can complete model aggregation within less communication rounds,achieving a good balance between privacy protection and global data accuracy,and accurately detecting the injection of false noise through the reinforced learning strategy,promoting the intelligence and security levels of IoV.
In order to improve the environmental perceive ability and better predict the behaviors of dynamic vehicle targets,a YOLOX model,as the front-end detector,combined with the optimized DeepSort method was proposed to develop the research of dynamic vehicle Multi-Object Tracking.In the process of features matching for dynamic vehicles,the change information of vehicles in the degree of light and shade was extracted to improve the object matching accuracy by adding Haarlike features.Furthermore,based on the application of DeepSort RE-identification network,the improved ResNet13 model was adopted as the backbone network for feature extraction,and SENet was introduced to adjust the feature weight of different channel dimensions.The results show that,compared to the conventional DeepSort method,by using the real on-road video data,the Multi-Object Tracking Accuracy(MOTA)and IDF1 indicator of the proposed algorithm increased by 1.4 percentage points and 7.7 percentage points respectively.
In order to improve the real-time and accuracy of parking slot detection in automatic parking,this paper proposed a lightweight parking-slot detection algorithm based on collaborative attention and graph neural network.Firstly,This algorithm used a lightweight network structure and the improved MobileNetV3 as the feature extraction network,obtained the location information and feature information of the parking-slot marker points through depthwise separable convolution,combined them to obtain the fused features of the marker points,then constructed a graph network structure to enhance the internal relationship of the parking-slot marker points,and combined the cooperative attention mechanism to integrate multiple attention.Finally,the algorithm was tested on the public parking-slot dataset PS2.0.The results indicate that the detection accuracy is better than the current mainstream algorithm,the average reasoning speed of each frame of image can reach 10.1 ms,with good accuracy and real-time performance.
For the problem of communication delay caused by the interference of the communication channel in the process of vehicle-road cooperative V2X communication,this paper proposed a V2X delay attack protection technology based on game theory.With the signal-to-noise ratio as the measurement index of communication quality,this paper firstly studied the function relationship between the transmission power of the attacking node and the signal-to-noise ratio to obtain the function relationship between the transmission power of the legitimate node and the attacking node,then this functional relationship was brought into the relationship between transmission power of legitimate node and the signal-to-noise ratio.This function also considered the probability of signal transmission,the probability of being detected and the transmission interference of other nodes to obtain the target function.Finally,the proposed protection technology is verified by simulation and test.The results show that by adjusting the transmission power of the nodes,it can effectively resist the attacker's interference on the V2X communication channel and reduce the communication delay.
In order to study the head crash conditions of two-wheeler cyclist in traffic accident, this paper verified the car-to-two-wheeler crash model by accident reconstruction, and analyzed the differences of head impact area, speed and angle on sedan and SUV models, proposed the evaluation suggestions in combination with the existing pedestrian protection evaluation requirements. The results show that the head crash speed of the cyclist is not different from that of pedestrians. For the vehicle with Bonnet Leading Edge（BLE） height bellow 850 mm, it is recommended to expand the Wrap Around Distance（WAD） of head crash area from 2 100 to 2 300 mm, and the collision angle is 45°. For vehicles with BLE height higher than 850 mm, there is no need to expand the area.
文章介绍了一种应用于全地形越野车双横臂独立悬架系统的设计、计算及有限元分析,可有效提升现代越野车辆的悬架性能,解决了传统型式非独立悬架对越野车辆平顺性、操稳性和通过性等性能的制约.首先提出该全地形越野车双横臂独立悬架系统的总体设计要求,然后根据参考车型、基础车型并以正常性能保障为基础确定主要性能参数.通过针对弹性元件、导向元件和阻尼元件的设计和计算完成该全地形越野车悬架系统的方案设计.通过对该全地形越野车悬架系统的有限元分析,仿真分析悬架跳动过程的四种工况,完成对该全地形越野车悬架系统结构强度的校核.该全地形越野车双横臂独立悬架系统设计的基本流程,将对后续独立悬架的结构设计、技术参数的确定及其有限元仿真等具有参考价值和指导意义.
针对职业教育在学习内容架构和考核模式等方面目前存在的弊端,依托中德先进职业教育合作项目(SGAVE)运行机制,引进德国双元制教育理念.对照汽车机电维修岗位,分析岗位工作领域技能要素及职责分工,提炼学习领域具体内容,重构课程体系.从教师分工协作策略、学生分工协作学习过程、校企分工协作模式构建了分工协作教学实践模型,实施了具体教学步骤,形成了岗位职责轮转考核模式,为分工协作教学实践的开展提供指导和依据.
随着新能源车的迅速发展和普及,汽车的轻量化技术也越来越受到重视.尼龙管由于质量轻、加工工艺简单,已逐渐成为冷却管路的主要使用材料,非常适合在新能源汽车冷却系统中应用.文章介绍了冷却水管的三种技术路线、三种材料使用对比以及采用胶管和尼龙管方案整车优缺点对比.示例通过对比一款新能源车橡胶水管和尼龙水管方案,说明了尼龙管方案批量采用的轻量化成果.最后探讨了尼龙管的设计注意事项,对同类车型设计与生产提供了参考和借鉴意义.
发动机生产质量状态的统计与表达存在着工序多、质量数据分散、评价标准复杂,以及分析与统计过程中易产生不透彻、不准确等困难,为改进工作带来了不便.文章从发动机生产质量信息展示分析、数据维度与表达方法、展示规划与视图设计、数据导入与页面操作,以及数字化成果展示等方面出发,在Tableau软件中建立了体系化的表达方法,实现了数据的高阶与动态展示.该研究减轻了工程人员的重复劳动,提高了统计的准确率,达成了突出重点问题、辅助领导决策,以及减少报废和控制索赔的最终目的.
为更好地探究轮毂电机角模块系统在运行过程中的多种物理场耦合特性,解决轮毂电机在有限空间中存在的散热难问题,文章基于键合图理论,建立了轮毂电机角模块系统的多物理场耦合模型,并导出数学模型,利用MATLAB/Simulink进行动态仿真,分析了轮毂电机在多物理场耦合作用下的输出转矩和温度特性.仿真结果表明,采用水冷模式对定子绕组的冷却效果明显;对于不同的水道截面尺寸和冷却液流速,轮毂电机呈现出不同的温升特性;相同的电机运行工况和冷却液流量下,增加水道内径可以达到更好的冷却效果.借助有限元分析软件 Fluent 进行流体仿真,得到的电机温度分布云图和温度变化曲线与上述结论基本一致,验证了耦合模型的实用性和可靠性,为轮毂电机角模块系统的设计和应用提供了理论参考.
