Most Down Articles

Published in last 1 year | In last 2 years| In last 3 years| All| Most Downloaded in Recent Month| Most Downloaded in Recent Year|

Most Downloaded in Recent Month

Please wait a minute...


For Selected: Download Citations EndNote Reference Manager ProCite BibTeX RefWorks Toggle Thumbnails

Select

Effect of EGR Exhaust Gas Composition and Temperature onMechanical Characteristics of Diesel Engine Particles Zhao Yang, Li Mingdi, Wang Zhihao, Xu Guangju, Yuan Yinnan, Wu Bin Automotive Engineering    2019, 41 (6): 634-640.   DOI: 10.19562/j.chinasae.qcgc.2019.06.004 Abstract （289）      PDF（pc） （2990KB）（576）       Knowledge map    Focusing on micro-mechanical properties of diesel engine particles, the variation of particle size, number and mass concentration were studied by using particle size analyzer and atomic force microscope for different EGR exhaust gas composition and temperature. The effect of EGR exhaust gas composition and temperature on the micro-mechanical properties such as particle elastic modulus, agglomeration forces and main action forms were analyzed. The results show that the total number concentration of nucleation mode particles has little change with the exhaust gas temperature increasing, however the total number concentration of accumulation mode particles increases significantly, and the particle elastic modulus, structure rigidity and agglomeration forces all increase significantly, while the force action type changes from liquid bridge force to Van Der Waals force. Compared with the introduction of exhaust gas, when N2 and CO2 are introduced respectively, the agglomeration force between particles is mainly in the form of Van Der Waals force and liquid bridge force. The N2 in exhaust gas is the main gas composition that leads to the increase of particle size, number concentration and mass concentration, structural rigidity and agglomeration force of accumulation mode particles with EGR introduced while the CO2 can significantly reduce the number and mass concentration of accumulated particles and reduce the structural rigidity and agglomeration force. Reference | Related Articles | Metrics

Select

A Criticality Assessment Model for the Intelligent Vehicle Test Scenario Based on the Onboard Camera Images Bing Zhu,Yinzi Huang,Jian Zhao,Peixing Zhang,Jingwei Xue Automotive Engineering    2024, 46 (4): 557-563.   DOI: 10.19562/j.chinasae.qcgc.2024.04.001 Abstract （155）   HTML （13）    PDF（pc） （4680KB）（107）       Knowledge map    Onboard camera images are the main data sources for constructing the intelligent vehicle test scenario library， but the probability of critical test scenarios occurring in the actual collected onboard camera images is very low， and most of the scenarios have little test value. If it is directly applied to the intelligent vehicle test， it will waste a lot of test resources. In this paper， a criticality assessment model for the intelligent vehicle test scenario based on the onboard camera images is proposed. Firstly， the images collected from real vehicles are processed based on the camera parameters to output parameters that have impact on driving safety. Then， the parameters are integrated using the risk field theory to output the criticality assessment results of the intelligent vehicle test scenario. Finally， the criticality assessment validation is conducted on the images collected from the actual vehicle. The results show that the proposed model can accurately output the specific values of the criticality of the test scenarios in order to compare the test values of different scenarios， proving that the model proposed in this paper can effectively screen the intelligent vehicle critical test scenarios. Table and Figures | Reference | Related Articles | Metrics

Select

Comprehensive Review and Prospect of the Modeling of Alkaline Water Electrolysis System for Hydrogen Production Yangyang Li,Xintao Deng,Junjie Gu,Tao Zhang,Bin Guo,Fuyuan Yang,Minggao Ouyang Automotive Engineering    2022, 44 (4): 567-582.   DOI: 10.19562/j.chinasae.qcgc.2022.04.012 Abstract （1130）   HTML （83）    PDF（pc） （4913KB）（2142）       Knowledge map    The status quo and prospect of the alkaline water electrolysis system for hydrogen production are summed up in this paper with the focus on its modeling. Firstly， various ways of water electrolysis for hydrogen production are comparatively analyzed with the status quo of alkaline water electrolysis system for hydrogen production emphatically expounded： the technology of hydrogen production by alkaline water electrolysis has the features of low investment cost， long service life and large scale and is an important means to achieve the carbon peak target at current stage. Then， in the aspect of modeling for the alkaline water electrolysis system for hydrogen production， the influencing mechanisms of the energy consumption and gas purity of electrolytic cell as well as the temperature and system control are quantitatively analyzed. This study provides theoretical and technical supports for the development of hydrogen production technology by alkaline water electrolysis. Table and Figures | Reference | Related Articles | Metrics

Select

An Analysis on Challenge and Development Trend of Safety Management Technologies for Traction Battery in New Energy Vehicles Wang Zhenpo, Yuan Changgui, Li Xiaoyu Automotive Engineering    2020, 42 (12): 1606-1620.   DOI: 10.19562/j.chinasae.qcgc.2020.12.002 Abstract （1063）      PDF（pc） （1831KB）（1491）       Knowledge map    The safety management of traction battery is important means to ensure the safe operation of new energy vehicles, which directly affects the durability and reliability of vehicle. In this paper,three aspects, i.e. the safety concept, key technologies and futural development trend of traction battery are reviewed, in which the key technologies of battery safety including the mechanism and control measures of thermal runaway and protective structures are expounded respectively, with their achievements and inadequacies comparatively analyzed. Finally aiming at the challenges the current safety management of traction battery faces, the development trend of battery safety management in the future is given -- from mechanism analysis to system design optimization and from passive safety protection to active safety prediction Reference | Related Articles | Metrics

Select

Comprehensive Evaluation Method for Automated Vehicle in Multiple Virtual Logical Scenarios Peixing Zhang,Kongjian Qin,Bing Zhu,Jian Zhao,Tianxin Fan,Wenbo Zhao Automotive Engineering    2024, 46 (3): 375-382.   DOI: 10.19562/j.chinasae.qcgc.2024.03.001 Abstract （349）   HTML （53）    PDF（pc） （1658KB）（289）       Knowledge map    The scenario-based simulation testing method has become the core idea for automated vehicle performance verification， which splits the continuous vehicle driving process to obtain non-repetitive and independent scenario segments and tests them in virtual environment. Fitting in with the test process， a comprehensive evaluation method for automated vehicle simulation testing in multi-logical scenarios is proposed in this paper. Firstly， a comprehensive evaluation method for automated vehicle in multi-logical scenarios is established and the scenarios weighting analysis process considering both the scenario's own characteristic information and simulation test process information is defined. Then， the logical scenario's own characteristic information weighting is built by exposure degree， control loss degree and hazard degree. The simulation test process information weighting is built by simulation accuracy information， element type information， parameter space information and discrete step information. Finally， the information of front braking， front left cut-in and front right cut-in scenarios is extracted based on HighD dataset and the scenario weight is calculated through the method proposed in this paper and base algorithm test results， and the two tested algorithms’ comprehensive evaluation results are obtained in multi-logical scenarios. Table and Figures | Reference | Related Articles | Metrics

Select

Review of Key Technologies for Autonomous Vehicle Test Scenario Construction Xiangyang Xu,Wenhao Hu,Honglei Dong,Yan Wang,Lingyun Xiao,Penghui Li Automotive Engineering    2021, 43 (4): 610-619.   DOI: 10.19562/j.chinasae.qcgc.2021.04.019 Abstract （1184）   HTML （87）    PDF（pc） （1499KB）（2270）       Knowledge map    For autonomous vehicle test scenarios construction， this paper firstly makes a comparative analysis of the existing scenario definition and architecture， and proposes that test scenarios should cover a total of 10 layers of information of scene elements and test elements. Secondly， a method system of scenario construction including direct construction of concrete scenario， mining and deduction of typical logical scenario and reconstruction and derivation of specific scenario is summarized and proposed. Thirdly， from the three dimensions of single segment test， combined segment test and integrated traffic flow test， the main virtual scenario test application methods are systematically sorted out. Finally， the research prospect is presented from the perspective of method chain and tool chain of scenario construction. The research results of the review will provide reference for the testing and evaluation of autonomous vehicles. Table and Figures | Reference | Related Articles | Metrics

Select

Research on Automatic Driving Motion Control Based on Double Estimator Reinforcement Learning Combined with Forward Predictive Control Guodong Du,Yuan Zou,Xudong Zhang,Wenjing Sun,Wei Sun Automotive Engineering    2024, 46 (4): 564-576.   DOI: 10.19562/j.chinasae.qcgc.2024.04.002 Abstract （87）   HTML （9）    PDF（pc） （8372KB）（76）       Knowledge map    Motion control research is an important part to achieve the goal of autonomous driving. To solve the problem of suboptimal control sequence due to the limitation of single-step decision in traditional reinforcement learning algorithm， a motion control framework based on the combination of double estimator reinforcement learning algorithm and forward predictive control method （DEQL-FPC） is proposed. In this framework， double estimators are introduced to solve the problem of action overestimation of traditional reinforcement learning methods and improve the speed of optimization. The forward predictive multi-step decision making method is designed to replace the single step decision making of traditional reinforcement learning so as to effectively improve the performance of global control strategies. Through virtual driving environment simulation， the superiority of the control framework applied in path tracking and safe obstacle avoidance of autonomous vehicles is proved， and the accuracy， safety， rapidity and comfort of motion control are guaranteed. Table and Figures | Reference | Related Articles | Metrics

Select

Autonomous Driving 3D Object Detection Based on Cascade YOLOv7 Dongyu Zhao, Shuen Zhao Automotive Engineering    2023, 45 (7): 1112-1122.   DOI: 10.19562/j.chinasae.qcgc.2023.07.002 Abstract （245）   HTML （19）    PDF（pc） （4587KB）（391）       Knowledge map    For the problems of incomplete feature information and excessive point cloud search volume in 3D object detection methods based on image and original point cloud， based on Frustum PointNet structure， a 3D object detection algorithm based on cascade YOLOv7 is proposed by fusing RGB image and point cloud data of autonomous driving surrounding scenes. Firstly， a frustum estimation model based on YOLOv7 is constructed to longitudinally expand the RGB image RoI into 3D space. Then the object point cloud and background point cloud in the frustum are segmented by PointNet ++. Finally， the natural position relationship between objects is explained by using the non-modal 3D box estimation network to output the length， width， height， heading et al. of objects. The test results and ablation experiments on the KITTI public dataset show that compared with the benchmark network， the inference time of cascade YOLOv7 model is shortened by 40 ms?frame-1， with the mean average precision of detection at the moderate， difficulty level increased by 8.77%， 9.81%， respectively. Table and Figures | Reference | Related Articles | Metrics

Select

Research and Analysis of Thermal Runaway Characteristics and Prevention and Control Technology of Power Battery Zhiyuan Li, Ruihua Lu, Qinghua Yu, Fuwu Yan Automotive Engineering    2024, 46 (1): 139-150.   DOI: 10.19562/j.chinasae.qcgc.2024.01.015 Abstract （100）   HTML （9）    PDF（pc） （3633KB）（185）       Knowledge map    In recent years， the thermal runaway problem of lithium-ion battery has become the main bottleneck restraining the development of power battery of new energy vehicles. In this paper， a comprehensive review of the research on the thermal runaway problem of the power battery of new energy vehicles is carried out， with the inducment of the thermal runaway of lithium-ion battery expounded and the thermal runaway process of lithium-ion battery and the characteristics of the thermal runaway of lithium-ion battery under different variable conditions introduced. Based on the characteristic parameters of thermal runaway of lithium-ion battery， the early warning methods and fire suppression methods applicable to lithium-ion battery fire are reviewed， and the shortcomings and development trend of the current research on thermal runaway of power battery of new energy vehicles are summarized， providing certain reference for the development of power battery of new energy vehicles. Table and Figures | Reference | Related Articles | Metrics

Select

Review of Autonomous Driving Decision-Making Research Based on Reinforcement Learning Lisheng Jin,Guangde Han,Xianyi Xie,Baicang Guo,Guofeng Liu,Wentao Zhu Automotive Engineering    2023, 45 (4): 527-540.   DOI: 10.19562/j.chinasae.qcgc.2023.04.001 Abstract （535）   HTML （54）    PDF（pc） （1155KB）（648）       Knowledge map    Decision-making technology of autonomous vehicle is promoted by the development of reinforcement learning， and intelligent decision-making technology has become a key issue of high concern in the field of autonomous driving. Taking the development of reinforcement learning algorithm as the main line in this paper， the in-depth application of this algorithm in the field of single-car autonomous driving decision-making is summarized. Traditional reinforcement learning algorithms， classic algorithms and frontier algorithms are summarized and compared from the aspect of basic principles and theoretical modeling methods. According to the classification of autonomous driving decision-making methods in different scenarios， the impact of environmental state observability on modeling is analyzed， and the application technology routes of typical reinforcement learning algorithms at different levels are emphasized. The research prospects for the autonomous driving decision-making method are proposed in order to provide a useful reference for the research of autonomous driving decision-making. Table and Figures | Reference | Related Articles | Metrics

Select

Real-Time Pavement Recognition Technology Based on Intelligent Tire System Weidong Liu,Zongzhi Han,Zhenhai Gao,Yanhu Kang Automotive Engineering    2024, 46 (4): 617-625.   DOI: 10.19562/j.chinasae.qcgc.2024.04.007 Abstract （50）   HTML （2）    PDF（pc） （4402KB）（57）       Knowledge map    Under complex and extreme conditions， road adhesion coefficient is an important state parameter for tire force analysis and vehicle dynamics control. Compared with the method of model estimation， the intelligent tire technology can feed back the interaction information between the tire and the road surface to the vehicle control system. In this paper， a method of obtaining road adhesion coefficient of vehicle by combining intelligent tire system and machine learning is proposed. Firstly， considering the driving conditions， the sensor selection is carried out， and the intelligent tire hardware acquisition system based on MEMS three-axis acceleration sensor is developed， and the wireless transmission mode with simplified hardware structure is adopted. Secondly， the data set of machine learning training is collected by vehicle experiments by collecting real car test data on different road surfaces and the wheel-ground relationship and signal characteristics are analyzed. Finally， the feature learning of acceleration timing signal is realized by combining the advantages of CNN and LSTM. The effectiveness and accuracy of the proposed CNN-LSTM dual channel fusion neural network model are verified by comparing with the training results of other neural network models. The road identification scheme proposed in this paper realizes the goal of real-time road recognition， and the hardware and software architecture and neural network model are more suitable for vehicle system loading， providing real-time and accurate road information for vehicle motion control. Table and Figures | Reference | Related Articles | Metrics

Select

Optimal Obstacle Avoidance Trajectory Planning Algorithm Considering Vehicle Motion Constraints Bin Yang,Xuewei Song,Zhenhai Gao Automotive Engineering    2021, 43 (4): 562-570.   DOI: 10.19562/j.chinasae.qcgc.2021.04.014 Abstract （520）   HTML （20）    PDF（pc） （2331KB）（728）       Knowledge map    The motion characteristics of the autonomous vehicle should be taken into account to ensure safety， comfort and stability when avoiding obstacles. An obstacle avoidance trajectory planning algorithm with the constraints of vehicle motion is proposed in this paper. Firstly， combining with the motion state and position information of obstacles， the algorithm derives the derivative status region where the vehicle can safely avoid obstacles from the local environment map. Then， the terminal state points are sampled in the derivative status region to form a discrete terminal state point set. The obstacle avoidance trajectory search problem in complex road environment is transformed into the problem of trajectory fitting and optimization between the vehicle and the state point set. Trajectory fitting is realized by Bézier curve planner based on vehicle lateral dynamics model while the optimization process takes into consideration of driving smoothness and operation stability in the process of vehicle trajectory following. By comparing the obstacle avoidance effect in multiple scenarios with the conventional State Lattice algorithm and MPC algorithm， the results show that the proposed algorithm can make the vehicle avoid obstacles safely and reasonably in the test scenarios， and has better performance in the aspects of trajectory smoothness and vehicle handling stability. Table and Figures | Reference | Related Articles | Metrics

Select

Research Review of Fault Diagnosis for Electric Drive Powertrain System of Pure Electric Vehicles Pengbo Zhang, Renxiang Chen, Yiming Shao, Shizheng Sun, Kaibo Yan Automotive Engineering    2024, 46 (1): 61-74.   DOI: 10.19562/j.chinasae.qcgc.2024.01.007 Abstract （181）   HTML （16）    PDF（pc） （1811KB）（253）       Knowledge map    In order to comprehensively review the current status and clarify the future trend of fault diagnosis in the electric drive system of pure electric vehicles， this paper first introduces the basic structure， functions and development history of the electric drive system of pure electric vehicles； then summarizes in detail the types and causes of faults of crucial components of the electric drive system of pure electric vehicles， and analyzes the main research status quo of fault diagnosis methods for key components of the electric drive system of pure electric vehicles. Then the domestic and international research progress and development of the diagnosis methods of the pure electric vehicle electric drive system are reviewed in detail from the four aspects of expert knowledge-driven， model-driven， signal-driven and data-driven， with the advantages and disadvantages of different methods compared. Finally， the problems faced by the fault diagnosis of electric drive system of pure electric vehicles and the development direction are analyzed and foreseen， and it is further discussed and pointed out that the future research on the fault diagnosis of electric drive system of pure electric vehicles can be focused on variable condition coupled fault diagnosis， micro-fault and pre-fault diagnosis， real-time online fault diagnosis， intelligent operation and maintenance， unknown fault diagnosis and system self-healing technology， etc. Table and Figures | Reference | Related Articles | Metrics

Select

Motor Fault Diagnosis and Failure Control for Distributed Four-wheel Drive Electric Vehicles Zhu Shaopeng, Fu Qitao, Huang Xiaoyan, Wang Zhiwei, Yang Xinghao Automotive Engineering    2020, 42 (9): 1284-1291.   DOI: 10.19562/j.chinasae.qcgc.2020.09.020 Abstract （221）      PDF（pc） （2059KB）（542）       Knowledge map    In this paper, a fault diagnosis and failure control strategy based on motor failure control gain is proposed for the soft and hard faults of motor in distributed four-wheel drive electric vehicles. A fault diagnosis module and a failure mode judgment and driving force redistribution module are designed, which are combined with vehicle direct yaw moment control to achieve the secondary distribution control of driving force based on fault diagnosis. By MATLAB/Simulink and CarSim joint simulation and RCP real vehicle test, the effectiveness of the fault diagnosis and failure control strategy proposed is verified. The proposed control strategy can make sufficient use of the motor redundancy characteristics of distributed four-wheel drive electric vehicle to ensure the safe driving of vehicle under the various common failure conditions of motor Reference | Related Articles | Metrics

Select

Intelligent Vehicle Lane Changing Trajectory Planning Based on Double Quintic Polynomials Guochen Niu,Wenshuai Li,Hongxu Wei Automotive Engineering    2021, 43 (7): 978-986.   DOI: 10.19562/j.chinasae.qcgc.2021.07.004 Abstract （574）   HTML （27）    PDF（pc） （3065KB）（673）       Knowledge map    In order to meet the requirements of safety and comfort during lane changing of the intelligent vehicle， an intelligent vehicle lane changing trajectory planning algorithm based on double quintic polynomials is proposed. The quintic polynomial programming algorithm is improved with the condition of dynamic programming of lane changing time and increased comfort constraints. On this basis， the transit state is calculated by combining the current environment and the beginning and end states of the lane changing， and the twice improved quintic polynomial algorithm is used to avoid collision with the vehicle in front. The simulation and experiment results of trajectory planning and trajectory tracking show that the proposed double quintic polynomials lane changing trajectory planning algorithm has advantages in lateral velocity， acceleration， acceleration rate of change and running time of the algorithm under different working conditions. In addition， the trajectory obtained can also meet the requirements of vehicle lane changing under the actual situation， with improved safety and good handling stability， which proves that the algorithm has certain practical application value. Table and Figures | Reference | Related Articles | Metrics

Select

A Cooperative Lane Change Strategy for Intelligent Connected Vehicles Oriented to Mandatory Lane Change Scenarios Shurui Guan,Keqiang Li,Junyu Zhou,Jia Shi,Weiwei Kong,Yugong Luo Automotive Engineering    2024, 46 (2): 201-210.   DOI: 10.19562/j.chinasae.qcgc.2024.02.002 Abstract （179）   HTML （24）    PDF（pc） （4054KB）（211）       Knowledge map    Collaborative lane change technology for intelligent connected vehicles has been widely studied， but existing strategies can hardly solve the problem of vehicle collaboration in mandatory lane change scenarios or may cause notable impact on upstream traffic. For mandatory lane change scenarios demand， a two-stage cooperative lane change strategy considering theoretical minimal safety space is proposed in this paper. Firstly， the control architecture for a two-vehicle cooperative lane change system is proposed and a collaborative lane change scheme is developed for mandatory lane change scenarios. Then， a two-stage receding-horizon trajectory planning strategy of spacing adjustment and collaborative lane change is designed， where the theoretical minimum safe distance is embedded as a constraint of spacing adjustment stage， to solve the problem of conservative spacing strategies in existing research. Finally， numerical simulation and hardware in-loop experiments are performed to verify the effectiveness， advantages and computational real-time performance of the proposed strategy. The results show that the proposed strategy can effectively improve the success rate of lane change， reduce the negative traffic impact while ensuring lane change safety， and is also applicable in real time computing and communication environment of actual edge cloud platform. Table and Figures | Reference | Related Articles | Metrics

Select

Review on Electro-Mechanical Brake Structure and Control Technology Lu Xiong,Congcong Li,Guirong Zhuo,Yulin Cheng,Le Qiao,Xinjian Wang Automotive Engineering    2023, 45 (12): 2187-2199.   DOI: 10.19562/j.chinasae.qcgc.2023.12.001 Abstract （302）   HTML （33）    PDF（pc） （3849KB）（538）       Knowledge map    As a complete form of brake-by-wire system， electro-mechanical brake （EMB） system has many advantages such as simplified structure and rapid braking response. To give a comprehensive review on the development status of EMB structure， the development and industrialization of various structure schemes are summarized based on investigation of a large number of patents in this paper. And four basic structure schemes including the ball-screw-type， wedge-type， ball-ramp-type and cam-type scheme are analyzed and compared. For the clamping force control problem of the actuator with nonlinear characteristics and slow time-varying parameter perturbations， firstly a review on the actuator modeling methods is conducted in this paper. Then through the classification based on the presence or absence of pressure sensors， the research progress both home and abroad is reviewed from two aspects： clamping force control methods based on the feedback force value and control methods based on the estimated force value. Finally， future development trends of the actuator structure design， clamping force control and vehicle coordination redundancy control are prospected. Table and Figures | Reference | Related Articles | Metrics

Select

Decision-Making for Autonomous Driving in Uncertain Environment Xinke Fu,Yingfeng Cai,Long Chen,Hai Wang,Qingchao Liu Automotive Engineering    2024, 46 (2): 211-221.   DOI: 10.19562/j.chinasae.qcgc.2024.02.003 Abstract （165）   HTML （17）    PDF（pc） （2036KB）（244）       Knowledge map    In the context of real-world driving environments， due to the perturbation of perception data and the unpredictable behavior of other traffic participants， rational decision-making in highly interactive and intricate driving scenarios considering the impact of uncertainty factors is one of the main concerns that decision-making and planning systems for autonomous vehicles must address. A behavioral decision-making method for autonomous vehicles navigating in uncertain environments is proposed in this paper. To mitigate the impact of uncertainty， the behavioral decision-making process is transformed into a partially observable Markov decision process （POMDP）. Furthermore， to tackle the computational complexity of the POMDP model， the complex network theory is applied for the first time for dynamically modeling the microscopic driving environment surrounding the autonomous vehicle， which allows for the effective characterization of interaction relationship between vehicle nodes and the scientific selection of significant vehicle nodes， guiding the autonomous vehicle's decision-making process， enabling precise identification of critical vehicle nodes， and pruning the decision space. The effectiveness of the proposed method is verified in a simulation environment， and the experimental results show that the proposed method has higher computational efficiency， superior performance， and enhanced flexibility in comparison to existing state-of-the-art behavioral decision-making methods. Table and Figures | Reference | Related Articles | Metrics

Select

Current Status and Trend of Automotive Safety Procedures/Programs Lin Hu,Ziyi Gu,Danqi Wang,Fang Wang,Tiefang Zou,Jing Huang Automotive Engineering    2024, 46 (2): 187-200.   DOI: 10.19562/j.chinasae.qcgc.2024.02.001 Abstract （321）   HTML （30）    PDF（pc） （1854KB）（294）       Knowledge map    In the process of electrification and intellectualization of the automobile industry， the automotive safety testing and evaluation technology has also been extended and expanded from simple passive safety to active and passive safety integration. In this paper， the differences between the world's mainstream automotive safety assessment procedures are compared and analyzed from three aspects： occupant protection in the vehicle， vulnerable road user protection outside the vehicle， and active safety. The key technical points of vehicle safety development for each evaluation condition are summarized and the development trend of safety evaluation procedures for new energy and intelligent networked vehicles is discussed. The research concludes that the mainstream automotive safety evaluation procedures are becoming more and more stringent in passive safety evaluation， with the proportion of active safety evaluation conditions gradually increasing， and the development focus of the future evaluation procedures will focus on the integration of active and passive safety and virtual evaluation for complex working conditions. In addition， the battery safety test for new energy vehicles has been relatively perfect， and the future research focus can be expanded to the direction of electronic control system testing， chassis stability testing， and unified standardization certification of charging and swapping facilities and supporting equipment. In the medium and long term， the construction of reasonable and reliable evaluation methods such as OTA （over the air） testing of intelligent networked vehicles and HMI （human machine interface） safety and comfort will become a major difficulty concerned by the industry， and a composite evaluation system combining the virtual and reality can be built with the help of tools such as autonomous driving simulators. Table and Figures | Reference | Related Articles | Metrics

Select

Evaluation Method for the Penetration Rate of Perception System Triggering Conditions Junyi Chen,Zhenyuan Liu,Xuezhu Yang,Tianchen Wang,Haixia Li,Tong Jia,Xingyu Xing,Xinzheng Wu Automotive Engineering    2024, 46 (4): 577-587.   DOI: 10.19562/j.chinasae.qcgc.2024.04.003 Abstract （46）   HTML （4）    PDF（pc） （3076KB）（48）       Knowledge map    The issue of safety of the intended functionality （SOTIF） restricts the application of autonomous vehicles. The various extreme driving environments faced by the perception system of autonomous vehicles are highly susceptible to SOTIF problems. Therefore， it is necessary to identify and evaluate a large number of triggering conditions in the safety analysis phase according to the existing SOTIF standards to select high-value trigger conditions so as to provide test scenarios for subsequent test and validation. Firstly， a set of three-dimensional evaluation system for triggering conditions of the perception system including exposure rate， penetration rate and hazard rate is proposed， based on the analysis of the risk evolution process of triggering conditions in autonomous driving system. Subsequently， based on the analytic hierarchy process （AHP）， a quantitative evaluation method for the penetration of triggering conditions is constructed. Finally， 15 triggering conditions for a mass-produced vehicle fusion perception system are selected and analyzed. Test cases are built and the closed site tests are conducted to evaluate the penetration rate of the above triggering conditions. Finally， through the calculation， 3 high-risk triggering conditions are screened， which verifies the feasibility of the quantitative evaluation method of trigger condition penetration rate. Table and Figures | Reference | Related Articles | Metrics