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|

Published in last 1 year

Please wait a minute...


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

Select

Study on the Technology Development of Multi-Domain Electrical and Electronic Architecture for Intelligent Networked Vehicles Yuan Zou,Wenjing Sun,Xudong Zhang,Jiahui Liu,Ya Wen,Wenbin Ma Automotive Engineering    2023, 45 (6): 895-909.   DOI: 10.19562/j.chinasae.qcgc.2023.06.001 Abstract （479）   HTML （50）    PDF（pc） （3130KB）（1045）       Knowledge map    With the continuous development of intelligent and networked vehicle technologies， the traditional electrical and electronic architecture can no longer meet the new requirements of future-oriented vehicle， road， cloud and network integration development. Focusing on the future-oriented multi-domain electrical and electronic architecture of intelligent networked vehicles， this review provides a detailed review of existing technologies in terms of the four aspects of overall design， hardware system， communication system and software system， and provides an outlook on the development of electrical and electronic architecture in China. This paper can provide an important reference value for the research of automotive electrical and electronic architecture technology. Table and Figures | Reference | Related Articles | Metrics

Select

Key Technologies of Brain-Inspired Decision and Control Intelligence for Autonomous Driving Systems Shengbo Eben Li,Guojian Zhan,Yuxuan Jiang,Zhiqian Lan,Yuhang Zhang,Wenjun Zou,Chen Chen,Bo Cheng,Keqiang Li Automotive Engineering    2023, 45 (9): 1499-1515.   DOI: 10.19562/j.chinasae.qcgc.2023.ep.006 Accepted: 25 April 2023 Online available: 25 April 2023 Abstract （532）   HTML （36）    PDF（pc） （3942KB）（562）       Knowledge map    As the technical trend of the next generation of high-level autonomous driving， brain-inspired learning is a class of methods that employ deep neural networks （DNN） as the strategy carrier and reinforcement learning （RL） as the training algorithm to realize strategy self evolution through continuous interaction with traffic environments， ultimately obtaining the optimal mapping from the environmental state to execution action. Currently， brain-inspired learning is mainly applied in decision-making and motion control modules of autonomous driving. Its key technologies include how to design its system framework to support interactive training， high-fidelity autonomous driving simulation platform， accurate and flexible representation of environment statues， multiple dimensional evaluation metrics， and effective training algorithm that drives policy updates. This paper systematically summarizes the history and future trends of decision-making and control functionalities in autonomous vehicles， including two main modular architectures （HDC， i.e.， hierarchical decision & control and IDC， i.e.， integrated decision & control） and three mainstream technical solutions （i.e.， rule-based design， supervised learning， and brain-inspired learning）. An overview of autonomous driving simulation platforms are briefly introduced， followed by three effective designing methods for representing traffic environment states （i.e.， object-based design， feature-based design， and combined design）. The paper also introduces multiple dimensional evaluation metrics for autonomous vehicles， which can describe self-driving performances including driving safety， regulatory compliance， driving comfort， travel efficiency， energy efficiency. Typical reinforcement learning algorithms， including their design principles， taxonomy， and algorithm performances， are introduced， as well as their application on brain-inspired autonomous driving systems in the systematic design of road-cloud cooperation. 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）（539）       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

Methodology of Critical Scenarios-Based Dual-Loop Testing and Verification for Safety of the Intended Functionality Siyu Wu,Wenhao Yu,Xingyu Xing,Yuxin Zhang,Chuzhao Li,Xueke Li,Xinyu Gu,Yunwei Li,Xiaohan Ma,Wei Lu,Zheng Wang,Zhenmao Hao,Hong Wang,Jun Li Automotive Engineering    2023, 45 (9): 1583-1607.   DOI: 10.19562/j.chinasae.qcgc.2023.09.008 Abstract （151）   HTML （12）    PDF（pc） （3139KB）（534）       Knowledge map    Safety of the Intended Functionality （SOTIF） is a vital part of autonomous driving and poses a significant challenge for intelligent connected vehicles， which requires comprehensive and high-efficiency testing and verification methodology to effectively assist the safety development process of the system. Based on critical scenarios， this paper proposes a dual-loop framework with close loop verification and dynamic evaluation， summarizes the technologies for critical scenarios construction， and further formulizes a quantitative method for acceptance criterion. Finally， this article looks forward to key researches in the area of SOTIF testing and verification. The paper aims to provide a maneuverable and theoretical reference for the engineering practice on the SOTIF for intelligent connected vehicle. Table and Figures | Reference | Related Articles | Metrics

Select

Technical Status and Development Trend of Automotive Operating System Zhihong Wang,Deying Yu,Tianze Ma,Bingquan Chen,Zongyang Li,Hongyan Li Automotive Engineering    2023, 45 (6): 910-921.   DOI: 10.19562/j.chinasae.qcgc.2023.06.002 Abstract （256）   HTML （31）    PDF（pc） （2374KB）（504）       Knowledge map    With the development of automotive electrification and intelligence， its electronic and electrical architecture is changing from traditional distributed architecture to domain centralized architecture and central computing architecture， and vehicle software is upgrading from signal oriented architecture to service-oriented software architecture. Automotive operating system is an important foundation of vehicle software ecology， and it is of great significance to strengthen the development of automotive operating system technology to ensure the safety of intelligent automobile industry in China. Based on this background， this paper reviews the technical architecture， typical products and development status of automotive operating system， compares the mainstream virtual technology products， kernels and middleware at home and abroad， and brings forward the development trend of automotive operating system. 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 （246）   HTML （19）    PDF（pc） （4587KB）（392）       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

Spatio-temporal Joint Planning Method of Intelligent Vehicles Based on Improved Hybrid A Jie Hu, Zhihao Zhang, Ruinan Chen, Ruipeng Chen, Haoyan Liu, Qi Zhu, Hui Chen Automotive Engineering    2023, 45 (7): 1123-1133.   DOI: 10.19562/j.chinasae.qcgc.2023.07.003 Abstract （289）   HTML （19）    PDF（pc） （4436KB）（356）       Knowledge map    Motion planning is the critical module of trajectory generation in autopilot system. The existing motion planning mostly adopts path-velocity decomposition method， which is easy to fall into trajectory suboptimal in complex dynamic scenarios. In this paper， a spatio-temporal joint motion planning method based on the combination of search and numerical optimization is proposed to solve the drivable trajectory directly. Firstly， the improved hybrid A* is used to search for the initial rough trajectory in the spatio-temporal range. Secondly， a drivable spatio-temporal corridor is constructed based on the initial trajectory， and considering vehicle dynamics and trajectory continuity constraints， the numerical optimization method is used to further smooth the initial trajectory. Finally， two typical complex dynamic scenarios of lane change overtaking and side-vehicle cut-in are selected for simulation test. The results show that the proposed planning method is more flexible and more reasonable than the traditional spatio-temporal decoupling planning method， and has better real-time computing performance. Table and Figures | Reference | Related Articles | Metrics

Select

Research on Integrated Thermal Management System of Hydrogen Fuel Cell Vehicle Zhongwen Zhu,Xin Wang,Weihai Jiang,Cheng Li Automotive Engineering    2023, 45 (11): 1991-2000.   DOI: 10.19562/j.chinasae.qcgc.2023.11.001 Abstract （312）   HTML （40）    PDF（pc） （4189KB）（352）       Knowledge map    Effective thermal management is crucial for the efficient operation of fuel cell vehicles （FCVs）. Fuel cell vehicle thermal management often adopts independent management methods for each subsystem， but this independent method cannot effectively utilize its own waste heat to improve thermal management efficiency and range. In this regard， a vehicle integrated thermal management （VITM） system that utilizes fuel cell waste heat is developed in this paper. The VITM uses a heat exchanger to achieve waste heat recovery of fuel cells and efficient thermal management of various components. The flexible management of each circuit decoupling is achieved through the integrated design of six-way valves. And simulation research on thermal management is conducted on the AMESim simulation platform. The results show that the VITM system developed in this paper can maintain the stability of various components of fuel cell vehicles within the specified operating temperature range. At an ambient temperature of -10 ℃， compared with direct heating mode， a heat pump air conditioner using fuel cell waste heat as a heat source to heat the power battery， the heating time is reduced by 55%.The heating time for the passenger compartment is reduced by 85%， and the energy consumption ratio （COP） value is 4， resulting in a 75% reduction in energy consumption. Table and Figures | Reference | Related Articles | Metrics

Select

Fatigue Simulation and Experimental Study of Super-size Integral Die Casting Aluminum Alloy Rear End Body Weihe Zeng, Ligang Gou, Yu Luo, Jun Zhang, Huihong Liao Automotive Engineering    2023, 45 (7): 1263-1275.   DOI: 10.19562/j.chinasae.qcgc.2023.07.017 Abstract （121）   HTML （8）    PDF（pc） （7302KB）（346）       Knowledge map    For the durability development problem of an vehicle with super-size integral die casing aluminum alloy rear end body， the E-N data of the cast aluminum alloy for the die casting body is tested and the key parameters of die-casting alloy E-N curve are obtained by fitting the experimental measured data of fatigue samples. Finite element model of Trim body is built and the dynamic stress response of the die casting body is calculated based on the modal transient method. Rain flow statistics is carried out to the stress time history response signal. Combined with the measured material E-N curve and Miner’s damage accumulation principle.， the body fatigue damage of initial design and optimized design are analyzed and compared. Finally， the optimized integral die casting part is loaded into the vehicle for the four-column strengthening durability test. The investigation results show that the E-N relation curve of die casting aluminum alloy can be described by Manson-Coffin-Basquin equation. Compared with the original design， the maximum damage of the improved integrated die casting aluminum alloy body is reduced from 2.67 to 0.32， and the risk of fatigue cracking is eliminated. No cracks are found in the body after the reinforced four-column endurance experiment verification. The research results can provide a reference for the development of integral die-cast aluminum alloy body to achieve the goal of vehicle durability properties. Table and Figures | Reference | Related Articles | Metrics

Select

Pedestrian Crossing Intention Prediction Method Based on Multimodal Feature Fusion Long Chen,Chen Yang,Yingfeng Cai,Hai Wang,Yicheng Li Automotive Engineering    2023, 45 (10): 1779-1790.   DOI: 10.19562/j.chinasae.qcgc.2023.10.001 Abstract （305）   HTML （34）    PDF（pc） （4689KB）（325）       Knowledge map    Pedestrian behavior prediction is one of the main challenges faced by urban environment intelligent vehicle decision planning system. It is of great significance to improve the prediction accuracy of pedestrian crossing intention for driving safety. In view of the problems that the existing methods rely too much on the location information of pedestrian boundary box， and rarely consider the environmental information in traffic scenes and the interaction between traffic objects， a pedestrian crossing intention prediction method based on multi-modal feature fusion is proposed. In this paper， a new global scene context information extraction module and a local scene spatiotemporal feature extraction module are constructed by combining multiple attention mechanisms to enhance its ability to extract spatiotemporal features of the scene around the vehicle， and rely on the semantic analysis results of the scene to capture the interaction between pedestrians and their surroundings， which solves the problem of insufficient application of the interactive information between the context information of the traffic environment and the traffic objects. In addition， a multimodal feature fusion module based on hybrid fusion strategy is designed in this paper， which realizes the joint reasoning of visual features and motion features according to the complexity of different information sources， and provides reliable information for pedestrian crossing intention prediction module. The test based on JAAD dataset shows that the prediction accuracy of the proposed method is 0.84， which is 10.5 % higher than that of the baseline method. Compared with existing models of the same type， the proposed method has the best comprehensive performance and has a wider application scenario. Table and Figures | Reference | Related Articles | Metrics

Select

Research on the Preheating Strategy of Lithium Batteries Under Subzero Temperature for Electric Vehicles Qiao Xue,Junqiu Li,Yansheng Xiao,Yu Zhao,Yu Liu,Dongxue Han Automotive Engineering    2023, 45 (11): 2014-2022.   DOI: 10.19562/j.chinasae.qcgc.2023.11.003 Abstract （194）   HTML （31）    PDF（pc） （3022KB）（314）       Knowledge map    To improve the driving range of electric vehicles under low temperatures， a battery pack heating strategy based on the optimization of heating target temperature is proposed in this paper， which can effectively enhance the battery energy efficiency to achieve the driving requirement under low temperature. Firstly， the maximum discharge capacity of the battery at different temperatures is determined by the experiment test. Secondly， based on the energy retention rate of the battery at different temperatures and considering the influence of temperature on the battery life， a nonlinear multi-objective constraint function is established and solved to obtain the optimal heating target temperature of the battery under different ambient temperatures and different SOC. Finally， the heating strategy is validated via simulation of the physical model calibrated with real world vehicle experiment data. The experimental results show that the vehicle driving range based on the optimized battery heating target temperature increases maximumly by 8.41% and 4.77% respectively at the initial temperature of -15 and -5 ℃， indicating the proposed method can effectively improve the driving range of electric vehicles at low temperature. Table and Figures | Reference | Related Articles | Metrics

Select

Predictive Cruise and Lane-Changing Decision for Platoon Based on Cloud Control System Run Mei,Duanfeng Chu,Bolin Gao,Keqiang Li,Wei Cong,Chaoyi Chen Automotive Engineering    2023, 45 (8): 1299-1308.   DOI: 10.19562/j.chinasae.qcgc.2023.08.001 Abstract （307）   HTML （35）    PDF（pc） （1638KB）（299）       Knowledge map    The predictive cruise and lane-changing decision method for platoon based on cloud control system is proposed in this paper to improve the safety， economy， efficiency and smoothness of platoon. This method obtains dynamic traffic information through roadside infrastructure and uploads it to the cloud platform， which uses the predictive model to estimate the future state of environmental vehicles. The penalty of different actions of the platoon is reflected in the objective function， by minimizing which the longitudinal acceleration and lateral lane-changing decision sequence are optimized synergistically， with the decision results sent to the vehicle for tracking and control. Sumo and Matlab are used to establish the simulation environment， and five sets of simulation conditions with different traffic flows are designed. The simulation results show that compared to the microscopic driving model （IDM+MOBIL）， the platoon with the proposed method can reduce the collision risk during cruise by 42.2% and the collision risk during lane change by 3.41%， with an average fuel saving rate of 1.22%， an increase of speed by 0.83%， and smoothness by 49.84%， better than the microscopic driving model in safety， economy， efficiency and smoothness. Table and Figures | Reference | Related Articles | Metrics

Select

An Overview of Intrusion Detection Methods for In-Vehicle CAN Network of Intelligent Networked Vehicles Yuxin Guan,Haojie Ji,Zhe Cui,He Li,Liwen Chen Automotive Engineering    2023, 45 (6): 922-935.   DOI: 10.19562/j.chinasae.qcgc.2023.ep.002 Accepted: 17 March 2023 Online available: 17 March 2023 Abstract （319）   HTML （20）    PDF（pc） （2564KB）（297）       Knowledge map    With the continuous integration of intelligent vehicle and vehicle networking technology， vehicles are developing towards intelligence and networking. As the complexity of in-vehicle network （e.g. CAN network） increases and the way in which vehicles are connected to the outside world increases， the cyber security risks faced by automobiles have risen dramatically. As an important barrier to protect vehicle network security， intrusion detection system can effectively detect external intrusion and abnormal vehicle behavior. Firstly， the security properties of the in-vehicle network are introduced， and the network security issues of the ICV， the vulnerability of the in-vehicle CAN network and the attack modes on it are analyzed. Secondly， the status quo of research on vehicle CAN network intrusion detection methods in recent years is summarized. Finally， several open questions are proposed for the future development of the in-vehicle network intrusion detection system. 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

Research on Motion Planning and Cooperative Control for Autonomous Vehicles with Lane Change Gaming Maneuvers Under the Curved Road Cheng Lin, Bowen Wang, Lü Peiyuan, Xinle Gong, Xiao Yu Automotive Engineering    2023, 45 (7): 1099-1111.   DOI: 10.19562/j.chinasae.qcgc.2023.07.001 Abstract （270）   HTML （20）    PDF（pc） （8385KB）（293）       Knowledge map    When multiple autonomous vehicles perform lane change and merging tasks on structured road， steering and merging actions need to be comprehensively considered to avoid potential accidents. Meanwhile， the changing road curvature and surrounding vehicle speed also increase the difficulty of cooperative control. Focusing on the above issues， this paper proposes a multi-vehicle lane change gaming motion planning and cooperative control method facing variable curvature road. Firstly， a multi-vehicle model in curvature coordinate system is developed to determine the inter-vehicle safety distance and dynamics state. Then， by systematically considering the road curvature variation and surrounding vehicle information， a game-based multi-vehicle lane change motion planning algorithm is proposed， which uses a distributed framework to quickly solve the optimal speed trajectory and lane change timing considering personalized driving. Finally， the road curvature and planning trajectory are identified effectively based on B-sample curve， and an adaptive time-varying model predictive control algorithm is constructed to achieve trajectory tracking. Specifically， the control parameters are updated in real time under the single-step prediction domain to eliminate the control deviations caused by frequently various vehicle speed and curvature. The co-simulation results show that the proposed method can reduce the tracking error by 58% compared to the Stanley method， with reduction of the merging time by 74% compared to the cooperative adaptive cruise control method. Moreover， the computational solution efficiency is only 10% of the centralized method. Table and Figures | Reference | Related Articles | Metrics

Select

Vehicle Trajectory Tracking Control Based on Road Adhesion Coefficient Estimation Yunfei Zha,Lü Xiaolong,Huiqin Chen,Yingchun Yi,Yanyan Wang Automotive Engineering    2023, 45 (6): 1010-1021.   DOI: 10.19562/j.chinasae.qcgc.2023.06.011 Abstract （235）   HTML （10）    PDF（pc） （6437KB）（289）       Knowledge map    For the trajectory tracking control problem of vehicles under high speed steering and different road adhesion coefficients， a variable sideslip angle constrained MPC control strategy is proposed based on model predictive control theory considering road adhesion coefficients. According to the magic formula tire model， the tire cornering property as well as the influence of different adhesion coefficients on the tire slip angle-lateral force linear region is analysed. Then the function relationship between tire slip angle constraint and different road adhesion coefficients is established. The genetic algorithm （GA） is used to optimize the BP neural network model to design the road adhesion coefficient estimator， and the estimation results are transmitted to the MPC controller as variables related to the tire slip constraint. Finally， the system control quantity constraint， the control increment constraint， and the variable sideslip angle constraint considering the road adhesion coefficient are established in the MPC controller. The trajectory tracking problem under different road adhesion conditions is transformed into the optimal value solution problem under various constraints to realize trajectory tracking and vehicle stability control. The simulation and experimental results show that the MPC control method considering the change of road adhesion coefficient has higher trajectory tracking accuracy and better vehicle stability than the traditional MPC control method under various working conditions， with high estimation accuracy of the GA-BP neural network road coefficient estimation method. Table and Figures | 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

Research Progress on Key Technologies of Basic Software and Hardware for Intelligent New Energy Vehicle Onboard Control Zhaolin Li,Huawei Li,Sifa Zheng,Wenwei Wang,Guangcai Zou,Chuang Zhang,Ying Liu,Yongchang Zhang Automotive Engineering    2023, 45 (9): 1530-1542.   DOI: 10.19562/j.chinasae.qcgc.2023.09.003 Abstract （223）   HTML （13）    PDF（pc） （6274KB）（274）       Knowledge map    The intelligence and networking of new energy vehicles have put forward higher requirements for the basic software and hardware of vehicle on-board control including core control chips， operating systems and networks， which must meet disruptive needs such as high-performance computing， high security control and big data communication. Focusing on the high reliability and safety design requirements of vehicle core control chips， vehicle control operating systems， and high-speed distributed fiber optic communication in vehicles， this paper introduces the latest research on key technologies of the architecture of vehicle control operating systems and vehicle core control chips that support intelligent control algorithms under complex driving conditions， the high reliability design technology and environmental adaptability enhancement technology of vehicle core control chips under harsh working conditions， functional safety design and guarantee technology for vehicle control operating system and onboard core control chip， control signal transmission tool based on high-speed distributed fiber optic communication technology， and communication protocol fault diagnosis and self testing technology. Based on the above research results， the independently developed vehicle core control chip and vehicle control operating system have all passed practical vehicle verification. The established research and development system for technology breakthrough， product development， standard formulation， and practical vehicle verification can provide necessary theoretical and technical support for the complete autonomy and controllability of the basic software and hardware of intelligent new energy vehicle on-board control in China. Table and Figures | Reference | Related Articles | Metrics

Select

A Motion Planning Method for Autonomous Vehicles Considering Prediction Risk Ming Wang,Xiaolin Tang,Kai Yang,Guofa Li,Xiaosong Hu Automotive Engineering    2023, 45 (8): 1362-1372.   DOI: 10.19562/j.chinasae.qcgc.2023.08.007 Abstract （149）   HTML （15）    PDF（pc） （4092KB）（263）       Knowledge map    In this paper， a motion planning method for autonomous vehicles considering prediction risk is proposed， which is based on the model predictive control algorithm while incorporating interactive prediction of the future trajectories of surrounding vehicles and the risks. Firstly， the interaction between the vehicles is modeled as a graph structure， which is then used to construct an interaction-aware motion prediction module. Then multiple prediction models with isomorphic and different parameters are trained and ensemble technology is used to obtain the uncertainty risk of the prediction network for the prediction results. The model predictive control algorithm is then applied to deal with the risk based on the obtained prediction algorithm uncertainty risk. By comprehensively considering the safety constraints， and vehicle physical property constraints in the optimization problem constraints， a motion planning method for autonomous driving considering the risk of prediction uncertainty is designed. Finally， the motion prediction capability of the established prediction model， the effectiveness of motion planning approach based on model predictive control， and the capability of motion planning to deal with prediction risks are verified based on real driving data set and SUMO simulation platform. The simulation results show that the motion planning method proposed in this paper is capable of sensing the uncertain risks posed by the prediction algorithm while acting to mitigate those risks when confronted with scenarios of high risk of prediction， such as the emergency acceleration and deceleration of nearby vehicles， which can increase the safety of road driving. Table and Figures | Reference | Related Articles | Metrics

Select

Review on Power Battery Safety Warning Strategy in Electric Vehicles Da Li,Junjun Deng,Zhaosheng Zhang,Peng Liu,Zhenpo Wang Automotive Engineering    2023, 45 (8): 1392-1407.   DOI: 10.19562/j.chinasae.qcgc.2023.08.010 Abstract （211）   HTML （14）    PDF（pc） （1940KB）（263）       Knowledge map    Battery safety has become an important issue restricting the development of electric vehicles. Accurate and timely battery safety warning can ensure the safety of occupants' life and property and improve the safety level of electric vehicles. A comprehensive review on the battery safety warning strategies in electric vehicles is conducted in this paper. Firstly， the definition of battery safety state is reviewed， and the framework of this review is proposed. Then， the battery safety characteristics and safety influencing factors analysis， battery-modeling methods， battery safety risk assessment/prediction methods are reviewed in detail. The advantages and disadvantages of different methods are summarized. Finally， the achievements and deficiencies of existing researches are summarized， and the development trend of battery safety warning technology in electric vehicle is proposed， including the new sensor technology， multi-factor integrated battery safety warning method and "terminal-side-cloud " battery safety warning system. This review provides a reference for further research on the safety warning strategy of electric vehicle battery. Table and Figures | Reference | Related Articles | Metrics