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Table of Content

    25 February 2024, Volume 46 Issue 2 Previous Issue   
    Current Status and Trend of Automotive Safety Procedures/Programs
    Lin Hu,Ziyi Gu,Danqi Wang,Fang Wang,Tiefang Zou,Jing Huang
    2024, 46 (2):  187-200.  doi: 10.19562/j.chinasae.qcgc.2024.02.001
    Abstract ( 321 )   HTML ( 30 )   PDF (1854KB) ( 294 )   Save

    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.

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    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
    2024, 46 (2):  201-210.  doi: 10.19562/j.chinasae.qcgc.2024.02.002
    Abstract ( 179 )   HTML ( 24 )   PDF (4054KB) ( 211 )   Save

    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.

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    Decision-Making for Autonomous Driving in Uncertain Environment
    Xinke Fu,Yingfeng Cai,Long Chen,Hai Wang,Qingchao Liu
    2024, 46 (2):  211-221.  doi: 10.19562/j.chinasae.qcgc.2024.02.003
    Abstract ( 165 )   HTML ( 17 )   PDF (2036KB) ( 244 )   Save

    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.

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    Two-Stage Multimodal Fusion Networks Based on Virtual Point Clouds
    Teng Cheng,Hao Ni,Qiang Zhang,Wenchong Wang,Qin Shi
    2024, 46 (2):  222-229.  doi: 10.19562/j.chinasae.qcgc.2024.02.004
    Abstract ( 56 )   HTML ( 5 )   PDF (2104KB) ( 42 )   Save

    To address the impact of sparsity and disorder of point clouds on target detection accuracy, a two-stage multimodal fusion network VPC-VoxelNet based on virtual point clouds is proposed in this paper. Firstly, virtual point clouds are constructed using image detection target information to increase the density of point clouds, thus improving the performance of target features. Secondly, the dimensionality of point cloud features is increased to distinguish real and virtual point clouds, and a voxel with confidence encoding is used to enhance the correlation of point clouds. Finally, the scale factor of the virtual point clouds is adopted to design the loss function to increase the supervised training of image detection and improve the training efficiency of the two-stage network, and avoid the cumulative model error problem of the two-stage end-to-end network model. The target detection network, VPC-VoxelNet, is tested on the KITTI dataset, and the detection accuracy is better than that of the classical 3-dimensional point cloud detection network and certain multi-sensor information fusion networks, with a vehicle detection accuracy of 86.9%.

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    Extraction and Application of Key Utility Term for Social Driving Interaction
    Xiaocong Zhao,Shiyu Fang,Zirui Li,Jian Sun
    2024, 46 (2):  230-240.  doi: 10.19562/j.chinasae.qcgc.2024.02.005
    Abstract ( 81 )   HTML ( 8 )   PDF (2589KB) ( 69 )   Save

    In shared road space, human driving interaction behavior has the social characteristics of considering the impact on surrounding vehicles. Lacking the understanding of such social characteristics, autonomous vehicles often struggle to estimate the potential impact of their behavior on surrounding vehicles, thus falling into over conservativeness of decision-making dilemma. A game-theory-based social driving interaction model is constructed by introducing in the behavioral characteristics of drivers considering the impact on surrounding vehicles to capture the action dependencies among road users. With this model, a generalized measurement, utility term of interaction activeness (UTIA), is proposed to quantify the potential impact of the host vehicle's anticipated behavior on its interactants. By introducing the UTIA into the planning objective, the interaction activeness of motion planning algorithm can be directionally adjusted. The results of highway exit experiments show that without compromising safety, enhancing interaction activeness can improve the success rate of the exit task within a given distance by 3.9% and 5.2% for optimization-based and sampling-based motion planning algorithm, respectively.

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    Multi-lane Trajectory Optimization for Intelligent Connected Vehicles in Urban Road Network
    Pangwei Wang,Cheng Liu,Yunfeng Wang,Mingfang Zhang
    2024, 46 (2):  241-252.  doi: 10.19562/j.chinasae.qcgc.2024.02.006
    Abstract ( 124 )   HTML ( 10 )   PDF (5271KB) ( 88 )   Save

    In order to improve the traffic efficiency and fuel utilization efficiency of intelligent connected vehicles (ICVs) under urban traffic networks, a multilane spatiotemporal trajectory optimization method is proposed in this paper. Firstly, the state and constraints of the ICVs are defined based on the multi-lane spatiotemporal position relationship and the compound optimization model of spatiotemporal trajectory is constructed by considering the traffic efficiency and fuel economy, which is solved by the Pontryagin Maximum algorithm. Furthermore, the rules of cooperative lane change are designed to obtain the optimal lane change strategy by Q-learning algorithm. Finally, the SUMO/Python co-simulation tests show that the method can effectively improve the traffic efficiency under different vehicle saturation levels, split allocation, and minimum traffic speed conditions, with great improvement of fuel efficiency.

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    Modeling on the Penetration Rate of China's Commercial Vehicle Market: Taking Heavy-Duty Long-Haul Trucks as an Example
    Xu Hao,Xiantao Lu,Jing Yang,Yali Zheng,Hewu Wang
    2024, 46 (2):  253-259.  doi: 10.19562/j.chinasae.qcgc.2024.02.007
    Abstract ( 70 )   HTML ( 4 )   PDF (1265KB) ( 61 )   Save

    Carbon reduction in commercial vehicles has become a key bottleneck in reducing carbon emission in China's road transportation. New energy commercial vehicles are seen as an important way to reduce carbon emission in heavy commercial vehicles, but the market penetration rate of new energy commercial vehicles is much lower than that of other vehicle sectors. However, at present, the development of new energy zero-emission commercial vehicles still faces significant bottlenecks such as complex application scenarios, diversified technological paths, and high cost. This study constructs a Discrete Choice-based Market Evolution of Green Truck Model (DC-MEGT), a multi-dimensional Logit discrete choice model based on factors such as the total cost of ownership (TCO) and ease of use of new energy vehicles. TCO is calculated using a bottom-up approach, and the usage convenience is quantified and monetized by supplementary energy time cost. A comprehensive utility function is constructed to predict and analyze the market penetration rate evolution of different power types, such as pure electric vehicles, fuel cell vehicles, and zero-emission fuels from the present to 2060. The study analyzes the heavy-duty long-haul towing scenario as an example and finds that the main technology paths in 2060 include fuel cell vehicles, pure electric vehicles, natural gas vehicles, and diesel vehicles, accounting for 48%, 28%, 12%, and 10%, respectively. If the uncertainty of different factors such as policy promotion, technological progress, and business models is taken into account, the market share of pure electric vehicles and fuel cell vehicles in 2060 may fluctuate by 17% ~ 19%.

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    Research on Fuel Cell Cold Start Strategy Based on Single Cell Impedance Consistency Purging
    Weifeng Kong,Chuan Fang,Jihong Liu,Jianqiu Li,Feiqiang Li,Shengtao Huang,Xingwang Zhao,Yan Shi,Dian Yuan,Liangfei Xu,Peng Sun,Enfei Zhou,Minggao Ouyang
    2024, 46 (2):  260-268.  doi: 10.19562/j.chinasae.qcgc.2024.02.008
    Abstract ( 62 )   HTML ( 0 )   PDF (2963KB) ( 69 )   Save

    The weak cold-start capability of fuel cells with graphite plates for vehicles is an important bottleneck that affects the large-scale promotion of fuel cell vehicles in the cold regions of northern China. Starvation self-heating is a common cold-start strategy whose basic principle is to increase overpotential by reducing the supply rate of reactants, and generate a large amount of heat inside the cell in a short period of time to achieve rapid heating. This approach is simple, but it requires a high degree of consistency in the initial water content of the stack monomers and is prone to single-chip reverse polarity and excess hydrogen concentration emission, which can affect the safety and durability of the fuel cell. To solve the above problems, the research group has developed a multi-channel AC impedance measurement device, proposed an optimized purging strategy for single cell impedance consistency, and established a constant voltage and variable air flow control method for cold-start of fuel cells, to achieve multi-objective and multi-parameter coupled coordinated control that provides high heat production, high safety, and high dynamics for voltage, current, and inlet/outlet air flow in the low-temperature start transient process. The bench test results show that the maximum impedance deviation of fuel cells is decreased from 0.7 to less than 0.2 mΩ, and the fuel cell engine system can achieve a fast start at -40 ℃ within 124 s, with good repeatability. The relevant technology is applied in the fuel cell demonstration at the 2022 Winter Olympics, with its effectiveness verified.

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    Impedance Spectroscopy and Characteristic Frequency Analysis of the PEMFC Cold Start Process
    A’ bang Tao,Jianjian Tao,Xuezhe Wei
    2024, 46 (2):  269-280.  doi: 10.19562/j.chinasae.qcgc.2024.02.009
    Abstract ( 83 )   HTML ( 4 )   PDF (5440KB) ( 85 )   Save

    In order to optimize the cold start process of PEMFC, it is essential to provide sufficient feedback data. Common impedance spectroscopy and equivalent circuits cannot provide sufficient and real-time feedback due to long acquisition period. Therefore, the cold start impedance model is developed in COMSOL, and the change of impedance spectroscopy is analyzed in combination with experiments. The characteristic frequencies of 1kHz, 50Hz and 1Hz are proposed in the high, medium and low frequency ranges respectively to characterize the cold start process of the fuel cell. The results show the above characteristic frequencies vary significantly in the pre-, mid- and post-cold start phases, with the change in impedance at characteristic frequencies of 1 kHz, 50Hz and 1Hz of 0.38, 0.31 and 1.47 respectively. It improves the real-time performance of data acquisition while retaining feature information compared to obtaining the full impedance spectroscopy and fitting the equivalent circuit. Therefore, the impedance at the characteristic frequency points can be used to characterize the cold start process, which provides real-time monitoring for the internal state of the cold start.

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    Research on Non-Current-Sensor Control of Permanent Magnet Synchronous Motor for Vehicle
    Nianzhong Zhang,Qiang Song,Guanfeng Wang,Mingsheng Wang
    2024, 46 (2):  281-289.  doi: 10.19562/j.chinasae.qcgc.2024.02.010
    Abstract ( 79 )   HTML ( 7 )   PDF (4141KB) ( 72 )   Save

    In view of the complex and changeable vehicle environment of electric vehicles, which affects the measurement accuracy of current sensors, and the worse situation will lead to the failure of one-phase or multi-phase current sensors in the motor drive system, therefore, a non-current-sensor control algorithm based on extended Kalman filter is proposed in this paper. The stator current of the motor is reconstructed by using the stator voltage, rotor position and speed information of the permanent magnet synchronous motor, and the feed forward compensation is designed to improve the dynamic performance of the system regarding the system delay caused by the non-current-sensor algorithm. The acceleration and deceleration and robustness tests of the proposed algorithm are carried out. The effectiveness of the proposed method is verified by the simulation and experimental results.

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    Research on Lightweight Design of CTB Battery Pack Cover Assembly Based on VRB/OW-GFRP Hybrid Structure
    Libin Duan,Yu Zhang,Zhanpeng Du,Yegang Liu,Xiangxin Meng,Guannan Tian,Haiyang Zheng,Chuang Wu
    2024, 46 (2):  290-299.  doi: 10.19562/j.chinasae.qcgc.2024.02.011
    Abstract ( 64 )   HTML ( 0 )   PDF (5278KB) ( 74 )   Save

    Cell to body (CTB) is a key technology to improve the endurance mileage of electric vehicles. The VRB/OW-GFRP hybrid structure formed by the variable-thickness rolled blanks (VRB) structure and the orthotropic woven GFRP (OW-GFRP) through the bonding process is an innovative structure, which can reduce the weight of the CTB battery pack, thus improve the endurance mileage of electric vehicles. Taking an electric vehicle as the research object, a CTB battery body integrated structure is designed to realize the integration of the upper cover of the battery pack and the floor of car body. Furthermore, the cover assembly of the uniform thickness (UT) CTB battery pack are replaced by the VRB structure, UT/OW-GFRP and VRB/OW-GFRP hybrid structure. The lightweight design of the upper cover assembly of the three types of CTB battery pack are carried out based on the multi-stage optimization method. The results show that the weight of VRB structure is reduced by 6.4% compared with that of UT structure when the stiffness performance of the CTB battery pack is met. The lightweight level of the upper cover assembly of the CTB battery pack based on the VRB/OW-GFRP hybrid structure is about three times that of the metal structure, with the weight of the VRB/OW-GFRP reduced further by 4.2% compared with that of the UT/OW-GFRP hybrid battery pack upper cover assembly. Thus, the VRB/OW-GFRP hybrid structure is the inevitable trend of the development of automotive lightweight technology in the future, showing a great application prospect in CTB battery pack cover assembly.

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    Efficient Group Key Distribution Scheme Based on Quantum Random Numbers in VANETs
    Qin Shi,Liu Shan,Teng Cheng,Qiang Liu,Chuansu Wang,Xing Zhang
    2024, 46 (2):  300-309.  doi: 10.19562/j.chinasae.qcgc.2024.02.012
    Abstract ( 41 )   HTML ( 1 )   PDF (3441KB) ( 44 )   Save

    To address the problem of high communication overhead and low security of key distribution in the near-field communication of VANETs, an efficient quantum group key distribution scheme based on quantum random numbers is proposed in this paper. In this scheme, Firstly, the anonymous credentials of the vehicle are jointly generated by quantum random numbers at the vehicle side and the cloud side, and zero-knowledge proof is used to achieve mutual identity recognition between the vehicle and the road side, which protects the privacy of the vehicle. Then, a two-stage group key achieves the update of the group key, i.e. two key parameters at the roadside and the cloud side. The group key reduces the signaling overhead by half and greatly shortens the group key issuance time while ensuring forward and backward security. Finally, the security of the scheme is demonstrated by security analysis and performance analysis.

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    A Comparative Study on Performance Between Single-motor and Dual-motor Electric-Drive Mechanical Transmission
    Ziwang Lu,Guangyu Tian,Runfeng Li,Wenfei Ji,Yiwen Sun,Yunchang Yu
    2024, 46 (2):  310-319.  doi: 10.19562/j.chinasae.qcgc.2024.02.013
    Abstract ( 55 )   HTML ( 3 )   PDF (5586KB) ( 40 )   Save

    A dual-motor non-synchronizer multi-gear mechanical transmission system can effectively improve the energy economy and power performance of heavy-duty commercial vehicles. In order to analyze the optimal performance of the system under the optimal parameters, and to consider the effect of vehicle weight and differences between no load and full load, this study optimizes both the drive motor parameters and mechanical transmission speed ratio parameters, and compares the energy economy and power performance of the single/dual-motor multi-gear mechanical transmission system under the optimal parameters. The results show that the dual-motor drive system reduces the sensitivity of the vehicle energy economy to the difference in vehicle weight and no/full load, with the maximum speed of the dual-motor drive system increased by about 8%, and the acceleration time saved by about 28%.

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    Optimization Design of Micro-texture on the Surface of Friction Plate in High-Speed Wet Clutch
    Lin Zhang,Hua Meng,Yu Feng,Xiaolong Zhao,Chao Wei,Yunbing Yan
    2024, 46 (2):  320-328.  doi: 10.19562/j.chinasae.qcgc.2024.02.014
    Abstract ( 76 )   HTML ( 0 )   PDF (3338KB) ( 110 )   Save

    The wet clutch is the core component of the vehicle transmission system. It is prone to rub-impact between the friction plate and steel plate during high-speed separation, resulting in a sharp increase in drag torque, and affecting its transmission efficiency and reliability. Therefore, in this paper, to reduce the rub-impact drag torque in high-speed wet clutch, the micro-texture on the surface of the friction plate is optimally designed. Firstly, a parameterized modeling method of arbitrary micro-texture shape lines on the surface of friction plate is proposed. Then the number, depth, circumferential proportion, radial proportion and shape line parameters of the micro-texture are selected to construct the design variables, constraint conditions and optimal objective function for micro-texture optimization. By combining the experiment design method, approximation modeling simulation and global search optimization method, an optimal design model of micro-texture on the surface of friction plate is established. Finally, a comparison test of drag torque before and after micro-texture optimization is carried out. The results show that the optimized micro-texture can significantly reduce the rub-impact drag torque at high circumferential speed, and greatly delay the critical speed at which the rub-impact phenomenon of friction pair occurs.

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    Research on Prediction Model and Assessment Parameters of Head Injury for Child Occupants Based on BP Neural Network
    Yanxin Wang,Haiyan Li,Shihai Cui,Lijuan He,Lü Wenle
    2024, 46 (2):  329-336.  doi: 10.19562/j.chinasae.qcgc.2024.02.015
    Abstract ( 79 )   HTML ( 2 )   PDF (3129KB) ( 66 )   Save

    The promotion of intelligent cockpit and virtual testing protocols bring new challenge to assess the occupant injury, with the injury mechanism and injury risk assessment parameters more diversified. Based on the TUST IBMs 6YO-O and the BP neural network algorithm, a predictive model for the correlation between occupant sitting angle and head injury indicators in frontal 100% overlapping rigid barrier condition is constructed in this paper, and the correlation and difference between evaluation indicators with the different seating postures are explored. The results show that the constructed correlation injury prediction model has high reliabilities (R2 > 0.90), which can be used for injury prediction and analysis. Existing head injury evaluation indicators have good consistency in the small angle range (95°~108°), but for the occupants with larger seating postures, there are significant differences to assess the head injury risks using different injury evaluation indicators. Therefore, there is certain limitation of the head injury assessment parameters implemented currently. In the future virtual testing, the kinematic and biomechanical parameters should be integrated to assess more comprehensively for the head injury risks. The research results can provide data and theoretical support for the improvement of child restraint systems, virtual testing, and selection of head injury evaluation parameters for occupants with larger seating postures.

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    Research on NVH Control Technology of Heat Pump System in Hybrid Electric Vehicles
    Tonghang Zhao,Junguang Wang,Shudong Tian,Xiangzhen Chen
    2024, 46 (2):  337-345.  doi: 10.19562/j.chinasae.qcgc.2024.02.016
    Abstract ( 93 )   HTML ( 8 )   PDF (5290KB) ( 95 )   Save

    The vibration and noise performance of the heat pump system plays an important role in the NVH evaluation of new energy vehicles. Based on the structure and working characteristics of the heat pump system and the principles of vehicle vibration and noise control, a research on the NVH control methods of the heat pump system is carried out in this paper from the vibration and noise excitation source, structural mode distribution, transfer path, evaluation conditions and other dimensions. Through the analysis and solution of NVH problems in the product development of a domestic hybrid electric car, the results indicate that the NVH control of heat pump system is a system engineering, and the compressor, air conditioning pipeline, HVAC shell, acoustic package and compressor control strategy are key factors of NVH, which provides a clear technical reference for the NVH performance control of new energy vehicle heat pump systems.

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    High-Performance Acquisition for Vehicle Sideslip Angle Based on Switch Strategy
    Jianfeng Chen,Qiang Wu,Xinyuan Ge,Jingbo Zhao
    2024, 46 (2):  346-355.  doi: 10.19562/j.chinasae.qcgc.2024.02.017
    Abstract ( 77 )   HTML ( 4 )   PDF (5053KB) ( 57 )   Save

    For the existing acquisition method of vehicle sideslip angle (VSA) based on fusion strategy, optimization and improvement are required for different scenarios, structures or signals. As a result, the calculation complexity and system cost rise up. A soft-sensing method for the VSA based on switch strategy is proposed in this paper. In the pretreatment part for sensor measurement signals, the Bessel filter is employed to realize the delay processing and noise filtering of lateral acceleration signal, and a reliability test module is designed to effectively eliminate the mutations in the signals of yaw rate, et al. On this basis, the switch strategy is determined based on the advantages of the existing kinematic and dynamic schemes. For the presented strategy, the continuous operating intervals of the kinematic scheme are shortened in a great deal of effort to restrain the error accumulation, and the dynamic one is restricted in linear region to avoid performance degradation. Simulations and hardware-in-loop experiments are implemented in multiple conditions to verify the effect of the proposed method. The experimental results show that the proposed method in this paper has obvious advantages in accuracy and execution time compared to the one utilizing the classical fusion strategy. Moreover, they are both robust to the change of road conditions.

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    Optimization of Aerodynamic Drag Reduction and Its Flow-Field Mechanism for a Sport Utility Vehicle (SUV)
    Jingfeng Shao,Huihui Zuo,Xingjun Hu
    2024, 46 (2):  356-365.  doi: 10.19562/j.chinasae.qcgc.2024.02.018
    Abstract ( 85 )   HTML ( 7 )   PDF (4267KB) ( 78 )   Save

    To improve the fuel economy of vehicles, simulation and experiments are combined to improve the aerodynamic drag coefficient during driving, taking a certain SUV model as the research object. Firstly, wind tunnel tests are used to determine the areas or components that have significant impact on the overall aerodynamic drag of the vehicle. Secondly, optimizations are made to the components or areas with high contribution values to the air resistance coefficient. The results show that the front wheel deflectors, taillights and spoilers contribute greatly to the overall air resistance coefficient of the vehicle. The restyling of the front wheel deflectors effectively reduces the frontal pressure area and interference drag from the wheels. Optimizations on taillights and spoilers improve the rear negative pressure zone and shorten the reattachment distance of separated flows on the upper part of the rear window. Based on the intrinsic orthogonal decomposition method for extracting and analyzing local flow field information, it can be concluded that the first and second order modals mainly constitute the key flow states in the wake. Compared to the initial scheme, a drag reduction rate of 7.5% can be achieved by the optimized combination design, which is verified by tests and simulations. Theoretical basis and technical support are provided in this paper for restyling and model change of the next generation of SUV.

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    Research on Detection Method of Failure Defects of Rivet on Riveted Aluminum Alloy Plates
    Liang Liu,Ying Zhang,Chenyang Shi,Xinhua Zhao,Xianming Meng,Zengchang Liu
    2024, 46 (2):  366-374.  doi: 10.19562/j.chinasae.qcgc.2024.02.019
    Abstract ( 70 )   HTML ( 4 )   PDF (5356KB) ( 62 )   Save

    For the difficulties in feature extraction and low recognition rate in defect types and grades of rivet on aluminum alloy plates for car body, the diagnosis model and detection method for rivet failure defects are proposed based on the Gaussian convolutional deep belief network and long short-term memory network. Firstly, the specimens are designed for five types of fracture defects and an automatic detection system is constructed. The planned path and pose of the probe are set to lower lift-off effect on signals. Secondly, the dual network fusion diagnostic model is designed to extract and learn the multi-dimensional defect feature information, solving the problem of extracting defect information represented by temporal variation characteristics and spatial distribution state in detection curves. The experiments results show that the optimized model has an average recognition rate of 99.85%, with an increase of 14.54% compared with that of the traditional convolutional network and single deep belief network. The model has better compatibility and robustness, which can realize online diagnosis of internal defects of rivets.

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