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  • 2024, Vol. 15 No. 3 Published on:30 June 2024 Previous issue    Next issue
    Review, Progress and Prospects
    Advancements in the powertrain technology of hybrid electric vehicles in China
    XU Min, ZHANG Yijia
    2024, 15(3):  269-294.  doi:10.3969/j.issn.1674-8484.2024.03.001
    Abstract ( 627 )   HTML ( 77)   PDF (4532KB) ( 241 )  

    Driven by both national policies and market demand, Chinese automakers have achieved breakthroughs in hybrid powertrain technology since 2021. They have launched a range of hybrid electric vehicles tailored to the market demand and consumer preference in China, embodying distinct Chinese characteristics and leading globally in the field. Recently, the sales of hybrid electric vehicles have exploded. In 2023, sales of hybrid passenger cars in the Chinese market exceeded 3 million units, marking an 83% year-on-year increase. However, influenced by the electrification megatrend, there still exists the viewpoint in the automotive industry that hybrid electric vehicles are merely transitional technology. Some consumers are also skeptical about the domestic hybrid electric vehicles. To correct these biased perceptions, this paper explores China's hybrid vehicle powertrain technology routes, focuses on diversified hybrid architectures and dedicated core components, and introduces a novel definition for the degree of hybridization, serving as a generalized index for evaluating the level of electrification in powertrains. It compares the mainstream hybrid technologies both domestically and internationally, analyzes cutting-edge features and development trends. The research highlights that Chinese hybrid electric vehicles feature large-capacity power batteries and plug-in hybrid technology, allowing for flexible integration and agile synergies between power sources (engine and motor) and energy sources (power battery and range-extending system). Compared to internal combustion engine vehicles, hybrids enable focusing on improvement in engine thermal efficiency, engine operating efficiency, and overall fuel economy through electric drive integration. In contrast to battery electric vehicles, hybrids mitigate range anxiety cost-effectively by using the engine-generated electricity. They also achieve endurant and strong power output at lower hardware costs by leveraging mechanical drivetrain technologies such as engine driving and transmission torque amplification. These distinctive advantages position hybrid electric vehicles as pivotal in steering the automotive industry towards a carbon-neutral direction in the long term. The sharpened insight into today’s market and clarified vision of the future presented in the article could be beneficial to the further advancement of hybrid powertrain technology in China.

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    Development status and challenges of vehicle terminals in intelligent and connected environments
    ZHANG Yongsheng, LI Yizhou, WANG Liang, XU Zhigang
    2024, 15(3):  295-308.  doi:10.3969/j.issn.1674-8484.2024.03.002
    Abstract ( 376 )   HTML ( 50)   PDF (1636KB) ( 982 )  

    With the rapid advancement of intelligent connected technology, the functionalities of intelligent vehicular terminals equipped in connected vehicles have correspondingly expanded. After decades of development, these intelligent vehicular terminal systems have made significant progress in various domains and demonstrated substantial potential in the field of autonomous driving. This paper begins with the current status of intelligent vehicular terminals within the connected environment, describes the architecture of these systems, and reviews their evolutionary journey facilitated by intra-vehicle communication and vehicle-to-road cooperative empowerment. Furthermore, the paper delves into the profound impact of innovations in vehicular network wireless communication technology in the 5G era on the development of intelligent vehicular terminals. It also thoroughly reviews recent research achievements in cooperative driving and control, edge computing and fog computing, and digital twinning, while also anticipating the challenges these terminals face in information security and autonomous driving testing.

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    Automotive Safety
    Real-time human-like speed planning method for curve entry considering experienced driving behaviors
    CHEN Qitong, ZHAO Dong, LIU Congzhi, LI Liang
    2024, 15(3):  309-320.  doi:10.3969/j.issn.1674-8484.2024.03.003
    Abstract ( 186 )   HTML ( 17)   PDF (3984KB) ( 214 )  

    A human-like safe-speed-planning method was proposed for vehicle curve entry considering coasting and safe-speed based on the chaos theory and the real curve driving velocity data to improve the safety, the comfort and the travel efficiency of autonomous vehicles. A comfort mode and an efficiency mode were constructed through formulating the curve-entry speed-planning problem of autonomous vehicles as the multi-objective optimization problems. A singularity velocity was defined to simplify the constraint condition with high-order and non-linear characteristics and to improve its computation efficiency. The results show that both the lateral accelerations and the longitudinal accelerations satisfied the friction circle constraint for the proposed strategy, with guaranteeing the driving safety in different curve scenarios. Compared with the method regardless of coasting, the maximum longitudinal acceleration, which are generated by the proposed strategy, was reduced by 9.76% in the comfort mode with the travel efficiency being improved by 61.73%. In the efficiency mode, the longitudinal accelerations values are the acceleration threshold, which satisfy the acceleration constraint with an increase of 88% in traffic efficiency. Therefore, both the comfort mode and the efficiency mode achieve a balance between comfort and travel efficiency.

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    Black spot discrimination method for road traffic accidents based on spatiotemporal combination
    CHEN Chun, WANG Chenyu, ZHANG Daowen
    2024, 15(3):  321-328.  doi:10.3969/j.issn.1674-8484.2024.03.004
    Abstract ( 205 )   HTML ( 15)   PDF (1230KB) ( 547 )  

    A black spot discrimination method for road-traffic accidents was proposed based on spatiotemporal combination to improve the identification accuracy, and to assist the prevention and control of traffic accidents. The spatiotemporal overlap rate was used to measure the road danger degree; the cumulative frequency of the spatiotemporal overlap rate was fitted by using the hyperbolic tangent function; and the point corresponding to the fitted-function curvature minimum-radius was stipulated as the critical value; and the spatiotemporal composite points, which were larger than the critical value, were discriminated as the accident black spots; The traffic accident data collected by the Traffic Police Brigade of the Second Jurisdiction of the Chengnan (Chengdu-Nanchong) Expressway were utilized to conduct an example study. A total of 13 accident black spots was discriminated from 64 effective cases by utilizing the time-space composite method. The results show that the Crash Prediction Accuracy Index (CPAI) values are 2.29, 2.03, 2.03, 2.29, respectively for the accident frequency method, for the cumulative frequency curve method, the kernel density analysis method, and the spatiotemporal overlap rate method. It means that the spatiotemporal overlap rate method has good discriminatory accuracy. The spatiotemporal overlap rate method, which combines both spatial and temporal dimensions, increases the reliability of black spot discrimination.

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    Crashworthiness of auxetic structure reinforced by embedding tubes with negative Poisson’s ratio
    ZHOU Jianzhong, NIE Bingbing, SUN Huiming, HUANG Jian, WANG Liangmo, GAO Qiang
    2024, 15(3):  329-336.  doi:10.3969/j.issn.1674-8484.2024.03.005
    Abstract ( 159 )   HTML ( 10)   PDF (3802KB) ( 57 )  

    An enhanced structure with negative Poisson's ratio was proposed to improve the structural durability and achieve light-weighting of vehicles. The enhanced structural consisted of embedded tubes, which composed of thin-walled square tubes imbedded into double arrow lattice. The coupling effect between the negative Poisson's ratio structure and the embedded tubes was enhanced through the shrinking effect of negative Poisson's ratio. A finite element model of the enhanced structure was established with its accuracy being verified through compression tests. By using numerical methods, the durability performances of the double arrow lattice structure, the structure-filled tubes, and the enhanced structure with negative Poisson's ratio embedded tubes under axial loads were compared, and parameter analysis was conducted. The results show that the total absorbed energy of the enhanced structure is 1.12 MJ, an increase of about 40% compared to the double arrow lattice structure and filled tube structure; The specific energy absorption is 13.2 kJ, an increase of about 30%; The structure-filled tube structure with short beam angle of 70°, long beam angle of 40°, long beam thickness of 1.4~1.6 mm, and short beam thickness of 1.2 mm has greater specific energy absorption and smaller collision peak force; Increasing the thickness of embedded tubes significantly improves durability performance, but the structural mass increases sharply; The embedded tube thickness of around 1.2 mm meets the requirements of durability and light-weighting simultaneously.

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    Dimensionality reduction and reconstruction method of dummy biomechanics response based on adaptive autoencode
    HOU Zhiping, ZHU Haitao, LIU Cancan, YANG Jialin
    2024, 15(3):  337-343.  doi:10.3969/j.issn.1674-8484.2024.03.006
    Abstract ( 134 )   HTML ( 9)   PDF (1501KB) ( 88 )  

    A adaptive autoencoder was proposed to solve the problem of reducing and reconstructing the biomechanics response curve of collision dummy. The adaptive autoencoder method was constructed based on the standard autoencoder principle and the dummy biomechanics-response-curve characteristics with adding some constraints. The synthetic acceleration curve data were selected as sample data after data cleaning and sampling for the dummy-head gravity-center. The correlation number and the reconstruction mean square error of the standard autoencoder and the adaptive autoencoder are calculated; while the linear and nonlinear reduction and reconstruction ability were compared and verified for the adaptive autoencoder. The results show that the adaptive autoencoder has a reconstruction error of 2.6% for linear dimensionality and 2.4% for nonlinear dimensionality, while the covariance value is close to 0 for the low-dimensional data. Therefore, the adaptive autoencoder proposed in this paper implements linear and nonlinear dimensionality reduction and dimensionality reconstruction with a highly independent for the low-dimensional data.

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    Automotive Energy Efficiency and Environment Protection
    Lithium plating detection based on characteristic impedance and sliding t-test with multi-stage current fast charging
    HAO Zhenqi, WANG Xueyuan, LI Jiawei, DAI Haifeng, WEI Xuezhe
    2024, 15(3):  344-350.  doi:10.3969/j.issn.1674-8484.2024.03.007
    Abstract ( 149 )   HTML ( 9)   PDF (1315KB) ( 91 )  

    Under low temperature and high-rate charging, the graphite anode of lithium-ion battery will have a lithium plating phenomenon, which has a serious impact on the life and safety of the battery. An on-line detection method based on characteristic impedance and sliding t-test was proposed to realize the on-line detection of lithium plating of lithium-ion battery under variable current fast charge condition. The characteristic frequency impedance was measured in real time by superimposing 1 Hz sinusoidal excitation alternating current on the direct current charging. Based on the correlation between the change of the real part of characteristic impedance and the lithium plating of the negative electrode of the battery, an on-line detection method of lithium plating starting point based on sliding t-method was proposed for the fast-charging condition of variable current. The results show that this method can realize the delayed identification of the initial point of lithium plating within 5%SOC during the charging process, which is conducive to forming a closed-loop charging strategy and minimizing the harm of lithium plating.

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    Structural design and mass-transfer performances of a proton exchange membrane fuel cell with a traveling-wave flow-field
    ZHU Xinning, WANG Xi, LIU Rongkang, ZHU Siming, ZHANG Jianbo, ZHOU Wei
    2024, 15(3):  351-359.  doi:10.3969/j.issn.1674-8484.2024.03.008
    Abstract ( 113 )   HTML ( 4)   PDF (2631KB) ( 92 )  

    A traveling-wave flow-field plate with an arc concave surface was designed as an enhanced mass transfer structure to improve the mass transfer performances of the membrane electrode assembly (MEA) and to improve the power density of proton exchange membrane fuel cells (PEMFC). By combining milling technology, the manufacturing of traveling wave flow field structures has been achieved. Using computational fluid dynamics software, a three-dimensional model of the PEMFC was established, including the traveling wave flow field and MEA. The accuracy of the model was experimentally verified. Explored the distribution pattern of enhanced mass transfer structure on the internal velocity field, concentration field, and electric field of PEMFC, and analyzed the improvement effect of PEMFC performance. The results showed that compared with the conventional flow field with a channel 0.6 mm depth and 0.8 mm width, the average flow velocity of the traveling wave flow field in this article increased by 27.7%, the pressure loss decreased by 19.2%, the oxygen content at the interface between the flow field plate and MEA increased by 1.44%, the drainage rate at the outlet increased by 16.7%, and the power density increased by 8.6%.

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    Numerical simulation of the effects of nozzle geometry on the in-nozzle flow-characteristics of flash boiling sprays
    YIN Peng, XU Min
    2024, 15(3):  360-367.  doi:10.3969/j.issn.1674-8484.2024.03.009
    Abstract ( 110 )   HTML ( 3)   PDF (1618KB) ( 94 )  

    This paper investigated the influence of nozzle geometry on the in-nozzle flow and phase-change process of flash boiling sprays in the direct-injection gasoline-engine cars. A one-dimensional two-phase-flow model was developed based on the thermal non-equilibrium assumption to analyze the in-nozzle flow characteristics of the flash boing spray with different nozzle lengths, different diameters, different rounding angles at the inlet, and different taper angles. The model’s results were verified through the accuracy comparison with the previous experimental results by the authors' team. The results show that the longer the nozzle channel length, the smaller orifice diameter, and the more intense of the phase transition in nozzles, while the round corners at the nozzle entrance reduces the vapor generated inside nozzles. The convergent nozzle has a smaller pressure drop and the generation of vapor phase inside the nozzle is reduced accordingly, while the divergent nozzle increases the vapor generation rate. The different nozzle geometries change the pressure distribution and the velocity distribution in the nozzle. The pressure distribution governs the bubble growth rate, while the velocity distribution affects the bubble growth time, both of which ultimately affect the phase change characteristics within the nozzle.

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    Data-driven fault early warning of electric vehicle power battery based on ensemble learning from multiple dimensions
    WANG Jianjun, CHEN Hao, FU Yuancheng
    2024, 15(3):  368-378.  doi:10.3969/j.issn.1674-8484.2024.03.010
    Abstract ( 220 )   HTML ( 11)   PDF (2358KB) ( 149 )  

    Aiming at the problems such as poor performance of single algorithm on unbalanced data set and insufficient analysis dimension in electric vehicle power battery risk prediction, a data-driven multi-model ensemble learning method based on multi-dimensional characteristics was proposed to realize battery fault warning. According to internal and external factors, the features from battery information, driving condition, historical situation and time environment was extracted to simulate real application scenarios. To complete feature filtering, redundant information was removed by Filter-Wrapper method, which improved the robustness. The heterogeneous Stacking integrated model was constructed with SVM, LightGBM and XGBoost as primary learners and LR as secondary learners based on Bayesian optimization with grid search to optimize hyperparameters. The results show that the ensemble model with the addition of external features has the best comprehensive performance in the evaluation index, among which the recall rate in the medium and high level fault warning reaches 85.81% and 88.92%, respectively. Therefore, the method has better prediction accuracy and generalization ability than the single model that only considers the internal characteristics of the battery.

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    Preparation and performance of the PAN/UiO-66-NH2/Nafion composite nanofiber proton exchange membrane
    SUN Jingyi, HAN Dingbo, GE Jing, GUO Han, ZHANG Jianbo, LIU Yong
    2024, 15(3):  379-386.  doi:10.3969/j.issn.1674-8484.2024.03.011
    Abstract ( 95 )   HTML ( 2)   PDF (1835KB) ( 61 )  

    The proton conductivity of the proton exchange membrane in fuel cells sharply decreases under low humidity conditions, and the membrane also excessively swells under high humidity conditions, which becomes one of the limiting factors for the application of fuel cells. The polyacrylonitrile (PAN) nanofibers with the metal-organic framework (MOF) UiO-66-NH2 was combined to balance the relationship between the two and improve the dimensional stability of the membrane. And the effects of hydrolysis time and reaction temperature on the in-situ growth of UiO-66-NH2 on PAN nanofibers were investigated, followed by the preparation of functionalized nanofiber proton exchange membranes with MOF. The results show that the proton conductivity of the composite membrane has a maximum improvement of 175.36% compared to PAN/Nafion; at 60 °C, the swelling rate of the composite membrane is reduced by 179.10% compared to Nafion, which can effectively improve dimensional stability and mechanical strength, and has good development prospects.

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    A temporal allocation method of motor vehicle emission inventories
    WANG Jinping, FENG Haixia, ZHAO Huanhuan, HAN Guohua, HUO Miaomiao, SHI Qingli, Ning Er-wei
    2024, 15(3):  387-394.  doi:10.3969/j.issn.1674-8484.2024.03.012
    Abstract ( 77 )   HTML ( 2)   PDF (1407KB) ( 631 )  

    The time allocation model was improved and optimized to improve the accuracy of gridded vehicle emission inventory. Based on the congestion delay index, a new time allocation model was proposed by combining the congestion delay index which reflects the actual traffic conditions with the three-parameter traffic flow model, and Jinan city was taken as the test area for analysis and verification. The results show that the monthly, daily and hourly variation trends of pollutant emissions allocated by the time allocation model are consistent with those of the monitoring data. Based on the grid NO2 emission inventory allocated with the constructed model in this paper, the simulation effect of the Community Multiscale Air Quality Modle(CMAQ) has been significantly improved, and the normalized mean deviation and normalized mean error are reduced by about 21.6% and 23.7%, respectively. The proposed time allocation model reflects the actual traffic flow situation, makes up for the shortage of sample survey data, and conforms to the three-parameter traffic flow model, showing that it has important reference significance for the accurate control of vehicle emissions and pollution control.

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    Digital simulation of the ammonia replacement rate on the combustion and emission performances of diesel engine
    HU Shengqi, WANG Jie, CAI Yunkai, ZHU Neng
    2024, 15(3):  395-401.  doi:10.3969/j.issn.1674-8484.2024.03.013
    Abstract ( 125 )   HTML ( 3)   PDF (1434KB) ( 121 )  

    Introducing ammonia fuel into internal combustion engines is beneficial for reducing vehicle pollutant emissions. This article investigated the combustion quality and pollutant emission performance of diesel engines doped with ammonia. A three-dimensional engine cylinder digital simulation model was established for a commercial vehicle diesel engine by using the engine cylinder the Converge simulation analysis software to analyze the combustion and emission performance of five fuel groups with ammonia blending energy ratios of 0%~40%. The results show that the engine ignition delay period tends to extend with the increase of ammonia substitution rate; The combustion duration first shortens and then extends; And the average temperature and the pressure in the cylinder decreases; The CO, NO, and soot emissions are significantly reduced; The CO emissions decreases by 41.6%, the NO emissions decreases by 68.7%, and the soot emissions decreases by 17.2%, when the ammonia substitution rate is 40%. Therefore, adding ammonia to diesel engines for combustion can effectively reduce emission levels, but it is necessary to control the ammonia energy ratio within a reasonable range to prevent combustion deterioration.

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    Intelligent Driving and Intelligent Transportation
    Design and analysis of distributed controller for longitudinal platoon of networked vehicles under the bidirectional communication delay
    WANG Jingyao, HUANG Jiangshan, GUO Jinghua, LI Keqiang
    2024, 15(3):  402-412.  doi:10.3969/j.issn.1674-8484.2024.03.014
    Abstract ( 135 )   HTML ( 15)   PDF (2367KB) ( 113 )  

    The bidirectional communication delay in connected vehicle platoon systems can significantly impact the control performance of the platoon. In extreme cases, it may even result in instability or collisions. A cloud-based distributed control algorithm was proposed, fully considering the bidirectional communication delay between vehicles and the cloud. Under certain assumptions, the vehicle platoon under cloud control was modeled with sampled control system methods, leading to the unification of bidirectional communication delay. A state feedback distributed controller was designed using the Riccati inequality, and the Lyapunov-Razumikhin theorem was utilized to analyze the asymptotic stability of the control algorithm, establishing the relationship between the upper bound of time-varying delay and the communication topology and coupling gain. The results show that the existence of an optimal coupling gain maximizes the tolerated upper bound of delay, and the ratio of the maximum to minimum eigenvalues of the Laplacian matrix of the communication topology is negatively correlated with the upper bound.

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    Path tracking control of autonomous container trucks using angular compensation LQR
    CAO Liling, LIU Wei, DAI Kunpeng, ZHOU Guofeng
    2024, 15(3):  413-423.  doi:10.3969/j.issn.1674-8484.2024.03.015
    Abstract ( 139 )   HTML ( 10)   PDF (1944KB) ( 1089 )  

    A linear quadratic regulator (LQR) control method with incorporating articulated angle deviation and steering angle compensation was proposed to address the issue of path deviation of semi-trailer in the process of driving of autonomous container trucks. Based on the three-degree-of-freedom dynamic model of the truck, a path tracking error model was established with considering articulated angle deviation. The linear quadratic regulator(LQR) path tracking controller was designed by compensating for the steering angle using the proportion-integral-derivative (PID) algorithm. A joint simulation platform was built using MATLAB/Simulink and TruckSim to perform simulation analysis under different condition. The results show that the average deviation in distance between the tractor and the desired path is reduced by more than 62%, and the average deviation in distance between the semi-trailer and the desired path is reduced by more than 31% by adopting the proposed path tracking algorithm and introducing PID steering compensation. The heading deviation and articulation angle deviation are also improved. Therefore, the proposed control algorithm demonstrates good path tracking performance, enhancing accuracy and stability in tracking the desired trajectory.

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    Research on virtual track system of superhighway based on vehicle road cooperation technology
    HE Yongming, QUAN Cong, XING Wanyu
    2024, 15(3):  424-432.  doi:10.3969/j.issn.1674-8484.2024.03.016
    Abstract ( 102 )   HTML ( 3)   PDF (1963KB) ( 78 )  

    A virtual track system model of the superexpressway was built to ensure the driving safety of the superexpressway and demonstrate the feasibility of the application of the virtual track system on the superexpressway based on the vehicle-road cooperation technology. The threshold of vehicle lateral deflection angle was calculated by establishing a real-time vehicle dynamic coordinate system with considering the deviation of vehicles from the safety zone. Simultaneously, the variation of the sampling frequency and installation spacing of the microwave ranging module with vehicle speed was studied by using a positioning system and a roadside unit detection system. The results show that when the virtual unilateral track safety zone is 10 cm, the maximum safe angle ranges for lateral deflection of small two box cars, small three box cars, medium size cars, medium to large size cars, and large size cars are 1.43°~1.59°, 1.30°~1.40°, 1.22°~1.33°, 1.17°~1.25°, and 1.10°~1.20°, respectively. When the vehicle is traveling at a speed of 180 km/h, the sampling frequency of the roadside unit sensor can reach a maximum of 27.72 Hz, and the installation distance of the sensor can reach a maximum of 6.87 meters.

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    Vehicle and lane detection algorithm based on MSFA-Net
    WEN Bin, DING Yifu, HU Yiming, PENG Shun, HU Hui
    2024, 15(3):  433-442.  doi:10.3969/j.issn.1674-8484.2024.03.017
    Abstract ( 139 )   HTML ( 5)   PDF (2291KB) ( 81 )  

    Vehicle detection and lane segmentation are important components of automatic driving sensing system, and their basic requirements are high precision and real-time. Therefore, a dual-task multi-scale feature aggregation network (MSFA-Net) was proposed, which was composed of one feature extraction network and two detection branch networks, and realized the simultaneous detection of vehicles and lane lines. First, E-ELAN network was used to construct the shared backbone feature network. Convolutional basic structure plus (CBS+) was designed for bottom-up feature fusion to improve accuracy in vehicle detection branch. To enhance the accuracy of discontinuous and nonlinear lane segmentation in lane segmentation branch, FeatFuse module was proposed for adaptive weight fusion of multi-features and context dilated convolutional basic structure (CDBS) for sampling fusion features through multi-dilation convolution of trapezoidal structure. The results show that on the BDD100K dataset, the average accuracy, recall rate and pixel accuracy of MSFA-Net reach 81.3%, 90.1% and 80.1% respectively, and the detection frame rate reaches 41.6 frames /s, which can better adapt to the needs of real-life driving scenarios.

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