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Welcome to Journal of Automotive Safety and Energy,
汽车安全与节能学报

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  • 2021, Vol. 12 No. 2 Published on:30 June 2021 Previous issue    Next issue
    Review, Progress and Prospects
    Current status and development trends of European new energy vehicles
    WANG Shanjin, CHENG Yuan
    2021, 12(2):  135-149.  doi:10.3969/j.issn.1674-8484.2021.02.001
    Abstract ( 1561 )   HTML ( 181)   PDF (1247KB) ( 10943 )  

    This article introduces the current status and development trends of new energy vehicles in Europe, covering the European auto market, the EU’s carbon emission regulations, the new energy promotion policies of EU governments, and the new energy vehicle strategies and technical road-maps of European original equipment manufactures (OEMs). Although the long-term goals of new energy vehicles of major European OEMs are different, because they must comply with the same CO2 emission regulations, the short-term technical road-maps are similar, that is, pure electric and plug-in hybrid vehicles go hand in hand. In terms of power batteries, European OEMs have all adopted lithium ion battery technology; In terms of pure electric powertrain system, European OEMs basically adopt the configuration of drive motor combined with single speed reducer; In terms of hybrid powertrain systems, the choice of European OEMs is based on the parallel structure, which has not only potential for optimizing energy transmission efficiency, enriching working modes, but also giving full play to the traditional advantages of European OEMs in engine and transmission technology. It is worth mentioning that dedicated hybrid transmission (DHT) technology has been successfully launched in Europe. This technology can give full play to the advantages of electrified powertrains and is forming a development trend. The EU’s strict CO2 emission regulations are the biggest driving force to ensure the sustainable development of new energy vehicles in the next few decades. Europe’s strength in traditional automotive technology, production, and sales is also becoming a strong advantage in the development of its new energy vehicles. It is expected that in the next ten years, the share of new energy vehicles in Europe will continue to grow steadily, and new energy vehicles will dominate the European market before 2040

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    Artificial intelligence technologies for engine control development: State-of-the-art review and outlook
    XU Hongming, ZHOU Quan
    2021, 12(2):  150-162.  doi:10.3969/j.issn.1674-8484.2021.02.002
    Abstract ( 865 )   HTML ( 59)   PDF (1361KB) ( 538 )  

    Connection, automation, sharing and electrification (CASE) are the future of vehicle and mobility systems. International Energy Agency (IEA) predicts that electric vehicles including plug-in hybrid vehicles will count for 97% of the market by 2050. The increasingly stringent emission legislations for CO2 reduction, especially when involving real driving emissions (RDE) testing are the main challenges to the control system of the vehicle powertrains. This paper focus on artificial intelligence (AI) technologies for engine control developments that follow the standard model-based routine. By reviewing state-of-the-art AI technologies for feedforward control, feedback control, and global optimization at system level, the advantage and disadvantage of the AI technologies are compared and summarized. An outlook is provided based on the literature survey. It indicates that AI will promote the fusion of technologies in three representative domains, 1) fusion of cyber systems and physical systems, e.g., digital twin of engine; 2) fusion of machine learning systems and classical control systems, e.g., AI-based calibration of engine controllers; and 3) fusion of information from multiple sources, e.g., powertrain domain control network. The technology fusions in these three domains are expected to promote the development of advanced engines which aims to achieve zero emissions.

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    Automotive Safety
    Trajectory prediction algorithm of unmanned vehicles at urban intersection based on edge computing
    HAO Lulu, XIE Hui, SONG Kang, YAN Long
    2021, 12(2):  163-172.  doi:10.3969/j.issn.1674-8484.2021.02.003
    Abstract ( 401 )   HTML ( 56)   PDF (2195KB) ( 287 )  

    A trajectory prediction algorithm was proposed based on the combination of driver intent classification and Bezier curve in the edge computing platform to provide prior information for unmanned vehicles to accurately formulate urban intersection trajectories. Proposed a support vector machine-based driver intention recognition algorithm to predict the probability of vehicles going straight, turning left or turning right at the intersection after analyzing the actual traffic data of 230 vehicles at two intersections. And proposed a traffic trajectory prediction method based on the combination of Bezier curve and cost function to predict the traffic trajectory of the intersection. The results show that the accuracy of the driver’s intention classification algorithm is above 92.5% comparing with the actual data collected from 120 vehicles. The maximum deviation range between the predicted trajectory of the vehicle and the true trajectory is 0.223~0.579 m. The average deviation between the predicted trajectory of all vehicles and the true trajectory is 0.214 m. Therefore, this method meets the needs of vehicle trajectory prediction at urban intersections.

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    Experiments and simulations of bimetal drum brakes at high temperature conditions
    BIAN Jiang, WANG Xiaoying, GUI Liangjin, FAN Zijie
    2021, 12(2):  173-179.  doi:10.3969/j.issn.1674-8484.2021.02.004
    Abstract ( 374 )   HTML ( 29)   PDF (2440KB) ( 219 )  

    A bench test was carried out at high temperature working conditions of nearly 500 ℃ for a bimetal drum brake of a heavy truck to explore the dynamic characteristics in the working process of the brake. Measured the dynamic strains and the dynamic temperature properties for the brake during braking. Conducted thermal-stress-wear coupling analysis by using a finite element (FE) software ABAQUS. The results show that the circumferential strain on the brake drum outer surface exhibits an approximately periodic alternating characteristic. The circumferential direction is the main deformation direction of the brake drum, and the maximum circumferential stress appears at the opening edge. The friction lining wear distribution is extremely uneven. These results verify the good accuracy of the bimetal drum brake FE model, which can be used as a basis of the failure analysis and structural optimization for bimetal drum brakes.

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    Discuss on the assessment method of airbag bottoming-out by the THOR 50 th dummy head in C-NCAP
    SHANG Enyi, LI Yueming, XI Bobo, CUI Xinkang, ZHANG Yi
    2021, 12(2):  180-185.  doi:10.3969/j.issn.1674-8484.2021.02.005
    Abstract ( 536 )   HTML ( 28)   PDF (1795KB) ( 300 )  

    Assessments of airbag bottoming-out were discussed to analyz the relationships among the head acceleration, the neck upper force, the cable force, and the facial force of the THOR 50 th dummy head in the China New Car Assessment Program (C-NCAP) tests. Two tests were done for simulating bottoming-out of airbag by using pendulum to hit the head through balloon at different velocities. The results show that the coordinate system differences between the head and the neck may be ignored; the rapid increase of the outer force head acceleration is independent of the cable action; facial force is caused by bottoming-out of the airbag when the facial force happen mutates. Therefore, airbag bottoming-out can be preliminarily judged by the head outer force acceleration, which is obtained by calculating the head accelerations, the head mass, and the neck upper force, and then it can be confirmed by analyzing if the facial force curve has any sudden change in the corresponding time.

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    Parameters optimization of hybrid electric vehicle based on crossover-mutation bee colony algorithm
    LIU Jianhui, YAO fangfang, ZHANG Yan
    2021, 12(2):  186-192.  doi:10.3969/j.issn.1674-8484.2021.02.006
    Abstract ( 248 )   HTML ( 24)   PDF (1108KB) ( 135 )  

    A parameters optimization method was proposed based on crossover-mutation bee colony algorithm to reduce fuel consumption and harmful gases emissions of hybrid electric vehicle (HEV). Energy management strategy was formulated by establishing vehicle dynamic model and key component model, comprehensively utilizing the efficiency of engine, motor and power battery. Taking the parameters of power system and energy control strategy as optimization variables, a multi-objective optimization model was established. On the basis of bee colony algorithm, crossover and mutation strategy were used to deepen local searching method, and half stochastic and half reserved method was used to improve global searching efficiency. The results show that verified by the urban dynamometer driving schedule (UDDS) condition, fuel consumption after optimization decreases by 4.85%, CO emission by 19.83%, hydrocarbon compound (CH) by 8.08%, nitrogen oxides (NOx) compound by 7.08%. This indicates the validity of crossover-mutation bee colony reckoning on parameters optimization.

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    Optimal strategy of passenger car powertrain control for improving vibration at low engine speed
    ZHANG Xuefeng, LIU Zhiwen, CHEN Guodong, YANG Yunbo, LI Shoukui
    2021, 12(2):  193-200.  doi:10.3969/j.issn.1674-8484.2021.02.007
    Abstract ( 278 )   HTML ( 31)   PDF (1947KB) ( 393 )  

    The vibration source, transmission path and occurring mechanism were analyzed inside a passenger car equipped with automatic transmission accelerating at high gear and low engine speed to solve the problems of vibration accompanied with low frequency roar. The effect on solving the vibration and roar problems inside the car from the aspects of flywheel inertia, half shaft stiffness, torsional damper stiffness, dynamic vibration absorber and powertrain software control strategy were demonstrated. A way was adopted through powertrain calibration control after evaluating comprehensively the factors such as project cycle, modification cost and practicability, to optimize the vibration problems. A series of noise-vibration-harshness (NVH) experiment was conducted on real vehicle. The results show that the vibration amplitude inside the car can be decreased by 44% comprehensively driving at high gear and low engine speed with the optimization strategy. Therefore, the improvement effect is significant.

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    Vehicle autonomous collision avoidance decision control model based on deep reinforcement learning
    LI Wenli, ZHANG Yousong, HAN Di, QIAN Hong, SHI Xiaohui
    2021, 12(2):  201-209.  doi:10.3969/j.issn.1674-8484.2021.02.008
    Abstract ( 541 )   HTML ( 53)   PDF (3044KB) ( 581 )  

    A vehicle autonomous collision avoidance decision control model was proposed based on a deep deterministic policy gradient (DDPG) to improve the self-learning and decision-making capabilities of vehicle in driving environment. A state space containing self-vehicle and target object information, and an action space including the self-vehicle deceleration were designed based on a reinforcement learning theory of Markov decision process and a longitudinal kinematic of vehicle. An end-to-end vehicle autonomous collision avoidance decision model was constructed which takes safety, comfort and efficiency into a multi-objective reward function. An interaction model was built by using MATLAB/Simulink with the DDPG algorithm and the traffic environment, and the model passed through test for scenarios of car to car stationary (CCRs) and scenarios of car to car braking (CCRb). The results show that the proposed decision-making algorithm has good convergence with introducing limit values of acceleration and jerk, realizes the effective collision avoidance of vehicle with considering ride comfort. Therefore, it has better performances than using fuzzy control.

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    Automotive Energy Efficiency and Environment Protection
    Real road tests of the emission from extended-range electric vehicles with different energy management strategies
    WANG Yu’an, LUO Jiaxin, WANG Yachao, WANG Xin, GE Yunshan, JIANG Zhen
    2021, 12(2):  219-225.  doi:10.3969/j.issn.1674-8484.2021.02.010
    Abstract ( 300 )   HTML ( 23)   PDF (997KB) ( 78 )  

    Several real driving tests were done on different extended-range electric vehicles to investigate the influence of two kines of energy management strategies at two driving conditions on the emission from extended-range electric vehicles. The instantaneous high emission set (IHES) was obtained by clustering the emission data. The influence of internal parameters such as engine speed and throttle position on instantaneous high emission of carbon monoxide (CO) and particle number (PN) was analyzed. The experimental results show that energy management strategies can significantly affect the distribution regularity of instantaneous high CO emissions. Compared with the power following strategy, the multi-point control strategy produces instantaneous high CO emissions when the vehicle speed is high. Different driving behaviors have no significant influence on the distribution regularity of instantaneous high CO and PN emissions in extended-range electric vehicles. However, the engine coolant temperature is relatively low under congestion road conditions, resulting in more PN instantaneous high emissions during restart.

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    Electric vehicle driver’s range anxiety model based on use behavior
    LI Zonghua, ZHAI Jun, WANG Xianjun, MA Mingze, DIAO Guantong
    2021, 12(2):  226-231.  doi:10.3969/j.issn.1674-8484.2021.02.011
    Abstract ( 280 )   HTML ( 26)   PDF (1318KB) ( 279 )  

    A judgment model of range anxiety degree was proposed based on user behavior of big data of Internet of Vehicles to investigate the influence of range anxiety on user behavior of pure Electric Vehicle (EV). Kernal K-means clustering algorithm was used to analyze the different performance of users’ range anxiety differences in charging frequency, start-stop state of charging (SOC), extremely use behavior, etc. Logical regression algorithm was used to establish the classification and recognition model of range anxiety. The probability of anxiety output by logistic regression model was converted into range anxiety grade by scoring card method. The accuracy and universality of the model were verified via questionnaire. The results show that the prediction accuracy of the model is 95.6%. Therefore, this model can effectively determine the extent of users’ range anxiety, and can be used for big data portrait analysis of EV users if integrated with other analytical dimensions.

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    Study on ignition temperature conditions and influencing factors of lean burn spark assisted compression ignition
    SUN Jian, GENG Lu, LAI Haipeng, GAO Dingwei, YU Shuhai
    2021, 12(2):  232-242.  doi:10.3969/j.issn.1674-8484.2021.02.012
    Abstract ( 286 )   HTML ( 19)   PDF (1107KB) ( 128 )  

    The ignition conditions and influencing factors of auxiliary compression ignition were studied to realize the control towards the moment of fire and to decouple the influence of key control parameters on the degree of compression combustion and the moment of compression combustion. Under the condition of negative valve overlap angle by using small lift camshaft and the air excess coefficient was 1.2, the experiments and calculations were carried out. The results show that the compression burning rate can be defined by the proportion of the heat released in the circulation compression burning part relative to that of the circulation emission, which can reflect the degree of compression burning. The compression burning rate can be reflected by the key control parameters such as the effective compression ratio, exhaust gas recirculation (EGR) rate and ignition advanced angle, which are the analytic relationship of independent variables. The temperature 958.13(±15) K of the unburned part of mixed gas at the moment of compression combustion is given as the ignition temperature. In a word, the influencing factors of the compression combustion rate can be decomposed into operation parameters and structural parameters. For a specific parameter, through the analytic formulation of the relationship between the compression combustion rate and key control parameters, the fire-timing can be predicted and controlled.

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    Three-dimensional multiphysics numerical simulation of solid oxide fuel cell for internal methane reforming
    CHEN Yuyao, WEI Mingrui
    2021, 12(2):  243-250.  doi:10.3969/j.issn.1674-8484.2021.02.013
    Abstract ( 413 )   HTML ( 23)   PDF (1053KB) ( 145 )  

    A numerical model of the anode-supported planar solid oxide fuel cell (SOFC) was established to study the performance and the distribution of internal parameters of SOFC with pre-reformed methane as fuel, based on the finite element simulation software COMSOL Multiphysics and with the method of direct reforming of methane inside the SOFC. The model couples the control equations of heat and mass transfer, momentum transfer, charge transfer, and chemical reactions inside the cell. The results show that the drop in operating voltage will increase current density, and the current density at the interface of anode functional layer and the electrolyte is mainly limited by the oxygen diffusion rate. The steam reforming reaction of methane will strongly absorb heat, which is beneficial to reduce the temperature gradient of the SOFC and improve the life of SOFC; When using methane as a fuel, thermodynamic carbon may deposit, especially near the fuel inlet due to the thermal decomposition of methane. Reducing voltage and increasing current density are beneficial to inhibit thermodynamic carbon deposition.

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    Study on the influence of operation parameters on the performance of proton exchange membrane fuel cell system
    JI Shaobo, MA Rongze, ZHAO Tongjun, LI Yang, HUANG Hai, ZHANG Shiqiang, CHENG Yong
    2021, 12(2):  251-256.  doi:10.3969/j.issn.1674-8484.2021.02.014
    Abstract ( 279 )   HTML ( 19)   PDF (773KB) ( 207 )  

    A Mark V proton exchange membrane fuel cell (PEMFC) analysis model was established to find out the influence of operating parameters on the output performance of PEMFC based on Simulink platform and Thermolib toolkit. The key operating parameters’ influence on the single cell voltage were studied, such as the stack temperature, air humidity, hydrogen pressure, air temperature, hydrogen pressure, air pressure, air excess coefficient and so on. The results show that the stack performance can be improved by increasing H2 pressure, air pressure and air humidity; the influence of stack temperature, air temperature and excess air coefficient on the performance of fuel cell is limited. When the fuel cell reaches the optimal state, increasing the parameters will not improve the performance of fuel cell. These analysis results are helpful to understand the influence of key operating parameters on the performance of fuel cell, and have certain guiding significance for the development of fuel cell control strategy.

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    Experimental investigation of nearly zero-emission direct injection hydrogen engine
    BAO Lingzhi, SUN Baigang, WANG Xi
    2021, 12(2):  257-264.  doi:10.3969/j.issn.1674-8484.2021.02.015
    Abstract ( 267 )   HTML ( 25)   PDF (1285KB) ( 597 )  

    The nitrogen oxides (NOx) emission level of a direct injection hydrogen engine is relatively high due to the uneven mixture distribution in the cylinder and high combustion temperature. The effect of excessive air coefficient, speed, ignition angle, and hydrogen injection pressure on NOx emission was investigated to explore the control method of reducing NOx emission with a 2.0 L naturally aspirated direct-injection hydrogen engine. Without post-treatment, the working boundary of the maximum power with near-zero-emission (NOx≤20×10 -6) was achieved by the coupling of multiple parameters. The results show that NOx emissions can be significantly reduced by lean-burning and delaying the ignition angle with making a sacrifice to a small extend in a small amount of thermal efficiency and combustion stability. The maximum power in the near-zero emission working area is 21.5 kW and the maximum thermal efficiency is 39%, and near zero emission can be achieved at all working points in this area.

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