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  • 2023, Vol. 14 No. 2 Published on:30 April 2023 Previous issue    Next issue
    Basic ideas and development trend of heavy-duty vehicle emission regulations in next stage
    JING Xiaojun, REN Shuojin, WANG Xiaowei, LI Tengteng, FANG Maodong
    2023, 14(2):  133-156.  doi:10.3969/j.issn.1674-8484.2023.02.001
    Abstract ( 484 )   HTML ( 192)   PDF (3351KB) ( 4388 )  

    Under the trend and background of continuous strengthening of motor vehicle pollution control and continuous electrification of vehicle power, in recent years, many countries around the world have been discussing the “no internal combustion engines” orders. Meanwhile, more stringent emission regulations have been introduced one after another, which have become a matter of life and death to the traditional internal combustion engine (ICE) power. However, ICEs will remain the main form of power for heavy commercial vehicles due to the requirement of transport capacity and driving distance. At present, the European Union, the California Air Resources Board (CARB) and the U.S. Environmental Protection Agency (EPA) have all issued new heavy-duty vehicle emission regulations, and China has also started research on the National VII emission standards. This article compares and analyzes the latest developments and trends of European and American heavy-duty vehicle and engine emission regulations at the next stage from 6 aspects: exhaust emissions, actual road tests, greenhouse gas emissions, on-board diagnostics (OBD) and remote monitoring, non-exhaust emissions, and durability requirements. The specific requirements of each standard are clarified, and possible technical routes are pointed out, aiming to provide reference for the heavy-duty vehicle and engine industry to respond to emission standard upgrades and related forward-looking research in a timely manner. The research results shows that there are 5 major development trends in the future emission standards of heavy-duty vehicles: Exhaust emission testing is developing towards ultra-low emissions of multiple pollutants, and in the case that it may become the final generation of emission regulations, long-term emission reduction plans should be considered in emission regulations at the next stage; Pay more attention to vehicle on-road, low load, idle and cold start emissions; Strengthen coordinated control of greenhouse gas and conventional gas emissions; Realize efficient monitoring of in-use vehicle emissions by means of remote big data; Add the tests of non-exhaust emissions such as braking and tire wear. In short, the next stage of pollution standards for heavy-duty vehicles will incorporate new methods and concepts in terms of pollution types, emission testing methods, and emission monitoring methods, so as to continuously promote the development of heavy-duty vehicles towards the goal of clean, environmentally friendly and efficient.

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    Accident causes and its topological hierarchy analysis for heavy-duty trucks and two-wheelers
    ZHANG Daowen, LI Min, PANG Shaorong, LUO Qirui
    2023, 14(2):  157-164.  doi:10.3969/j.issn.1674-8484.2023.02.002
    Abstract ( 196 )   HTML ( 122)   PDF (1950KB) ( 75 )  

    An improved DEMATEL-AISM method combined Decision Making Trial and Evaluation Laboratory (DEMATE) with Adversarial Interpretative Structural Model (AISM ) was proposed to explore the relationship between factors influencing accidents involving heavy-duty trucks and two-wheelers. Combined literature analysis method and the National Automobile Accident In-depth Investigation System (NAIS) data (China), an index system of accident causes was established. According to the characteristics of accident data, the DEMATEL method was improved to analyze the influence degrees between accident factors. Based on AISM, the topological hierarchy model of accident factors was established to analyze the topological variability of accident system and the interaction of factors. The results show that the effect of overload on other factors is only 0.150 in the heavy-duty truck and two-wheeler accidents. Among resulting factors, the decision failure is the critical factor easily influenced with a centrality of 5.25 and an influence of 5.18. The accident system is an active system, with the occurrence of accidents being affected by a combination of the driving layer, the direct layer and the intermediate layer factors.

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    Core risk factors of major guardrail-type traffic accidents based on an integrated DEMATEL/ISM
    CHENG Yufeng, ZOU Tiefang, LI Pingfan
    2023, 14(2):  165-172.  doi:10.3969/j.issn.1674-8484.2023.02.003
    Abstract ( 175 )   HTML ( 113)   PDF (1038KB) ( 988 )  

    A core risk factor system of major guardrail-type traffic accidents (MGTA) was constructed by using deeply data mining (DM) to investigated the formation causes of the MGTA, according to the characteristics of five types of accidents: men, vehicles, roads, environments and managements. The key core risk factors and their causal relationships, action paths and hierarchical structures were determined based on the integrated analysis of the DEMATEL (decision-making trial and evaluation laboratory) method and the Interpretive Structural Model (ISM). The results show that the MGTA formation is the result of the coupling between the risk factors; and the driver factors and management factors are the important source of accident prevention. Weak security awareness, driving against road rules, improper operation, speeding, driver supervision omissions and vehicle supervision omissions are the key core risk factors affecting the accident formation, among them, driver supervision omission and vehicle supervision omission are the key root causes, which have high driving force.

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    Reliability analysis of battery thermal management system based on DTBN and T-S fault tree
    LIU Chiwei, GUO Meihua
    2023, 14(2):  173-181.  doi:10.3969/j.issn.1674-8484.2023.02.004
    Abstract ( 181 )   HTML ( 114)   PDF (1045KB) ( 231 )  

    A reliability analysis algorithm for evaluating the thermal management system of electric vehicle power batteries was proposed. The T-S dynamic fault tree of the battery thermal management system was constructed, which was transformed into a Discrete-Time Bayesian Network (DTBN) model. Meanwhile, the T-S dynamic gate rules were transformed into the conditional probability table of network nodes, and the reliability analysis algorithms were proposed. According to the established reliability model and the failure rates of components, the failure probability value of the power battery thermal management system in the task time was 0.453 by calculated, and the posterior probability, probability importance, and the key importance of each component were calculated. The results show that: Compared with the Monte Carlo simulation method, the error of the calculated value of fault probability were less than 5%. The components with the highest probability importance are the single battery temperature sensor, battery coolant pump, battery coolant pipeline, and other components. This method can overcome the difficulties of traditional fault tree analysis in constructing conditional probability tables for Bayesian networks.

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    Difference of car driver’s reaction in a typical car-electric two-wheeler collision scenario
    HAN Yong, LU Ming, WANG Bingyu, YUAN Xiaobin, ZHANG Haiyang
    2023, 14(2):  182-190.  doi:10.3969/j.issn.1674-8484.2023.02.005
    Abstract ( 153 )   HTML ( 6)   PDF (1347KB) ( 457 )  

    In order to investigate the differences in pre-crash behavior of car drivers and the effects on vehicle active collision avoidance of electric two-wheelers accidents. By building 3 typical scenarios of electric two-wheeler accidents and 3 driving speed scenarios in a six-degree-of-freedom driving simulator to conduct volunteer tests, the differences in drivers’ emergency collision avoidance behaviors in different accident scenarios and their effects on accident occurrence were investigated by combining nonparametric tests and binary logistic regression analysis methods. The results showed that the driver’s pre-crash characteristics of braking reaction time, perception time, movement time, average brake pedal opening and average accelerator pedal opening were significantly different in different typical scenarios, and the driver’s reaction characteristics were significantly different in different driving speeds only in the case of large speed differences. Among them, brake reaction time, average brake pedal opening and average steering wheel angle are important factors affecting the occurrence of collision. The results of the study provide theoretical references to improve the safety design of the vehicle automatic emergency braking system for collision avoidance electric two-wheelers.

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    Parallel parking operation model for driverless vehicles based on driver experiences
    XIU Guotao, XIE Hui, SONG Kang, BI Fengrong
    2023, 14(2):  191-201.  doi:10.3969/j.issn.1674-8484.2023.02.006
    Abstract ( 182 )   HTML ( 8)   PDF (2988KB) ( 201 )  

    A parallel parking operation model was proposed for driverless vehicles with fully integrated drivers' parking experience and with less parking energy consumption. The driver's parallel parking experiences were summarized and described as an operation model of the steering wheel rotation angle with double trapezoidal curve image. A parallel parking quality evaluation system was established for three configuration parameters at the key trajectory points of the model to find the influence law of the parameters about parking quality. The double trapezoidal operation model was optimized and rectified by considering the vehicle kinematic constraints and the no-collision constraints. The comparative validations were carried out under multiple algorithms with the adaptive validation under different variable situations on a 6.6 m driverless bus. The results show that the double-trapezoidal operation model has a more fluent parking process with a less energy consumption by 44.7% reducing for eliminating the tracking link, compared with the traditional parking methods of quantic-polynomial trajectory-planning and proportional integral-differential control.

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    Global path planning strategy based on an improved deep reinforcement learning
    HAN Ling, ZHANG Hui, FANG Ruoyu, LIU Guopeng, ZHU Changsheng, CHI Ruifeng
    2023, 14(2):  202-211.  doi:10.3969/j.issn.1674-8484.2023.02.007
    Abstract ( 177 )   HTML ( 7)   PDF (2468KB) ( 525 )  

    A Suppresses Q Deep Q Network (SQDQN) algorithm was proposed based on traditional deep reinforcement learning (DRL), with being established a global path planning strategy, to solve the problem of model over-dependence and overestimation. The SQDQN algorithm combined the Deep Q Network (DQN) algorithm with information entropy to suppress overestimation; Evaluated the update process in real time, with the help of information entropy, to suppress the over-estimation of the damage performances of the DQN strategy. An environmental model to obtain the global path planning strategy was established with the help of the interaction between the SQDQN algorithm and the environment model. The results show that the SQDQN algorithm selects three better strategies from 20 experiments compared with the DQN strategy. And reduces the route planning travel time by 11.32% than that by the Dijkstra's traditional route planning method. The global path planning strategy of this paper reduces the output error caused by DQN's over expectation of actions.

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    Stability control of distributed drive electric vehicles based on the nonsingular fast terminal sliding mode control (NFTSMC)
    ZHANG Yixi, ZHAO Xuan, MA Jian, WANG Xinglu, HU Yueqi
    2023, 14(2):  212-223.  doi:10.3969/j.issn.1674-8484.2023.02.008
    Abstract ( 232 )   HTML ( 7)   PDF (4221KB) ( 603 )  

    A direct yaw moment control strategy with a three-layers structure was proposed to improve the stability of distributed drive electric vehicles for extreme conditions. The top controller was designed to resolve the desired driving state value of the driver. The additional yaw moment required of the vehicle was determined in the upper controller by utilizing the nonsingular fast terminal sliding mode control (NFTSMC). To maximize the vehicle stability margin, the low controller was designed to optimal assign torque to four wheels by using the weighted least square method, which synchronously considered the motor output capability, road adhesion limitation, and the coupling relationship between the longitudinal and lateral tire forces. The simulation experiments were carried out on the MATLAB/Simulink and Carsim platform. The results show that when the vehicle speed is 70 km/h, the maximum tracking error of side slip angle decreases by 66.7% and 45.8%, and the root mean square error decreases by 64.8% and 56.4%, respectively, compared with the sliding mode control, Which shows that this strategy can improve the expected state tracking accuracy and improve the stability of the vehicle in the extreme conditions.

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    Compound aerodynamic drag reduction schemes of van type trucks based on morphological bionics
    XU Jianmin, GONG Xiaoyan, SONG Lei, ZHENG Qingjie
    2023, 14(2):  224-231.  doi:10.3969/j.issn.1674-8484.2023.02.009
    Abstract ( 190 )   HTML ( 5)   PDF (3258KB) ( 210 )  

    Three types of new aerodynamic drag reduction schemes for the shroud, the cab and the cargo compartment were designed based on morphological bionics, and so done a composite bionic drag reduction scheme of a van type truck to reduce the aerodynamic drag. The effects of three single bionic drag reduction schemes on the aerodynamic drag coefficient and their drag reduction mechanism were investigated. The drag reduction effect of the composite bionic drag reduction scheme was investigated by combining the three single drag reduction methods together. The results show that the optimal drag reduction rates of bionic shroud model, bionic cab model and bionic cargo compartment model are 3.57%, 9.45% and 11.86%, respectively, compared to the original truck model. The reduction rate of aerodynamic drag coefficient of the composite drag reduction scheme is 24.5%, and the drag reduction effect is obvious. Therefore, the drag reduction structure of the van based on morphological bionics design improves the flow field structure around the van and reduces the aerodynamic drag.

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    Fault diagnosis of vehicle motor-bearings under safe running by digital-twin technology
    ZHANG Xi, LIAO Yulan, LI Qinyi, CHEN Yiqing
    2023, 14(2):  232-238.  doi:10.3969/j.issn.1674-8484.2023.02.010
    Abstract ( 136 )   HTML ( 2)   PDF (2206KB) ( 229 )  

    To ensure the driving safety of automobiles and timely capture the fault status of motor bearings, a fault diagnosis of motor bearings was completed through the combination of deep learning and digital twin technology. The detailed attributes of the bearings were transformed into virtual space through digital twin technology, and a digital twin body with shape, attributes, criteria, and behavior was constructed. The shape and attribute modules integrated the object parameters of the motor bearings to build a criterion module based on fault signal processing, diagnosis, and classification, and combined the historical records injected by the behavior module to generate data for network training. Data analysis was completed using Matlab 2020a. The results show that the diagnostic accuracies of this method for conventional signals, inner race fault, outer race fault, and rolling element fault are 97.5%, 97.8%, 96.8%, and 97.1%, respectively. Therefore, this method has superior diagnostic effect and algorithmic performance compared with that by using the methods of the hybrid neural network and the migrated residual network.

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    A comparison study between heavy-duty remote monitoring and on-road experimental data
    REN Shuojin, TONG Chang, LI Gang, ZHANG Chao, LI Tengteng, LIU Dong, ZHANG Peng, LIU Zhiwei, GUAN Min
    2023, 14(2):  239-248.  doi:10.3969/j.issn.1674-8484.2023.02.011
    Abstract ( 126 )   HTML ( 6)   PDF (2672KB) ( 469 )  

    In order to study the difference between the remote monitoring data of heavy-duty vehicles and the actual road test data, this paper studies the consistency of the data received by the remote monitoring platform and the measurement data from the portable emission measurement system (PEMS) by fitting the results of two vehicles and analyzing the statistical results of 100 vehicles. The results show that the measured or calculated results from the PEMS equipment can be applied to the consistency verification of the remote monitoring data of heavy-duty vehicles; The consistency of the speed data is acceptable, followed by the consistency results of the fuel flow rate and the intake flow; For NOx emissions, the data consistency requirements should be more flexible. The remote monitoring data can reflect the actual operating conditions of vehicles on the road. The work-based windows from the remote monitoring data and the PEMS test data are basically the same. However, the accuracy error of NOx sensors may lead to a large deviation of the work-based window method calculation results between the remote monitoring and the PEMS measurement.

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