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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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  • 2023, Vol. 14 No. 3 Published on:30 June 2023 Previous issue    Next issue
    Review, Progress and Prospects
    A unified framework for vehicle-infrastructure-cloud autonomous driving
    ZHANG Yaqin, LI Zhenyu, SHANG Guobin, ZHOU Guyue, GAO Guorong, YUAN Jirui
    2023, 14(3):  249-273.  doi:10.3969/j.issn.1674-8484.2023.03.001
    Abstract ( 480 )   HTML ( 238)   PDF (10987KB) ( 168 )  

    While major advances have been made in the R&D and commercialization of autonomous driving (AD) in the past decade, there still exists significant challenges in the large-scale commercial deployment of AD in complex open-road scenarios, such as longtail perception problem and limited operational design domain (ODD). Information from vehicles, traffic and the underlying infrastructure (V2X) can be used to enhance the overall system safety and accelerate the deployment, with integration of multi-scaled, multi-dimensional diverse sources. This integration would enable cooperated perception, decision-making, and control, expanding single-vehicle intelligence’s capability boundaries. By using this combined knowledge, some of the obstacles encountered in the commerciliazation of autonomous driving can be addressed. This paper introduces a unified framework for autonomous driving known as Vehicle-Infrastructure-Cloud Autonomous Driving (VICAD). VICAD combines the diverse collaborative deployment strategies related to vehicles, infrastructure, and the cloud with autonomous driving algorithms via an integrated framework. Simulations and evaluations are conducted to evaluate the performance of VICAD system, and evaluation results are then feedback as input of the VICAD system. This iterative process enables the continuous optimization of collaborative deployment strategies and autonomous driving algorithms, thereby enhancing the capabilities of autonomous driving. Moreover, this paper describes the key role of VICAD in fostering the large-scale commercial deployment of autonomous driving with practical cases and industrial applications, and concludes with suggestions for further VICAD development.

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    Automotive Safety
    Temperature rising state of the brake disc of electric bus on long-downhill considering kinetic energy recovery
    LI Zitian, LI Bin, HUO Shenyang, ZHANG Jing, LÜ Xiaoxia
    2023, 14(3):  274-281.  doi:10.3969/j.issn.1674-8484.2023.03.002
    Abstract ( 140 )   HTML ( 214)   PDF (2672KB) ( 73 )  

    The high brake-disc temperature-rise in long downhill conditions was investigated for pure electric buses with central drive to improve the safety of pure electric buses. The simulations and the real road tests were used to investigate the temperature correlation between the ventilated disc brakes and the brake calipers of a certain vehicle model. A thermodynamic coupling model of brake disc was established based on Ansys Workbench software, and the temperature fitting function between brake caliper and brake disc was fitted by Matlab based on the experimental data. The results show that the continuous braking gradient is about 3.99% by anti-drag braking, and the service braking involvement is required when the gradient is larger. Brake calipers and disc temperature rise correlation coefficients is up to 0.9. That means that brake caliper temperature is used to monitor the brake-disc thermal decay for safety warning. These results provide data support for the long-downhill braking safety for pure electric buses.

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    Effect of head rotation on neck responses under rear impact
    WU Hequan, GONG Chuangye, REN Qifan, ZHOU Huilai, MAO Haojie
    2023, 14(3):  282-289.  doi:10.3969/j.issn.1674-8484.2023.03.003
    Abstract ( 124 )   HTML ( 213)   PDF (3126KB) ( 52 )  

    In order to study the effect of head and neck rotation posture of occupants on neck injury during low-speed rear collision, Global Human Body Models Consortium (GHBMC) head and neck model was used to change the head and neck posture through a flexible impactor. After activating the neck muscles of head-and neck finite element models with different poses, acceleration curve was applied to the first thoracic vertebra for low-speed rear collision simulation. The results show that the axial rotation angle of the right side of the head has a great influence on the motion of the occupant's head in the low speed rear collision. When the head and neck are in a rotating state, the activated neck muscles drive the head to turn quickly, resulting in the head hitting the side of the head pillow; Axial head rotation posture dose not affect the process of neck bending and backward extension during collision, but it affects the lateral bending and axial rotation of the neck. Among them, the horizontal lateral bending between the fourth and fifth cervical vertebrae is the most obvious. The peak value of right lateral bending neck injury under 0°, 20° and 40° head rotation posture is 0.11, 2.66 and 5.6, respectively.

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    Design and control strategy research of C1 electric driver-training vehicle power system
    LIU Kan, QI Haibo, NIU Ahui, YAN Bingqiang, QIN Junchao
    2023, 14(3):  290-298.  doi:10.3969/j.issn.1674-8484.2023.03.004
    Abstract ( 142 )   HTML ( 184)   PDF (1912KB) ( 244 )  

    A power system of C1 electric driver-training vehicles was designed to reduce fuel consumption and exhaust emission to meet the requirements of driving schools. Based on V mode of software development, the control strategy and software realization of a motor simulating engine ignition, idling, starting and running were explored; The designed power system and control strategy software and the improved direct torque control algorithm were loaded into the Chery Kai wing vehicle based on sliding mode control, and the simulation and calibration were carried out. The results show that the motor speed is 100-200 r / min lower than the engine speed at idle speed, saving energy consumption; the starting speed of the motor is 0.5 s faster than that of the engine, improving the power performance; the handling experience of the right angle, S-turn, side parking, reverse parking, and project 3 test is basically the same as that of fuel driver-training vehicles; a comparative test is conducted in Shijiazhuang Yuhua driving school with the fuel driver-training vehicles, which verifies the technical feasibility of the designed power system and its control strategy.

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    Identification of braking condition for heavy truck on long downhill
    SHI Peilong, GAO Yipeng, ZHANG Zihao, ZHAO Xuan, YU Qiang
    2023, 14(3):  299-309.  doi:10.3969/j.issn.1674-8484.2023.03.005
    Abstract ( 179 )   HTML ( 78)   PDF (4051KB) ( 62 )  

    The traditional continuous braking system excessively relies on the subjective judgment of the driver to open and close, which is prone to the problem of thermal decline of the whole vehicle’s braking performance caused by improper operation. Therefore, this paper proposed a method to construct and identify the braking condition of heavy truck on long downhill, which provided a basis for the continuous braking system to intervene or withdraw from active control. Based on the long downhill test data of heavy trucks, including brake pedal action, vehicle speed and GPS data, the long downhill braking conditions was constructed using short stroke division, K-clustering, coding techniques and the Markov-Monte Carlo method, where the total time was 1 194 s and the total distance was 21.18 km. Based on the principle of rolling time window, the Back Propagation(BP) neural network working condition identification model was established, and offline training and identification verification was carried out. The results show that the recognition accuracy of general braking and forced braking working conditions is 89.30%, proving that the proposed method can effectively identify the braking status of heavy trucks on long downhill.

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    Intelligent Driving and Intelligent Transportation
    Prediction of automobile claims and warranty costs method based on two-dimensional warranty data
    PANG Huan, SHI Dongyang, GONG Zheng, LIU Jingyi
    2023, 14(3):  310-318.  doi:10.3969/j.issn.1674-8484.2023.03.006
    Abstract ( 129 )   HTML ( 76)   PDF (1955KB) ( 62 )  

    A claim ratio calculation method based on the correction of in-warranty ratio was proposed to improve the prediction accuracy of automobile claim ratio and accurately predict the warranty cost of automobile enterprises in the future period, considering the censoring characteristics of two-dimensional warranty data and the over-warranty situation of automobile products. A prediction method of the warranty cost based on the claim ratio and repair-replacement rate was proposed due to the difference of the warranty cost under the two modes of parts repair and replacement. The warranty cost of the automobile enterprise in the next quarter was predicted, combining with the actual two-dimensional warranty data of a certain brand of automobile. The results show that the relative error between the predicted warranty cost and the actual warranty cost is within 6.5%. Compared with the method that does not consider the in-warranty ratio of automobile, the prediction accuracy of the proposed warranty cost prediction method is improved by more than 4.5%, which can provide support for warranty strategies formulation, product pricing and warranty reserve planning of automobile enterprises.

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    Vehicle global speed planning for unstructured roads scenario
    LI Han, YU Guizhen, ZHOU Bin, ZHANG Yudi, OUYANG Dongzhe, TIAN Jiangtao
    2023, 14(3):  319-328.  doi:10.3969/j.issn.1674-8484.2023.03.007
    Abstract ( 144 )   HTML ( 10)   PDF (4152KB) ( 248 )  

    Based on a segmented uniform acceleration model, a global velocity planning method was proposed to achieve intelligent connected vehicle navigation in complex and unstructured road scenarios. By analyzing the vehicle’s dynamic characteristics with driving safety and smoothness as the principles, the critical speeds for rollover and sideslip were calculated as the maximum traveling speeds for each path point on unstructured roads. The global velocity planning problem was formulated using a segmented uniform acceleration model, taking into account efficiency, smoothness and energy consumption through a comprehensive loss function. The model considered the continuous variation of slope curvature on unstructured roads and designs variable bounds for vehicle velocity, acceleration, and jerk to constrain the decision variables. By integrating the regenerative braking function of heavy-duty electric vehicles, a specific velocity planning model for electric vehicles in unstructured road scenarios was proposed, and the method was validated through simulations. The results show that the acceleration range of the ego vehicle is stable within -1.0―1.0 m/s2, and the jerk range is stable at -0.5―0.8 m/s3. Compared with the speed planning based on dynamic programming, the proposed speed planning algorithm not only ensures the stability of the vehicle but also reduces the vehicle control inputs. The proposed method has been applied to the autonomous trucks which travel smoothly, the maximum jerk of the truck does not exceed 0.45 m/s3, which shows the stability of the truck.

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    Remote upgrade system for the on-board diagnostic system based on an improved Bsdiff algorithm
    QIAN Feng, YI Qi, ZHU Neng, WANG Jie
    2023, 14(3):  329-337.  doi:10.3969/j.issn.1674-8484.2023.03.008
    Abstract ( 91 )   HTML ( 10)   PDF (1905KB) ( 253 )  

    A remote upgrade system was designed for On-board Diagnostic (OBD) System based on an improved Bsdiff algorithm to shorten time consumption, minimize power consumption and stable firmware upgrade with easier operation and less cost in the OBD terminal remote upgrade. The system optimized redundant zero values in the differential region when the Bsdiff algorithm generated differential files. Bandwidth utilization was enhanced by adopting a multi-threading mechanism. The design of flash memory partitioning was optimized by adjusting flash memory partitioning in a dynamic manner. Comparison tests were conducted between full upgrade and differential upgrade in a built test environment. The results show that the system rises of 81.2% in the file size performance metrics with rising of 62.5% in the file compilation time consumption performance metrics, compared to the full remote upgrade approach. Therefore, this system improves the flash space utilization with reducing the time required for firmware updates.

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    Optimal lateral acceleration driver model based on trajectory prediction
    ZHOU Xing, LIU Fuyun, TANG Zhentian, DENG Jucai
    2023, 14(3):  338-345.  doi:10.3969/j.issn.1674-8484.2023.03.009
    Abstract ( 140 )   HTML ( 10)   PDF (2563KB) ( 137 )  

    An optimal lateral acceleration driver model was proposed based on the trajectory prediction to improve the active safety of intelligent vehicles. The model was used to predict the vehicle trajectory with an assumption of the vehicle driving at a constant yaw velocity according to the current vehicle attitude; Determine the ideal steering wheel angle by calculating the lateral deviation after the preview time. The path tracking effect of the model was simulated and analyzed for the driving conditions on the double-shift roads and circular roads; The simulation model was verified by using a series of real vehicle tests. The results show that the maximum tracking lateral deviation of the simulation results is less than 10 cm with the deviation of the real vehicle tests being less than 25 cm at the constant speed of 54 km/h. Therefore, the model can stably follow the target path when the vehicle is traveling, verifying the accuracy of the model.

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    Resource allocation optimization and performance evaluation for 5G cellular vehicle-to-everything (C-V2X)
    HONG Ying, SHA Yuchen, DING Fei, CHEN Zhu, ZHANG Dengyin
    2023, 14(3):  346-354.  doi:10.3969/j.issn.1674-8484.2023.03.010
    Abstract ( 106 )   HTML ( 5)   PDF (2387KB) ( 104 )  

    To improve the spectrum utilization efficiency of C-V2X (cellular vehicle to everything), a resource allocation algorithm was proposed to maximize system downlink throughput and ensure the connectivity of the V2V (vehicle to vehicle) communication. A channel model of cellular vehicle to everything was defined, the optimization model was established under the constraints of maximum transmission power, outage probability, etc., and was solved step by step. The KM (Kuhn-Munkras) algorithm was used to dynamically schedule channel resources to realize the dynamic allocation of network resources between the V2I (vehicle to infrastructure) downlink and the V2V link in the C-V2X communication system. The optimization performance of the algorithm was evaluated through different traffic scenarios. The results show that the proposed algorithm enters a steady state after seven iterations, achieves the optimal allocation of V2I link resources while ensuring the connectivity of V2V links, and the downlink spectrum efficiency increased by an average of more than 3.5% compared to the greedy algorithm.

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    An automatic control method for semi-active suspension of driverless vehicle based on multi-sensor information fusion in complex environment
    DING Peng, ZOU Ye, GUO Xianglong, CHEN Xun, LU Fushuo
    2023, 14(3):  355-364.  doi:10.3969/j.issn.1674-8484.2023.03.011
    Abstract ( 138 )   HTML ( 6)   PDF (3480KB) ( 166 )  

    A semi-active suspension control method based on multi-sensor information fusion was proposed to improve the safety and smoothness of driverless vehicles on damaged and small obstacles. A quarter suspension vibration model considering multi-sensor information fusion was established, revealing the relationship between road roughness information and vehicle vibration. The camera and radar wave were used to scan and identify the uneven road conditions, and a mathematical model of road roughness was created. The information fusion and matching of uneven road surface were carried out by detecting the edge intersection ratio and Graph Neural Network(GNN) algorithm, obtaining a more reliable mathematical model of uneven road surface in complex environment. It is proposed to calculate the optimal damping ratio of semi-active suspension using the information of vehicle speed and road roughness, and to adjust the suspension to this damping ratio to adapt to different road conditions in real time. The vehicle ride comfort test under typical road input conditions was carried out, and the vibration acceleration time domain response signals of different suspensions were compared and analyzed. The results show that the maximum peak vibration acceleration of the unmanned suspension controlled by multiple information fusion is reduced by 43% comparing with that in the passive suspension under the same conditions, which verifies the superiority of the proposed method.

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    Automotive Energy Efficiency and Environment Protection
    Parameter relationship between exhaust emissions and driving behaviors for commercial heavy-duty vehicles
    XU Ting, CHEN Shuyi, PENG Chong, CHEN Yixin, LIANG Zekai, ZHAO Lei
    2023, 14(3):  365-374.  doi:10.3969/j.issn.1674-8484.2023.03.012
    Abstract ( 104 )   HTML ( 11)   PDF (1784KB) ( 80 )  

    The exhaust emissions were analyzed for commercial heavy-duty vehicles to reduce exhaust emissions with ecological driving behavior. Five exhaust emissions, namely CO2, CO, NOx (nitrogen oxides), THC (total hydrocarbon), and PM (particulate matter), were measured at different speeds and operating conditions; The influence of abnormal driving on emissions were also analysed. The cumulative average value of the data clustered according to the speed was used to divide the model construction interval. The speed, acceleration and Vehicle Specific Power (VSP) were selected as the independent variables of the emission model. Ternary linear regression equations were constructed to reflect the relationship between driving behavior and emissions. The results show that the multiple decision coefficients of the prediction equations are more than 0.5, and the prediction data passes the paired T test; In emission prediction equations, the acceleration has a significant impact on five exhaust emissions. Suggestions on reducing pollutant emissions, optimizing driving behaviors, and ecological driving behaviors are put forward.

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    Heavy-duty vehicle emission characteristics based on the remote-monitoring three-bin moving-average window method
    REN Shuojin, ZHANG Chao, LI Gang, LI Tengteng, Yu Quanshun, GUAN Min, JI Zhe, JING Xiaojun
    2023, 14(3):  375-384.  doi:10.3969/j.issn.1674-8484.2023.03.013
    Abstract ( 105 )   HTML ( 5)   PDF (2562KB) ( 81 )  

    A three-bin moving average window (3B-MAW) model was proposed and compared with the work-based window method (WB-WM) to investigate the on-road emission characteristics of heavy-duty vehicles. The invalid data of remote monitoring were mainly composed of the NOx sensor’s abnormal data and the uploaded data after the engine shutdown. In the 3B-MAW model, each data was attributed to one, two or three bins. The percentage of the three bins were linked to the vehicle’s real driving conditions. In order to gain the emission calculation accuracy and a smaller scale of required data, the value of the four main parameters, i.e., the minimum window number, the window width, the first cut-off and the second cut-off are set around 2 400 s, 300 s, 6% and 20%, respectively. Since the window power threshold is no longer required, the 3B-MAW method is able to capture the low load emission characteristics more effectively, compared to the WB-WM. Therefore, the 3B-MAW method is a more appreciate approach to analyse on-road random driving conditions.

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    Performance optimization of a snake-like channel liquid cooled plate for lithium-ion power batteries
    LI Xue, ZHANG Furen, LU Xinglong, HUANG Zhikai, ZHAO Haodong, SHI Yazhou
    2023, 14(3):  385-392.  doi:10.3969/j.issn.1674-8484.2023.03.014
    Abstract ( 161 )   HTML ( 16)   PDF (3726KB) ( 116 )  

    A liquid cooling plate with serpentine channel structure was propose to improve the heat dissipation performance of the lithium-ion power battery thermal management system with a more uniform temperature distribution. The liquid cooling plate in the serpentine passage was preliminarily optimized. The temperature uniformity of the liquid cooling plate was improved by adding fins in the passage and opening a guide channel. The optimal solution of the channel structure of the liquid cooling plate was obtained through multi-objective genetic algorithm optimization, with the structural parameters of the cold plate (the percentage of the fin width in the passage, the channel connection width, and the gap) as variables, and the average temperature and pressure drop as optimization objectives. The software CFD (computational fluid dynamics) was used to verify the accuracy of the optimization results. The results show that the heat dissipation performance of the liquid cooled plate after multi-objective optimization is effectively improved with an average temperature reduced by 6.19 K and a temperature standard deviation reduced by 5.19 K compared with the initial structure.

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