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  • 2022, Vol. 13 No. 4 Published on:31 December 2022 Previous issue    Next issue
    Review, Progress and Prospects
    Review of energy-saving planning and control technology for new energy vehicles
    SUN Chao, LIU Bo, SUN Fengchun
    2022, 13(4):  593-616.  doi:10.3969/j.issn.1674-8484.2022.04.001
    Abstract ( 423 )   HTML ( 137)   PDF (2764KB) ( 6553 )  

    Improving the energy-saving effect of new energy vehicles through vehicle motion planning and control has become a key research focus at home and abroad. This paper summarizes the latest research status of energy-saving planning and control technology for new energy vehicles, and analyzes the eco-routing, eco-driving, eco-charging, energy management and multi-task optimization techniques involving multiple fields above. The study found that although the current energy-saving planning and control technology for new energy vehicles has made considerable research progress, it is difficult to solve the problem in dynamic or random traffic behavior scenarios, and the integrated and collaborative optimization, which considers deeply related behaviors such as path, speed and charging, remains to be explored, and the high-value research results also need to develop from experimental verification to industrial application. This paper proposes that the future development trends of energy-saving planning and control technology for new energy vehicles include: 1) new problems considering the time-varying environment and random behaviors; 2) new algorithms using advanced prediction and efficient solutions; 3) new methods to systematically solve multi-vehicle, multi-task and multi-dimensional problems; 4) new applications that can be replicated and promoted in real scenarios. studying and solving the above problems is of great significance to achieve a higher level of energy-saving control of new energy vehicles.

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    Automotive Safety
    Kinematic equation and injury risk analysis of the chest of 6-year-old child occupant under frontal crash
    YE Fan, WANG Bingyu, HAN Yong, YE Saifeng, YU Yi
    2022, 13(4):  617-624.  doi:10.3969/j.issn.1674-8484.2022.04.002
    Abstract ( 125 )   HTML ( 9)   PDF (4564KB) ( 612 )  

    This paper aimed at clarifying the thoracic injury mechanism of 6-year-old child occupants in frontal crashes. A child restraint system (CRS) was selected based on the ECE R129 regulation. The differences between the Hybrid III 6YO dummy model and the THUMS 6YO human finite element model were compared of the kinematic response and of the injury indicators. Thoracic kinetic equations were established on the Hybrid III 6YO dummy model to analyzed the effects of internal and external forces on the thorax acceleration in frontal crashes, and to analyzed the strains on the ribs, the heart and the lungs of the THUMS 6YO human finite element mode, before deriving the thoracic injury risk to the child occupants. The results show that the neck force and the safe shoulder belt force on the Hybrid III 6YO dummy model have a greater effect on the chest centroid synthesis acceleration. The chest centroid synthesis acceleration achieves 52.1g for the THUMS 6YO human finite element model, and 38.8g for the Hybrid III 6YO dummy model, both are below the regulatory reference values.

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    Thermal comfort experimental study of non-uniform vehicle environment in chilly freezing and snowstorm
    LIN Hongxia, WU Jinmo, SONG Yuhan, LIN Xiaoyong, ZHOU Fan, JI Xiaobo
    2022, 13(4):  625-633.  doi:10.3969/j.issn.1674-8484.2022.04.003
    Abstract ( 106 )   HTML ( 3)   PDF (3436KB) ( 42 )  

    An evaluation method based on the heating, ventilation and air conditioning (HVAC) automobile air conditioning manikin was proposed to study the thermal comfort of air-conditioning system in asymmetrical vehicle thermal environments. The climate wind tunnel was employed to simulate a chilly freezing and snowstorm atmospheric environment, and based on the HVAC manikin, the local/whole body thermal sensation and comfort in non-uniform and transient vehicle cab was investigated. The results shows that the head temperature is 10.8℃ higher than that of leg after the maximum heating operation of the air conditioner runs for 60 min in face and foot blowing mode. All 14 local comfort values of the manikin are bigger than 0.1 except hands while the overall comfort is 0.1 indicating that the comfort of the segments such as hands will greatly affect the overall comfort in cold condition. The experimental results can provide theoretical guidance for the design of air conditioning duct to optimize the thermal environment distribution in the car cabin to improve the riding comfort of passengers.

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    Analysis of differences in far side protection responses of different occupant genders based on a certain vehicle
    YANG Mingjun, BU Xiaobing, GUO Qingxiang
    2022, 13(4):  634-642.  doi:10.3969/j.issn.1674-8484.2022.04.004
    Abstract ( 99 )   HTML ( 4)   PDF (7036KB) ( 405 )  

    A side impact sled test of a certain vehicle model was carried out to gain an deeply understanding of the response differences of different occupant genders in the collision process of far side occupant protection based on Euro NCAP 2020 far side occupant protection test and evaluation procedures. Based on the movement and response principle of the occupants, the differences of the injury situation and response time between male (WorldSID 50th) and female (SID IIs 5th) occupants were compared and analyzed. The results show that the maximum bending moment of the lower neck of the SID IIs 5th female occupant is about 2.2 times that of the WorldSID 50th male occupant, and the average abdominal compression deformation of the female occupant is about 50% smaller than that of the male occupant; the 3 ms composite acceleration of the female occupant's head, and the response time of the neck bending moments are about 12 ms earlier than that of male occupants. This research provides effective technical support for the further development of the side impact far side occupant protection scheme in the future.

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    Analysis of the severity of vehicle to vehicle accidents considering the interaction of factors
    ZHANG Daowen, WANG Chaojian, JIANG Jun, LI Huawei
    2022, 13(4):  643-650.  doi:10.3969/j.issn.1674-8484.2022.04.005
    Abstract ( 96 )   HTML ( 5)   PDF (2004KB) ( 332 )  

    This paper investigated the key factors affecting the severity of vehicle to vehicle (V2V) accidents and the influence of the interaction of key factors on fatal- accident rate. Taking the 583 V2V accidents selected from the National Automobile Accident In-Depth Investigation System (NAIS) database (China) as samples, an analytical model of the V2V accident severity was established by the Bayesian network (BN). The association rule method was integrated to mine the rules with high frequency and strong coupling degree. The results showed that the factors, such as the at-fault party vehicle type, the at-fault party state, the injured party vehicle type, the accident time period, the accident place, and the traffic lights, have significant effects on fatal-accidents rate. The joint effect of factors was significant under the interaction of factors, and the effect was higher than the respective marginal effects. Road junctions had a higher incidence of accidents involving two passenger-cars, but the fatal accident rate is 18.4% lower than the a priori probability of the fatal accident rate. The fatal accident rate of a large car on the common roadway without traffic signals would be 42.6% higher than the a priori probability of the fatal accident rate.

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    Fatigue driving state detection method based on improved EfficientDet
    SONG Wei, ZHANG Guangde
    2022, 13(4):  651-658.  doi:10.3969/j.issn.1674-8484.2022.04.006
    Abstract ( 108 )   HTML ( 7)   PDF (8721KB) ( 163 )  

    A visual detection method was proposed for drivers’ fatigue driving state based on the improved EffcientDet deep learning network to improve the accuracy and efficiency of visual detection and to reduce the requirements of hardware configuration. An EfficientNet network was constructed for extracting driver facial image features by using the deep separable convolution and the visual attention mechanism. An EffcientDet driver state detection network was constructed by using the bidirectional feature pyramid network and the k-means prior frame clustering. The PERCLOS drowsy degree measurement coefficient was used to judge driver fatigue state. Three EfficientDet networks, YOLO V3, and Faster-RCNN were compared and analyzed with different depths, widths and input resolutions. The results show that the improved efficientdet-D2 algorithm has the best efficiency among these algorithms with an average accuracy of 97.92%, a recall rate of 96.75%, an error rate less than 2.39%, and a missed rate less than 1.78%.

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    Research on occupant high-risk accident scenarios of passenger cars in China
    YANG Zhen, WANG Xingchang, GUANG Lijun, SUN Haiyun, FAN Yukun, ZHU He, ZHOU Dayong, GU Xianguang
    2022, 13(4):  659-666.  doi:10.3969/j.issn.1674-8484.2022.04.007
    Abstract ( 161 )   HTML ( 3)   PDF (3916KB) ( 66 )  

    In order to clarify the main safety risk types of Chinese passenger car occupants at present, and to promote the establishment of automobile safety evaluation standards and regulatory systems that are more in line with China’s actual road environment and traffic accident characteristics, the accident scenarios causing the death of passenger car occupants were classified and counted based on China in-depth accident study (CADIS) data by using basic classification variables. The results show that 6 high-risk conflict scenarios suitable for evaluating the active safety performance and 7 high-risk collision scenarios applicable to the evaluation of passive safety performance are extracted with the new classification method for accident scenarios. Meanwhile compared with the current test scenarios of Euro NCAP and C-NCAP, it is found that the scenarios such as passenger cars’ drilling into trucks, drivers’ abnormal physical conditions, frontal impact on posts and guardrail ends cannot be covered, showing that institutions like C-NCAP, China Automobile Standardization Commission, road traffic management departments need to establish vehicle safety evaluation standards and legal systems that are more consistent with China’s actual road environment and traffic accident characteristics through further in-depth research and quantitative analysis of relevant scenarios. At the same time, it also points out some related topics that need to be studied as soon as possible.

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    Characteristics of negative stiffness of vibration isolation for a quasi-zero stiffness suspension system
    DU Xianfeng, MA Xiyang, SUI Xi, WANG Yunlong, SHI Yunxu
    2022, 13(4):  667-675.  doi:10.3969/j.issn.1674-8484.2022.04.008
    Abstract ( 90 )   HTML ( 5)   PDF (2896KB) ( 500 )  

    A quasi-zero stiffness suspension system was proposed with a parallel connection of magnetic ring negative stiffness mechanism and positive stiffness spring to improve rider comfort during driving of mine passenger vehicles by aiming at the characteristics of low-frequency and large-amplitude vibration of mine transport vehicles. An analytical model of negative stiffness was derived by equivalent magnetic charge method to investigate the magnetic negative stiffness mechanism. Based on Maxwell software, a simulation model of the magnetic ring negative stiffness mechanism was established to analyze the effects of the magnetic conductivity device, magnet geometry parameters, magnetizing direction and remanent magnetic strength on the magnetic negative stiffness mechanism. The application matching research of the quasi-zero stiffness suspension system was carried out by taking a body of mine transport vehicle as an example. The results show that the suspension system has a large load-bearing capacity when subjected to static forces and a small dynamic stiffness when subjected to excitation forces. The magnetic negative stiffness mechanism is conducive to realize the high static and low dynamic characteristics of the suspension system, and has important application value for the design of new suspension systems.

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    Intelligent Driving and Intelligent Transportation
    Two-stage eco-driving control strategy for heterogeneous connected and automated vehicle platoons
    YANG Jinsong, ZHAO Dezong, JIANG Jingjing, LAN Jianglin, LI Liang
    2022, 13(4):  676-685.  doi:10.3969/j.issn.1674-8484.2022.04.009
    Abstract ( 125 )   HTML ( 6)   PDF (3098KB) ( 91 )  

    A two-stage eco-driving control strategy was proposed for the heterogeneous platoon consisting of different Connected and Automated Vehicles (CAVs) to improve the fuel efficiency of the platoons. The speed optimisation based on dynamic programming (DP) created an energy-efficient reference speed profile for the CAV platoon at the offline planning control strategy. A Bi-Directional Leader Following (BDLF) strategy was employed at real-time control strategy, to maintain the platoon string stability and to track the reference speed profile in real-time. The proposed two-stage eco-platoon control strategy was established in MATLAB. Its performances were validated by the Autonomie Vehicle System Simulation tool based on the traffic data provided by the California Department of Transportation (Caltrans) (USA) Performance Measurement System (PeMS). The results show that the proposed two-stage eco-driving strategy improves the fuel efficiency of the CAV platoon by 10.1% compared to benchmark strategies. Therefore, this method can maintain the string stability and provide a more energy-efficient solution for the heterogeneous CAV platoons.

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    Integrated control strategy for path tracking of human-machineco-driving vehicle
    ZHANG Xinrong, XU Quanning, GONG Xinle, LI Xueyun, HUANG Jin
    2022, 13(4):  686-696.  doi:10.3969/j.issn.1674-8484.2022.04.010
    Abstract ( 134 )   HTML ( 6)   PDF (13678KB) ( 50 )  

    Aiming at the problems of human-machine co-driving vehicle path tracking control accuracy and vehicle stability that were difficult to guarantee effectively, an integrated control framework was proposed, mainly including active front wheel steering system (AFS) variable ratio curve and path tracking controller based on model predictive control (MPC). In terms of stability control, the AFS variable ratio function considering road adhesion conditions and vehicle speed was constructed to ensure the safety and lateral stability during vehicle path tracking; in terms of path tracking control, the MPC-based path tracking controller was designed to track the target path. Finally, a joint simulation platform based on Carsim / Matlab was built and simulated for verification. The results show that the integrated control strategy can effectively improve the operational stability of the human-machine co-driving vehicle, significantly improve the tracking performance of the vehicle, and weaken the impact of driver driving state fluctuations on vehicle driving safety.

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    Complexity evaluation of vehicle-vehicle accident scenarios for autonomous driving simulation tests
    LI Pingfei, JIN Siyu, HU Wenhao, GAO Li, CHE Yaoyu, TAN Zhengping, DONG Xiaofei
    2022, 13(4):  697-704.  doi:10.3969/j.issn.1674-8484.2022.04.011
    Abstract ( 149 )   HTML ( 2)   PDF (2097KB) ( 162 )  

    The complexity of vehicle-vehicle accident scenarios was evaluated to solve the problem of lack of basis for selecting autonomous driving simulation test scenarios. 670 vehicle-vehicle accidents were selected from the National Automobile Accident In-depth Investigation System (NAIS) database of China. 13 variables were extracted according to different dimensions of the scenario. The complexity evaluation model of vehicle-vehicle accident scenarios was established based on information entropy theory. The logical regression was used to obtain the variable level odds ratio to calculate the level complexity, and the dimensions and variables weights of the scenario were obtained by Back Propagation (BP) neural network algorithms. The model was applied to calculate the complexity of the scenario for each accident case. The scenario complexity was divided into four levels by K-means clustering. The dominant characteristics and deaths of various scenarios were obtained. The results show that level 4 complexity scenarios account for 1.6 %, but with a mortality rate of 90.9 %, such scenarios deserve priority attention

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    Deep reinforcement learning-based lane-changing trajectory planning method of intelligent and connected vehicles
    FENG Yao, JING Shoucai, HUI Fei, ZHAO Xiangmo, LIU Jianbei
    2022, 13(4):  705-717.  doi:10.3969/j.issn.1674-8484.2022.04.012
    Abstract ( 172 )   HTML ( 9)   PDF (2779KB) ( 141 )  

    A deep reinforcement learning-based lane-changing trajectory planning method of intelligent and connected vehicles (ICVs) was proposed to improve the lane-changing safety and efficiency of ICVs and reduce fuel consumption. A hierarchical ICV lane-changing trajectory planning architecture was designed based on the functional requirements of ICVs in complex traffic scenarios. Considering vehicle safety and lane-changing efficiency, a lane-changing behavior decision model was constructed based on complete information pure strategy game. A joint optimization function representing fuel consumption and passenger comfort was also constructed with decoupling the longitudinal and lateral motion states of vehicles. And based on twin delayed deep deterministic policy gradient (TD3) algorithm, a longitudinal and lateral lane-changing trajectory planning method of ICVs was proposed to achieve the longitudinal and lateral optimized lane-changing trajectory. The effectiveness of the algorithm was verified by using 3 typical lane-changing simulation scenarios. The results show that compared with the deep deterministic policy (DDPG) algorithm, the training efficiency of the proposed method in the experiment of left lane-changing and right lane-changing is increased by about 10.5% on average, the average fuel consumption is reduced by 65% and 44%, respectively, and the single step trajectory planning time is within 10 ms, which can obtain a safe, energy-saving and comfortable lane-changing trajectory in real time.

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    Vehicle trajectory oscillation characteristics and lane width control under human natural driving conditions
    XU Jin, ZHANG Yu, DAI Zhenhua, LI Fei, CHEN Jian
    2022, 13(4):  718-728.  doi:10.3969/j.issn.1674-8484.2022.04.013
    Abstract ( 111 )   HTML ( 3)   PDF (3212KB) ( 175 )  

    A real-vehicle driving test was carried out in order to study the vehicle trajectory oscillation characteristics on an urban main road. The Caiyuanba Yangtze River Bridge and the Binjiang Road on the Yangtze River in the Chongqing city were chosen as research objects. Onboard instruments collected data on driving speed, vehicle position, and lateral distance between the vehicle centroid and the lane under natural driving conditions. The results show that most vehicles tend to deviate from the center of the lane and drive to the left. The vehicle is more inclined to move towards the road center on the bridge section. Female drivers pay more attention to controlling vehicle trajectory than male drivers. Skilled drivers have better control over vehicle trajectory than unskilled drivers on the road surface. Compared with human driving, the autonomous vehicle can control its trajectory more accurately with the trajectory lateral oscillation will be significantly reduced. The lane width of 2.75~3.00 m can meet the driving requirements of an autonomous vehicle.

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    Path tracking and remote control of driverless sweeper
    SUN Zhiwei, PEI Xiaofei, LIU Yiping, YONG Chenghao, CHEN Ci
    2022, 13(4):  729-737.  doi:10.3969/j.issn.1674-8484.2022.04.014
    Abstract ( 233 )   HTML ( 4)   PDF (3094KB) ( 792 )  

    An unmanned research was were carried out for an electric driverless sweeper to investigate the vehicle path tracking and the remote control with carrying real vehicle experiments. A prototype vehicle was modified by using wire-controlled chassis with designed the software and the hardware architecture of the driverless sweeper. The path tracking control adopted the feedforward plus feedback method, the feedforward control adopted the pure tracking method, and the feedback control used the position deviation between the vehicle and the reference path to perform sliding mode control. The results show that compared with the pure feedback control method, the vehicle position deviation under the feedforward plus feedback control method is reduced by 67.41%, the overall fluctuation of the front wheel angle is reduced by 7.56%, and the overall fluctuation of the lateral acceleration is reduced by 8.04%. The vehicle tracking accuracy under the feedforward plus feedback control method is higher, and the lateral motion is smoother. Therefore, the path tracking and remote-control scheme designed in this paper is safe and reliable, and will have good engineering application value.

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    End-to-end autonomous driving method based on multi-source sensor and navigation map
    ZHU Bo, ZHANG Jiwei, TAN Dongkui, HU Xudong
    2022, 13(4):  738-749.  doi:10.3969/j.issn.1674-8484.2022.04.015
    Abstract ( 121 )   HTML ( 3)   PDF (5620KB) ( 95 )  

    This paper proposed a multiple-input single-output (end-to-end) autonomous driving decision control model based on multi-source sensors and navigation map to make up for the shortcomings of existing end-to-end autonomous driving methods in active obstacle avoidance and passing through intersection by using the PilotNet model based on Deep Neural Network (DNN). The sensor data in model’s input end consisted of three parts: a monocular front view camera, a 2-D top view obtained by 360° multi-layer Light-Laser Detection and Ranging (LiDAR), and a local navigation map based on accurate positioning. The model’s output end generated the steering wheel angle, which was a vehicle control command. Some multi-condition simulations and real vehicle tests were conducted. The results show that the root mean square error (RMSE) of steering wheel angle decreases by 37% compared with that by using the PilotNet model. Therefore, the model has the ability of active obstacle avoidance and intersection passing.

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    Highway lane change decision control model based on deep reinforcement learning
    LI Wenli, QIU Fanke, LIAO Daming, REN Yongpeng, YI Fan
    2022, 13(4):  750-759.  doi:10.3969/j.issn.1674-8484.2022.04.016
    Abstract ( 281 )   HTML ( 4)   PDF (2809KB) ( 87 )  

    A lane change tracking control model was proposed based on the deep reinforcement learning algorithm and simulation experiments were carried out to solve the problem of safe lane change for automatic driving vehicles on highways. A model of the vehicle lane change path was built by using a quintuple polynomial approach with the tracking error functions. A three-degree-of-freedom vehicle dynamics model was fused with the deep reinforcement learning framework to build the lane change path tracking control model, which was updated by a deep deterministic policy gradient (DDPG) algorithm. The steering angle was learned for optimal lane change path tracking to control the vehicle complete the lane change process. The results show that at a speed of 100 km/h, the maximum value of the lateral position error absolute value is close to 0 with the maximum value of the angular deviation absolute value of 10 mrad controlled by using the proposed method; The lateral position error and angular error by using the proposed trajectory tracking method are smaller than that by using the traditional model prediction control method. Therefore, this model can achieve the lane change process autonomously in a high-speed environment, which is meaningful for ensuring traffic safety and alleviating traffic.

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    Automotive Energy Efficiency and Environment Protection
    Design and performance analysis of the array scroll hydrogen recirculation pump
    WANG Han, SONG Panpan, WEI Mingshan, LU Zhenbo, LI Jianwei, ZHUGE Weilin, ZHANG Yangjun
    2022, 13(4):  760-769.  doi:10.3969/j.issn.1674-8484.2022.04.017
    Abstract ( 111 )   HTML ( 3)   PDF (4298KB) ( 59 )  

    A structure scheme of array scroll was proposed based on asymmetric single arc modification to meet the requirements of the compact and large-displacement design of scroll Hydrogen Recirculation-Pump (HRP) in fuel cell hydrogen supply system. The parametric design and modeling were carried out for the HRP with double scrolls and triple scrolls. Two-dimensional Computational Fluid Dynamics (CFD) overset-mesh method was used to analyze the effects of the rotating speed and pressure rise on the performances of double-scrolls HRP, and the performance differences between the double scrolls HRP and the triple-scrolls HRP were compared. The results show that the pressure and temperature uniformity of triple-scrolls HRP is better. The performance of the double-scrolls HRP and the triple-scrolls HRP are greatly improved with the increasing rotating speeds or the decreasing pressure rising, the efficiency continues to drop by about 30% and 40% respectively when the pressure rises increase from 20 kPa to 100 kPa at design speed, and the tangential leakage and hydrogen backflow have a great impact on the performances of HRP. Under the requirements of design displacement and volume, the performances of the double scrolls HRP are better than that of the triple scrolls HRP, and the maximum efficiency difference is about 19%.

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    Optimal operating characteristics for trans-critical CO2 heat pump of new energy vehicles under different control strategies
    JIA Fan, WANG Anci, YIN Xiang, CAO Feng, LIU Hecheng
    2022, 13(4):  770-777.  doi:10.3969/j.issn.1674-8484.2022.04.018
    Abstract ( 194 )   HTML ( 4)   PDF (2667KB) ( 757 )  

    For the transcritical CO2 automotive heat pump system, the main factors affecting the optimal discharge pressure were investigated under different control strategies. The simulation model was established based on the GT-Suite simulation platform and calibrated with experimental data of heat production performance. A constant supply air temperature was used to constrain the heating capacity. The optimal discharge pressure was simulated numerically at different ambient temperatures, different supply air temperatures and different air volumes, and then compared with the constant speed control mode. The results show that there is no optimal discharge pressure in the constant speed control mode; the optimal discharge pressure increases with increasing indoor air volume, increasing ambient temperature and increasing outlet air temperature in the constant supply air control mode. The air supply temperature affects the optimal discharge pressure variation by 13.09%; the ambient temperature affects the optimal discharge pressure variation by 9.64%; the air volume affects the optimal discharge pressure variation by 5.95%. The optimal discharge pressure correlation formula is proposed based on the simulation data.

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    Compression ignition characteristics and surrogate formulation of a high reactivity low research octane number (RON) gasoline
    GUO Zexian, WANG Buyu, WANG Boyuan, ZHANG Qihang, CAI Kaiyuan, WANG Zhi, SHUAI Shijin
    2022, 13(4):  778-784.  doi:10.3969/j.issn.1674-8484.2022.04.019
    Abstract ( 210 )   HTML ( 4)   PDF (2012KB) ( 267 )  

    A surrogate design was conducted for a high reactivity low octane number gasoline (HRG) to investigate the combustion and emission characteristics of gasoline compression ignition (GCI) mode. The ignition delay times of the HRG were measured using a rapid compression machine (RCM) in the effective temperature range of 690~920 K. Kinetic modelling study was conducted using Chemkin software with 3 surrogate fuels: n-heptane/iso-octane (PRF), n-heptane/iso-octane/toluene (TRF), and iso-hexane surrogates (iso-HS) consisting of iso-hexane, n-heptane, iso-octane and toluene. The results show that compared with PRF and TRF, the iso-hexane surrogates show more obvious negative temperature coefficient (NTC) behavior; The variation amplitude of the ignition delay times within the NTC region increases approximately linearly with iso-hexane contents increasing; The surrogate iso-HS2 consisting of 49.63% iso-hexane, 18.30% iso-octane, 26.29% n-heptane and 5.78% toluene (by mole fraction) can better capture the ignition characteristics of the HRG.

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    Equivalent factor of energy management strategy for fuel cell hybrid electric vehicles based on Q-Learning
    YIN Yanli, ZHANG Xinxin, PAN Xiaoliang, ZHAN Shen, HUANG Xuejiang, WANG Fuzhen
    2022, 13(4):  785-795.  doi:10.3969/j.issn.1674-8484.2022.04.020
    Abstract ( 198 )   HTML ( 6)   PDF (3097KB) ( 492 )  

    An energy management strategy based on equivalent factor Q-learning algorithm was proposed to improve the fuel economy of fuel cell hybrid electric vehicles (FCHEVs) and maintain the battery energy balance. The objective function of minimizing equivalent hydrogen consumption and maintaining battery state of charge (SOC) was constructed to establish the energy flow conversion balance model of FCHEVs power source, and the equivalent factor of hydrogen consumption was obtained through the energy conversion balance mechanism. The transfer probability matrix of required power was solved under urban dynamometer driving schedule + world light vehicle test cycle (UDDS+WLTC) conditions, and the output power of fuel cells and batteries was optimized offline by Q-learning algorithm. The forward simulation model was established based on MATLAB/Simulink platform, and the vehicle simulation was carried out under different working conditions. The results show that the equivalent of the hydrogen consumption per 100 km is 0.730 kg under WLTC cycle conditions in the proposed strategy, which is close to that based on the dynamic programming (DP) control strategy, and the SOC is kept within a reasonable range, which verifies the effectiveness of the proposed strategy. And the adaptability of the proposed control strategy is also verified in the actual working conditions of Xining City.

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    Energy saving effect of PHEV battery cooling system with low temperature radiator
    YONG Anjiao, XIANG Yang, FU Yonghong, WANG Shuang, GUO Ting, WANG Yong
    2022, 13(4):  796-803.  doi:10.3969/j.issn.1674-8484.2022.04.021
    Abstract ( 128 )   HTML ( 10)   PDF (2524KB) ( 1568 )  

    This paper quantitatively evaluated the energy saving effect and investment cost of the plug-in hybrid electric vehicles (PHEVs) with Low Temperature Radiator (LTR) for batteries. Designed the two kinds of battery cooling architectures equipped with and without LTR and its control logic, and propose three user actual driving conditions as commuter, trip and travel. After analyzed the benefits of the two kinds of battery cooling architectures in single drive cycle and the average annual energy saving of some typical cities in China, the cost performance of the two architectures were compared. The results show that under single low load cycle, the working interval of LTR with profit is 24~27 ℃. At the user actual driving frequencies discussed, the benefit of battery cooling system with LTR is less than 3.14 CNY per year, which does not match Its cost input. It is recommend to cancel the LTR in the battery cooling system of PHEVs.

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