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  • 2026, Vol. 17 No. 2 Published on:30 April 2026 Previous issue   
    Review, Progress and Prospects
    Key materials, technology status, and prospect analysis of proton exchange membrane fuel cells for hydrogen-based electric vehicles
    LIU Yang, GUAN Sulin, QIN Ziwei, SHAO Qinsi, NI Yun, ZHAO Yufeng, ZHANG Jiujun
    2026, 17(2):  149-169.  doi:10.3969/j.issn.1674-8484.2026.02.001
    Abstract ( 42 )   HTML ( 1)   PDF (3387KB) ( 23 )  

    Guided by the “dual carbon” strategic goals, China's energy structure transformation has entered a critical phase. Hydrogen, as a clean, low-carbon, and abundant secondary energy source, has become an integral part of the national energy system. Among them, the transportation sector is a key area for achieving carbon emissions reductions. Hydrogen fuel cell vehicles, with advantages such as zero emissions, high efficiency, and rapid refueling, are widely recognized as a technically viable and scalable solution for the electrification of transportation. This paper reviews hydrogen fuel cells, primarily focusing on the working principles and core components (membrane electrode assemblies, catalysts, proton exchange membranes, etc.) of proton exchange membrane fuel cells (PEMFCs), as well as their performance. It also analyzes the scientific and technological challenges confronted with fuel cells during commercialization. The paper examines and summarizes the effects of Pt-based catalyst degradation and carbon support corrosion on catalyst activity loss, and discusses trends toward enhancing catalyst activity and reducing costs. It concludes the factors affecting the durability of proton exchange membranes (PEMs) and proposes improvement measures such as chemical modification and physical reinforcement. It also explores the impact of mechanical and chemical degradation of the gas diffusion layer (GDL) under operating conditions on durability and lifespan, and summarizes the optimization strategies for the microstructure of the GDL and water/thermal management. Regarding the policy and market environment, this paper analyzes hydrogen energy policy trends in China and some advanced nations, it also elaborates on the evolutionary paths of China's two business models: the “vehicle-station-source” closed-loop and full-chain integration, and it expounds the commercialization progress of major global economies. Finally, recommendations are proposed for China's hydrogen fuel cell vehicle industry, emphasizing that overcoming the “bottleneck” of domestic production for critical materials, improving the standards system, and establishing a full-chain innovation ecosystem encompassing “technology research and development-pilot testing-commercial application” are indispensability tasks for driving the high-quality development of the automotive PEMFC industry.

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    Automotive Safety
    Tire parameter fitting for combined conditions based on artemisinin hybrid optimization
    DING Wenhao, WANG Fei, JIN Yanxi, ZHAO Yirui, WU Tianqi
    2026, 17(2):  170-178.  doi:10.3969/j.issn.1674-8484.2026.02.002
    Abstract ( 33 )   HTML ( 4)   PDF (63723KB) ( 13 )  

    A parameter identification method, named the artemisinin hybrid optimization (AHO) algorithm, was proposed with combining the artemisinin optimization (AO) algorithm and the post-processing optimization to provide a tire model foundation for vehicle control strategies. The AO algorithm conducted the global parameter identification of the tire model based on the magic formula, using the test data from 3 conditions (the pure longitudinal slip, the pure side slip, and the combined conditions involving the tire roll, the side slip, and the longitudinal slip), before performing post-processing optimization by integrating the sensitivity analysis and the parameter significance. The results show that the AHO increases the overall accuracy of the longitudinal force by 1.83%, 1.87%, and 1.71%, and that of the lateral force by 1.62%, 3.86%, and 1.80% respectively under the combined conditions, compared with the stepwise identification method, genetic algorithm, and least squares method. Therefore, the AHO algorithm improves the identification accuracy of tire mechanical models under the combined conditions.

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    Evaluation method and influencing factor analysis of safety events for combined driver assistance system
    ZHANG Fan, YU Feng, HU Xinlei, ZHANG Zihan, ZHU Yu, JIANG Tenglong, PEI Tianxiao, SHEN Jinhua, CANG Xuejun, LI Quan, ZHOU Qing, WANG Chen
    2026, 17(2):  179-187.  doi:10.3969/j.issn.1674-8484.2026.02.003
    Abstract ( 42 )   HTML ( 1)   PDF (2219KB) ( 14 )  

    To clarify the safety boundaries and performance differences of the combined driving assistance system (CDAS), and solve the problems of single existing evaluation condition, insufficient scenario adaptation and unclear coupling mechanism of multiple influencing factors, a systematic evaluation methodology system for CDAS safety events was constructed, which integrated scenario classification, function decomposition and multi-dimensional quantification. Four mass-produced vehicle models were taken as research objects, and real-vehicle road evaluations were carried out in six cities. 36 types of sub-functions, 10 types of driving behaviors and 3 levels of scene complexity were defined in detail, and typical driver emergency intervention events were extracted through data slicing. With the driver emergency intervention disengagement rate and interval mileage as indicators, a comparative analysis was conducted on scene complexity and over-the-air (OTA) updates. The results show that there are differences in disengagement rates among different sub-function scenarios; the disengagement rate in high-complexity scenarios is 8.97%~19.88%, which is significantly higher than that in low-complexity scenarios (<5%); the disengagement rate in game scenarios is 3~7 times that in non-game scenarios; OTA improves the safety of most sub-function scenarios, while performance degradation is prone to occur in complex scenarios such as right turns at intersections, evasion, and merging/diverging. The safety performance of CDAS is jointly affected by the coupling of traffic scene complexity, game scenarios and OTA. It is suggested that a scenario-based priority matrix should be established in the algorithm iteration process, the training data should be balanced to avoid the bias effect of training.

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    Three alternative filtering methods for vehicle crash data
    Filandow E, NIE Bingbing, ZHOU Qing
    2026, 17(2):  188-199.  doi:10.3969/j.issn.1674-8484.2026.02.004
    Abstract ( 32 )   HTML ( 2)   PDF (1709KB) ( 13 )  

    Automotive crash test signal filtering is a key step in data processing. This study used vehicle body acceleration data and crash dummy head acceleration data obtained from vehicle crash tests to evaluate and compare three signal noise reduction techniques: the SAE J211 standard filter, the Moving Average(MA) method, and the Cumulative Integration. Based on the analysis of crash pulses and head acceleration data, the filtering results were directly correlated with body structure optimization and restraint system matching. The results show that the SAE filter provides precise frequency control, with a cutoff frequency of 100 Hz performing optimally in processing vehicle crash pulse acceleration data. The MA method, by obtaining the optimal window of data points, effectively removes noise while preserving key signal features. The Integration method reveals data trends through cumulative summation operations, naturally eliminating noise interference through summation. The SAE standard filter achieves a signal-to-noise ratio of 18.95 dB for crash pulse acceleration data and 30.49 dB for dummy head acceleration data; whereas the MA method based on 100 data points achieves corresponding signal-to-noise ratios of 8.59 dB and 13.82 dB, respectively. Additionally, directly integrating the acceleration signal yields smooth velocity and displacement curves. This study offers evidence-based guidance for the practical implementation of the three filtering methods under investigation.

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    Data-driven prediction and multi-parameter optimization of fatigue life of commercial vehicle drive shafts
    LIU Xiang, YIN Yuming, WU Zhiwen, DING Xiaoyu, XU Huafu, GAO Jiaqing, YANG Dasheng
    2026, 17(2):  200-208.  doi:10.3969/j.issn.1674-8484.2026.02.005
    Abstract ( 26 )   HTML ( 1)   PDF (3324KB) ( 9 )  

    A data-driven method was proposed to efficiently and accurately predict and optimize the fatigue life of vehicle drive shaft assemblies. Based on experimental testing and finite element analysis (FEA), a deep neural network (DNN) was utilized to optimize the parameters of key components. The reliability of the finite element model for the drive shaft assembly was verified through strain testing, based on which a reliable fatigue life calculation model was established. Subsequently, a fatigue life dataset under various installation conditions of different loads and spatial installation angles was constructed with the model. A DNN was then employed to extract features and construct a fatigue life prediction model. To further optimize the structural life, a multi-parameter dataset was constructed by selecting nearly 40 design dimensions from 7 key components, and a collaborative optimization of the key parameters was conducted based on the DNN prediction model. The results show that the overall fatigue life of the drive shaft assembly is significantly improved by 22.6% after the multi-parameter collaborative optimization. The proposed data-driven method can rapidly and accurately predict, as well as effectively optimize, the fatigue life of drive shafts.

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    Automotive Energy Efficiency and Environment Protection
    Thermal management system for power batteries based on flat heat pipes
    DONG Jiashuo, DAN Dan, WEI Mingshan, ZHAO Yihang, ZHANG Yangjun
    2026, 17(2):  209-217.  doi:10.3969/j.issn.1674-8484.2026.02.006
    Abstract ( 25 )   HTML ( 3)   PDF (2873KB) ( 5 )  

    For the situation where the battery pack composed of lithium-ion batteries operates under conditions with significant heat generation, a thermal management system for a power battery flat heat pipe (FHP) suitable for low temperatures (10 ℃) and high-rate discharge (2C) has been designed. A co-simulation platform combining an electrochemical-thermal coupled battery model and a multi-heat-source thermal resistance network model for the FHP was established and experimentally validated. The results show that the system reduces the battery pack's maximum temperature by 8.63 K and the temperature difference by 10.67 K, at 10 °C and 2C discharge, compared to the condition of pure air cooling. Increasing FHP total thickness from 3 mm to 7 mm lowers the maximum temperature by 8.43 K and the average temperature difference by 4.82 K. Higher external airflow enhances condenser heat dissipation, reducing maximum temperature but increasing the average temperature difference. Conversely, increasing the FHP total thickness or decreasing the dimension-one wick thickness, τw, improves the FHP thermal conductivity, with reducing both maximum temperature and average temperature difference, where, τw = tw / (tw + tv), tw is the wick thickness, tv is the vapor chamber thickness. Experiments confirm accuracy of the model.

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    In-situ measurement of heat generation performance of a high-capacity pouch lithium-ion battery
    ZHANG Xiaojun, WANG Jie, SHENG Lei, ZHANG Huanjvan, LAN Huaiyu, ZHOU Qinjian, WANG Jian, SHI Junming, SUN Xuhui
    2026, 17(2):  218-224.  doi:10.3969/j.issn.1674-8484.2026.02.007
    Abstract ( 27 )   HTML ( 1)   PDF (2214KB) ( 6 )  

    An in-situ measurement method with heat-compensated was proposed considering heat loss factors to investigate the heat generation performances of the high-capacity pouch lithium-ion batteries under two charging and discharging conditions, the one without forced air cooling and thermal insulation, and the other with forced air cooling. The results show that the battery heat generation rate curves exhibit a U-shaped pattern of “high-low-high” under the heat preservation conditions; The heat generation rate curve shows an in-creasing trend of “fast-slow-fast” under the forced air-cooling conditions; The meas-urement accuracy considering heat loss reaches 93.5% compared to the conditions considering no heat loss; The heat generated under the conditions with no forced air cooling and heat preservation, increases by 4.74%, 11.56%, and 16.25% respectively when battery discharging at 0.7 C, 1.0 C, and 1.2 C, compared to the forced air-cooling conditions. Therefore, this method can provide a reference for the accurate characteri-zation of the heat generation performances of pouch batteries under the charging and discharging conditions of heat preservation and forced air-cooling.

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    Thermal comfort optimization of automotive passenger cabin enabled by concealed air vent design
    CHENG Zhenbo, LONG Zihang, PENG Tenghua, SUN Yachao, WANG Quansheng
    2026, 17(2):  225-235.  doi:10.3969/j.issn.1674-8484.2026.02.008
    Abstract ( 30 )   HTML ( 3)   PDF (6530KB) ( 6 )  

    To investigate the influence of the novel hidden air outlet on the thermal comfort of an automotive passenger cabin, computational fluid dynamics (CFD) was employed to numerically simulate the internal airflow field. The built-in thermal comfort model of STAR-CCM+ combined with user-defined field functions was used to analyze the airflow, temperature field, and thermal comfort characteristics of the cabin under different air-supply parameters. Furthermore, the design of experiments (DOE) method and a Kriging surrogate model were applied to optimize the geometry of the hidden air outlet. The results indicate that the air-supply volume has a significant effect on the cabin temperature distribution and air quality. The optimized hidden air outlet effectively improves the airflow distribution, enhances the uniformity of temperature and velocity fields, and increases overall air-circulation efficiency. Consequently, the overall equivalent temperature deviation ηAEQT rises by 47.2%, demonstrating a notable improvement in driver thermal comfort.

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    Performance analysis and its experiments of turbochargers with 3 types of cooling structures
    ZHANG Chaowei, LI Song, LÜ Baicang, KANG Xiuchen, DING Kaifang, BAI Yachen, WANG Ziyi
    2026, 17(2):  236-243.  doi:10.3969/j.issn.1674-8484.2026.02.009
    Abstract ( 28 )   HTML ( 1)   PDF (2860KB) ( 8 )  

    A combined simulation and an experimental approach were adopted on a marine power platform and compared the cooling characteristics of three turbocharger exhaust devices: dry-type (DTC), single water-cooled (SWC), and double water-cooled (DWC), to optimize the thermal management strategy of turbochargers and to balance the energy-saving and the emission performances. The results indicate that while the DWC scheme significantly reduces the exhaust pipe outlet temperature by 32 ℃, its filter smoke number (FSN) of 1.6 exceeds the national standard limit of 1.5, and its brake specific fuel consumption (BSFC) of 203.8 g/kWh is approximately 3.8% higher than that of the DTC scheme (196.4 g/kWh). In contrast, the SWC scheme maintains a reasonable exhaust pipe outlet temperature of 418 ℃, achieves an FSN of 1.17 which complies with emission regulations, and has a BSFC of 204.9 g/kWh comparable to the DWC scheme. Consequently, the SWC scheme achieves the best balance among thermal management, emission compliance, and fuel economy, making it the optimal engineering solution with the best comprehensive performance.

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    Design and performance study of integrated thermal management system for electric vehicles based on energy storage box
    WU Xiangcheng, GUO Junxuan, CHEN Huayu, SU Liangbin, LU Jin
    2026, 17(2):  244-252.  doi:10.3969/j.issn.1674-8484.2026.02.010
    Abstract ( 33 )   HTML ( 1)   PDF (1955KB) ( 10 )  

    An integrated thermal management system based on an energy storage tank incorporating highly integrated circuit was developed to meet the temperature control needs of the passenger compartment and the battery in high and low temperature environments and to reduce the energy consumption of the thermal management system. The influence of the energy storage tank on the thermal management system's performance was investigated across various operating conditions. The results show that the energy storage tank can reduce system energy consumption by storing energy. At -20 °C and 40 °C, and the initial temperature of the energy storage tank is set to 17.6 °C and 22.2 °C, respectively, the system's energy consumption is reduced by approximately 34.44% and 28.27%; Compared to a distributed thermal management system, the integrated system reduces hundred kilometer power consumption by 3.56% during winter, improves the coefficient of performance (COP) by 18.55%, and effectively mitigates temperature fluctuations under step conditions. Consequently, the integrated design of energy storage tank is an important means of improving the energy efficiency and temperature stability of vehicle thermal management systems.

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    Influence of hydrogen supply strategies on the performance of air-cooled proton exchange membrane fuel cell stacks
    XU Jianjun, QIAO Wenshan, LIU Ying, WANG Zhifeng
    2026, 17(2):  253-260.  doi:10.3969/j.issn.1674-8484.2026.02.011
    Abstract ( 22 )   HTML ( 1)   PDF (2195KB) ( 4 )  

    A bidirectional hydrogen supply strategy and an alternating hydrogen supply strategies were proposed to enhance the operational of air-cooled proton exchange membrane fuel cell (PEMFC) stacks. A combined methodology of numerical simulation and experimental calibration was employed to systematically investigate the distributions of hydrogen concentration and membrane water content within the PEMFC stacks, as well as the corresponding stack output characteristics under all different strategies. The results show that the bidirectional strategy achieves the highest uniformity of hydrogen distribution across the anode catalytic layer, with a maximum hydrogen mass fraction difference of 0.27, significantly lower than the 0.46 observed under the conventional unidirectional strategy. The alternating strategy yields the most uniform water distribution in the proton exchange membrane, markedly outperforming the unidirectional strategy. In the high current density regions, as the load current density increases, the differences in output voltage of the stack under the three strategies become progressively more pronounced; the alternating strategy delivers the superior electrochemical performance, followed closely by the bidirectional strategy. At a current density of 0.5 A/cm2, the alternating strategy exhibits a maximum voltage fluctuation of 3.4 mV and a current density standard deviation of 140.2 mA/cm2, while the bidirectional hydrogen supply strategy has 2.7 mV, and 136.1 mA/cm2, respectively, demonstrating the improved voltage stability and the marginally better current distribution uniformity, thereby outperforming both the other strategies under high-load conditions. The experimental results validate the quantitative accuracy of the simulated performance trends for the bidirectional strategy, thereby confirming its technical feasibility and practical potential.

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    Intelligent Driving and Intelligent Transportation
    Vehicle speed planning method with the vehicle-road-cloud integration system and incorporating human-vehicle game theory
    WEN Jiayan, ZOU Haifeng, ZHONG Wei, GAO Bolin, LU Yanbo
    2026, 17(2):  261-269.  doi:10.3969/j.issn.1674-8484.2026.02.012
    Abstract ( 27 )   HTML ( 2)   PDF (2875KB) ( 9 )  

    The vehicle-pedestrian interaction (VPI) for autonomous vehicles was investigated to resolve the conflicts between the driving continuity and the safety caused by sudden pedestrian crossing. A Social Force model was constructed for pedestrian crossing with roadside perception and cloud-side historical information to characterize the pedestrian behaviors and to deliver the corresponding data to on-board terminals. A two-layer collaborative decision-making and control strategy was proposed with its upper layer introduced the Stackelberg game model and with its lower layer adopted an improved model predictive control (MPC). The lower layer took upper-layer game results as the trajectory optimization objective. Simulation experiments were conducted on VPI scenarios in uncontrolled urban road segments. The results show that the proposed method reduces interaction time by 0.59 s and 0.27 s respectively, compared with the single obstacle avoidance control (OAC) method and the MPC method; improves traffic light passing rate by 6.2% and 2.9% respectively, compared with the above two control methods. Therefore, the proposed method improves the efficiency and the safety of vehicles within limited traffic time window, and can simulate the vehicle-pedestrian collaboration and conflict scenarios.

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    Human-machine interface design methods in autonomous driving takeover scenarios based on the Trust Theory
    XUE Qingyuan, QU Jue, WANG Wei, NIU Tianlin, LI Xing
    2026, 17(2):  270-277.  doi:10.3969/j.issn.1674-8484.2026.02.013
    Abstract ( 28 )   HTML ( 2)   PDF (3599KB) ( 9 )  

    A human-machine interface (HMI) interface design method was proposed based on the dynamic Trust Theory to improve the safety at autonomous driving takeovers. The trust levels were classified into three categories: the insufficient trust, the calibrated trust, and the over-trust. A hierarchical situation-aware transparency (SAT) interface was designed, and an empirical investigation was conducted in high-speed lane-changing scenarios. The eye-tracking data were recorded and analyzed by aligning event lock timing (ELT) with critical time windows (CTW), and the subjective evaluations were carried out through questionnaires. The results indicate that the interface optimized through the trust mechanism reduced drivers' takeover response time (RT) by 26.71% compared to the original interface, thereby enhancing safety margins during critical moments; it also decreased the incidence of delayed takeovers from 23.7% to 9.2%, reducing potential collision risks. Therefore, these results would provide a methodological reference for the engineering application of intelligent cockpit HMIs.

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