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    Research progress and prospect on safety of all-solid-state batteries
    GUO Chunli, TANG Shengkai, CUI Yu, MAO Yuqiong
    Journal of Automotive Safety and Energy    2025, 16 (5): 657-678.   doi:10.3969/j.issn.1674-8484.2025.05.001
    Abstract782)   HTML840)    PDF (3718KB)(3429)      

    All-solid-state batteries (ASSBs) possess potential performance advantages, such as high safety and high energy density, making them a strategic frontier in global power battery technology competition, which has been incorporated into the development strategies of major countries including China, the United States, Japan, South Korea, etc. Currently, the research & development of ASSBs has entered a critical breakthrough phase, with the leading enterprises such as Toyota, BYD, and CATL expecting to initiate the applications of ASSBs in electric vehicles around 2027. However, before large-scale application, comprehensive performance evaluation and failure analysis of ASSBs are still required to ensure their safe and reliable operation under complex working conditions in electric vehicles. Notably, existing research indicates that ASSBs still suffer from risks of thermal runaway and are not absolute safe, as their failure mechanisms under complex operating conditions remain inadequately understood. In light of this, this paper systematically reviews the potential safety issues of ASSBs from the perspectives of materials, interfaces, and cell design, including the intrinsic thermal stability of key materials such as cathodes, anodes, and solid state electrolytes; high-temperature thermochemical reactions at the cathode/anode-electrolyte interfaces; lithium dendrite growth and the resulting internal short circuits; and toxic gas production and environmental hazards during battery failure. Building on this analysis, the paper further outlines future research strategies for the safety of ASSBs from the perspectives of in-depth failure-mechanism analysis, optimization of key materials and interfacial stability, and system-level gas management and thermal protection, thereby offering systematic theoretical support and practical guidance for their safety assessment and engineering deployment.

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    Safety and protection technologies for intelligent vehicles with strongly coupled structural, functional and information domains
    ZHAO Jian, GONG Jue, FAN Kefeng, LIU Pengbo, LI Linhui, WANG Xiang, XU Zheng, DONG Zeyuan, YAO Nianmin
    Journal of Automotive Safety and Energy    2025, 16 (6): 813-831.   doi:10.3969/j.issn.1674-8484.2025.06.001
    Abstract370)   HTML1620)    PDF (3355KB)(216)      

    Intelligent-vehicle structures are highly integrated with sensors, electronic systems, in-vehicle networks, communications, and cloud services, and these components interact strongly with each other. Such integration results in a pronounced fusion between physical structure and vehicle functions. Accordingly, the associated safety technologies have evolved into a strongly coupled framework that integrates structural safety, functional safety, and information security. This trend may have profound impacts on individuals, industries, and even national strategic interests. With data-flow transmission and interaction taken as the main thread, a comprehensive safety architecture with strong coupling across the structural, functional, and information domains is systematically reviewed. Major gaps are identified, including insufficient adaptability to extreme scenarios, an incomplete understanding of cross-domain coupling mechanisms, and inadequate full life-cycle safety assurance. The coupling between structural dynamic responses under multi-source disturbances and abnormal behaviors in electronic subsystems (perception, control, and connectivity) is further examined. On this basis, a strongly coupled structure-function-information safety and protection approach is proposed, and a safety detection and evaluation mechanism is established by explicitly considering cross-domain parameter interactions. The proposed mechanism supports multi-source risk linkage analysis, coordinated strategy management and control, and quantitative safety assessment. These results can serve as a technical reference for the large-scale deployment of intelligent vehicles and the improvement of related safety standards.

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    Robust model prediction based clamping force control for electro-mechanical braking systems
    ZHANG Rongyu, ZHAO Xuan, WANG Shu, LI Meiying
    Journal of Automotive Safety and Energy    2025, 16 (6): 832-842.   doi:10.3969/j.issn.1674-8484.2025.06.002
    Abstract339)   HTML247)    PDF (2170KB)(142)      

    A robust model predictive control (RMPC) strategy based on an active disturbance rejection extend state observer (ESO) was proposed to improve the robustness and tracking accuracy of clamping force control in an electro-mechanical brake (EMB) system. Firstly, electrical disturbances, mechanical disturbances, and environmental disturbances inherent in the EMB system were analyzed, and a mathematical model incorporating a lumped disturbance term was established. Secondly, an EMB clamping force control strategy based on RMPC was formulated, introducing an active disturbance rejection ESO to estimate and compensate for disturbances. Finally, a hardware-in-the-loop (HIL) experimental platform was developed to validate the proposed method. The results show that the EMB clamping force controlled solely by MPC exhibits significant fluctuation under load disturbance, with a maximum error of 228 N and a maximum error rate of 5.7%; In contrast, the clamping force under the combined RMPC with ESO action shows a maximum steady-state tracking error of only 38 N, with a maximum error rate of 1.52%, indicating that the proposed control strategy effectively suppresses disturbance effects, which can achieve high clamping force tracking precision and strong anti-disturbance capability.

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    Effect of vehicle crash severity and advanced restraint system parameters on occupant injuries
    DENG Gongxun, CAI Yani, LEI Feibing, LIU Hengjin, QI Lulin, FAN Yubo
    Journal of Automotive Safety and Energy    2025, 16 (5): 698-706.   doi:10.3969/j.issn.1674-8484.2025.05.004
    Abstract283)   HTML140)    PDF (2668KB)(380)      

    Aiming at the matching problem of advanced restraint system in vehicle crashes, the distribution frequencies of vehicle Occupant Load Criterion (OLC) and the advanced restraint system parameters during the frontal rigid barrier collisions conducted over the recent three-year of a company were statistically analyzed. A Finite Element (FE) for crash simulation matrix was established. The Kruskal-Wallis non-parametric test and the Spearman correlation analysis methods were used to investigate the vehicle OLC effect and the restraint system parameters on occupant injuries. The results show that the increased OLC significantly increases the occupant injuries severities (the correlation coefficient ρ=0.66, the significance p value<0.01) while the airbag vent size and the retractor TTF (time to fire) cannot significantly affect occupant injuries. The increased seatbelt first-level load limiter mitigates head injury but increases chest compression. Using the Pyrotechnic Lap Pretension (PLP) to pretension lap belt and the Crash Locking Tongue (CLT) to cut off the transfer of seatbelt forces can slightly decrease the chest compression. Moreover, the occupant hip restraint is enhanced and the movements of hip and legs are reduced, which alleviate the vehicle interior-leg impact severity and significantly reduce the lower limbs injury risks.

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    Analysis of collision patterns in truck-bicycle accidents on injuries and the kinematic of rider
    ZHENG Wenxiang, WANG Bingyu, YANG Yao, GONG You, QIN Liyan
    Journal of Automotive Safety and Energy    2025, 16 (6): 859-866.   doi:10.3969/j.issn.1674-8484.2025.06.005
    Abstract279)   HTML404)    PDF (2346KB)(126)      

    The relationship between collision patterns in truck-versus-electric-two-wheeler crashes, the kinematic responses of riders, and injury characteristics were investigated. 16 simulation experiments were constructed by using the multi-body modeling software MADYMO based on 263 scenario-related cases to analyze the collision angles and the positions. The results show that the head injury metrics (the head injury criterions (HIC) and the head angular accelerations) sharply increase when the collision angles exceeds 110°, with the peaking at the collision angle of 120° (the HIC of 11 931, the head angular acceleration of 73.9 krad/s2). When the collision position is in the central area of the truck, the cyclist’s HIC (1 231~1 461) and the head angular acceleration (22.6~26.9 krad/s2) fall within lower ranges, that means lower risk of head injury. When the collision occurs on either side of the truck, the cyclist’s chest 3-ms acceleration is 25.8g~121.8g, that means a lower risk of chest injury. Therefore, both the collision angle and the collision position have a significant impact on the cyclist’s kinematic response.

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    Hierarchical energy management strategy for PHEVs based on segmented SOC trajectory prediction
    DAI Lihong, JIN Nini, MO Zonghua, HU Peng, WAN Wenjun, LIU Haoye, WANG Tianyou
    Journal of Automotive Safety and Energy    2025, 16 (5): 736-746.   doi:10.3969/j.issn.1674-8484.2025.05.008
    Abstract278)   HTML75)    PDF (5607KB)(155)      

    A hierarchical energy management strategy-adaptive initial equivalent factor strategy (HEMS-AIEFS) was proposed to achieve near-global optimal energy allocation under real driving conditions. HEMS-AIEFS adopted a two-layer structure: The upper layer implemented a node-split state-of-charge (SOC) planning method for batteries, which used a dynamic programming (DP) algorithm to generate the relevant data for training neural network models. These models can predict the SOC node trajectories of different road sections in real time; In the lower layer, the predicted equivalent consumption minimization strategy (P-ECMS) was used to track the predicted SOC trajectories, in which the adaptive initial equivalent factor strategy (AIEFS) was added to set the initial equivalent factor (EF0). The results show that the proposed AIEFS reduces fuel consumption by 2.36% to 7.69% compared to the conventional method of determining the initial equivalence factor, and that HEMS-AIEFS saves 1.56% to 9.13% of fuel consumption under different operating conditions comparing to the CD-CS strategy and requires 4.9% to 5.6% of the computation time of the DP algorithm. This study provides an effective optimization method for plug-in hybrid elective vehicle (PHEV) energy management optimization and demonstrates the potential application of navigation information in PHEV energy management optimization.

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    Research on electrical vehicle's sliding mode in small overlap impact crash test
    LI Yixuan, WU Xiao, TANG Kai, LI Zheng
    Journal of Automotive Safety and Energy    2025, 16 (6): 867-876.   doi:10.3969/j.issn.1674-8484.2025.06.006
    Abstract269)   HTML75)    PDF (3782KB)(220)      

    To achieve lateral displacement control of pure electric vehicle models during the safety development process for small offset frontal collisions, a combined simulation and experimental approach ware employed to identify the key structural factors influencing lateral displacement, and to investigate the design methodology and evaluation metrics for front compartment configurations associated with such displacement behavior. Taking a certain type of pure electric architecture sedan of the company as an example, an optimization plan was designed. The results indicate that the proposed scheme increases the lateral displacement of the vehicle during collision disengagement by 236 mm, reduces the maximum structural intrusion by 119 mm in the structural rating assessment, achieves controlled vehicle sideslip. And the G rating is met, validating the effectiveness of the evaluation index, and providing a valuable reference for the development of small-overlap safety strategies in new energy vehicle programs.

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    Active grille shutter technology for hybrid electric light-duty trucks based on computational fluid dynamics
    ZHENG Songfeng, QIAN Duode, GONG Zhen, QIAN Yejian
    Journal of Automotive Safety and Energy    2025, 16 (5): 757-765.   doi:10.3969/j.issn.1674-8484.2025.05.010
    Abstract268)   HTML78)    PDF (3174KB)(85)      

    The application of active grille shutter (AGS) technology was investigated to address the challenge of traditional fixed grilles in hybrid commercial vehicles failing to dynamically adapt to differentiated thermal management demands under dual-heat-source coupling conditions. The impact of AGS de-flection orientation and angle on the aerodynamic and thermal balance performance of a hybrid light truck was analyzed using computational fluid dynamics (CFD) simulations. And an optimized AGS control strategy was proposed to enhance heat dissipation efficiency while reducing aerodynamic drag, thereby balancing energy consumption and thermal regulation requirements in complex oper-ating scenarios. The results show that the full operating condition of AGS can significantly increase the air intake of the intercooler and radiator, improving the thermal balance performance. The lower deviation of the AGS blades can guide the airflow to the cooling components, and avoid complex chassis parts, resulting to enhance the heat transfer situation and reduce the drag coefficient by about 2.85%. Under the conditions of 50 km/h climbing and 110 km/h high-speed, setting 60° and 75° grille opening can meet the heat transfer needs of the hair cabin, but also reduce the wind resistance coefficient of about 3.21% and 3.88%, respectively. Therefore, it is an important technical means to improve the thermal balance performance and energy consumption state to carry out the AGS optimal matching design and to associate the AGS control strategy on the hybrid light truck model.

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    Distribution of body regions of multiple injuries in vulnerable road users based on real collisions accidents
    WANG Hanying, PAN Di, LI Zhuo, LIU Hui, HAN Yong
    Journal of Automotive Safety and Energy    2025, 16 (6): 843-850.   doi:10.3969/j.issn.1674-8484.2025.06.003
    Abstract264)   HTML101)    PDF (1450KB)(154)      

    The distribution of multiple injuries across body regions of vulnerable road users (VRUs) in vehicle collision accidents was investigated to provide data support for assessing accident occurrence probabilities. 159 cases of in-depth traffic accident were selected from the existed VRU traffic accident database with video (VRU-TRAVi). The impact velocities were acquired by using the method of Direct Linear Transformation (DLT) and the frame-by-frame video analysis. The body injury regions were evaluated by using the Abbreviated Injury Scale (AIS) and the Maximum Abbreviated Injury Scale (MAIS). The results show that the head and the lower limbs are the most common sites of injury. The head injuries total 139 cases, accounting for 87.4% of the total. Lower limb injuries reach 111 cases (69.8%), with the severity being classified into three grades: the minor (AIS 1), the moderate (AIS 2), and the serious (AIS 3). Dual-site/triple-site injuries reach AIS 2 or above, the combination of the head-thorax and abdomen/the head-thorax and abdomen-lower limbs is the most frequent, accounting for 49.0% and 58.8%. The highest proportion of cases is the Maximum Absolute Injury Severity (MAIS) score of 6 in the head region, accounting for 95.7% of all MAIS 6 cases, it is also the primary cause of fatalities in VRUs.

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    Effective area estimation method based on performance degradation mechanism of rolling-lobe air springs
    WU Mingyu, WANG Yafei, CHEN Junjie, ZHONG Hong, LI Yaochao, WEI Yintao, LIU Xiang, ZHANG Yifei
    Journal of Automotive Safety and Energy    2025, 16 (5): 679-687.   doi:10.3969/j.issn.1674-8484.2025.05.002
    Abstract261)   HTML200)    PDF (1860KB)(139)      

    An effective area prediction model was built based on composite material theory and fatigue degradation mechanisms to predict the dynamic response behaviors of rolling-lobe air springs over their full lifecycle. The evolving fatigue characteristics of cords and rubber materials were introduced to establish a multi-physical coupling relationship, in which the effective area was modeled as a function of the fatigue cycles and the deformation excitation amplitude under force. Dynamic validation tests were carried out under different fatigue cycles and deformation excitation amplitudes. The results show that the model prediction error is within 1% at different degradation stages. The effective-area increases with both the fatigue cycles and the deformation excitation amplitude; but decreases with the elastic modulus of the cords and the rubber materials. The effective-area growth trend at 50 °C accelerates and exhibits nonlinear characteristics.

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    Review of LiDAR-based SLAM methods
    LIU Kaiqi, KANG Fuxiang, LI Wei, GAO Bolin
    Journal of Automotive Safety and Energy    2026, 17 (3): 279-295.   doi:10.3969/j.issn.1674-8484.2026.03.001
    Abstract259)   HTML220)    PDF (4940KB)(87)      

    As the core technology of robot navigation and environment perception, LiDAR-based simultaneous localization and mapping (SLAM) technology has been widely used in the fields of autonomous driving, drones, robots and so on. This paper summarizes the basic framework and key technologies of LiDAR-based SLAM, and focuses on the point cloud processing, front-end data registration, back-end optimization and closed-loop detection steps of LiDAR. It further reviews classical LiDAR-based SLAM methods and their corresponding improvements, discusses their technical innovations, and reveals the developmental trajectory and research trends of LiDAR-based SLAM, namely the transition from single-sensor-driven systems to multi-sensor fusion, from traditional geometric constraints to enhanced semantic understanding, and from local pose estimation to global consistency optimization. Meanwhile, an indoor 3D mapping experiment was conducted using a Livox HAP LiDAR to validate the effective support of high-precision maps constructed by SLAM for environmental perception tasks. Experimental results show that point cloud maps obtained through LiDAR-based SLAM can not only reconstruct the spatial structure of a scene with relatively high accuracy, but also provide a reliable data foundation for downstream tasks such as semantic segmentation, thereby demonstrating the significant application value of LiDAR-based SLAM in perception systems. Finally, the paper discusses the development potential of LiDAR-based SLAM in directions such as deep learning, neural radiance fields, and multi-sensor fusion, and points out that challenges remain in dynamic environment adaptation, the trade-off between real-time performance and accuracy, and large-scale engineering deployment.

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    A coupled decision-making and trajectory planning approach for vehicle emergency collision avoidance in multi-obstacle scenarios
    GUAN Yongxue, LIU Senhai, HAN Yong, XU Li, SHU Weibin, FAN Chenxu
    Journal of Automotive Safety and Energy    2025, 16 (6): 945-954.   doi:10.3969/j.issn.1674-8484.2025.06.014
    Abstract249)   HTML53)    PDF (2058KB)(96)      

    An integrated framework coupling decision-making with trajectory planning was proposed to enhance the emergency collision avoidance capability of vehicles in high-speed multi-obstacle scenarios and address the challenge of real-time responsiveness in decision-making and planning due to computational complexity. The high-dimensional game problem was simplified into a sequence of single-obstacle interaction processes by establishing a multi-vehicle non-cooperative game model to describe dynamic interactions and designing a sequential decision-making mechanism based on threat assessment. A graphics processing unit (GPU)-accelerated trajectory optimization algorithm was implemented using the open source machine learning framework PyTorch, generating safe and comfortable collision avoidance trajectories while satisfying vehicle dynamic constraints. The results show that the average decision-making computation time of the proposed method in typical high-speed scenarios is 20~50 ms, and trajectory planning takes 33.1~149.1 ms, outperforming traditional model predictive control (MPC) methods. The lateral velocity and acceleration of the planned trajectories are controlled within 4.0 m/s and 4.0 m/s2, respectively, meeting safety and comfort requirements. When tracking the planned trajectories, the maximum lateral tracking error and speed error are 0.22 m and 0.59 m/s, respectively, fulfilling the requirements for high-speed emergency collision avoidance. In CARLA simulations, successful collision avoidance is achieved in all scenarios. The conclusion demonstrates that the proposed framework effectively balances decision-making optimality and real-time performance, providing a reliable solution for vehicle active safety in complex scenarios.

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    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
    Journal of Automotive Safety and Energy    2026, 17 (2): 149-169.   doi:10.3969/j.issn.1674-8484.2026.02.001
    Abstract243)   HTML85)    PDF (3387KB)(323)      

    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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    Materials underpin BIW safety: SMARTeX innovation practices of Baosteel automotive sheet
    BAO Ping, JIA Fanghui, HAN Fei
    Journal of Automotive Safety and Energy    2026, 17 (3): 296-313.   doi:10.3969/j.issn.1674-8484.2026.03.002
    Abstract236)   HTML261)    PDF (6221KB)(101)      

    With the global automotive industry transitioning toward electrification and intelligence, and with the continuous advancement of vehicle safety assessment systems, automotive body safety technologies are evolving from traditional passive safety concepts to a comprehensive and systematic safety framework integrating active and passive safety, intelligence and information security, and low-carbon safety. This paper reviews the development of vehicle crash safety regulations and assessment programs both domestically and internationally. From the perspective of body safety, it summarizes the evolution of automotive materials from conventional steels to advanced high-strength steels (AHSS). Taking Baosteel automotive steel products as the example, the technical characteristics and body applications of all three-generations AHSS is introduced. Furthermore, from the perspective of advanced manufacturing technologies such as forming and joining, the critical role of synergistic innovation between material properties and manufacturing processes in enhancing vehicle safety performance is discussed. On this basis, Baosteel's “SMARTeX” safety innovation practice is introduced, which establishes a comprehensive vehicle body safety solution featuring a three-layer, seven-dimensional framework encompassing body-in-white (BIW), assemblies, components, joining, corrosion protection, digital intelligence, and low-carbon safety. Finally, the paper provides perspectives and discussions on the future development of vehicle body safety technologies, emphasizing that the realization of a safe vehicle body relies on the combined intelligence of structural design and material application. Material innovation plays a vital supporting role in body safety and overall vehicle safety development, as well as in the coordinated advancement of high safety, lightweighting, and low-carbonization within the automotive industry.

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    Mental workload variations of drivers navigating over the differential types of interchange ramps
    LIANG Yuchen, DUAN Weijian, ZHANG Shi, ZHU Xinglin, XU Jin
    Journal of Automotive Safety and Energy    2025, 16 (6): 851-858.   doi:10.3969/j.issn.1674-8484.2025.06.004
    Abstract236)   HTML109)    PDF (1590KB)(80)      

    Interchange ramp areas present complex environments where drivers' mental workload varies significantly. The drivers' mental workloads were analyzed while they crossed different interchange ramp types, with the data of driver heart rates being collected by real-vehicle experiments. A mental workload evaluation system was established by using dual-modal electrocardiogram indicators (the HR (heart rate) and the HRV (heart rate variability)). The results show that drivers experience higher mental workload in hub interchange ramps than that in general interchange ramps. Within interchanges, the mental workload is the highest in small-radius loop ramps, followed by the left-turn semi-directional ramps, and the lowest in right-turn directional ramps. Drivers also exhibit greater tension in hub interchange scenarios. The mental workload demonstrates a significant negative correlation with ramp radius. The authors recommend installing deceleration signs in advance on hub interchange sections.

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    Fault-tolerant and safety control of intelligent connected vehicles under stealthy network attacks
    QIU Zhaoyu, ZHU Xiaoyuan, TIAN Guangyu, YIN Guodong
    Journal of Automotive Safety and Energy    2025, 16 (6): 914-922.   doi:10.3969/j.issn.1674-8484.2025.06.011
    Abstract222)   HTML11)    PDF (8563KB)(90)      

    An adaptive neural network control method integrated with dynamic watermark-based attack detection to enhance vehicle safety was proposed to address the dual safety threats of actuator faults and stealthy replay attacks in intelligent connected vehicles. An adaptive fault-tolerant controller with disturbance rejection capability was designed by integrating a radial basis function neural network (RBFNN) and a nonlinear disturbance observer (NDO). Additionally, a dynamic watermark sequence was embedded into the control loop, and an attack detection mechanism was constructed based on system residuals to identify covert replay network attacks. Finally, hardware-in-the-loop (HIL) validation was conducted using a dSPACE-NI co-simulation platform. The results show that the average error during the fault is reduced by 80.71%, comparing with the non-fault-tolerant controller. Furthermore, stealthy replay attacks are successfully detected, and the presence of faults enhances the detection effectiveness without causing false alarms.

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    From decoupling to synergy: A paradigm shift in data and computation co-scheduling for intelligent connected vehicles
    YUAN Hong, HUANG Kaisheng, TIAN Guangyu
    Journal of Automotive Safety and Energy    2026, 17 (1): 1-17.   doi:10.3969/j.issn.1674-8484.2026.01.001
    Abstract217)   HTML33)    PDF (1586KB)(812)      

    Intelligent vehicle cyber-physical systems (IVCPS) are pivotal for transcending the limitations of single-vehicle intelligence, yet their performance is constrained by the conflict between massive data demands and dynamic, scarce communication and computation resources. This conflict stems from the strong coupling between data flow scheduling and computation task scheduling. Prevailing research often adopts a decoupled approach by optimizing these two aspects independently, overlooking the resultant systemic performance bottlenecks and lacking a comprehensive framework for Data-Computation Co-Scheduling. Therefore, this paper systematically reviews the paradigm shift in IVCPS scheduling from resource-driven independent optimization to task-driven integrated co-design. It dissects the evolution of coordination mechanisms, from explicit coordination to implicit fusion, and identifies key future research directions, particularly in applying multi-agent reinforcement learning to resolve distributed resource conflicts and ensuring the trustworthiness of artificial intelligence (AI) decisions. This study aims to establish a clear theoretical framework for the core issue of data-computation co-scheduling, providing crucial theoretical and technical support for the architectural design of next-generation intelligent transportation systems and advanced autonomous driving.

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    Aerodynamic drag optimization design of a commercial battery electric pickup truck
    CHEN Chunju, LI Xiaohua, YU Xianzhong, QI Qi, ZOU Jiayi
    Journal of Automotive Safety and Energy    2025, 16 (6): 896-904.   doi:10.3969/j.issn.1674-8484.2025.06.009
    Abstract214)   HTML18)    PDF (3138KB)(212)      

    A modular optimization scheme for aerodynamic components was proposed to enhance the performance of a commercial pure electric pickup truck built on a traditional fuel vehicle platform. The research combined computational fluid dynamics (CFD) simulation, wind tunnel testing, and coast-down testing to analyze, optimize, and validate the vehicle's aerodynamic performance. The simulations using STAR-CCM+ software identified an excessively high front face, an uneven underbody, and poor sealing to be the three major sources of aerodynamic drag. The investigation focused on eight key components, including the front air dam, side steps, and roof rack, to examine their aerodynamic effects and drag reduction mechanisms. The results indicate that the optimized design reduces the drag coefficient (Cd) by 21.06% in CFD simulations and by 20.6% in wind tunnel tests. The deviation of less than 3% between these values confirms the reliability of the CFD model. Coast-down tests further demonstrates a 6.3% increase in driving range. This work provides practical engineering methodologies and experimental evidence for the aerodynamic development of commercial “fuel-to-electric” converted pickup trucks.

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    Trajectory tracking control based on adaptive prediction time-domain MPC
    ZHENG Xunjia, CAO Zeyi, CHEN Xing, LIU Hui, GAO Jianjie
    Journal of Automotive Safety and Energy    2025, 16 (5): 773-783.   doi:10.3969/j.issn.1674-8484.2025.05.012
    Abstract213)   HTML9)    PDF (2467KB)(129)      

    A trajectory tracking control algorithm integrating fuzzy control strategy with time-domain adaptive adjustment model predictive control (MPC) was proposed. to address the issue that road curvature and vehicle speed information are usually not considered in autonomous vehicle trajectory tracking control, and to suppress lateral deviations during vehicle trajectory tracking while enhancing the anti-interference ability of the control system, A vehicle kinematic model and a model predictive controller were established, different speed conditions were designed, road curvature and desired vehicle speed were taken as fuzzy control inputs, and the prediction horizon parameters of the MPC algorithm were optimized via the fuzzy controller. Joint simulations using Carsim and Simulink were carried out to implement trajectory tracking control at different speeds on two trajectories with distinct curvatures. The results show that, in the double lane change scenario, compared with the fixed-horizon controller and linear quadratic regulator (LQR), the adaptive time-domain MPC controller achieves a maximum reduction of 85.81% and 78.86% in lateral errors at low speed (30 km/h) and high speed (90 km/h) respectively; in the multi-curve scenario, it realizes a maximum reduction of 96.32% and 86.4% in lateral errors at low speed and high speed respectively. These findings confirm that the proposed control strategy can significantly improve the system's tracking performance, effectively reduce trajectory deviations and maintain the dynamic stability of the vehicle under different speed conditions.

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    Research on global optimal control strategy for hybrid power system with composite energy storage
    LI Zhao, LONG Wuqiang, TIAN Hua
    Journal of Automotive Safety and Energy    2025, 16 (6): 877-885.   doi:10.3969/j.issn.1674-8484.2025.06.007
    Abstract212)   HTML8)    PDF (2064KB)(69)      

    To address the insufficient energy management efficiency of composite energy storage hybrid systems in engineering vehicles under complex operating conditions, a global optimization strategy based on dynamic programming (DP) was proposed. This strategy constructed an optimal power allocation control model using load demand torque, the state of charge (SOC) of hydraulic accumulator, and battery SOC as state variables, and solved the control sequence through inverse recursive-forward optimization. The feasibility of applying the DP strategy in practical engineering was further validated through hardware-in-the-loop testing. The results show that compared to rule-based (RB) and adaptive neural fuzzy inference system (ANFIS) strategies, the DP strategy increases the proportion of engine operation within the high-efficiency zone by 38.28% and 30.27%, respectively. It reduces the comprehensive fuel consumption by 15.17% and 11.23%, and the battery SOC fluctuation by 34.02% and 23.97%, respectively. The average SOC of the brake energy recovery accumulator are increased by 29.46% and 23.51%, and the average battery SOC are improved by 11.57% and 8.62%, respectively. These results demonstrate that the DP strategy effectively enhances engine efficiency, maintains stable operation within the high-efficiency zone, and achieves overall system energy optimization. The DP strategy provides both theoretical justification and practical solutions for energy-saving control in construction machinery.

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