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  • 2025, Vol. 16 No. 6 Published on:31 December 2025 Previous issue   
    Review, Progress and Prospects
    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
    2025, 16(6):  813-831.  doi:10.3969/j.issn.1674-8484.2025.06.001
    Abstract ( 50 )   HTML ( 4)   PDF (3355KB) ( 38 )  

    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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    Automotive Safety
    Robust model prediction based clamping force control for electro-mechanical braking systems
    ZHANG Rongyu, ZHAO Xuan, WANG Shu, LI Meiying
    2025, 16(6):  832-842.  doi:10.3969/j.issn.1674-8484.2025.06.002
    Abstract ( 33 )   HTML ( 3)   PDF (2170KB) ( 11 )  

    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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    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
    2025, 16(6):  843-850.  doi:10.3969/j.issn.1674-8484.2025.06.003
    Abstract ( 26 )   HTML ( 3)   PDF (1450KB) ( 11 )  

    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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    Mental workload variations of drivers navigating over the differential types of interchange ramps
    LIANG Yuchen, DUAN Weijian, ZHANG Shi, ZHU Xinglin, XU Jin
    2025, 16(6):  851-858.  doi:10.3969/j.issn.1674-8484.2025.06.004
    Abstract ( 28 )   HTML ( 2)   PDF (1590KB) ( 10 )  

    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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    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
    2025, 16(6):  859-866.  doi:10.3969/j.issn.1674-8484.2025.06.005
    Abstract ( 26 )   HTML ( 4)   PDF (2346KB) ( 10 )  

    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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    Research on electrical vehicle's sliding mode in small overlap impact crash test
    LI Yixuan, WU Xiao, TANG Kai, LI Zheng
    2025, 16(6):  867-876.  doi:10.3969/j.issn.1674-8484.2025.06.006
    Abstract ( 21 )   HTML ( 2)   PDF (3782KB) ( 7 )  

    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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    Automotive Energy Efficiency and Environment Protection
    Research on global optimal control strategy for hybrid power system with composite energy storage
    LI Zhao, LONG Wuqiang, TIAN Hua
    2025, 16(6):  877-885.  doi:10.3969/j.issn.1674-8484.2025.06.007
    Abstract ( 22 )   HTML ( 2)   PDF (2064KB) ( 8 )  

    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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    Application of wheat starch-acrylamide dual-crosslinked hydrogel in flexible zinc-air batteries
    WANG Hengwei, WANG Keliang, WEI Manhui, CHEN Yunxiang, LIU Hanchao, PEI Pucheng
    2025, 16(6):  886-895.  doi:10.3969/j.issn.1674-8484.2025.06.008
    Abstract ( 32 )   HTML ( 2)   PDF (3366KB) ( 7 )  

    A dual-crosslinking strategy, in which wheat starch and acrylamide was used to construct a low-cost and high-performance gel electrolyte, was proposed to overcome the challenges of high cost, poor water retention, and interfacial instability of electrolytes in flexible zinc-air batteries,. Material characterization, electrochemical testing, and quantum chemical calculations were employed to evaluate its structural and electrochemical properties and to elucidate the mechanisms of performance enhancement. The results demonstrate that, in comparison with polyacrylamide gel, the developed gel exhibits a water retention rate of 81.7% after 12 hours, representing a 16% improvement; a fracture strain of 135%, indicating an 81% enhancement; an ionic conductivity of 375 mS/cm, reflecting a 69% increase; and a discharge power density of 175 mW/cm2, showing a 48% rise. Furthermore, the cycling stability of the assembled flexible zinc-air battery exceeds 45 hours, indicating a twofold enhancement in operational lifespan. This dual-crosslinking strategy, which forms continuous hydrophilic ion channels and enhances interfacial wettability, significantly improves water retention, mechanical strength, ionic conductivity, and electrochemical stability, thereby offering an optimization solution for the development of flexible zinc-air batteries.

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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
    2025, 16(6):  896-904.  doi:10.3969/j.issn.1674-8484.2025.06.009
    Abstract ( 33 )   HTML ( 10)   PDF (3138KB) ( 17 )  

    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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    Optimization of heat dissipation in proton exchange membrane fuel cells and coupling of waste heat-hydrogen storage system
    LANG Dongyu, BAO Gang, ZHANG Shu, YU Zhenyu, SUN Jiahong, XIE Huaqing
    2025, 16(6):  905-913.  doi:10.3969/j.issn.1674-8484.2025.06.010
    Abstract ( 17 )   HTML ( 1)   PDF (1991KB) ( 5 )  

    In order to reduce the impact of waste heat on performance in the operation of proton exchange membrane fuel cells (PEMFCs) and to improve energy utilization efficiency during the operation of the PEMFC, the numerical optimizations of PEMFC’s output characteristics and cooling conditions were carried out based on the traditional single direct current cooling channel, with a thermal coupling model being established between PEMFC and metal hydride hydrogen storage reactor. The results show that PEMFC achieves an output of 561.2 W under the operating conditions of 333 K and 1.41 A/cm2; the optimal cooling conditions, where the heat generated by the fuel cell can fully drive hydrogen release from the hydrogen storage reactor, are an inlet water temperature of 330 K and a flow rate of 15 cm/s. The system operates stably, the temperature of the hydrogen storage tank is maintained at 314 K, and the total power supply reaches 0.78 kWh during the period from 334 s to 3 615 s. Therefore, optimizing the operating parameters of PEMFC enables efficient thermal coupling between the power generation and hydrogen storage systems.

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    Intelligent Driving and Intelligent Transportation
    Fault-tolerant and safety control of intelligent connected vehicles under stealthy network attacks
    QIU Zhaoyu, ZHU Xiaoyuan, TIAN Guangyu, YIN Guodong
    2025, 16(6):  914-922.  doi:10.3969/j.issn.1674-8484.2025.06.011
    Abstract ( 20 )   HTML ( 3)   PDF (8563KB) ( 15 )  

    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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    BI-RRT* path planning method based on GA optimization and path extension heuristic sampling
    ZHANG Bingli, ZHANG Zhisen, ZHANG Yangyang, LIU An, XU Yonghua
    2025, 16(6):  923-933.  doi:10.3969/j.issn.1674-8484.2025.06.012
    Abstract ( 22 )   HTML ( 2)   PDF (6288KB) ( 17 )  

    To address the issues of slow convergence and excessive path randomness in traditional BI-RRT*, this paper proposed a two-stage optimization framework algorithm, GEP_BIRRT, which combined an improved BI-RRT* algorithm with evolutionary strategies. Firstly, flexible boundary constraints to the BI-RRT* algorithm were introduced to enhance search efficiency by limiting the sampling range, and a metric function to obtain high-quality feasible paths was designed. Second, a path optimization was performed based on a genetic algorithm, in which an optimization region centered on feasible paths was constructed and a multi-objective fitness function was designed to balance path smoothness and safety, ultimately yielding the planned path. Finally, simulation experiments were conducted using MATLAB software. The strong robustness of GEP_BIRRT across three distinct environments was demonstrated by the results. The results show that compared to Informed-RRT* and traditional BI-RRT*, the planning duration is reduced by 59.48% and 20.08% on average, respectively, with average path length reductions of 1.26% and 1.51%, and cumulative turning angle reductions of 32.60% and 40.84%, respectively. It also effectively avoids dynamic obstacles, validating the superiority and feasibility of the GEP_BIRRT algorithm.

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    Predictive trajectory tracking control by a linear time-varying model for emergency collision avoidance of autonomous vehicles
    WU Hangzhe, JIAO Yizhou, LIU Yang, ZHONG Wei, WANG Shuihe, GUO Jinghua, ZHAO Jian
    2025, 16(6):  934-944.  doi:10.3969/j.issn.1674-8484.2025.06.013
    Abstract ( 21 )   HTML ( 4)   PDF (3113KB) ( 13 )  

    A trajectory tracking method was proposed to improve the stability and safety of autonomous vehicles during emergency collision avoidance. A three-freedom dual-track nonlinear vehicle dynamics model was established based on the dual-track vehicle dynamics model to build a linear time-varying trajectory tracking prediction model; The trajectory tracking control algorithm were converted into an online quadratic programming problem to solve for the optimal control input. Simulation tests and real-vehicle experiments were conducted. The results show that the lateral displacement error is less than 90 mm and yaw angle error is less than 50 mrad in the double lane change simulations at the vehicle speed of 50 km/h with the road adhesion coefficients range of 0.5~1.0. The maximum lateral error is 160 mm with the maximum yaw angle tracking error of 34 mrad in the lane change experiments at the vehicle speed of 60 km/h with a road adhesion coefficient of 0.38. Therefore, the trajectory tracking controller exhibits effectiveness and robustness, guaranteeing the vehicle’s stability and safety during lane changes.

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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
    2025, 16(6):  945-954.  doi:10.3969/j.issn.1674-8484.2025.06.014
    Abstract ( 28 )   HTML ( 3)   PDF (2058KB) ( 18 )  

    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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