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Table of Content

    25 November 2025, Volume 47 Issue 11 Previous Issue   
    A Review of Key Technologies and Application of Flying Cars
    Jiaxin Ma,Zhihong Wang,Zhuo Liu,Zongyang Li,Bingquan Chen
    2025, 47 (11):  2049-2069.  doi: 10.19562/j.chinasae.qcgc.2025.11.001
    Abstract ( 409 )   HTML ( 41 )   PDF (2532KB) ( 268 )   Save

    As a three-dimensional expansion of automobile functions, flying cars have attracted much attention for alleviating traffic congestion, reshaping travel modes, and developing an efficient and low-carbon transportation system. It is generally accepted that flying cars have more than 70% technological homology with electric vehicles. Based on the analysis of the development history of flying cars, the general configuration and the performance of the typical global flying cars are compared in this paper. Six characteristics of the electrification development are proposed. Combined with the analysis of the homology and difference in electric vehicle technology, key technologies such as the propulsion system, autonomous driving, lightweight, and NVH are analyzed. The paper concludes that the development experience, technology, and supply chain advantages of electric vehicles have provided a good industrial foundation for flying cars. Different from electric vehicles, flying cars should focus on the power battery with higher energy density and higher discharge rate, the motor with higher torque density, low speed, and high torque, and high safety autonomous driving technologies that consider the impact of low-altitude complex meteorological environment, obstacles, and bird collision.

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    An Efficient Learning Method for Multi-Modal Task Path Planning of Flying Vehicles
    Jing Zhao,Chao Yang,Weida Wang,Ying Li,Changle Xiang
    2025, 47 (11):  2070-2082.  doi: 10.19562/j.chinasae.qcgc.2025.11.002
    Abstract ( 179 )   HTML ( 12 )   PDF (5016KB) ( 67 )   Save

    Flying vehicles have attracted significant attention in urban traffic, rescue transportation, and other operational fields. Efficient multi-modal task path planning effectively improves their operational efficiency in these fields. Therefore, an efficient learning method for multi-modal task path planning of flying vehicles is proposed. Firstly, the action space of the flying vehicle is optimized, retaining the actions of take-off, landing, and moving towards the target position. Simultaneously, a probability selection mechanism for non-target direction actions is designed. Secondly, considering the air-ground coordination characteristics of the flying vehicle, a novel reward function of Q-learning is designed. And a reward enhancement mechanism based on historical optimal path experience is proposed. Finally, a path smoothing method is proposed to obtain a smooth and continuous path for the air-ground cooperative task. Compared with the multi-modal paths planned by A*, Q-learning, and D* Lite, the multi-modal path planned by this method successively reduces the running distance by 10.35, 126.75, and 162.10 m, respectively. In terms of learning efficiency, the method reduces the learning time by 45.97% compared to Q-learning.

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    Research on Decision-Planning-Tracking Hierarchical Motion Control of Flying Car in Urban Scene
    Yongjun Yan,Chenshuo Zhang,Shilong Tao,Pengyu Xue,Hongliang Wang,Dawei Pi
    2025, 47 (11):  2083-2092.  doi: 10.19562/j.chinasae.qcgc.2025.11.003
    Abstract ( 149 )   HTML ( 13 )   PDF (3276KB) ( 71 )   Save

    Flying car technology has brought solutions to alleviate urban traffic pressure, but the three-dimensional obstacles of urban low-altitude traffic are dense. How to realize safe and efficient intelligent control of flying cars is still an urgent problem to be solved. In this paper, a decision-planning-tracking hierarchical motion control system for flying cars in urban scenes is designed. In the upper decision-planning module, an optimal path decision mechanism is designed based on the goals of safety and energy consumption, and a longitudinal-lateral-vertical risk field in urban scenes is established. Based on the designed longitudinal-lateral-vertical risk field and combined with model predictive control, real-time trajectory planning is carried out to achieve trajectory planning control that meets energy consumption requirements and is safe. In the lower path tracking controller, the cascade controller is used to realize the path tracking control. The controller calculates the motor speed control quantity according to the expected trajectory, and realizes the precise control of the flying car. The Matlab/Simulink simulation environment is built. The simulation results show that the proposed hierarchical motion control system of the flying car can plan a safe and comfortable driving trajectory, and the real-time performance of the controller meets the requirements, with the solution time of each step less than 10 ms.

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    Research on Energy Management Strategy for Hybrid Electric Flying Vehicles Based on an Improved TD3 Algorithm
    Zhongkai Luan,Yukun Shen,Wanzhong Zhao,Chunyan Wang,Jianhao Zhou,Pengchang Jiang
    2025, 47 (11):  2093-2102.  doi: 10.19562/j.chinasae.qcgc.2025.11.004
    Abstract ( 152 )   HTML ( 14 )   PDF (4787KB) ( 77 )   Save

    For severe power fluctuation, challenges in SOC and temperature control, frequent engine start-stop, and poor fuel economy in hybrid flying vehicles under air-ground coordination, in this paper a series connected architecture based on a turboshaft engine-generator set and battery collaborative power supply is constructed. An improved TD3 strategy (KI-TD3) is proposed, guided by structural priors. By incorporating the prior information of the engine’s economic working zone, positive working point reward, dynamic exploration mechanism, and action space restriction method are constructed to enhance the performance of the strategy. The simulation results show that the KI-TD3 strategy achieves better power distribution and battery control. Compared to standard TD3, it ensures more accurate SOC convergence to the target value of 0.25, stabilizes the temperature rise, concentrates engine operation in efficient zones, and cuts fuel use by 3.5%. Compared to DP, it further reduces fuel use by 5.2%, suppresses start-stop and power spikes, and keeps operation near minimum BSFC, significantly improving economy.

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    Numerical Study on Aerodynamic Characteristics of Electric Vertical Take-off and Landing Aircraft with Lift-and-Cruise Configuration
    Quan Zhou,Qing Jia,Chao Xia,Reng Mo,Huanxia Wei,Yingchao Zhang,Qiangqiang Hu,Zhigang Yang
    2025, 47 (11):  2103-2112.  doi: 10.19562/j.chinasae.qcgc.2025.11.005
    Abstract ( 140 )   HTML ( 9 )   PDF (5447KB) ( 71 )   Save

    In this study a simplified aerodynamic model applicable to various electric vertical take-off and landing (eVTOL) configurations is established and the improved delayed detached-eddy simulation method is used to numerically simulate the aerodynamic characteristics of different eVTOL configurations during typical flight phases, including take-off, landing, cruise, and climb. The results show that the lift-to-drag ratio of the lift-and-cruise configuration during take-off is approximately one-third that of the multi-rotor configuration, while the two are comparable during landing. During the cruise phase, the lift-to-drag ratio of the lift-and-cruise configuration is 20.52% lower than that of the fixed-wing configuration, and 17.14% lower during the climb phase. Overall, the lift-and-cruise configuration is inferior to the multi-rotor configuration during take-off, slightly outperforms it during landing, and falls short of the fixed-wing configuration in both cruise and climb phases. The findings provide scientific guidance and an engineering basis for eVTOL configuration selection and aerodynamic performance optimization.

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    Study on the Impact of Structural Safety and Empathy Differences on the Willingness to Use eVTOLs
    Zhuzi Liu,Yin Li,Qiqi Li,Lin Hu,Tiefang Zou
    2025, 47 (11):  2113-2125.  doi: 10.19562/j.chinasae.qcgc.2025.11.006
    Abstract ( 97 )   HTML ( 6 )   PDF (752KB) ( 27 )   Save

    The willingness to use electric Vertical Take-Off and Landing vehicles (eVTOL) is influenced by various factors. Currently, research on the role of structural safety and empathy in shaping this willingness remains limited. Based on the Technology Acceptance Model (TAM), in this study a framework for the willingness to use eVTOLs that incorporates the latent variable of "structural safety" is proposed. Data is collected through a questionnaire survey, yielding 760 responses. After reliability and validity tests, TAMs for different empathy groups are established. The results show that empathy levels significantly affect users' perception and acceptance of eVTOLs, and there are extremely significant differences among different empathy groups in latent variables such as willingness to use, perceived usefulness, and structural safety, leading to completely different model structures. All models show that perceived usefulness has a significant positive impact on attitudes, and structural safety indirectly influences attitudes by enhancing perceived usefulness. The analysis suggests that perceived usefulness needs to be verified through practical application, and structural safety requires a balance between lightweighting and safety, along with strengthened collision testing protocols. The findings extend the TAM theory by integrating technical and affective dimensions, offering interdisciplinary insights for optimizing eVTOL safety systems and tailoring market penetration strategies.

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    Study on the Uniformity of Physical Field Distribution and Operation State of Proton Exchange Membrane Fuel Cells Under Multiple Operating Conditions
    Pengyu Qiao,Siyuan Wu,Zhiming Bao,Daokuan Jiao,Xueliang Liu,Kaige Zhu,Haoran Du,Weirui Luo,Qing Du,Kui Jiao
    2025, 47 (11):  2126-2140.  doi: 10.19562/j.chinasae.qcgc.2025.11.007
    Abstract ( 91 )   HTML ( 3 )   PDF (16000KB) ( 24 )   Save

    Proton exchange membrane fuel cells (PEMFCs) face challenges of non-uniform physical field distribution under complex operating conditions, which can result in local “water flooding,” “hot spots,” and “gas starvation” during long - term operation, severely undermining system performance and durability. To deeply reveal the evolution characteristics of the internal physical field under multiple operating conditions and its compact on the battery operation status, in this study a full - scale three - dimensional multi - physics field coupling simulation model is constructed to systematically examine the influence of three key parameters of inlet air stoichiometric ratio, operating temperature, and inlet air humidity on liquid water content, oxygen concentration, current density, and temperature distribution within PEMFCs. Furthermore, an operational state index Hi is proposed to quantitatively evaluate PEMFC operating health by integrating physical field distribution characteristics. The results show that all three parameters significantly impact the distribution uniformity and overall levels of physical fields. High - temperature, high - humidity, and extreme stoichiometric ratio conditions are more likely to disrupt local distribution uniformity, triggering non - healthy states. This research provides crucial theoretical and simulation - based support for PEMFC operation optimization and life management.

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    Simulation Analysis of the Effect of Variable Altitude Environment on Fuel Cell Performance
    Mingyang Li,Xiuli Zhu,Mingjie Shi,Baojuan Jia,Xiaojun Zhao,Fengwen Pan
    2025, 47 (11):  2141-2149.  doi: 10.19562/j.chinasae.qcgc.2025.11.008
    Abstract ( 115 )   HTML ( 8 )   PDF (4339KB) ( 40 )   Save

    The current matching design of hydrogen fuel cell engine (FCE) and stationary electricity generation is primarily optimized for flat terrains, and there is relatively little research on the performance impact brought by high altitude, low air pressure, and thin oxygen. In this paper the influence of altitude changes from 0 to 4 000 meters on fuel cells is analyzed from the perspectives of chemical reaction theory and Cruise M modeling and simulation. The results show that as altitude increases, the air compressor needs to compensate for the air flow rate to maintain the stable power of the fuel cell. In the high power range of the fuel cell, the air compressor is prone to entering or even exceeding the high-pressure ratio boundary during operation, while in the low power range of the fuel cell, it is easy to cause air compressor surge faults. Therefore, in this paper, an altitude-adaptive control strategy for fuel cells is proposed, dynamically regulating the air excess ratio or inlet pressure to enhance the altitude adaptability of the fuel cell engine and simultaneously improve the operational stability of the air subsystem and the air compressor.

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    Degradation Trend Prediction of Vehicular PEMFC Based on Dynamic Feature Parameters and Improved GOA-BP Neural Network
    Fajun Xue,Jibin Yang,Pengyi Deng,Xiaohua Wu,Li Chen,Wenlong Wang,Huaixiang Hu
    2025, 47 (11):  2150-2158.  doi: 10.19562/j.chinasae.qcgc.2025.11.009
    Abstract ( 79 )   HTML ( 2 )   PDF (2838KB) ( 26 )   Save

    For the problems of insufficient characterization of dynamic operating conditions and the tendency of traditional optimization algorithms to fall into local optima in the prediction of remaining useful life (RUL) for proton exchange membrane fuel cell (PEMFC), in this paper a novel prediction method is proposed that combines dynamic feature parameters with an improved grasshopper optimization algorithm (IGOA) and back propagation neural network. Firstly, the seasonal component of voltage data is extracted through seasonal-trend decomposition method, while the power fluctuation rate during operating cycles is quantified. Then, key feature parameters are selected using grey relational analysis. Subsequently, the IGOA is employed to optimize the hyper parameters of the back propagation neural network and construct the IGOA-BP neural network prediction model. Finally, the model performance is validated by real-world vehicle data and laboratory test datasets. The results demonstrate that the proposed method achieves higher prediction accuracy with the mean absolute percentage error below 0.06%, which enables more accurate RUL prediction for PEMFC.

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    Study on Fault-Tolerant Control for Fuel Cell Air Supply Systems via Extended State Observer
    Sheng Zeng,Meiling Yue,Xintong Li
    2025, 47 (11):  2159-2167.  doi: 10.19562/j.chinasae.qcgc.2025.11.010
    Abstract ( 80 )   HTML ( 4 )   PDF (2154KB) ( 21 )   Save

    To address the fault-tolerant control issue in the air supply system of proton exchange membrane fuel cell (PEMFC) for automotive application, an adaptive control method based on extended state observer and input-output feedback linearization (IOFL) is proposed, which effectively observes the state changes of the system under fault conditions, adaptively adjusts the control input, and ensures the reliable and stable operation of the system. Firstly, a feedback linearization controller is constructed based on the PEMFC system state-space model from the literature. Subsequently, the system states are reconstructed using an extended state observer to achieve effective estimation of fault parameters. Based on the constructed model and controller, the control performance of both the IOFL controller and the proposed adaptive controller on the oxygen excess ratio is investigated for compressor overheating, increased mechanical friction and air manifold leakage faults. The results show that the adaptive controller can effectively eliminate steady-state errors, ensure stable system operation, and provide reliable state estimation when dealing with single and multiple faults, which significantly enhances the robustness and reliability of the air supply system control. Furthermore, the control results also verify that the proposed adaptive control strategy can effectively avoid compressor voltage oscillations, thereby further improving the stability and extending the lifespan of the fuel cell system.

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    Study on Power System of Heavy Truck Based on Solid-State Hydrogen Storage Combined with Thermal Management
    Yu Liang,Fushou Xie,Weikuo Xie,Yi Zhou,Heng Wang
    2025, 47 (11):  2168-2177.  doi: 10.19562/j.chinasae.qcgc.2025.11.011
    Abstract ( 81 )   HTML ( 3 )   PDF (3133KB) ( 18 )   Save

    To demonstrate the feasibility of applying solid-state hydrogen storage in heavy trucks, in this paper a new system is proposed that couples a power system with a thermal management system for heavy trucks based on solid-state hydrogen storage and combined with a heat pump system. The Amesim software is used to model the system, and a study is conducted on the system's feasibility and the matching characteristics of key parameters of each component. The results show that the proposed power coupling system is feasible and effective, and can ensure the stable long-distance operation of heavy trucks. Taking the working condition where the solid-state storage tank can hold 110 kg of hydrogen as an example, the cargo capacity is approximately 36.8 t, and the heavy truck can travel stably for more than 1 100 km. A comparative analysis of the impact of heat pump performance on system efficiency reveals that heat pump performance has a significant effect on the driving range and energy efficiency of heavy trucks. Meanwhile, a comparison of high-pressure hydrogen storage, liquid hydrogen storage, and solid-state hydrogen storage shows that the parameters of solid-state hydrogen storage heavy truck are found to be within a reasonable range. The research results indicate that the application of solid-state hydrogen storage in hydrogen-powered heavy trucks is feasible to a certain extent.

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    Single-Atom Catalysts Empowering Next-Generation Fuel Cells: From Computational Screening to Application
    Haonian Liu,Xin Cai,Michael Harenbrock,Rui Lin
    2025, 47 (11):  2178-2186.  doi: 10.19562/j.chinasae.qcgc.2025.11.012
    Abstract ( 64 )   HTML ( 0 )   PDF (3456KB) ( 13 )   Save

    Proton exchange membrane fuel cell is a green power generation technology that has attracted much attention in today's energy field, with the advantages of high-energy conversion efficiency and environmental friendliness. However, the high-cost precious metal catalysts have limited its large-scale application. Single-atom catalysts, with the high atom utilization, low cost, and good selectivity, show great potential for application in the catalytic reaction of fuel cells, and are an important direction for the development of fuel cell catalysts in the future. In this paper, the constitutive relationship and practical application of single-atom catalysts in proton exchange membrane fuel cells are systematically elaborated, particularly focusing on their roles in anodic antitoxicity and cathodic oxygen reduction. The structural characteristics and application advantages of both platinum-based and non-platinum-based single-atom catalysts are introduced in details, with high-throughput computational methodologies summarized integrating first-principle calculations with machine learning, which offers innovative approaches for efficient catalyst screening and atomic-scale precise design in fuel cell development. Furthermore, opportunities and remaining challenges in advancing single-atom catalysts for next-generation fuel cell technologies are outlined, providing theoretical foundation and technical reference for the future development and application of single-atom catalysts for proton exchange membrane fuel cells.

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    HMI Touch Interaction Evaluation Method for User Experience Improvement
    Tingting Cao,Hailun Zhang,Quan Yuan
    2025, 47 (11):  2187-2201.  doi: 10.19562/j.chinasae.qcgc.2025.11.013
    Abstract ( 103 )   HTML ( 10 )   PDF (7090KB) ( 38 )   Save

    With the rapid advancement of intelligent cabin technology, touch - based interaction systems have gradually become a core component of human - vehicle interaction. User experience has become a significant objective in the design and optimization of these systems. In order to enhance the applicability of the current evaluation system in terms of interaction experience, a touch - based interaction evaluation method for Human - Machine Interface (HMI) aimed at improving user experience is proposed in this paper. Based on an analysis of typical evaluation methods such as C - SAEE, C - ICAP, and I - VISTA, a comprehensive evaluation system is designed, covering six dimensions of visual coordination, operational rationality, human - machine convenience, information readability, functional integrity, and safety. Combining subjective user evaluations with objective interaction performance data, the Analytic Hierarchy Process (AHP) is used to set the weights of the evaluation indicators. The validation of the proposed method is carried out on a mid - sized intelligent electric vehicle through a combination of static simulation experiments and dynamic in - vehicle tests. The results show that the constructed method can effectively reflect the overall impact of the touch - based interaction system on user experience. The findings of this research provide a reference for the interaction design of intelligent cabins, human factors engineering evaluation, and the optimization of evaluation systems.

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    Research on Unbiased Full State Feedback Path Tracking Control Method for Four-Wheel Steering Vehicles for the Extreme Sideslip Scenario
    Guoying Chen,Jiahao Dong,Xinyu Wang,Jiaqi Wang,Lei Lu,Lun Li
    2025, 47 (11):  2202-2211.  doi: 10.19562/j.chinasae.qcgc.2025.11.014
    Abstract ( 140 )   HTML ( 9 )   PDF (6357KB) ( 54 )   Save

    For the problem of non-convergence of lateral and heading errors of path tracking in extreme lateral slip scenarios of the motion control method widely used in four-wheel steering vehicles based on feedback mechanism, a control method integrating unbiased feedforward and hysteresis-corrected full-state feedback is proposed. Firstly, a full-state feedback controller considering path preview and hysteresis correction is designed, and based on this, a closed-loop analysis of the lateral motion of four-wheel steering vehicles is conducted. The unbiased feedforward steering angle with zero lateral and heading errors in the steady state is deduced, thereby establishing the control algorithm combining unbiased feedforward and hysteresis-corrected full-state feedback. Finally, the proposed control algorithm is applied in real vehicle tests and compared and verified with the pure feedback control algorithm and the proportional feedforward plus full-state feedback control algorithm. The results show that the proposed control algorithm reduces the maximum lateral error by 26.6% and 20.5% respectively, and the maximum heading error by 21.9% and 15.7% respectively in the high-curvature working condition. In the high-speed serpentine working condition, the maximum lateral error is reduced by 29.9% and 15.6% respectively, and the maximum heading error is reduced by 37.8% and 32% respectively.

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    Robust Coordinated Yaw Stability Control for Distributed Electric Drive Wheel Corner Module Vehicle
    Xinrong Zhang,Yudong Zhang,Xingyu Li,Yanzhao Su,Haoyu Wang,Jin Huang
    2025, 47 (11):  2212-2223.  doi: 10.19562/j.chinasae.qcgc.2025.11.015
    Abstract ( 119 )   HTML ( 4 )   PDF (2576KB) ( 56 )   Save

    Under extreme scenarios such as emergency obstacle avoidance or sharp turns, vehicles may experience yaw instability. Distributed corner module vehicles, equipped with independent four-wheel drive (4WID) and independent four-wheel steering (4WIS), offer high mobility advantages. However, the elimination of physical constraints between wheels increases the risk of yaw instability under extreme conditions. To enhance the yaw stability of corner module vehicles in such scenarios, in this paper a constraint-based yaw stability control strategy is proposed. An adaptive robust direct yaw moment control (ARC) driven by embedded equality constraints is designed, along with a longitudinal speed control mechanism. Additionally, an active rear steering (ARS) control strategy satisfying the steady-state cornering equality constraint is developed. By integrating a four-wheel torque optimization strategy, the proposed ARC+ARS cooperative control mechanism effectively improves the yaw stability of corner module vehicles under extreme conditions. The co-simulation results show that in a high-speed, high-adhesion double lane change scenario, the proposed control strategy reduces the root mean square (RMS) of yaw rate error and centroid sideslip angle by at least 53.1% and 15.3%, respectively. In a medium-speed, low-adhesion scenario, the reduction reaches at least 77.5% and 15.2%, respectively, with strong robustness in dealing with the systematic uncertainties and external disturbances.

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    Coordinated Control of AFS and DYC for Distributed Electric Drive Vehicles Based on Critical Turning Angle
    Xu Xia,Guoquan Ren,Zhongjie Zhang,Ruixuan Wang,Shiju Pan,Zixian Li
    2025, 47 (11):  2224-2237.  doi: 10.19562/j.chinasae.qcgc.2025.11.016
    Abstract ( 79 )   HTML ( 8 )   PDF (6292KB) ( 36 )   Save

    In order to improve the maneuvering stability of distributed electric drive vehicles under extreme operating conditions, a cooperative control system of active front wheel steering (AFS) and direct yaw moment control (DYC) based on the critical turning angle divided regions is designed in this paper. Firstly, a method of determining the tire state region based on the critical angle threshold is proposed, and the tire state region is divided into linear region, transition region and saturation region. Then on this basis, the AFS and DYC controller is respectively established, and the adaptive cooperative control of the two controllers is realized based on the “linear distance coefficient”. Then, the torque of each wheel is assigned according to the phase plane region of the vehicle state. Finally, based on the joint simulation platform of MATLAB/Simulink and CarSim, experimental validation is carried out under serpentine and double-shift conditions. The results show that the critical angle determination method can accurately identify the tire state region, solve the problem of difficult direct measurement of the tire state in the real vehicle, and significantly improve the applicability of the controller in the unknown tire parameters or complex working conditions. The collaborative control system designed on the basis of this system can effectively make up for the shortcomings of a single controller, significantly improve the stability of the vehicle's handling, and has certain engineering application value.

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    Estimation of Front Wheel Steering Angle for Vehicle Steer-by-Wire System Considering Tire Cornering Characteristics
    Xiaoqiang Sun,Jiawei Ding,Haoran Tang,Yingfeng Cai,Long Chen
    2025, 47 (11):  2238-2249.  doi: 10.19562/j.chinasae.qcgc.2025.11.017
    Abstract ( 103 )   HTML ( 8 )   PDF (3230KB) ( 45 )   Save

    The steering angle of the front wheels is the primary tracking control objective in vehicle steer-by-wire (SBW) system, and its accurate estimation is a critical aspect of the redundancy design in such systems. For the problem that traditional methods fail to ensure the estimation accuracy of the front wheel steering angle across a wide range of driving conditions, an estimation method for the front wheel steering angle in SBW systems is proposed, which takes into account of the nonlinear characteristics of tire lateral deflection. Firstly, a two-degree-of-freedom yaw-roll vehicle dynamics model and a SBW system model are constructed, followed by the completion of piecewise affine (PWA) identification for the tire nonlinear cornering characteristics. Subsequently, the state equation of the PWA system is derived, and a front wheel steering angle estimation strategy for the vehicle SBW system is designed using the maximum correlation square root cubature Kalman filter (MCSCKF) algorithm to enhance the estimation accuracy during extensive state transitions. Finally, a co-simulation validation platform for the performance estimation of the front wheel steering angle in vehicle SBW systems is established based on CarSim and Simulink. The effectiveness of the front wheel steering angle estimation is verified in conjunction with two typical operational conditions. The results show that under sinusoidal steering conditions, the MCSCKF algorithm has a maximum reduction in estimation error of 66.3% and 41.1% compared to EKF and MCEKF algorithms, respectively. Under the dual lane steering condition, the MCSCKF algorithm has a maximum reduction in estimation error of 64.3% and 38.2% compared to the EKF and MCEKF algorithms, respectively, which verifies that the proposed method can effectively improve the accuracy of front wheel steering angle estimation under a wide range of driving conditions for automobiles.

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    Research on the Drive-Brake Load Characteristics of Electric Vehicles Under User Data
    Lihui Zhao,Shaojie Shen,Shuo Weng,Desheng Chen,Dongdong Zhang
    2025, 47 (11):  2250-2264.  doi: 10.19562/j.chinasae.qcgc.2025.11.018
    Abstract ( 99 )   HTML ( 6 )   PDF (10166KB) ( 62 )   Save

    The study of drive-brake load characteristics of electric vehicles based on user operation data is an important foundation for the reliability-oriented design of electric drive systems. In this paper, by integrating telematics big data with vehicle longitudinal dynamics modeling, typical driving condition characteristics, user behavior differences, and the gap between user targets and existing standards are systematically investigated. Firstly, a longitudinal dynamics model is developed and validated using over one million kilometers of real-world driving data from seven regions, enabling the transformation of user operation data into drive-brake loads. Secondly, an analysis of operating time, mileage, and acceleration characteristics under different driving conditions is conducted. The results show that frequent speed variations under low to medium speeds are key factors contributing to damage in critical components. Lastly, regional differences in user behavior are compared, and a user target profile suited to Chinese road conditions is constructed. A further comparison with existing standards reveals significant discrepancies in load frequency within the low-to-medium load range. The research results can provide data support and methodological references for the reliability-oriented design and validation standard development of electric drive systems.

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    Regenerative Braking Control Strategy for Electric Unmanned Vehicles Based on Speed Prediction
    Xueqin Lü,Xinrui Zhai,Shenchen Qian,Tao Wu,Peiyinquan Wang,Jiawei Gu
    2025, 47 (11):  2265-2275.  doi: 10.19562/j.chinasae.qcgc.2025.11.019
    Abstract ( 105 )   HTML ( 6 )   PDF (14771KB) ( 47 )   Save

    In order to improve the energy recovery rate of electric unmanned vehicles during operation and to ensure the safety and economy of vehicle operation, a regenerative braking control strategy for electric unmanned vehicles based on speed prediction is proposed. The road condition detection algorithm based on offline training neural network model and the vehicle speed prediction method based on improved Markov chain are used to make the control process more accurate and stable. The sliding sampling window method is used for online pattern recognition of the vehicle driving state, and the predicted speed values are converted into the power demand for vehicle operation, and then the braking torque applied to the vehicle tires is solved by a model prediction controller to determine the optimal solution for the electric unmanned vehicle braking for different braking torques applied to each tire. The experimental results indicate that electric unmanned vehicles employing regenerative braking control strategies can effectively manage the efficiency of energy recovery during braking and extend their cruising range.

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