IEEE Open Journal of Vehicular Technology最新文献_第2页

Design of a 65-kW Wireless Charging Station Characterized by Optimal Load Impedance Tracking Control 基于最优负载阻抗跟踪控制的65kw无线充电站设计

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-09-01 DOI: 10.1109/OJVT.2025.3604561

Martin Zavrel;Pavel Drabek;Vladimir Kindl;Michal Frivaldsky

{"title":"Design of a 65-kW Wireless Charging Station Characterized by Optimal Load Impedance Tracking Control","authors":"Martin Zavrel;Pavel Drabek;Vladimir Kindl;Michal Frivaldsky","doi":"10.1109/OJVT.2025.3604561","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3604561","url":null,"abstract":"This article presents the design and development of a low-level control approach for a wireless charger intended for modern electro-mobility (e-mobility) applications. It outlines future trends in the e-mobility market and technical advancements in wireless power transfer (WPT) systems, aligning them with the proposed wireless charger design methodology. A key advantage of the proposed solution is its full competitiveness with conventional wired charging stations. The primary focus of this work is the control system design for the wireless charging station (WCS), which features active and optimal load impedance tracking. This tracking adapts to varying load parameters (such as battery characteristics) and misalignments in coupling elements, ensuring maximum power transfer efficiency and high-power transfer controlled by supply voltage. The system complies fully with the SAE J2954 standard for wireless charging in e-mobility. The developed test system achieves power transfer of up to 65 kW across an air gap of 15 to 25 cm, with an overall system efficiency exceeding 95.5%.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2462-2478"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11145950","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint User Activity Detection and Channel Estimation in MC-GFMA Systems by Block Sparse Bayesian Learning With Threshold Optimization 基于阈值优化的块稀疏贝叶斯学习在MC-GFMA系统中的联合用户活动检测和信道估计

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-28 DOI: 10.1109/OJVT.2025.3603690

Yi Zhao;Mohammed El-Hajjar;Lie-Liang Yang

{"title":"Joint User Activity Detection and Channel Estimation in MC-GFMA Systems by Block Sparse Bayesian Learning With Threshold Optimization","authors":"Yi Zhao;Mohammed El-Hajjar;Lie-Liang Yang","doi":"10.1109/OJVT.2025.3603690","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3603690","url":null,"abstract":"Future wireless communications are expected to support massive connectivity in various applications, such as massive Machine-Type Communications (mMTC) and different types of IoT networks, where many applications have the data traffic of sporadicnature. To support these kinds of applications, grant free multiple-access (GFMA) has been recognized to be more efficient thanthe conventional granted multiple access (GMA). However, due to sporadic transmission, GFMA faces the main challenges of User Activity Detection (UAD) and Channel Estimation (CE). To meet these challenges, in this paper, a multicarrier GFMA (MC-GFMA) system is introduced for supporting massive connectivity. A block-sparse signal model is derived, where the Expectation Maximization assisted Block Sparse Bayesian Learning (EM-BSBL) algorithm is employed to solve the joint UAD and CE problem. Furthermore, to augment the performance of EM-BSBL algorithm in GFMA systems, the statistical properties of the activity weights generated by EM-BSBL algorithm are investigated, showing that the activity weights follow closely the Gamma distribution. Then, using the Gamma modelling of the activity weights, the Neyman-Pearson (NP) method is considered for optimizing the threshold used for decision making in the EM-BSBL algorithm. Finally, the performance of GFMA systems is comprehensively studied by numerical simulations. Our results and analysis demonstrate that MC-GFMA is a feasible signalling scheme for supporting a massive number of users transmitting sporadic information. With the aid of the EM-BSBL algorithm enhanced by the NP-assisted threshold optimization, MC-GFMA is robust for operation in the communications environments where active users are random and the number of them is highly dynamic.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2441-2458"},"PeriodicalIF":4.8,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11143207","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Integrated Modeling Framework for Motion Control and Energy Management in Multi-Motor Electric Vehicles 多电机电动汽车运动控制与能量管理集成建模框架

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-27 DOI: 10.1109/OJVT.2025.3603417

An-Toan Nguyen;Binh-Minh Nguyen;João Pedro F. Trovão;Minh C. Ta

{"title":"An Integrated Modeling Framework for Motion Control and Energy Management in Multi-Motor Electric Vehicles","authors":"An-Toan Nguyen;Binh-Minh Nguyen;João Pedro F. Trovão;Minh C. Ta","doi":"10.1109/OJVT.2025.3603417","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3603417","url":null,"abstract":"Multi-motor electric vehicles (MMEVs) present complex challenges for control and optimization due to the distribution of control actions and state variables across multiple subsystems and hierarchical levels. Although electric vehicle (EV) modeling has been widely studied, accurately capturing and optimizing the longitudinal energy efficiency and dynamic performance of MMEVs remains a significant challenge. This complexity is further increased by the presence of different motor types, such as induction motors (IMs) and permanent magnet synchronous motors (PMSMs), and various mechanical configurations in all-wheel drive systems. To address these issues, this paper proposes a global-local modeling framework that extends the Energetic Macroscopic Representation (EMR) methodology. The framework integrates detailed models of the electrical drive system with comprehensive mechanical subsystem modeling, including gearbox, differential, half-shafts, wheels, and tires. A global input power model links local control actions and state variables to overall energy flow, supporting a unified approach to longitudinal motion control and energy optimization. In contrast to conventional EMR-based models, the proposed framework explicitly incorporates driveline and tire dynamics, which significantly affect energy consumption due to drivetrain losses and tire slip. The model is evaluated through two scenarios that assess the effects of drivetrain modeling and force distribution strategies. The results show improved control system performance and enhanced energy efficiency, supporting future advancements in longitudinal dynamics modeling for MMEV.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2479-2493"},"PeriodicalIF":4.8,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated Cooperative Sensing and Two-Way Communications With Half-Duplex Base Stations 基于半双工基站的集成协同传感和双向通信

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-21 DOI: 10.1109/OJVT.2025.3601542

Dong-Hua Chen;Peifu Peng

{"title":"Integrated Cooperative Sensing and Two-Way Communications With Half-Duplex Base Stations","authors":"Dong-Hua Chen;Peifu Peng","doi":"10.1109/OJVT.2025.3601542","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3601542","url":null,"abstract":"In case the dual-functional base station (BS) is only equipped with half-duplex (HD) transceivers, integrated sensing and communications (ISAC) becomes a challenge task especially when the bidirectional communications for each HD user are involved. To address this situation, under the framework of a wireless network with two adjacent cells and with the aid of BSs cooperation, this paper presents two integrated cooperative sensing and bidirectional communication schemes that involve two and four transmission phases, respectively. Power minimization problems under the constrains of bidirectional communication rates and sensing signal to interference plus noise ratios (SINRs) are formulated for optimizing the downlink transmit beamforming vectors, uplink transmit power, and transmission time of each phase. Due to variables coupling, the problems are shown to be non-linear and non-convex. Relying on the successive convex approximation, iterative algorithms that are guaranteed to be convergent are derived to obtain these design variables. Simulations show that both of the proposed schemes well accomplish the bidirectional communications and cooperative target sensing in the considered situation. By contrast, the scheme with two transmission phases possesses lower implementation complexity while the scheme with four transmission phases owns the performance advantage. When uplink non-orthogonal multiple access is further used, the performance difference between the two schemes is reduced substantially.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2392-2405"},"PeriodicalIF":4.8,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11134088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MTFENet: A Multi-Task Autonomous Driving Network for Real-Time Target Perception MTFENet：一种实时目标感知的多任务自动驾驶网络

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-19 DOI: 10.1109/OJVT.2025.3600512

Qiang Wang;Yongchong Xue;Shuchang Lyu;Guangliang Cheng;Shaoyan Yang;Xin Jin

{"title":"MTFENet: A Multi-Task Autonomous Driving Network for Real-Time Target Perception","authors":"Qiang Wang;Yongchong Xue;Shuchang Lyu;Guangliang Cheng;Shaoyan Yang;Xin Jin","doi":"10.1109/OJVT.2025.3600512","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3600512","url":null,"abstract":"Effective autonomous driving systems require a delicate balance of high precision, efficient design, and immediate response capabilities. This study presents MTFENet, a cutting-edge multi-task deep learning model that optimizes network architecture to harmonize speed and accuracy for critical tasks such as object detection, drivable area segmentation, and lane line segmentation. Our end-to-end, streamlined multi-task model incorporates an Adaptive Feature Fusion Module (AF<inline-formula><tex-math>$^{2}$</tex-math></inline-formula>M) to manage the diverse feature demands of different tasks. We also introduced a fusion transform module (FTM) to strengthen global feature extraction and a novel detection head to address target loss and confusion. To enhance computational efficiency, we refined the segmentation head design. Experiments on the BDD100k dataset reveal that MTFENet delivers exceptional performance, achieving an mAP50 of 81.5% in object detection, an mIoU of 93.8% in drivable area segmentation, and an IoU of 33.7% in lane line segmentation. Real-world scenario evaluations demonstrate that MTFENet substantially outperforms current state-of-the-art models across multiple tasks, highlighting its superior adaptability and swift response. These results underscore that MTFENet not only leads in precision and speed but also bolsters the reliability and adaptability of autonomous driving systems in navigating complex road conditions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2406-2423"},"PeriodicalIF":4.8,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11130405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

6G-Enabled Vehicle-to-Everything Communications: Current Research Trends and Open Challenges 支持6g的车对一切通信：当前研究趋势和开放挑战

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-15 DOI: 10.1109/OJVT.2025.3599570

José Rodríguez-Piñeiro;Zhongxiang Wei;Jingjing Wang;Carlos A. Gutiérrez;Luis M. Correia

{"title":"6G-Enabled Vehicle-to-Everything Communications: Current Research Trends and Open Challenges","authors":"José Rodríguez-Piñeiro;Zhongxiang Wei;Jingjing Wang;Carlos A. Gutiérrez;Luis M. Correia","doi":"10.1109/OJVT.2025.3599570","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3599570","url":null,"abstract":"With the developments on Advanced Driver-Assistance Systems (ADAS), autonomous driving and purely unmanned vehicles, such as the Unmanned Aerial Vehicles (UAVs), the pressure on the requirements for Vehicle-to-Everything (V2X) communications has drastically increased during the last few years. However, a new and appealing horizon is open for V2X applications with the advent of the Sixth Generation (6G) of mobile communications. In this paper, we present a review of V2X standards to offer a holistic perspective on the evolution of this technology toward 6G. Then, the key technological enablers for the 6G V2X are identified, namely <italic>(a) Non-Terrestrial Networks (NTNs), <italic>(b) Ultra Reliable Low Latency Communications (URLLC), <italic>(c) Artificial Intelligence (AI), <italic>(d) Integrated Sensing And Communications (ISAC) and <italic>(e) propagation channel modeling. For each of these technological enablers, the most recent proposals are thoroughly studied and the open challenges and opportunities identified. Our paper intends to serve as a timely roadmap for the development of future 6G V2X networks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2358-2391"},"PeriodicalIF":4.8,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11126933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Steerable Subarrays for Practical mmWave Massive MIMO: Algorithm Design and System-Level Analysis 实用毫米波大规模MIMO的可操纵子阵列：算法设计与系统级分析

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-11 DOI: 10.1109/OJVT.2025.3597730

Noud B. Kanters;Andrés Alayón Glazunov

{"title":"Steerable Subarrays for Practical mmWave Massive MIMO: Algorithm Design and System-Level Analysis","authors":"Noud B. Kanters;Andrés Alayón Glazunov","doi":"10.1109/OJVT.2025.3597730","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3597730","url":null,"abstract":"This paper investigates the application of recently proposed practical subarray (SA)-based hybrid beamforming (HBF) architectures—implemented entirely with passive beamforming networks and switches—for millimeter wave (mmWave) multi-user (MU)-MIMO base stations. Building on this practical hardware platform, we propose a joint SA configuration and signal processing framework that exploits the natural non-uniformity of user locations in 3-D space via elevation domain subsectorization. Specifically, we adapt established channel estimation and HBF techniques to the constraints of switch-based SAs, and introduce a novel 2-stage channel estimator that leverages the unique properties of mmWave channels. System-level simulations in realistic line-of-sight (LoS) and non-line-of-sight (NLoS) propagation scenarios demonstrate that the proposed solution delivers strong performance with low complexity, providing a viable path toward practical, scalable mmWave MU-MIMO deployments. In LoS scenarios, using directions-of-arrival-based channel estimation, the proposed framework achieves up to 92.6% of the average spectral efficiency (SE) of a full-digital array antenna with the same number of elements but 4 times more radio frequency chains. In NLoS environments, using the novel 2-stage estimator, this increases up to 99.7%.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2224-2235"},"PeriodicalIF":4.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11122600","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144918318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy Efficient and Resilient Task Offloading in UAV-Assisted MEC Systems 无人机辅助MEC系统中的节能和弹性任务卸载

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-11 DOI: 10.1109/OJVT.2025.3598154

Mohamed El-Emary;Diala Naboulsi;Razvan Stanica

{"title":"Energy Efficient and Resilient Task Offloading in UAV-Assisted MEC Systems","authors":"Mohamed El-Emary;Diala Naboulsi;Razvan Stanica","doi":"10.1109/OJVT.2025.3598154","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3598154","url":null,"abstract":"Unmanned aerial vehicle (UAV)-assisted Mobile Edge Computing (MEC) presents a critical trade-off between minimizing user equipment (UE) energy consumption and ensuring high task execution reliability, especially for mission-critical applications.While many frameworks focus on either energy efficiency or resiliency, few address both objectives simultaneously with a structured redundancy model. To bridge this gap, this paper proposes a novel reinforcement learning (RL)-based framework that intelligently distributes computational tasks among UAVs and base stations (BSs). We introduce an <inline-formula><tex-math>$(h+1)$</tex-math></inline-formula>-server permutation strategy that redundantly assigns tasks to multiple edge servers, guaranteeing execution continuity even under partial system failures. An RL agent optimizes the offloading process by leveraging network state information to balance energy consumption with system robustness. Extensive simulations demonstrate the superiority of our approach over state-of-the-art benchmarks. Notably, our proposed framework sustains average UE energy levels above 75% under high user densities, exceeds 95% efficiency with more base stations, and maintains over 90% energy retention when 20 or more UAVs are deployed. Even under high computational loads, it preserves more than 50% of UE energy, outperforming all benchmarks by a significant margin—especially for mid-range task sizes where it leads by over 15–20% in energy efficiency. These findings highlight the potential of our framework to support energy-efficient and failure-resilient services for next-generation wireless networks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2236-2254"},"PeriodicalIF":4.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11122595","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144918204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Cluster-Based Channel Model Incorporating Quasi-Stationary Segmentation for Vehicle-to-Vehicle Communications 基于类平稳分割的车对车通信聚类信道模型

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-11 DOI: 10.1109/OJVT.2025.3597659

Fan Yu;Mingqi Guo;Qi Wang;Pengqi Zhu;Yixiao Tong;José Rodríguez-Piñeiro;Xuefeng Yin

{"title":"A Cluster-Based Channel Model Incorporating Quasi-Stationary Segmentation for Vehicle-to-Vehicle Communications","authors":"Fan Yu;Mingqi Guo;Qi Wang;Pengqi Zhu;Yixiao Tong;José Rodríguez-Piñeiro;Xuefeng Yin","doi":"10.1109/OJVT.2025.3597659","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3597659","url":null,"abstract":"Vehicle-to-vehicle (V2V) wireless communication is vital for intelligent transportation systems (ITSs). The high mobility of transceivers, along with the complex 3D propagation caused by low antenna heights and short communication ranges, present challenges to propagation modeling. Accurate V2V channel models are crucial for capturing these characteristics to design reliable V2V systems. Existing cluster-based V2V channel models neglect Doppler frequency variations in cluster classification, reducing classification and model accuracy. They describe clusters in single snapshot, missing temporal channel stationarity, and their complex structures slow model generation, hampering ITS applications. This paper presents a cluster-based V2V channel model incorporating quasi-stationary segmentation. First, SAGE algorithm extracts Multipath components (MPCs), followed by clustering and tracking. By analyzing clusters' Doppler frequency variations alongside angle, delay, and power changes, clusters are more accurately classified into global, static and dynamic types. Next, the model uses Correlation matrix distances (CMDs) to perform quasi-stationary segments for each cluster type, characterizing their distributions within each segment via inter- and intra-cluster parameters. This simplifies the model structure compared to single-snapshot models, improving generation efficiency. Segment duration and quantity statistics characterize channel stationarity. The model is validated by comparing simulated second-order channel statistics with comparable models and measured data. Its complexity is evaluated by comparing model generation time with alternative models in the literature.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2424-2440"},"PeriodicalIF":4.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11122388","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Dual-Level Hierarchical Functional Control Strategy for Four-Wheel Independent Drive Vehicles: Coordination for Enhanced Stability and Safety 四轮独立驱动车辆的双层分层功能控制策略：协调提高稳定性和安全性

IF 4.8

IEEE Open Journal of Vehicular Technology Pub Date : 2025-08-07 DOI: 10.1109/OJVT.2025.3596560

Zhiqi Guo;Liang Chu;Xiaoxu Wang;Yuhang Xiao;Zixu Wang;Zhuoran Hou

{"title":"A Dual-Level Hierarchical Functional Control Strategy for Four-Wheel Independent Drive Vehicles: Coordination for Enhanced Stability and Safety","authors":"Zhiqi Guo;Liang Chu;Xiaoxu Wang;Yuhang Xiao;Zixu Wang;Zhuoran Hou","doi":"10.1109/OJVT.2025.3596560","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3596560","url":null,"abstract":"With the advancement of electric vehicles towards intelligence and integration, four-wheel independent drive (FWID) vehicles, characterized by high controllability and structural flexibility, have gained widespread attention. Due to multi-degree-of-freedom coupling characteristics, the FWID constitutes complex nonlinear system, necessitating an adaptive control framework to enhance stability and safety. In this paper, a dual-level hierarchical functional control (DHFC) is proposed for FWID, aiming to exploit the potential of the FWID in achieving coordinated optimization of driving safety and stability. The high-level controller is designed to accurately determine the global stability status of FWID by enhancing both parameter estimation accuracy and safety constraints. A reinforcement learning-enhanced high-order cubature Kalman filter (RL-HCKF) improves adaptability and responsiveness in FWID state estimation. Additionally, a hybrid offline-online region of attraction (ROA) identification mechanism is established to delineate safety constraint boundaries for FWID. Meanwhile, the low-level controller adopts stochastic model predictive control (SMPC) to synthesize wheel-level torque vectoring, with dynamically adjusted constraints to enhance the robustness and safety of FWID under uncertain conditions. Simulation evaluations and hardware-in-the-loop (HIL) tests confirm the effectiveness of the proposed strategy. The results demonstrate that, compared to representative existing methods, the DHFC exhibits superior control stability and disturbance adaptability under various driving conditions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"2255-2271"},"PeriodicalIF":4.8,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11119462","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0