International Journal of Vehicle Design (7 papers in press)

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• This is a test paper, pleaseignore it
  by ReviewerV ReviewerC 
  Abstract: This is a test submission. Please ignore it
  Keywords: test test test test test test test test test test test test test test test test.
  
  
• Research on MPC path tracking control based on adaptive adjustment of near and far preview distance  
  by Shaosong Li, Detao Li, Feizhang Feng, Kai Zhang, Xiaohui Lu, Gaojian Cui 
  Abstract: Path tracking capability is a pivotal element of intelligent vehicle motion control technology. This paper introduces an innovative path tracking control method, integrating near and far-point previews, to enhance path tracking precision and vehicle stability. Employing fuzzy rule design, an adaptive near-point preview model is developed, dynamically adjusting the near-point preview distance by considering vehicle speed, path deviation, and road curvature information. Building upon this foundation, a path tracking controller is crafted using model predictive control (MPC) to enhance adaptability and tracking performance to the path. Furthermore, the far-point preview distance is determined based on vehicle speed and dynamic characteristics, thereby establishing the desired longitudinal speed of the vehicle. Subsequently, closed-loop control of longitudinal velocity is implemented to bolster safety and traffic efficiency during path tracking. Ultimately, a collaborative simulation platform, merging Carsim and Matlab/Simulink, is established to authenticate the effectiveness of the proposed control algorithm.
  Keywords: path tracking; adaptive preview; model predictive control; longitudinal speed control.
  DOI: 10.1504/IJVD.2025.10077355
   
  
• Battery anti-ageing improvement for hybrid energy storage system in plug-In hybrid electric vehicle using historical information passing network  
  by S. Mythili, S.S. Sivaraju, S. Chitra Selvi, R. Karthick 
  Abstract: The automotive industry increasingly focuses on plug-in hybrid electric vehicles (PHEVs) to reduce energy consumption and carbon emissions. However, high instantaneous power demands during driving cause frequent battery charging and discharging, which accelerates battery aging. To address this, this paper proposes a novel approach to extend battery life for hybrid energy storage systems (HESS) in PHEVs. The system combines the Historical Information Passing Network (HIPN) and Wombat Optimization Algorithm (WOA), referred to as WOA-HIPN. The WOA optimizes the power and size of the HESS, while HIPN predicts system performance. The goal is to prolong battery life and reduce operational costs. The proposed technique is tested in MATLAB and compared with existing methods, including Genetic Algorithm (GA), Back Propagation Neural Network (BPNN), and Particle Swarm Optimization (PSO). Results show that WOA-HIPN outperforms these techniques, reducing the operational cost to $3877.5, compared to $4966.6, $5517.5, and $6151.6 for the existing approaches.
  Keywords: supercapacitor; battery life improvement; DC/DC converter; energy management; HESS; hybrid energy storage system; electric vehicle; PHEVs; plug-in hybrid electric vehicles.
  DOI: 10.1504/IJVD.2025.10078606
   
  
• Intelligent vehicle path planning algorithm based on the fusion of improved RRT and dynamic window method  
  by Maofei Zhu, Fangya Hu, Nake Li, Wei Sha, Ao Zhao 
  Abstract: A smart vehicle path planning algorithm based on the fusion of improved rapidly-exploring random tree (RRT) and dynamic window method is proposed to address the problems of traditional RRT algorithms path planning not meeting vehicle motion characteristics, low efficiency, and the tendency of traditional dynamic window approach (DWA) algorithm to fall into local optima. Firstly, in RRT node expansion, a multi-sampling strategy and A* heuristic are introduced, followed by vehicle kinematics constraints to obtain sampling points. Secondly, the obtained initial path removes redundant points and extracts the critical points on the path, as well as constructing the evaluation function with the global path critical point information, which serves as the foundation for the DWA algorithm to plan the local path. Finally, the simulations in Matlab and real experiments on ROS platform demonstrate that the proposed algorithm rapidly generates global paths and effectively avoids unknown obstacles.
  Keywords: path planning; fast extended random tree; dynamic window method; fusion; obstacle avoidance.
  DOI: 10.1504/IJVD.2026.10079039
   
  
• An ergonomic approach to carsharing design for future vehicles: an evaluation of interior and exterior design proposals in medium-term and long-term perspectives  
  by Kevin Guelle, Barré Jessy, Natacha Métayer 
  Abstract: Carsharing offers a means to reduce vehicle fleets and is increasingly integrated into mobility services; however, it remains underutilised. This study aims to evaluate design concepts intended to enhance user intention. A three-phase methodology was employed. First, creativity sessions produced 8 Interior Design Proposals (IDPs) and 8 Exterior Design Proposals (EDPs). Second, after evaluation by experts, one IDP (good smell diffuser) and one EDP (retrofit) were selected. Third, an online survey (N = 236) assessed the influence of these design proposals on declared willingness to use carsharing. Findings indicate that the EDP positively affects the intention to use carsharing services in both the medium-term and long-term. In contrast, the IDP elicited less favourable responses but underscored the significance of sensory and comfort considerations in carsharing vehicles. The study underscores the need to address social and ergonomic aspects of carsharing vehicles to promote broader adoption.
  Keywords: carsharing; vehicle designs; prospective ergonomics; interior designs; exterior designs; sustainable mobility.
  DOI: 10.1504/IJVD.2026.10079109
   
  
• A lightweight model for detecting traffic signs  
  by Zhang Rongyun, Zheng Kunming, Shi Peicheng, Xu Yuxiang, Zhou Bingzhou 
  Abstract: Accurate detection of traffic signs is a prerequisite for ensuring the safety of intelligent-assisted driving vehicles. This article proposes a structure based on Ghost convolution and CBAM attention mechanism cascaded with YOLOv5's backbone feature extraction network to optimize it, thereby reducing model complexity and increasing the detection speed of traffic signs. The WIoU is adopted as the bounding box loss function, and a CARAFE upsampling module is introduced in the feature fusion layer to better recover local details of the detection targets. Simulation results show that the improved YOLOv5 model achieves a 1.8% increase in mAP, reaching 91.9%, while reducing the model's weight by 65.1% and its parameter count by 58.8%. Additionally, the detection speed increases by 8.6 frames per second (f/s).
  Keywords: Traffic sign recognition; Lightweight; YOLOv5; GhostNet.
  
  
• Adaptive inverter nonlinear compensation and full parameter online identification of permanent magnet synchronous motor based on DEKF algorithm  
  by Yong Li, Jiexin An, Han Hu, Xing Xu 
  Abstract: Inverter nonlinearities can significantly deteriorate the accuracy of parameter identification for permanent magnet synchronous motors (PMSM). To address this issue, this paper proposes a full parameter identification method of surface permanent magnet synchronous motor (SPMSM) considering inverter nonlinearity based on a dual extended Kalman observer. First, a mathematical model of the motor incorporating inverter-induced disturbance voltages is established. Then, a dual extended Kalman observer is designed to achieve high-accuracy multi-parameter identification. Meanwhile, the identified nonlinear disturbance voltages are fed into the control system for dead-time compensation, thereby suppressing the adverse effects of inverter nonlinearities on identification accuracy. The results of the simulation and motor test bench demonstrate that the proposed method can effectively compensate for inverter nonlinear disturbances, with multi-parameter identification errors below 5%, and exhibits excellent disturbance rejection performance under various operating conditions.
  Keywords: PMSM; permanent magnet synchronous motor; Extended Kalman filter algorithm; online parameter identification; dead-time compensation; inverter nonlinearity.
  DOI: 10.1504/IJVD.2025.10079232