Forthcoming Articles

International Journal of Vehicle Design

International Journal of Vehicle Design (IJVD)

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International Journal of Vehicle Design (8 papers in press)

Regular Issues

  •   Free full-text access Open AccessIntelligent obstacle avoidance control method for autonomous vehicles based on improved SAC algorithm
    ( Free Full-text Access ) CC-BY-NC-ND
    by Yulin Ma, Yide Qian, Teng Ma, Yicheng Li, Jian Wan 
    Abstract: To improve the success rate of collision avoidance for autonomous vehicles and shorten response time, an intelligent obstacle avoidance control method based on an improved SAC algorithm is proposed. This method is based on a self-organizing cluster model, integrating short-range repulsion, medium-range velocity calibration, and obstacle avoidance rules to achieve collision-free cluster collaboration. The conventional SAC algorithm adopts the AC framework to maximize the expected reward and entropy value while reducing the estimation bias of the value function through the value network component. On this basis, the PER-SAC method is proposed, which integrates priority experience replay and importance sampling weight strategy while optimizing network structure, reward and punishment functions, continuous state and action space design. Additionally, transfer learning is incorporated. The experimental results demonstrate the effectiveness of this method, achieving a collision avoidance success rate of 97%, with a maximum response time of just 0.54 s.
    Keywords: improved SAC algorithm; autonomous vehicles; intelligent obstacle avoidance control; PER; priority experience replay.
    DOI: 10.1504/IJVD.2025.10073969
     
  • 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.

  • A stable adaptive control method for the four wheel independent steering vehicle   Order a copy of this article
    by Zhiyao Pan, Hongyu Zheng 
    Abstract: Vehicle stability control is crucial for securing vehicle driving safety, while precise stability classification can assist in enhancing the performance of vehicle control. A stable adaptive model predictive controller (MPC) of the four-wheel independent steering (4WIS) vehicle is introduced in this paper. Firstly, a new vehicle dynamic model derived from a long short-term memory (LSTM) network is established and an attribute dataset representing vehicle stability is procured further. Subsequently, we employ the Gaussian mixture model (GMM)-hidden Markov model (HMM) to classify the stability of the 4WIS vehicle. According to the different classification results, the stable adaptive MPC integrated with Bayesian optimization (BO) is designed to track an optimal trajectory with high accuracy while working under different conditions. Through the simulation tests in various typical driving scenarios, the advantages of the stability classification strategy and the stable adaptive control method proposed in this paper are confirmed.
    Keywords: stability classification; stable adaptive control; four-wheel independent steering; LSTM; HMM-GMM; dataset; trajectory.
    DOI: 10.1504/IJVD.2025.10072493
     
  • Prediction of the pedestrian landing mechanism in pedestrian-vehicle collisions   Order a copy of this article
    by Tiefang Zou, Pengchen Luo, Zhuzi Liu 
    Abstract: The pedestrian-ground injuries in pedestrian-vehicle collision has always been a research focus. This study explores the prediction model of pedestrian landing mechanism in pedestrian-vehicle collision. First, seven important parameters before, during and after the collision were extracted from 1,300 cases. The obtained parameters are converted into input parameters through Principal Component Analysis (PCA). Finally, the pedestrian landing mechanism prediction model under default parameters are constructed based on Back-Propagation Neural Network (BPNN), Genetic Algorithm (GA) optimized BPNN (GA-BPNN), Support Vector Machine (SVM), Decision Tree (DT) and Random Forest (RF). The results showed that the GA-BPNN model is the optimal model under default parameters; the performance of GA-BPNN was improved after hyperparameter optimization, and the prediction accuracy of the improved GA-BPNN (IGA-BPNN) model was 76.78%, 94.86% and 95.09%, respectively. Considering the pedestrian landing mechanism can significantly reduce the risk of vehicle braking control method and improve their protection efficiency.
    Keywords: pedestrian-vehicle collision; ground-related injury; pedestrian injury protection; prediction model of pedestrian landing mechanism; neural network; vehicle braking control.
    DOI: 10.1504/IJVD.2025.10073935
     
  • Dynamic modelling of the stator system of flat wire motors   Order a copy of this article
    by Chao Yang, Ju-Guang Lin, Su-Xin Chen, Yong-Bin Zhang 
    Abstract: The dynamic behaviour of a stator system is crucial for the development of electric motors, as it plays a vital role in predicting and optimising the motor noise, which has emerged as a primary source of noise emissions in pure electric vehicles. Although the finite element method (FEM) is widely employed for modelling stator systems, existing FEM models typically focus on circular wire windings and fail to accurately represent stator systems with flat wire windings. Consequently, this paper aims to develop more precise FEM models for flat wire motor stator systems. The FEM models for the stator core, flat wire windings, insulating material, and the entire stator system are constructed by incorporating the unique characteristics of flat wire stator systems, particularly their radial stacking features. These proposed FEM models are validated through modal experiments conducted on an 8-pole 48-slot permanent magnet synchronous motor with flat wire windings.
    Keywords: stator; flat wire windings; finite element method; dynamic modelling.
    DOI: 10.1504/IJVD.2025.10074108
     
  • Research on vehicle stability control under crosswind disturbance   Order a copy of this article
    by Jun Yang, Rui Qi, Yan Zheng 
    Abstract: Aiming at the problem that the high-speed vehicle is prone to yaw instability and drive away from the predetermined path under crosswind disturbance, this paper established an eight-degree-of-freedom vehicle dynamics model considering crosswind action, and used the phase plane method to identify the vehicle's state in crosswind environment. The coordinated controller of active front-wheel steering (AFS) and direct yaw-moment control (DYC) is designed to control the stability of the vehicle in the crosswind environment. The control algorithm is simulated and verified under the crosswind disturbance condition, and the results show that the lateral displacement of the vehicle with the coordinated controller of AFS and DYC is smaller than that of the vehicle with no control and a single controller, and the vehicle yaw rate, sideslip angle, and lateral acceleration are all significantly improved. The controller improves the driving safety and stability of the vehicle in the crosswind environment.
    Keywords: crosswind disturbance; stability control; active front-wheel steering control; direct yaw-moment control; phase plane method; coordinated control.
    DOI: 10.1504/IJVD.2025.10074109
     
  • Parameter optimisation of heavy-duty vehicle wet clutch based on Kriging approximation model and multi-island genetic algorithm   Order a copy of this article
    by Xiaoyan Wang, Jie Li, Weijia Zhou, Ying Chen, Wenjing Chen, Yumeng Shen 
    Abstract: In the transmission system of heavy-duty vehicles, when the friction pair of the wet clutch is in the separation condition, due to the viscous effect of the oil, the relative speed difference between the friction plate and the steel disc will generate the drag torque in the clearance of the friction pair and the drag power loss in wet clutch, which will cause a decrease in the transmission efficiency of the power system and an increase in the failure rate. Therefore, the fluid model of friction pair was established with composite groove as the research object. Based on the Kriging approximation model, 8 groove parameters were selected as optimisation variables, and the minimum drag torque was taken as the optimisation objective. The multi-island genetic algorithm was used to optimise the structure parameters of the friction pair groove, the results showed that the optimised friction plate effectively improved the oil circulation.
    Keywords: wet clutch; optimisation of groove parameters; Kriging model; multi-island genetic algorithm.
    DOI: 10.1504/IJVD.2025.10075616
     
  • Electric control and hydraulic steering control method for corn combine harvester   Order a copy of this article
    by Fang Zeng, Shuai Qiao 
    Abstract: In order to improve the accuracy of steering control for corn combine harvesters, a PID algorithm based fully hydraulic steering control method for corn combine harvesters is proposed. Firstly, by analyzing the steering process, a steering dynamics model is constructed. Secondly, clarify the relevant variables and parameters, and derive the calculation formula for the electro-hydraulic steering control model. Again, the PID algorithm was used to design the steering controller, calculate the angular velocity deviation value, and design proportional, integral, and derivative control functions. Finally, by transforming the transfer function through Laplace transform, optimizing the parameters of the PID controller, and considering practical factors such as delay for correction, the optimization of the electronic control full hydraulic steering control was ultimately achieved. The experimental results show that the steering control accuracy of the proposed method is always above 90%, with low steering angle control error and good stability.
    Keywords: corn combine harvester; electric control full hydraulic; steering control; improve PID algorithm; Laplace transform.
    DOI: 10.1504/IJVD.2025.10075617