Forthcoming and Online First Articles

International Journal of Vehicle Systems Modelling and Testing

International Journal of Vehicle Systems Modelling and Testing (IJVSMT)

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International Journal of Vehicle Systems Modelling and Testing (7 papers in press)

Regular Issues

  • Designing and optimising seat's new suspension using TPS-NSS to enhance driver's comfort   Order a copy of this article
    by Li Zhang, Vanliem Nguyen, Hui Zan 
    Abstract: Based on the isolation efficiency of negative-stiffness-structures (NSS) in vertical direction and three parallel suspensions (TPS) in the pitch and roll directions, a seat's new suspension combined with TPS and NSS (TPS-NSS) has been proposed for enhancing ride quality in three directions of driver. In order to further enhance TPS-NSS performance, Genetic-algorithm is also applied for optimising its design parameters. Root Mean Square acceleration of driver seat in vertical, pitch, and roll directions are used to assess the TPS-NSS’s isolation efficiency. The results indicate that all Root-Mean-Square seat accelerations with TPS-NSS are strongly improved by 29.08%, 85.75%, and 91.25% compared to the NSS. Therefore, based on the good isolation and simple structure of TPS-NSS, this new isolation model should be equipped in the seat suspension for enhancing driver's ride quality in vehicles.
    Keywords: seat's new suspension; TPS-NSS; driver's comfort; vehicle vibration model.
    DOI: 10.1504/IJVSMT.2024.10062757
     
  • A study of boundary conditions for pedestrian thorax impact test   Order a copy of this article
    by Yongcheng Long, Yu Liu, Yu Xiao, Zhisheng Ruan, Zhi XIAO, Guanjun Zhang, Huang Jing 
    Abstract: Thorax injury is one of the main injuries during pedestrian impact accidents, and it is very important to evaluate the vehicle performance for pedestrian thorax injury protection, which is required to determine the boundary conditions for thorax impactor tests. A series of virtual numerical cases were carried out to simulate the impact accidents between sedan, SUV and pedestrians based on the statistical characteristics of VRU traffic accident data in China, then the kinematic process were analyzed during the vehicle-pedestrian impacts, and thorax impact parameters such as the wrap-around distance (WAD), the impact angle, the impact speed, and the angle of thorax impact velocity were extracted in each case, finally the statistical characteristics of these impact parameters were obtained for thorax impactor tests. These results can provide the effective reference data to set the test areas and the loading conditions for pedestrian thorax impactor tests.
    Keywords: pedestrian impact; thorax; boundary condition; simulation.
    DOI: 10.1504/IJVSMT.2024.10063656
     
  • Control system for electric vehicles energy use in urban routes   Order a copy of this article
    by Carlos Armenta-Déu, Alejandro Alonso 
    Abstract: One of the most relevant issues of the electric vehicle industry is the driving range. Driver attitude and driving conditions may lower the theoretical autonomy set up by car manufacturers. The result is the complaining action of unsatisfied car owners because of a reduction in the driving range. In this paper, we develop a method to maximize electric vehicle driving range by controlling driving conditions and drivers' attitudes. The methodology predicts the maximum autonomy with high accuracy based on the energy consumption of the electric vehicle. The predicting method uses a computational simulation process based on the driver's selection of specific parameters to calculate the energy consumption. The control system blocks the starting up of the electric vehicle if the selected driving conditions for the chosen urban route are non-compatible with the energy state of charge of the battery. The control system also avoids any change in driving conditions during the running that is non-compatible with the battery state of charge. As a result sudden stop due to battery exhaustion is prevented, warrantying the fulfilment of the selected route.
    Keywords: electric vehicle; driving range; control system; driving conditions simulation; software design.
    DOI: 10.1504/IJVSMT.2024.10063843
     
  • A strategy for vehicle air resistance and rolling resistance calculation based on the hierarchical estimation method   Order a copy of this article
    by Jun Luo, JiaXi Guan, XingLin Zhou, Pan Zhu 
    Abstract: To accurately calculate the air resistance and rolling resistance of the moving vehicle, we propose an adaptive hierarchical estimation method. Firstly, real-time road slope is obtained by correcting the accelerometer with angular velocity short-time integration. Then, a sliding mode observer (SMO) is employed to estimate the vehicle’s longitudinal driving force and tire lateral force. The obtained road slope and tire forces from the sliding mode observer are used as inputs with proportional parameters to an adaptive extended Kalman filter (AEKF), enabling the separate estimation of tire rolling resistance coefficient and air resistance coefficient. Further, the rolling resistance for different tires is calculated by applying vertical loads. In the hierarchical algorithm, a new sliding mode observer, adaptive extended Kalman filter, and fast slope fusion algorithm are introduced, enhancing the precision and robustness of the algorithm. Finally, the effectiveness of the algorithm is validated through simulation tests and real vehicle experiments.
    Keywords: Vehicle dynamics; rolling resistance; air resistance; parameter estimation; extended Kalman filter.

  • Thermal Optimization Study on Electrical Machine Controller for an Electric Vehicle   Order a copy of this article
    by Yang Ping, Ahmad Zhafran Ahmad Mazlan 
    Abstract: In this study, IGBT module of a pure electric vehicle motor is investigated through thermal simulation and analysis, experimental verification, and structural optimization. Based on the temperature rise test, and the comparison of temperature rise and heat dissipation curve using FEA, it is found that the result can accurately simulates the heat dissipation of the IGBT module, with the temperature error within 2 ? and the natural heat dissipation errors less than 3 ? during forced heat dissipation. This data supports the optimization of the controller radiator heatsink. Finally, the ANSYS optimization module was employed to parametrically optimize dimensions and positional parameters such as length, width, and spacing of the heat sink fins, as well as fan-to-heatsink distance. The ideal parameter solution was produced using multi-objective optimization algorithms and iterative methods, resulting in minimizing mass and lowest temperature while meeting the heat dissipation requirements.
    Keywords: Pure electric vehicles; Motor controller; IGBT; Heatsink optimization; Simulation study.

  • Integrated decision-making methodology based on reinforcement learning and imitation learning for automated commercial vehicles in the urban traffic environment   Order a copy of this article
    by Weiming Hu, Jinchao Hu, Yan Liu, Jinying Zhou, Mengyue Su 
    Abstract: Driving decision-making plays an important role in determining the rationality and safety of automated commercial vehicles. Unlike extensively studied passenger vehicles, commercial vehicles exhibit longer braking distances, inferior roll stability, and increased visual blind spots. To achieve safe automated driving, with due consideration for low carbonization and energy conservation, we present an integrated driving decision-making methodology based on multi-head attention (IDDM-MA). The IDDM-MA model comprises two interconnected networks. Initially, the soft actor-critic algorithm is employed to acquire driving strategies in hazardous scenarios via unsupervised learning. Subsequently, generative adversarial imitation learning is applied to simulate safe driving maneuvers modeled after human drivers. Finally, the IDDM-MA model is trained and evaluated within the SUMO (Simulation of Urban Mobility) environment. Experimental outcomes reveal that our proposal ensures reasonable clearances and lateral acceleration when the perception system detects obstacles within blind areas. Simultaneously, it demonstrates lower carbon emission intensity and improved fuel economy.
    Keywords: safe driving decision-making; automated commercial vehicle; urban traffic environment; deep reinforcement learning; imitation learning.
    DOI: 10.1504/IJVSMT.2024.10065246
     
  • Ship longitudinal structural stiffening for navigating turbulent water environment   Order a copy of this article
    by Moses Oyaro Okello, Jian Zhang, Shi Hua 
    Abstract: This paper proposes techniques to enhance the longitudinal strength of cargo ships to ensure minimum stress and deformation during sagging and hogging. The first technique is stern-to-bow, which uses curve support structures to increase the longitudinal strength of a cargo ship. Another technique to stiffen a ship's lateral plate is the use of different design patterns, such as wavy curves, stars, and zigzags etc. for the side plate stiffening. In addition, structural topology optimisation is used to generate the optimal plate designs with the minimum plate mass. A numerical study on different stiffened plates with fixed supports on both ends subjected to a uniform load distribution show that there is a decrease in both the total deformation and mass of the plate when the wavy, star, and zigzag pattern plate stiffening is used. Furthermore, curving the plate on top can increase its strength during sagging as well as hogging.
    Keywords: finite element analysis; finite element method; sagging; hogging; topology optimisation; plate stiffening.
    DOI: 10.1504/IJVSMT.2024.10065317