Subjects -> TRANSPORTATION (Total: 214 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (43 journals)
    - TRANSPORTATION (117 journals)

AUTOMOBILES (26 journals)

Showing 1 - 26 of 26 Journals sorted alphabetically
ATZ - Automobiltechnische Zeitschrift     Hybrid Journal   (Followers: 7)
ATZ worldwide     Hybrid Journal   (Followers: 2)
ATZautotechnology     Hybrid Journal   (Followers: 1)
ATZelektronik     Hybrid Journal   (Followers: 2)
ATZelektronik worldwide     Hybrid Journal   (Followers: 1)
ATZextra     Hybrid Journal   (Followers: 1)
ATZextra worldwide     Hybrid Journal  
ATZproduktion     Hybrid Journal   (Followers: 1)
ATZproduktion worldwide     Hybrid Journal  
Auto Tech Review     Hybrid Journal  
Automotive Agenda     Hybrid Journal   (Followers: 1)
Automotive and Engine Technology     Hybrid Journal  
Automotive Experiences     Open Access  
Automotive Innovation     Hybrid Journal  
Bulletin of NTU - Dynamics and strength of machines     Open Access  
IEEE Transactions on Intelligent Vehicles     Hybrid Journal   (Followers: 2)
International Journal of Automotive Composites     Hybrid Journal   (Followers: 5)
International Journal of Automotive Science And Technology     Open Access   (Followers: 1)
International Journal of Automotive Technology     Hybrid Journal   (Followers: 4)
International Journal of Automotive Technology and Management     Hybrid Journal   (Followers: 5)
International Journal of Vehicle Performance     Hybrid Journal  
MECCA Journal of Middle European Construction and Design of Cars     Open Access  
MTZ - Motortechnische Zeitschrift     Hybrid Journal   (Followers: 1)
MTZ industrial     Hybrid Journal   (Followers: 2)
MTZ worldwide     Hybrid Journal  
Proceedings of the Institution of Mechanical Engineers Part D: Journal of Automobile Engineering     Hybrid Journal   (Followers: 14)
Similar Journals
Journal Cover
International Journal of Vehicle Performance
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1745-3194 - ISSN (Online) 1745-3208
Published by Inderscience Publishers Homepage  [439 journals]
  • Torsional vibration analysis and optimisation of a hybrid vehicle
           powertrain

    • Free pre-print version: Loading...

      Authors: Bowen Ruan, Guangqiang Wu
      Pages: 337 - 357
      Abstract: Aiming at a dual-motor torque coupling hybrid vehicle, its powertrain model is established by using the lumped mass method, and an engine transient torque model based on cylinder pressure is established to analyse its natural characteristics and torsional vibration response under typical working modes. Then, the sensitivity analysis of the main parameters of the powertrain such as flywheel inertia is carried out. Based on the analysis results, the multi-objective genetic algorithm is used to optimise the parameters of the powertrain. The results show that the optimised parameters can reduce the peak second-order angular acceleration of the transmission input shaft by 25.93% and 8.06%, and reduce the peak second-order angular acceleration of the driving wheel by 32.72% and 35.14% in two working modes.
      Keywords: hybrid; powertrain; torsional vibration; multi-objective genetic algorithm; multi-mode; simulation; parameter optimisation
      Citation: International Journal of Vehicle Performance, Vol. 9, No. 4 (2023) pp. 337 - 357
      PubDate: 2023-10-04T23:20:50-05:00
      DOI: 10.1504/IJVP.2023.133851
      Issue No: Vol. 9, No. 4 (2023)
       
  • Active variable geometry suspension system development for a small
           off-road vehicle

    • Free pre-print version: Loading...

      Authors: Khashayar Moridpour, Mohammad Hasan Shojaeefard, Masoud Masih-Tehrani, Rambod Yahyaei
      Pages: 358 - 375
      Abstract: In this paper, a non-linear full-vehicle model of a mini Baja off-road vehicle is retrofitted with a series active variable geometry suspension (SAVGS). Small off-road vehicles usually have trouble performing tight cornering maneuvers due to loss of tire normal force generation and grip, leading to poor steering performance. The maneuverability is of paramount importance for race cars, thus increasing the front axle roll stiffness by changing spring forces could lead to oversteer behavior which is desired. The SAVGS can improve the cornering performance of the off-road vehicle. A powerful multibody dynamics model is proposed for vehicle and suspension dynamics behavior simulation. Overly, a configuration of 45 degrees left (outer) link and 150 degrees right (inner) link produced the best results. The proposed SAVGS satisfies the stability in the high LATAC cornering test, contrary to the conventional vehicle, and improves the understeer gradient between 15% to 58% in the other cases.
      Keywords: off-road vehicles; multibody dynamics simulation; variable geometry suspension; understeer gradient; active suspension; mini Baja; SAVGS; cornering maneuvers; steering performance; race cars
      Citation: International Journal of Vehicle Performance, Vol. 9, No. 4 (2023) pp. 358 - 375
      PubDate: 2023-10-04T23:20:50-05:00
      DOI: 10.1504/IJVP.2023.133855
      Issue No: Vol. 9, No. 4 (2023)
       
  • Objectification and prediction of the subjective criticality of axle
           damages using artificial neural networks as well as multibody- and
           real-time simulations

    • Free pre-print version: Loading...

      Authors: Robert Schurmann, Alexander Lion, Bernhard Schick, Philipp Rupp
      Pages: 376 - 403
      Abstract: For the assessment of axle damages, real vehicle tests have mostly been used so far, but they are dangerous and difficult to reproduce. Therefore, driving simulators are becoming increasingly important for the virtual rating of vehicles. Regardless of whether a real vehicle or a driving simulator is used, the prediction of the subjective perception of axle damages requires time-consuming driving tests. A powerful dynamic driving simulator is used to obtain subjective evaluations of various axle damages. Objective vehicle quantities are logged simultaneously. Subsequently, multilinear regression (MLR) models and artificial neural networks (ANN) are used to identify correlations and predict subjective evaluations based on objective data. Furthermore, real-time capable vehicle models in CarMaker and multibody dynamic (MBD) models in ADAMS/Car are used to virtually carry out driving manoeuvres and generate synthetic data. By combining the simulated vehicle data with an ANN, subjective driver evaluations can be predicted entirely virtual.
      Keywords: ANN; artificial neural network; axle damage; correlation; driving simulator; multibody simulation; MLR; multilinear regression; objective metrics; realtime simulation; subjective assessments; vehicle stability
      Citation: International Journal of Vehicle Performance, Vol. 9, No. 4 (2023) pp. 376 - 403
      PubDate: 2023-10-04T23:20:50-05:00
      DOI: 10.1504/IJVP.2023.133854
      Issue No: Vol. 9, No. 4 (2023)
       
  • Driving authority allocation model for human-machine co-driving system
           considering fault tolerant control

    • Free pre-print version: Loading...

      Authors: Jinli Xie, Xiaojun Huang, Licheng Li
      Pages: 404 - 428
      Abstract: To improve driving safety of the human-machine co-driving (HMC) vehicles, an HMC system with a dynamic authority allocation model is extended in the base of the parallel shared steering control system. The proposed system consists of a compensation control loop, a driver model control loop, and an automatic controller control loop. These three control loops can be coupled using the dynamic authority allocation model. According to the status of the driver and the HMC system, the authority allocation model dynamically changes the authority level of each control loop and coordinates each control loop to complete the driving task. The effectiveness of the extended system is verified by simulation. The results show that the impacts of different driving characteristics and states, interferences, and controller faults on the system can be weakened, and the full load working time of the trajectory tracking controller is reduced.
      Keywords: human-machine co-driving system; redundancy; safety margin; fault tolerant control
      Citation: International Journal of Vehicle Performance, Vol. 9, No. 4 (2023) pp. 404 - 428
      PubDate: 2023-10-04T23:20:50-05:00
      DOI: 10.1504/IJVP.2023.133853
      Issue No: Vol. 9, No. 4 (2023)
       
  • Twin delayed deep deterministic reinforcement learning application in
           vehicle electrical suspension control

    • Free pre-print version: Loading...

      Authors: Daoyu Shen, Shilei Zhou, Nong Zhang
      Pages: 429 - 446
      Abstract: Coming with the rising focus of the driving comfort request, more efforts are being delivered into the study of suspension system. Comparing with other traditional control methods, the machine learning control strategy has demonstrated its optimality in dealing with different class of roads. The work presented in this paper is to apply twin delayed deep deterministic policy gradients (TD3) in suspension control which enables suspension controller to go beyond searching for an optimal set of system parameters from traditional control method in dealing with different class of pavements. To achieve this, a suspension model has been established together with a reinforcement learning algorithm and an input signal of pavement. The performance of the twin delayed reinforcement agent is compared against deep deterministic policy gradients (DDPG) and deep Q-learning (DQN) algorithms under different types of pavement. The simulation result shows its superiority, robustness and learning efficiency over other reinforcement learning algorithms.
      Keywords: vehicle vertical vibration; suspension system control; artificial intelligence; reinforcement learning; twin delayed deep deterministic policy (TD3); neural network design
      Citation: International Journal of Vehicle Performance, Vol. 9, No. 4 (2023) pp. 429 - 446
      PubDate: 2023-10-04T23:20:50-05:00
      DOI: 10.1504/IJVP.2023.133852
      Issue No: Vol. 9, No. 4 (2023)
       
 
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