Forthcoming and Online First Articles

International Journal of Vehicle Performance

International Journal of Vehicle Performance (IJVP)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Vehicle Performance (8 papers in press)

Regular Issues

  • Exploration of robust and intelligent navigation algorithms to ensure off-road autonomous vehicle mobility   Order a copy of this article
    by Michael Cole, Kumar B. Kulkarni, Jordan Ewing, Seth Tau, Christopher Goodin, Paramsothy Jayakumar 
    Abstract: The combat capabilities development command (DEVCOM) ground vehicle systems centre (GVSC) is supporting unmanned ground vehicle (UGV) development. Past experimentations of a military UGV demonstrated that its autonomous mode performed worse than the tele-operated mode. To address this, a systematic investigation into path planners for military vehicles in off-road environments was executed. A UGV simulator was used to evaluate vehicle and planner performance through a range of obstacle avoidance scenarios in deformable soil to capture the effects of vehicle-terrain interactions across multiple soil types. Monte Carlo methods were used to evaluate the robustness of five path planners ranging from classical to state-of-the-art planners, with normally-distributed variability in environmental and vehicle initial conditions. After running thousands of simulations, results show how each algorithm compares to one another in several key metrics including overall success rates. These results will help inform decisions in future military UGV path planner selection.
    Keywords: navigation algorithms; vehicle mobility; autonomous vehicles; unmanned ground vehicles; UGV; path planning; vehicle-terrain interactions; VTI.
    DOI: 10.1504/IJVP.2024.10062615
     
  • Optimal adaptive Lipschitz continuous sliding mode controller with APSO algorithm for an autonomous vehicle   Order a copy of this article
    by Ayoub Belkheir, El Mehdi Mellouli, Vidas Žuraulis 
    Abstract: he paper presents a method for controlling lateral movement with uncertain and unknown dynamics for an autonomous vehicle that combines the adaptive particle swarm optimisation (APSO) algorithm and the Lipschitz continuous sliding mode controller (LCSMC). Designing the desired trajectory, and modelling the vehicle using the bicycle model is the initial step. The control law is defined using the classical Lipschitz continuous sliding mode control (LCSMC) in the following step. In the next step, the systems nonlinear functions are modelled using a radial basis function neural network (RBFNN), the developed intelligent triangular observer is proposed, and the suggested approach adaptive Lipschitz continuous sliding mode control (ALCSMC) is suggested with stability analysis using the Lyapunov function and optimising the parameters gain using APSO algorithm after. Finally, the study is finished by simulating this strategy to see their performance and effectiveness in accomplishing the desired results.
    Keywords: adaptive particle swarm optimisation; APSO; autonomous vehicle; Lipschitz continuous sliding mode control; LCSMC; Lyapunov function; triangular observer.

  • A systematic approach to design electric vehicle powertrains: model-based simulation and real-world application   Order a copy of this article
    by Shafi Md. Istiak, Md. Rashed Hossain, Nahin Tasmin 
    Abstract: In this age of electric vehicle (EV) technology, simulating the vehicle system cuts prototyping expenses and aids engineers in choosing the appropriate components and systems for the vehicle. This study presents a methodology for developing a mathematical model for electric vehicles using CarSim 2017 Software, which lacks an inherent electric vehicle model but can be connected to MATLAB Simulink. Additionally, the research applies the insights derived from simulation results to guide the conversion of a combustion engine vehicle into an electric one. The process starts with creating a simulation model in MATLAB/Simulink that integrates a permanent magnet synchronous motor (PMSM), motor controller, and battery with a vehicle model in CarSim software. Based on simulation results, appropriate powertrain specifications were generated for an EV prototype developed by converting a conventional vehicle. The prototype was tested in real-world conditions using a standard driving cycle to evaluate its performance.
    Keywords: electric vehicle; MATLAB; electric powertrain; Simulink; CarSim; simulation; prototyping.

  • High-speed trajectory following of a heavy-duty vehicle via adaptive nonlinear model predictive controller   Order a copy of this article
    by Volkan Bekir Yangin, Ozgen Akalin, Yaprak Yalcin 
    Abstract: In this paper, a controller based on novel discrete-time adaptive nonlinear model predictive control (AN-MPC) is proposed to enhance the trajectory tracking performance of a heavy-duty vehicle preventing the wheel lift-off and lateral slip, increasing maximum NATO double lane change (DLC) speed. An eight-DOF nonlinear vehicle model is designed as a system model to obtain the realistic behaviour of the vehicle. This model is experimentally validated by using the data obtained in NATO DLC tests. The proposed controller is based on a two-DOF nonlinear single-track vehicle model and configured to be adaptive in two aspects: linearisation of the base model at each sampling instant and online tuning of the controller parameters. The tuning process is achieved by an artificial-neural-network structure. The simulated results revealed that the DLC speeds can be significantly improved due to the predictive capability of the proposed controller, compared to the classical PID controllers or human drivers.
    Keywords: vehicle dynamics; lateral stability; maximum speed; trajectory tracking; steering angle control; model predictive control; MPC.
    DOI: 10.1504/IJVP.2023.10059665
     
  • Theoretical investigation of the rail vehicle suspension system using different optimised controllers by harmony search algorithm incorporating magnetorheological dampers   Order a copy of this article
    by Shaimaa Ahmed Ali, Hassan Metered, A.M. Bassiuny, A.M. Abdel Ghany 
    Abstract: Magnetorheological (MR) dampers are highly valuable semi-active devices for vibration control applications rather than active actuators in terms of reliability and implementation cost. This paper offers a deeply theoretical investigation into the use of proportional integral derivative (PID), fractional order PID (FOPID), and single-neuron PID (SNPID) for the first time in conjunction with the damper controller of a rail semi-active MR vehicle suspension. The different gains of the three mentioned controllers are tuned and optimised using the harmony search (HS) algorithm to achieve good suspension performance in the vertical direction. The self-adaptive global best harmony search (SGHS) method is selected to optimise controllers' gains due to its effectiveness in reducing tuning time and minimising the objective function value. A quarter-rail vehicle model consisting of six degrees of freedom (6-DOF) is derived and simulated using MATLAB/Simulink software. System performance criteria are evaluated in the time and frequency domains to evaluate the effectiveness of proposed controllers. The simulated results show that the SNPID significantly improves ride comfort over the applied controllers.
    Keywords: magnetorheological dampers; rail vehicle suspension; self-adaptive global best harmony search algorithm; SGHS; PID; fractional order PID; FOPID; single-neuron PID.
    DOI: 10.1504/IJVP.2024.10061373
     
  • A comparative analysis of energy consumption in conventional and electric vehicles   Order a copy of this article
    by S. Gopiya Naik, Syed Mohammed Mustafa Nabi 
    Abstract: Most widely used motorised vehicles until now are petroleum-based vehicles. But, environmental concerns, policy change and technological advancements are resulting in steady replacement of the conventional vehicles with electric vehicles (EV). With widespread adoption of EVs, it is a must to compare their performance against conventional vehicles. In this paper, the performance of electric propulsion (EP)-based scooters and internal combustion engine (ICE)-based scooters are analysed in terms of power requirement, torque requirement, energy consumption, and mileage. These scooters are modelled using MATLAB Simulink considering longitudinal vehicle dynamics. For this, drive cycle of Mandya City (Karnataka state) is constructed by gathering speed versus time data by driving a scooter with various rolling resistance coefficients. In addition, a standard signal having constant and zero acceleration, constant deceleration phases is also considered to simulate the models in a hilly region by varying the grade angle. Four popular commercial scooters available in India were modelled.
    Keywords: electric vehicle; internal combustion engine vehicle; drive cycle; battery-to-wheel efficiency; tank-to-wheel efficiency; vehicle dynamics; Arduino UNO.
    DOI: 10.1504/IJVP.2024.10062296
     
  • An empirical vehicle speed model for tuning throttle controller parameters   Order a copy of this article
    by Christopher Goodin, Marc N. Moore, Daniel W. Carruth, Christopher R. Hudson, Lucas D. Cagle, Paramsothy Jayakumar 
    Abstract: Modelling vehicle longitudinal dynamics is critical for developing speed-control strategies. In this work an empirical model of vehicle longitudinal dynamics is proposed. The purpose of the empirical model is to facilitate the tuning of proportional-integral-differential (PID) parameters for a real-world vehicle. With a short series of measurements, a predictive model of the vehicle speed was developed by fitting the model to the measured data. The empirical model presented in this work has the advantages that it is simple - it does not require any detailed measurements of the vehicle properties but is rather easily fit to real measurements. The model is also flexible, being applicable to a range of different vehicles. In this work, the development of the model is outlined and an application of the model is shown for two different vehicles, the Polaris MRZR4 and the Clearpath Warthog, which have different drive-train and suspension characteristics. The applicability of the empirical model is demonstrated by tuning and testing a real PID controller for the MRZR4.
    Keywords: dynamic systems and control; autonomous vehicles; vehicle dynamics; autonomous driving.
    DOI: 10.1504/IJVP.2024.10061372
     
  • A novel traction control strategy for an electric bus   Order a copy of this article
    by Changcheng Yin, Zhongyi Mei, Ying Feng, Liang Tang 
    Abstract: The traction control system (TCS) of an electric vehicle is the key to ensuring sufficient stability when the vehicle starts with a large throttle opening. Therefore, a novel control method for the TCS of a single-motor, non-fully driven electric vehicle is proposed in this paper. First, to obtain the road type and optimal slip rate of the driving wheels, an extended Kalman filter (EKF) is used to estimate the gradient and total mass of the vehicle, and an unscented Kalman filter (UKF) is used to estimate the road adhesion coefficient. Second, a TCS controller based on the road type and optimal slip rate of the driving wheels is established for coordinated control of the motor torque and brake pressure, including a brake controller for compensating the load on the side with a lower adhesion coefficient on split roads, a model predictive control (MPC) torque controller for wheel slip control, and an additional torque controller for compensating the torque required by crossing roads. Finally, the effectiveness and accuracy of this method are proven by a joint simulation in TruckSim and MATLAB/Simulink. The slip rate of the driving wheels can indeed be kept near the optimal slip rate on various pavements.
    Keywords: electric vehicles; model predictive control; EPC; optimal slip rate; traction control system; TCS; unscented Kalman filter; UKF.
    DOI: 10.1504/IJVP.2024.10062312