International Journal of Vehicle Performance (7 papers in press)

Regular Issues

• Research on automatic lane-changing decision of heavy trucks in highways based on Bayesian networks and rough set theory  
  by Libo Mao, Guangqiang Wu 
  Abstract: This paper addresses the lane-changing decision problem of unmanned heavy-duty trucks in highway scenarios and develops a novel algorithm integrating rough set theory and Bayesian networks. Nine conditional attributes related to vehicle speed, relative distance and relative speed are selected, along with three decision categories including left lane change, right lane change and no lane change. The training dataset is built using data from the public HighD dataset and real driving data collected on Donghai Bridge. Attribute values are discretised by the Chimerge algorithm, and redundant attributes are eliminated through rough set reduction. A Bayesian network is then established to learn lane-changing patterns and judge the appropriate lanechanging moment. PreScan-Simulink co-simulations and real-vehicle tests are conducted for comprehensive validation. Results show that the proposed method possesses high decision accuracy and low computational overhead, which fully meets the practical requirements of engineering applications
  Keywords: autonomous heavy truck; rough set theory; Bayesian networks; data discretisation; attribute reduction.
  DOI: 10.1504/IJVP.2026.10079457
   
  
• A dual energy efficient hybrid control strategy for electric vehicle-IoT driven by in-wheel-motors based on adaptive sliding mode control and medium access control  
  by Mahdi Al-Quran, Yahia Al-smadi, Waleed Nayfeh, Majd Abbad 
  Abstract: In the present work, a dual energy-efficient hybrid control strategy is proposed for the electric vehicle-internet of things (EV-IoT) systems driven by in-wheel motors. The proposed approach integrates the adaptive sliding mode control (ASMC) with the bit mapping buffer status of medium access control (MAC) to optimise the data transmission and energy consumption. A proposed strategy utilises the bit mapping of slide mode control, which dynamically adjusts the operational modes through control signals. The data management is organised into data slots. Each slot contains four sub-slots that accommodate mixed data from the magnetometer, LIDAR and RADAR (MLR) sensors, global navigation satellite system (GNSS), inertial measurement unit (IMU) and barometric altitude sensor (BAS). Each vehicle transmits its bit mapping data to the roadside unit (RSU) which indicates the buffer status of each sensor type are full or empty. This information allows the RSU to selectively activate the radio during the necessary sub-slots. It processes only the relevant data and thus optimises the usage of energy. The proposed approach enhances the overall system performance by ensuring real-time data processing while minimising the energy resources. The proposed approach offers a structured and efficient method for managing sensor data channels. Thus, the present work contributes in the advancement of energy-efficient EV-IoT systems. In the present work, the proposed method is also compared with the existing variants of TDMA protocols. The results prove the superiority of the proposed method.
  Keywords: sliding mode control; SMC; medium access control; MAC; bit-mapping; electric vehicle-internet of things; EV-IoT.
  DOI: 10.1504/IJVP.2026.10079677
   
  
• Design of optimal drive control strategy for extended range electric vehicles  
  by Long Huang 
  Abstract: This paper proposes a drive control strategy based on reference SOC curve and simulated annealing particle swarm optimisation (SA-PSO) to address the problems of high energy consumption, large battery SOC fluctuations, and low drive system efficiency in extended range electric vehicles (EREVs) under complex operating conditions. By combining vehicle dynamics with the equivalent circuit model of the battery, a control model with the goal of minimising energy consumption is constructed. The operating condition reference SOC curve is generated through dynamic programming, and the PSO update process is optimised using SA. The results show that compared with traditional logic threshold and single PSO strategy, this strategy significantly reduces SOC tracking deviation and energy consumption by 9.5%19.8%. Compared to genetic algorithms, it has a 46.2% increase in convergence speed and stronger stability, balancing energy efficiency and system stability.
  Keywords: particle swarm optimisation; PSO; extended-range electric vehicle; drive control strategy; dynamic programming; DP; simulated annealing; SA.
  DOI: 10.1504/IJVP.2026.10079968
   
  
• Designing a terminal sliding mode controller for steer-by-wire system considering vehicle's network delay  
  by Ali Anisi, Moosa Ayati 
  Abstract: This paper presents a fault-tolerant algorithm specifically designed for the steer-by-wire (SbW) system, addressing critical challenges such as random fractional delays and network-induced packet loss issues rarely addressed comprehensively in existing research. The algorithm integrates innovative elements, including a terminal sliding-mode disturbance observer and a discrete-time sliding-mode controller with a time-delay compensator, both optimised for the SbW system using a simplified model. Extensive validation and performance assessment, conducted using the CarSim/MATLAB co-simulator platform, provide unprecedented insights into its capabilities under simulated real-world conditions, marking an advancement in the field.
  Keywords: steer-by-wire; SbW; discrete-time sliding mode controller; networked delay; fault detection; input disturbance.
  DOI: 10.1504/IJVP.2026.10080061
   
  
• Optimising electric vehicle motor mounts: a comprehensive review of design, materials and analysis  
  by Nimay Koojappady, Kiran Manjunath, Trishul Subaiah, Mantesh Basappa Khot 
  Abstract: Electric vehicle (EV) motor mounts play a critical role in supporting the powertrain while isolating vibrations and reducing noise transmission to the vehicle structure. Unlike internal combustion engine (ICE) vehicles, EVs generate high-frequency electromagnetic excitations and operate with reduced acoustic masking, making occupants more sensitive to structure-borne vibrations and noise. Consequently, conventional engine mount designs are often inadequate for meeting EV-specific noise, vibration, and harshness (NVH) requirements. This review examines the design principles, material selection, and optimisation strategies employed in EV motor mount development. Particular emphasis is placed on passive mount systems, elastomeric and metallic materials, finite element analysis (FEA), topology optimisation, and stiffness tuning techniques used to improve vibration isolation, durability, and lightweighting. Current challenges, research gaps, and emerging trends, including advanced materials and adaptive damping concepts, are discussed. The review highlights the importance of optimised motor mount designs in enhancing NVH performance, ride comfort, and overall EV powertrain efficiency.
  Keywords: powertrain mount; vibration isolation; finite element analysis; FEA; electric vehicle; passive mounts; active damping.
  DOI: 10.1504/IJVP.2026.10080557
   
  
• Experimental investigation of the effects of steady and pulsed blowing flow separation control techniques on the aerodynamic performance of a sports car  
  by Hasan Hidayet Dumrul, Emre Kara 
  Abstract: Aerodynamic drag represents a significant factor in the performance of vehicles operating at high speeds. In this study, effects of the active blowing techniques on flow separation in the rear region of the model are evaluated. The employment of steady blowing and pulsed blowing techniques, utilising a programmable pressure controller and an electronical flow controller along with a 75 cm 75 cm wind tunnel, serves to modify flow structure and reduce pressure drag. The steady blowing technique reduced the drag coefficient from 0.3314 to 0.3197 at ReL = 422,303, corresponding to a maximum drag reduction of 3.54%. Under same Reynolds number condition, pulsed blowing technique decreased the drag coefficient to 0.2336, achieving a maximum aerodynamic improvement of 29.51%. A general evaluation of the study concluded that process of flow separation can be delayed by the employed techniques, most significantly by pulsed blowing.
  Keywords: active flow control; AFC; steady blowing; pulsed blowing; flow separation control; aerodynamic drag reduction; vehicle aerodynamics.
  DOI: 10.1504/IJVP.2026.10080989
   
  
• Multi-output sensitivity analysis of the powertrain mounting system with parametric uncertainty and correlation  
  by Xiaoting Huang, Haibiao Zhang, Hui Lü, Weihua Li 
  Abstract: To address the complex situation where the dynamic parameters of powertrain mounting system (PMS) are simultaneously uncertain and correlated, and to overcome the limitations of traditional sensitivity analysis in evaluating the influence of system parameters on multiple responses, the multi-output sensitivity analysis of an electric vehicle PMS is carried out by considering parametric uncertainty and correlation. First, a 13-degree-of-freedom dynamic model of PMS is established, and the correlated probabilistic variables are employed to characterise the parametric uncertainty and correlation. Then, the first-order and total global sensitivity indices for the single-output sensitivity analysis of PMS are derived based on Rosenblatt transform. Subsequently, a multi-output global sensitivity analysis method of PMS is proposed relying on principal component analysis, and the calculation process of multi-output sensitivity indices is developed by Monte Carlo analysis. Finally, the effectiveness of proposed method is demonstrated by the application example.
  Keywords: powertrain mounting system; PMS; multi-output sensitivity analysis; parametric uncertainty; parametric correlation; principal component analysis.
  DOI: 10.1504/IJVP.2026.10081484