International Journal of Heavy Vehicle Systems (23 papers in press)

Regular Issues

• Assessment of the dynamic stability of mine-rollers-equipped heavy vehicle  
  by Mostafa I. Yacoub, Mootaz E. Abo-Elnor, Ahmed M. Ali, Ibrahim A. Elsherif, Mohamed A. El-Latif, Alhossein Mostafa Sharaf 
  Abstract: One of the strategies to protect vehicle platoons against Improvised Explosive Devices (IEDs) is to use a mine-roller mounted at the front of the vehicle with a telescopic lever and fork ending with two sets of freely rotating solid tyres. However, rough vehicle handling or cornering in unstable conditions may be encountered particularly at high speeds. This paper presents a detailed investigation to ensure sufficient handling and stability of mine-rollers-equipped vehicle. In the design phase, both the kinematic and dynamic analyses are illustrated. The mathematical analysis of the dynamic stability problem is validated by in-field measurements of a real mine-rollers-equipped heavy vehicle. Results show that vehicle stability could be achieved using the pre-manufacturing mathematical analysis illustrated in this article. Furthermore, the analysis is extended to address the effect of some mine-rollers design parameters, such as increasing setup length and weight, which would certainly enhance the protection of the mobile platoon.
  Keywords: mine-rollers; heavy vehicle stability; handling performance; convoying security.
  
  
• Deep learning-based forecasting of port cargo throughput using PCA and error correction multivariate LSTM  
  by Sihao Wei, Wei Deng 
  Abstract: As an emerging technology, deep learning has been well-used in many fields. This paper mainly studies the application of deep learning in smart cities about port cargo throughput forecasting. Firstly, the port cargo throughput is analysed by Principal Component Analysis (PCA). Correlation analysis was carried out on the impact factors, and the screened GDP and container throughput was put into the multivariate long-term short-term memory neural network (LSTM) as external input factors to improve the accuracy, and a multivariate LSTM prediction model based on PCA was built; then, using the errors generated by the prediction model in the prediction of cargo throughput in Ningbo Zhoushan Port as training data, training to generate error sequences, and the prediction data are subjected to error correction to increase the prediction accuracy. Lastly, the model's forecast outcomes are contrasted with the vector autoregressive model (VAR), Holt-Winters, grey prediction model, and univariate LSTM model prediction results were compared and analysed. The comparison results show that the multivariate LSTM prediction model based on PCA and error correction has higher prediction accuracy
  Keywords: smart cities; artificial intelligence; deep learning; principal component analysis; multivariate long short-term memory neural network; error correction; port cargo throughput.
  DOI: 10.1504/IJHVS.2023.10059804
   
  
• Analysis and evaluation of CFD simulation uncertainty based on aerodynamic drag of the Ahmed car  
  by Peng Li, Xiaoyu Yang, Sha Huang, Zhan Huang, Jiqiang NIU 
  Abstract: To identify the key factors affecting aerodynamic drag prediction in the aerodynamic shape optimisation design of ground transportation, a quantitative and sensitivity analysis of aerodynamic drag uncertainty were conducted with Ahmed car as the object. Grid size, turbulence model, pressure velocity coupling and spatial discretisation scheme are selected as variables, and their values are assumed. Then, an orthogonal experimental design scheme was used to calculate aerodynamic drag using the CFD method. Multi factor CFD uncertainty quantification and sensitivity analysis were conducted, and verified with wind tunnel experimental data. The results show that, the degree of effect on the aerodynamic drag of the Ahmed car is in the order of spatial discretization scheme, grid size, pressure velocity coupling, and turbulence model. The best simulation strategies for aerodynamic drag are: QUICK scheme, fine grid, SIMPLEC algorithm, SST k- turbulence model.
  Keywords: uncertainty analysis; Ahmed car; aerodynamic drag; CFD; grid independence.
  DOI: 10.1504/IJHVS.2023.10060022
   
  
• Research on an all-axle active steering control strategy of articulated vehicles based on feedforward-feedback control  
  by Song Zhongchao, Zhang Liwei, Zhang Menglei, Jiao Yanbin 
  Abstract: To improve the trajectory tracking ability of multi-module articulated vehicles, an all-axle active steering control strategy based on feedforward-feedback control is proposed. Based on the kinematics model, the expected steering angle is calculated as the feedforward control signal. The trajectory error of each axle is defined, a vehicle controller based on sliding mode control algorithm is designed to obtain additional steering angle as the feedback control signal. The vehicle model is built and run in ADAMS. Compared with no control, the tracking error of each axle of the front and middle cars is reduced by about 50%, and that of the rear car is reduced by about 75%. It indicates the control strategy is more effective in improving the tracking ability of each axle of the rear. In conclusion, the proposed control can reduce the tracking error of each axle and improve the trajectory tracking ability of the vehicle.
  Keywords: articulated vehicles; all-axle active steering control; feedforward-feedback control; sliding mode control.
  DOI: 10.1504/IJHVS.2023.10060077
   
  
• Dynamic response analysis of hydraulic-mechanical composite drive system of anchor drill truck  
  by Hong Zhang, Chaochao Yang, Wanli Wang, Yuyan Wu 
  Abstract: In order to meet the unique adaptability of the anchor drilling truck driving on complex underground road surfaces and overcome the problem of slow transfer of tracked vehicles, a hydraulic-mechanical composite transmission wheel driving system is designed. The hydraulic, mechanical and ground models of the driving part are constructed and the model is verified. Finally, the driving power response of the vehicle's hydraulic-mechanical transmission on complex road surfaces such as plane roads, passing obstacles, climbing hills, and braking, turning conditions is simulated. The results show that the vehicle can drive on complex road surfaces, with a maximum speed of 5.76 km/h, a maximum long-distance climbing angle of 10.8
  Keywords: anchor drilling truck; compound drive; pressure flow; torque speed; power response.
  DOI: 10.1504/IJHVS.2024.10061185
   
  
• Vibration optimisation of truck cargo transport compartment using numerical simulation  
  by Mostafa Mirtabaee, Seyed Amirhossin Ahmadi 
  Abstract: Reducing vibrations in truck cargo transport compartments has become increasingly important to prevent damage to the cargo and ensure the safety of passengers. Optimising truck cargo transport compartments based on transportation vibration standards, such as MIL-STD-810H, can considerably improve their performance, reduce transportation damages, and increase the agility and speed of heavy vehicles. The purpose of the current research is to analyse and optimise the cargo transport compartment of the Benz 911 truck by numerical methods. For this purpose, the frequency transfer function of the truck cargo transport compartment is determined by considering the effects of the weight of loads and road and engine dynamic forces at natural frequencies. Finally, after 14 optimisation steps, the obtained weight reduction is 38.8% compared with the initial state, and the maximum acceleration has also been reduced by 56.6% compared with its initial value.
  Keywords: truck cargo transport compartment; MIL-STD-810H; optimisation; vibration; modal analysis; frequency transfer function.
  DOI: 10.1504/IJHVS.2024.10061272
   
  
• Study on cold chain logistics vehicle path optimisation method based on improved artificial bee colony algorithm  
  by Fengju Chen, Jingzhao Zhang 
  Abstract: Cold chain logistics describes the process of transporting and storing perishable items from their point of manufacture to the final customer transportation and storage facilities equipped with refrigeration systems. Using cold chain logistics, perishable foods such processed foods, meats, seafood, ice creams, poultry, dairy products, vegetables, and fruits can be safely transported from the producer to the consumer. Effective planning of the cold chain logistics vehicle is crucial for minimising travel time, distance, and overall logistics costs in order to get the product to the consumer. One such artificial swarm intelligence technique is the Artificial Bee Colony (ABC) algorithm , which is inspired by the activities of bees and their colonies. The fundamental aim of this research is to reduce the time, distance and cost associated in transportation. The results show that effective cold logistics transportation and optimal path selection have been achieved with a 98 83% success.
  Keywords: cold chain logistics; path optimisation; artificial intelligence; transportation; artificial bee colony.
  DOI: 10.1504/IJHVS.2023.10061595
   
  
• Practice of fast body attitude control for multi-axle active suspension vehicles via bi-directional attitude-suspension kinematics modelling  
  by Fan Zhang, Zhenhua Wu, Chu Li, Jintian Cai, Jiguo Yang 
  Abstract: Multi-axle off-road vehicles with suspension lifting function can achieve some robotic manoeuvring effects through body attitude and wheel lifting adjustment, but carry larger loads. In the face of the hyperstatic and coupled-bearing challenges of multi-axle suspension systems, constructing a kinematic model to guide attitude transitions is a fundamental part of active suspension control. Firstly, the bi-directional kinematic relationship between body attitude and suspension displacement on uneven ground is presented to provide graphical interaction for the driver. Secondly, multibody dynamics simulations are carried out for vehicle state calculation and body attitude adjustment. Finally, a three-axle independent hydraulic suspension experimental platform is developed, and active attitude control experiments are carried out. Experimental results show that the scheme can achieve flexible and effective attitude control of multi-axle vehicles under complex ground conditions, thus playing a positive role in enriching the active suspension control functions of multi-axle vehicles and supporting the vehicle extrication.
  Keywords: multi-axle vehicle; active suspension; attitude control; Hydraulic system; hyperstatic problem.
  DOI: 10.1504/IJHVS.2024.10061893
   
  
• Research on active suspension-based anti-rollover control strategy for side-unloading dump trucks during lifting operations  
  by Tianmin Zhu, Mingmao Hu, Qinghe Guo, Min Liu, Renjun Liu, Mengchao Wang, Zhongcheng Fu, Yu Wang 
  Abstract: Aiming at the problem of poor stability of side-unloading dump trucks under lifting conditions, an anti-rollover control strategy combining active suspension and fuzzy sliding mode control was proposed. Considering the changes in the mass and spatial position of the cargo during lateral unloading, a four-degree-of-freedom side-unloading dump truck nonlinear model was established, and the model's accuracy was validated using MATLAB/Simulink. The adjustment of sliding mode control parameters is realized through fuzzy logic, and the fuzzy-sliding mode controller is used to obtain the anti-roll moment that suppresses suspension deformation. A rollover warning controller was designed using the ratio of the right wheel load to the total vehicle weight as the rollover evaluation index. Simulation is conducted using ordinary sliding mode control and without any control for comparison. The results indicate that this strategy enhances the lateral stability of side-unloading dump trucks under lifting operations, effectively preventing rollover incidents.
  Keywords: side-unloading dump truck; active suspension; anti-rollover; fuzzy-sliding mode control.
  DOI: 10.1504/IJHVS.2024.10062414
   
  
• Development of a direct yaw moment control strategy for an articulated bus equipped with on-board electric motors  
  by Kerem Bayar 
  Abstract: Considering the damping moment associated with the articulation joint of buses, the degree of actuation freedom increases, for stabilising the vehicle during harsh manoeuvres on slippery surfaces. With this background, this study aims at developing a direct yaw moment control strategy for an articulated bus, equipped with on board electric motors at middle and rear axles, that is capable of braking / accelerating the left and right wheels independently. The yaw moment control problem is treated as a control allocation problem, where the corrective yaw moment action for front and rear compartments, is distributed onto individual wheel braking/acceleration and articulation joint damping moment. Through lane change and snaking manoeuvre simulation results, the effectiveness of the proposed controller is shown, in terms of tracking the desired front and rear compartment yaw rates. This is achieved without sacrificing vehicle sideslip and articulation angles.
  Keywords: direct yaw moment control; articulated bus; control allocation; yaw rate; articulation angle; vehicle sideslip angle; on board electric motor.
  DOI: 10.1504/IJHVS.2024.10062569
   
  
• Lightweight security scheme for data management in the e-commerce platform  
  by Zhiwen Cai, Jingying Ke 
  Abstract: This paper proposes Lightweight Distributed Accessible Control (LW-DAC) for data management to secure users' data in an E-commerce Platform. The Lightweight Security method enables distributed user information access control for protected users. This system's security is reduced to the Bilinear Discrete Diffie-Hellman (BDDH) assumption, which helps the Decision Making Algorithm minimize the execution time. The proposed method provides easy data encryption, trapdoor keyword generation and data recovery. BDDH filters the keyword search to avoid accessing the terminal. The algorithm has been compared with the existing system and proven based on reliability and scalability highly efficient. The simulation analysis demonstrated that the proposed Lightweight Security Scheme for data management system encrypts the user data and prevents the backdoor access with high scalability, performance, and lesser mean square error.
  Keywords: bilinear Diffe-Hellman; lightweight; security; keyword search; backdoor and data management.
  DOI: 10.1504/IJHVS.2024.10064242
   
  
• Optimisation-enabled deep learning model for traffic sign recognition  
  by Soja Salim, J.S. Jayasudha, B. Soniya 
  Abstract: A novel optimisation algorithm-trained deep learning network is developed to recognise all symbol-based traffic signs. The deep learning method employed here for the recognition is Deep Q Network (DQN) with an optimization algorithm, named Gradient Descent- Team Work Optimisation algorithm (GD-TOA), for training the DQN. Initially, the Gaussian filter is used for the pre-processing phase, in which the noise can be eliminated. Thereafter, the sign localisation is performed using SegU-Net with a modified loss function that includes balance cross-entropy, rescaled hinge loss, and insensitive loss to localise the sign region from the image. Finally, TSR is performed using the proposed GD-TOA-based DQN so as to improve the TSR performance. The experimentation reveals that the proposed GD-TOA-based DQN technique attains an overall improvement regarding the precision, accuracy, recall, and F measure with values 0.977, 0.972, 0.971, and 0.973, respectively.
  Keywords: traffic safety; traffic sign recognition; deep learning; sign localisation; optimisation algorithm.
  DOI: 10.1504/IJHVS.2024.10064331
   
  
• Real-time emission test and evaluation method of heavy-duty diesel vehicle SCR system based on dynamic time warping  
  by Xuejian Ma, Tao Qiu, Yan Lei, Zexun Chen 
  Abstract: Selective catalytic reduction (SCR) technology is the most important technical to solve the high NOx emission of diesel vehicles. In-use heavy-duty diesel vehicles must undergo emission spot checks at inspection stations to avoid exceeding the NOx emission limits due to abnormal operation of the SCR system. A method that can quickly carry out in-situ emission tests on heavy-duty diesel vehicles on the road to evaluate SCR operation status is of great significance. In this paper, a method based on dynamic time warping (DTW) is proposed to quickly judge the SCR operation status when the vehicle is stationary. The variation of similarity between SCR inlet NOx and SCR outlet O2, the variation of similarity between SCR outlet O2 and SCR outlet NOx, and the effect of SCR working efficiency on SCR outlet O2 were analysed through experiments, and the proposed method was validated.
  Keywords: selective catalytic reduction technology; dynamic time warping; SCR outlet NOx; SCR outlet O2; diesel vehicle.
  DOI: 10.1504/IJHVS.2024.10064600
   
  
• A review of road surface recognition and tyre-road friction coefficient estimation methods  
  by Linhui Wang, Xiaobin Fan, Xueliang Yu, Zipeng Huang, Kaikai Zhao 
  Abstract: The tyre-road friction coefficient (TRFC) characterises the maximum interaction force that can be generated between the road surface and the tire, which directly affects the driving, braking, and handling stability of vehicles. Obtaining accurate estimates of TRFC can optimise the vehicles active safety control and improve decision-making and planning performance in autonomous driving. However, the existing TRFC identification methods are not very accurate and real-time when dealing with sudden changes inroad conditions under extreme working conditions. Therefore, this paper discusses the current domestic and international road recognition methods, provides a review based on recognition principles, and elaborates on the two main categories of existing identification methods. It introduces the adhesion rate estimation and road type recognition methods commonly involved in TRFC identification, analyses the new methods brought by neural networks and rubber friction theory to the adhesion coefficient estimation issue, and provides an outlook on future development directions.
  Keywords: tyre-road friction coefficient estimation; road recognition; Kalman filtering; neural networks; rubber friction.
  DOI: 10.1504/IJHVS.2024.10064673
   
  
• Advancing transport safety with faster pre-convoluted neural networks and lightweight multi-scale fusion for driver distraction detection  
  by M. Joel John, K. Dinakaran, N. Bharathiraja 
  Abstract: This abstract discusses advancements in automated vehicle technology focusing on improving driving safety by minimizing human errors. While autonomous driving aims to eliminate driver distraction, challenges persist, leading to a surge in interest in driver-assistance technologies. This paper proposes a novel architecture, Faster Pre-Convoluted Neural Networks (FPCNN), for classifying and detecting driver distraction. The research emphasizes enhancing generalisation performance in CNNs, addressing overfitting issues through techniques like data augmentation, batch normalisation, and dropouts. The study introduces a Lightweight Multi-scale Fusion (LMF) architecture for intensive convolutional networks, achieving a high accuracy of 97.8% in detecting distractions. Transfer-learning techniques are employed to enhance the performance of FPCNNs, reducing computational complexity and training times. The proposed system leverages raw data from activity monitors, demonstrating a significant improvement in generalization effectiveness and highlighting advancements in automated safety systems for vehicles.
  Keywords: automated vehicles; CNN; convolutional neural networks; transport safety; multi-scale fusion; driver distraction; generalisation; overfitting prevention.
  DOI: 10.1504/IJHVS.2024.10064928
   
  
• Community transport experiences, in connection with diesel-LPG mixed operation buses belonging to the category of heavy vehicles  
  by István Lakatos 
  Abstract: Various international literature sources and papers address the issue of the theoretical implementation of using liquefied petroleum gas (LPG) gas as catalyst material injected into the carburetor system of diesel engines and its positive impact on the characteristic features of the engine and its emission. In Europe, for example, Landi-Renzo, one of the biggest Italian companies dealing with traditional gas systems, is developing a compressed natural gas (CNG)-diesel system. The present paper outlines the operational characteristics of a diesel LPG dual operating system based on our own experiments and measurements which have been carried out on the transformed buses of the Southern Transdanubian Transportation Centre (DDKK, Hungary). In the process of evaluation two aspects were taken into consideration: the impact on emission and that on fuel consumption. Of course, the tests can be extended to wider areas, which take into account both vehicle structures and the environment (Palkovics and El-Gindy, 1993; Palkovics et al., 1996; Shokouhfar et al., 2016).
  Keywords: LPG; LPG-diesel mixed operation; fuel consumption; exhaust emission.
  DOI: 10.1504/IJHVS.2024.10065025
   
  
• Lateral stability control of heavy-towing taxi-out based on differential braking  
  by Jiahao Qin, Jiaqi Ma, Peiyang Xu, Wei Zhang 
  Abstract: The new mode of towing taxi-out consisting of rodless tractor and aircraft, is prone to extreme lateral instability accidents such as slipping and jack-knifing during high-speed turns. To address this issue, a ten-degree-of-freedom dynamic model of the aircraft towing system is established using the Lagrangian analysis method. This model does not consider constraints and limitations at hinge points. Based on this model, a high-speed turn differential braking controller uses yaw rate deviation as yaw moment controller inputs and determine their respective additional yaw moments. According to the braking strategy and braking moment allocation rules, the controller outputs the required braking moments for the target wheels. Finally, through Matlab/Simulink simulations, the steering angle input and initial speed are varied under J-turn and double lane change condition. This allows the delineation of safe and dangerous areas for steering angles and speeds in towing taxi-out mode, and a comparison of the control effectiveness of differential braking.
  Keywords: Lagrangian analysis method; jack-knifing; differential braking; lateral stability.
  DOI: 10.1504/IJHVS.2024.10065548
   
  
• Optimising liquid level in two tank spherical interacting system with fractional order PID control via hybrid POA-RERNN approach  
  by P.E. Kamalakkannan, Vinoth Kumar Bojan, M. Kalamani 
  Abstract: This paper proposes a hybrid technique for Liquid Level in Two Tank Spherical. Of the three controllers, the FOIMC tuned using the proposed Fractional-Order Proportional Integral Derivative (FOPID) controller in an Interacting System (TTSIS). Recalling-enhanced recurrent neural network (RERNN) and Pelican Optimization Algorithm (POA) combined performance is the proposed hybrid technique. The FOPID controller is used to control the system's level. The hybrid approach that has been proposed tunes the FOPID's ideal gain parameter. The proposed method's performance is evaluated using the MATLAB site and contrasted with other methods that are currently in use, such as the Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), and Salp Swarm Algorithm (SSA). After analyzing the control efforts (errors) and robustness, it is determined that the proposed approach has better robustness than the current methods and requires less control effort overall.
  Keywords: spherical two tank system; liquid level control; tank surface area and height; non-linear system; FOPID controller; optimal gain.
  DOI: 10.1504/IJHVS.2024.10066643
   
  
• ANN-based RBF prediction for maximal energy recovery using hybrid optimisation in electric vehicles  
  by A. Velu, N. Chellammal 
  Abstract: Owing to the increasing number of Electric vehicles (EVs) that have propelled the global trend towards transportation electrification over the past few decades, the automotive industry has expanded its excessive investment in transportation electrification technology. However, the widespread maintenance of EVs is significantly complicated by their short driving range. Therefore, a lot of research is done to improve the efficiency and driving range of automobiles in both business and academia. The operational range of EVs can be expanded using regenerative braking technology. Initially, the parameters, like speed of the EV and State of Charge (SOC) of the battery are taken as input to the Artificial Neural Network (ANN) and the corresponding predicted regenerative braking force has been obtained as the desired outcome of ANN. The estimated accurateness of the ANN classifier is then enhanced by optimally altering its weight parameters by Wild Horse Insisted Sparrow Search Optimization (WHI-SSO).
  Keywords: regenerative braking force; EV; energy recovery; ANN; optimisation.
  DOI: 10.1504/IJHVS.2024.10066991
   
  
• Moving vehicle detection and tracking under hazy environment for traffic surveillance system  
  by Agha Asim Husain, Tanmoy Maity, R.K. Yadav 
  Abstract: Vehicle location is crucial for transportation and computer vision Bounding boxes distinguish cars, crucial for real-time applications like movement estimation, requiring precise area data This study presents an adaptive approach for accurate vehicle detection and tracking in challenging scenarios such as heavy traffic, poor visibility, and adverse weather conditions The proposed method integrates Fuzzy Subtraction and Gradient Partial Equation (FGPE) techniques for background subtraction, overcoming fluctuations and shadows It also uses energy and histogram-oriented gradient features, chosen through recursive feature elimination, to improve discrimination capability Further, a Normalization-based Attention Module (NAM) is integrated into the Enhanced YOLOv5 model for vehicle detection The feature extractor is enhanced with the Multi-Object based DeepSORT algorithm for vehicle tracking Deployment on edge devices achieves a traffic flow detection accuracy of 0 98% Evaluation metrics including Multiple-Object Tracking Algorithm (MOTA) and Multiple-Object Tracking Precision (MOTP) validate the effectiveness of the proposed model for real-world traffic
  Keywords: vehicle detection; tracking; MOTA; multiple-object tracking algorithm; traffic monitoring systems; MOTP; multiple-object tracking precision.
  DOI: 10.1504/IJHVS.2024.10067276
   
  
• Implementation of multi input DC-DC converter based fuel minimisation in hybrid vehicle using HBO optimisation method  
  by S. Dineshkumar, N. Senthilnathan 
  Abstract: This manuscript proposes a multi-input DC to DC converter based on fuel minimization in hybrid vehicle using Heap Based optimization method. The proposed system inputs include Fuel Cell (FC), Energy Storage System (ESS), and Photovoltaic (PV) group. Fuel cell is regarded as important power source and the roof-top photovoltaic is utilized for charging batteries, improving performance and reducing fuel economy. The converter has the ability to provide power demand from one or two resources that are not present through a load. Moreover, a power management method is defined and given in the Heap-Based Optimizer (HBO) technique. The main objective of the proposed method is to "meet tight direct current (DC) bus voltage regulation, better monitor the PV current to their reference and minimize fuel consumption". The proposed HBO technique based hybrid electric vehicle (HEV) system is implemented in MATLAB/ Simulink software.
  Keywords: ESS; energy storage system; fuel cell; HBO; heap based optimisation; HEVs; hybrid electric vehicles; photovoltaic.
  DOI: 10.1504/IJHVS.2025.10067739
   
  
• Coordinated control of acceleration slip regulation and direct yaw moment control for distributed in-wheel motor drive electric articulated heavy vehicles  
  by Wei Gao, Wei Minxiang, Yuping He, Deng Zhaowen, Yonghui Jin, Baohua Wang 
  Abstract: This paper presents a coordinated control strategy for acceleration slip regulation (ASR) and direct yaw moment control (DYC) to improve the lateral stability of a distributed in-wheel motor drive electric articulated heavy vehicle (DIMDEAHV). A non-linear TruckSim model and a linear three-degree-of-freedom (3-DOF) yaw-plane model of DIMDEAHV are generated, and their fidelity is evaluated. An algorithm is then developed to identify road conditions using the - standard curve of the Burckhardt tire model. Built upon the road identification algorithm, an ASR controller is designed and proved to be effective in preventing wheel slip. Finally, a coordinated control strategy for ASR and DYC is developed and validated using co-simulation under a double lane change (DLC) manoeuvre. The simulation results demonstrate that compared to the DYC alone, the ASR and DYC coordinated control can effectively prevent the wheel slip and improve the lateral stability of the DIMDEAHV traveling at high speeds on
  Keywords: distributed in-wheel motor drive electric articulated heavy vehicle; acceleration slip regulation control; coordinated control; lateral stability; numerical simulation.
  DOI: 10.1504/IJHVS.2024.10068044
   
  
• Discovery of the global landscape for railroad pantograph research: a bibliometric review  
  by Munaliza Ibrahim, Mohd Azman Abdullah, Mohd Hanif Harun, Fathiah Mohamed Jamil, Fauzi Ahmad 
  Abstract: Railroad vehicles are highly dependent on the proper functioning of the pantograph, which makes it an indispensable device that picks up the electric current from the overhead line cable system. This study addresses the lack of a comprehensive analysis by conducting a bibliometric study of research publications on pantographs in railroads available in the Scopus database. The data was analysed using a sample of 1,234 publications between 1928 and 2023. The bibliometric analysis shows a significant increase in this research. The publication involved contributions from 159 authors across 41 countries and 160 institutions. The year 2018 saw the highest number of published articles, with 89. Southwest Jiaotong University from China was the most prolific institution in this research area. This study provides a pioneering overview of worldwide publications on pantographs using three bibliometric tools Microsoft Excel, VOSviewer and, Harzing's Publish or Perish software package.
  Keywords: railroad pantograph; Scopus database; bibliometric review; frequency analysis; Microsoft excel; data visualisation; VOSviewer; citation metrics; Harzing’s publish or perish.
  DOI: 10.1504/IJHVS.2024.10068045