Operated Vehicle Research Articles

Impacts of On-board Energy Storage Devices on the Energy Consumption of Train Operations

Urban rail transit systems consume significant electrical power, with traction accounting for 50% of the total energy (from China Urban Rail Transit Association [1]). As operational mileage and vehicle counts rise, so does energy consumption, underscoring the importance of vehicular energy conservation. This study evaluates the impact of on-board energy storage devices on train energy efficiency. Using operational data from Changsha Metro Line 5 and incorporating literature reviews and simulations, the energy-saving potential was assessed. Integrating these storage devices with vehicle energy monitoring systems shows promising potential for energy conservation and operational efficiency. This research presents a viable strategy to reduce energy consumption in urban rail vehicles, enhancing system competitiveness.

A method for calculating the technical readiness of aviation refuelling vehicles

In the paper a mathematical model of the process of operating aviation refuelling vehicles supplying fuel to aircraft before flight was developed. The present work is a continuation and supplement to the model contained in [52]. The phase space of the process under study was mapped by a 7-state directed graph of the operation process. To calculate the technical readiness index (K_gt) Markov chains and processes were used. Also, in Section 3, Results and discussions, optional methods for determining the technical readiness coefficient of a vehicle were provided k_gt) , based on the total time of the object in individual operating states. This is an alternative in a situation where the analysed process cannot reach a stable average state indefinitely. Two types of measures were used to determine the readiness, i.e. border probabilities and average times of the object in individual states. In both cases, the basis was statistical databases with operational vehicle data, which enabled the calculation of the readiness index and coefficient.

Improving the knowledge base of Vulnerable Marine Ecosystems’ distribution in the Amendolara Bank (Ionian Sea)

The Amendolara Bank was recently designated as a Site of Community Importance; however, information on its ecosystems remains limited, with a particular dearth of knowledge regarding the deeper zone (>100 m). Previous studies have discovered the existence of Vulnerable Marine Ecosystems (VMEs) within the bank, underscoring the necessity for more comprehensive data and its significance in terms of conservation in the Ionian Sea. This study aims to investigate various aspects of the bank using Remotely Operated Vehicles (ROVs) to shed light on the possible presence of VME indicator species, their relationship with environmental variables, their connection with the observed fish, and to assess anthropogenic impact via the identification of fishing gear within the study area. This present research provides new information on the biodiversity of the Amendolara Bank, revealing the presence of four VME indicator species including the first sightings of black coral Antipathella subpinnata and the precious red coral Corallium rubrum. Moreover, it provides evidence on the interaction between fish fauna and VME indicator species as well as signs of anthropogenic impact from abandoned, lost, or otherwise discarded fishing gear (ALDFG). These findings highlight the urgent need for additional research to improve the knowledge base on the biodiversity of this unique spot in the Ionian Sea which would in turn ensure the development and implementation of more effective conservation and management measures.

A Branch-and-Price Algorithm for an Integrated Online and Offline Retailing Distribution System with Product Return

This study identifies critical inefficiencies within a dual-channel operation model employed by a fast fashion company, particularly the independent operation of three logistics distribution systems. These systems result in high operational costs and low resource utilization, primarily due to redundant vehicle dispatches to meet the distinct demands of retail store replenishment, online customer orders, and customer return demands, as well as random and scattered return requests leading to vehicle underutilization. To address these challenges, we propose a novel integrated logistics distribution system design and management method tailored for dual-channel sales and distribution businesses. The approach consolidates the three distribution systems into one cohesive framework, thus streamlining the delivery process and reducing vehicle trips by combining retail and customer visits. An optimization algorithm is introduced to factor in inventory and distribution distance, aiming to achieve global optimization in pairing retail store inventory with online customer orders and unifying the distribution of replenishment products, online products, and returned products. The paper contributes to the field by introducing a new variation of the Vehicle Routing Problem (VRP) that arises from an integrated distribution system, combining common VRP issues with more complex challenges. A custom Branch-and-Price (B&P) algorithm is developed to efficiently find optimal routes. Furthermore, we demonstrate the benefits of the integrated system over traditional, segregated systems through real-world data analysis and assess various factors including return rates and inventory conditions. The study also enhances the model by allowing inventory transfers between retail stores, improving inventory distribution balance, and offering solutions for scenarios with critically low inventory levels. Our findings highlight a significant reduction in total operating cost savings of up to 49.9% and vehicle usage when using the integrated distribution system compared to independent two-stage and three-stage systems. The integrated approach enables the utilization of vacant vehicle space and the dynamic selection and combination of tasks, preventing unnecessary mileage and space wastage. Notably, the integration of inventory sharing among retail stores has proven to be a key factor in generating feasible solutions under tight inventory conditions and reducing operational costs and vehicle numbers, with the benefits amplified in large-scale problem instances.

Dynamic, fair, and efficient routing for cooperative autonomous vehicle fleets

This paper addresses challenges in agricultural cooperative autonomous fleet routing through the proposition, modeling, and resolution of the Dynamic Vehicle Routing Problem with Fair Profits and Time Windows (DVRP-FPTW). The aim is to dynamically optimize routes for a vehicle fleet serving tasks within assigned time windows, emphasizing fair and efficient solutions. Our DVRP-FPTW accommodates unforeseen events like task modifications or vehicle breakdowns, ensuring adherence to task demand, vehicle capacities, and autonomies. The proposed model incorporates mandatory and optional tasks, including optional ones in operational vehicle routes if not compromising the vehicles’ profits. Including asynchronous and distributed column generation heuristics, the proposed Multi-Agent-based architecture DIMASA for the DVRP-FPTW dynamically adapts to unforeseen events. Systematic Egalitarian social welfare optimization is used to iteratively maximize the profit of the least profitable vehicle, prioritizing fairness across the fleet in light of unforeseen events. This improves upon existing dynamic and multi-period VRP models that rely on prior knowledge of demand changes. Our approach allows vehicle agents to maintain privacy while sharing minimal local data with a fleet coordinator agent. We propose publicly available benchmark instances for both static and dynamic VRP-FPTW. Simulation results demonstrate the effectiveness of our DVRP-FPTW model and our multi-agent system solution approach in coordinating large, dynamically evolving cooperative autonomous fleets fairly and efficiently in close to real-time.

Effect of Motivation on Job Satisfaction and Performance: A Study of Nigeria Police Force

The study examined the Effect of Motivation strategies on Job satisfaction and performance: A Study of Nigeria Police Force. Data were elicited using questionnaire. Descriptive statistics were used to analyse the data. The responses were analysed using both simple and multiple linear regressions. Findings revealed that the promotion strategy has a significant impact on motivation and performance, while the other two variables (police training and retraining strategy, and donation of operational vehicles) do not show a statistically significant relationship at the conventional alpha level of 0.05. Overall, the findings indicate that the promotion strategy has a stronger influence on job satisfaction and performance in the Nigeria Police Force compared to the other strategies (training and re-training and donation of operational vehicle) examined. Focus on enhancing and improving the promotion strategy within the Nigeria Police Force, as it has shown to have a significant impact on motivation and performance. The study recommends that the management of NPF should consider ways to make the promotion process transparent, fair, and rewarding for deserving officers. While police training and retraining strategies and the donation of operational vehicles did not show a statistically significant relationship with job satisfaction and performance, it is still important to continue investing in these areas to ensure that officers have the necessary skills and resources to perform their duties effectively. Implement a holistic approach to improving motivation and performance by considering a combination of strategies that address various aspects of officer well-being and job satisfaction, such as provision of effective operational vehicle, worklife balance, leadership support, and career development opportunities.

A multi-objective spatio-temporal pricing method for fast-charging stations oriented to transformer load balancing

To address the challenges posed by the fast-charging demand of electric vehicles, causing feeder load and voltage imbalances during operation, this paper introduces a spatio-temporal pricing strategy tailored to enhance feeder operation equilibrium. This approach facilitates the spatio-temporal guidance of fast-charging loads for electric vehicles in operation. This paper begins by formulating a spatio-temporal distribution model for electric vehicle fast-charging loads, considering owners’ preferences. It further develops a behavioral model for the travel choices of electric vehicles, illustrating the impact of spatio-temporal electricity pricing at fast-charging stations on load distribution. Next, it proposes a multi-objective spatio-temporal pricing model and its solution method specifically designed for feeder-balance-oriented fast-charging stations. This model targets the minimization of the spatio-temporal imbalance in feeder voltage and load. It takes a comprehensive approach, considering the constraints of the spatio-temporal load distribution model and optimal power flow model. The resulting spatio-temporal pricing model for fast-charging stations is effectively solved using the extended Pareto evolutionary algorithm. To validate the effectiveness of the proposed method in achieving feeder balancing, this paper analyzes two examples: a self-built 29-node road network and a 9-node distribution network, as well as a 66-node road network and a 33-node distribution network in the Xinjiang region. The results show that the proposed method can effectively guide the charging of electric vehicles and make the load distribution more balanced.

Peran Biro Kesejahteraan Rakyat Sekretariat Daerah Provinsi Jawa Timur Sebagai Fasilitator Operasional Organisasi Kemasyarakatan

The People's Welfare Bureau has a role in increasing social awareness through policy formulation in the fields of spiritual mental development, basic service people's welfare and non-basic service people's welfare. In implementing the distribution of grant aid, the East Java Regional Secretariat's People's Welfare Bureau is the institution tasked with administering administrative matters. The People's Welfare Bureau is a facilitator for community organizations, one of which is supporting operational vehicles for community organizations. However, in practice, the role as a facilitator still has obstacles in the administration process. The research method used is a qualitative method which aims to determine the role of the People's Welfare Bureau as an operational facilitator of community organizations and to find solutions to the problems mentioned above. The research results show that the flow of submissions, procurement and accountability is quite good. However, there are still obstacles related to the special conditions for applying for grant funds as well as regulations regarding the letter of accountability for the applicant's responsibility to the provincial government, which is a weakness in terms of accountability for the circulation of grant funds. Therefore, the aim of this research is not only to find out the role of the Welfare Bureau as a facilitator but also to find solutions to answer existing problems related to improving disbursement flow, the implications of which can lead not only to administration, but also to increasing effectiveness and efficiency.

Whale fall chemosymbiotic communities in a southwest Australian submarine canyon fill a distributional gap

A whale fall community of chemosymbiotic invertebrates living on cetacean bones has been identified off southwestern Australia during a Remotely Operated Vehicle (ROV) survey at bathyal depths within the Bremer Marine Park, which is part of important marine mammal areas (IMMA) of the Albany Canyon Region. Cetacean bones on the seafloor of the Hood Canyon, consisted of isolated skulls of three species of beaked whales (family Ziphiidae): Mesoplodon cf. layardii, M. grayi, and M. hectori, a few vertebrae, and lower jaws. One of the beaked whale skulls (Mesoplodon cf. layardii) was sampled and found to be intensely colonised by hundreds of specimens of a bathymodilinae mussel (“Adipicola” s.l.). Live polychaetes (Phyllochaetopterus?), skeneimorph gastropods, and amphipods (Seba, Leptamphopus) colonised the skull bone, which represent a later stage (sulfophilic) of carcass decomposition. The reducing sediment below the skull was inhabited by lucinid (Lucinoma) and vesicomyid (Calyptogena) chemosymbiotic bivalves. Additionally, the sediment thanatocoenosis comprised shells of various other chemosymbiotic bivalves, such as Acharax, thyasirids, lucinids, vesicomyids, and limpets, representing the complex ecological turnover phases through time in this whale fall chemosynthetic habitat. With one exception, all bones recovered were colonized by bathymodiolin mussels. This is the first documented case of a chemosynthetic community and associated chemosymbiotic fauna relating to beaked whales, and the first fully documented record of a whale fall community within the Australian Southern Ocean region.

Preview-based terrain adaptive active suspension control strategy for heavy-duty trucks

This paper proposes a preview-based active suspension control method for heavy-duty trucks, where the vehicle front wheel terrain preview information is employed to improve the performance of the rear, focusing on enhancing the handling stability and vehicle smoothness. To begin with, the vehicle front wheel preview information is introduced to the half-vehicle model, and a state quantity is employed to calculate the time lag between front and rear for predicting the control input of the rear wheel. Secondly, based on the developed model, an [Formula: see text] controller is designed with the half-vehicle model based on the current stochastic linear optimal control combined with the preview controller, which provides more stable effect than the prior controllers by merging perceived ground information. Furthermore, an established seven-degree-of-freedom vehicle suspension model is utilized for the preview-based controller to govern the kinetic behavior of the heavy-duty truck, allowing for a more thorough analysis of operation smoothness and vehicle stability. At last, the vehicle comparison simulations are carried out, which indicates that the preview-based [Formula: see text] controller designed by inspecting the terrain preview information can straighten out the smoothness and safety of the heavy-duty truck more effectively in contrast with the LQG controller.

UOWC Integration with ROVs: A Fiber-Optic Approach for Enhanced Underwater Exploration

Underwater Optical Wireless Communication (UOWC) revolutionizes underwater exploration, leveraging seawater's unique property—reduced absorption of blue-green light. This offers superior advantages over traditional communication methods, providing higher bandwidth and lower latency. This paper explores the integration of UOWC with Remotely Operated Vehicles (ROVs), enhancing data exchange and command capabilities in challenging underwater environments. Seawater's unique properties empower UOWC to outperform acoustic and RF methods, crucial for real-time applications. The study utilizes advanced techniques like Fiber-Optic Communication, High Order Sliding Mode Control, and Hybrid Blockage Detection for ROV integration and control. While the abstract focuses on theory and design, it sets the stage for empirical validations, emphasizing the need for future research to quantify improvements in real-world underwater scenarios

Experimental investigation of time-dependent electrical load effects through multipoints in-situ measurement of temperature and relative humidity of PEMFC bipolar plate under transient operation

In this study, multiple micro-relative humidity and temperature (RH/T) sensors were installed in the anode and cathode channels of a proton exchange membrane fuel cell (PEMFC) bipolar plate to simultaneously observe and analyze the variation in RH/T behaviors during transient operation. In order to simulate the acceleration and deceleration process, the electrical load was ramped from 10 to 40 A and then back to 10 A, with time intervals of 0, 2, and 5 s. The data corresponding to different acceleration/deceleration time intervals were compared and analyzed to assess the time-dependent effects of load changes. The analyzed data provide visual information, including the transient voltage response, transient behavior of temperature and water distribution, and evolution of RH/T within PEMFC. The results indicate that the acceleration and deceleration interval times significantly influence the temperature and water distribution within PEMFC during transient operation. Shorter acceleration times lead to more rapid changes in temperature and humidity within the PEMFC active area, resulting in higher transient temperature and water concentration. This finding explains why the output voltage decreases more when the load changes with a short time interval. This research enhances our understanding of transient temperature and water behavior, providing a foundation for further research and development of effective operational strategies and vehicle PEMFC designs.

An Equivalent-Perceptional Intertemporal Choice Heuristics Model for Electric Operation Vehicle Charging Behavior

The inherent stochasticity of electric operation vehicle (EOV) charging poses challenges to the stability and efficiency of regional power distribution networks. Existing charging behavior decision-making models often prioritize revenue considerations, neglecting the influence of multi-time-span characteristics and the potential irrationality of EOV owners. To address these limitations, this study proposes a comprehensive framework encompassing three aspects. First, operational data are statistically analyzed to reconstruct EOV operation scenarios, establishing a dynamic charging scheme tailored to multi-time-span characteristics. Second, an improved ITCH model is developed using operational equivalent change to incorporate both gains and losses. Third, a WFL framework is employed to integrate the perceptual attenuation of revenue into the ITCH model. Simulation results show that decision-makers (DMs) demonstrate a preference for charging schemes with high equivalent perceived revenues and low time costs. Moreover, when the charging price is doubled, revenue perception attenuation leads decision-makers to postpone their charging behavior. Compared to other models, the equivalent perception intertemporal choice heuristics (EP-ITCH) charging model results in reduced load peaks, valleys, and variances on the grid side. This study highlights the model’s effectiveness and accuracy in optimizing EOV charging infrastructure.

Trajectory Tracking Control of Remotely Operated Vehicles via a Fast-Sliding Mode Controller with a Fixed-Time Disturbance Observer

Time-varying nonlinear external disturbances, as well as uncertainties in model and hydrodynamic parameters, make remotely operated vehicles (ROVs) trajectory tracking control complex and difficult. To solve this problem, this paper proposes a fast sliding mode controller with a fixed-time disturbance observer (FSMC-FDO), which consists of a sliding mode controller based on a fast reaching law and a novel fixed-time disturbance observer. The FSMC can solve the contradiction between system response time and chatter amplitude in sliding mode control. The FDO can compensate for time-varying external disturbances. The Lyapunov theory is used to prove the stability of the entire control scheme. Simulation results show that FSMC-FDO exhibits a good trajectory tracking performance with a better robustness than the conventional sliding mode control (CSMC) on the basis of exponential reaching law (ERL), while significantly reducing chatter.

An integrated approach for the benthic habitat mapping based on innovative surveying technologies and ecosystem functioning measurements

Among marine ecosystems globally, those in the Mediterranean Sea, are facing many threats. New technologies are crucial for enhancing our understanding of marine habitats and ecosystems, which can be complex and resource-intensive to analyse using traditional techniques. We tested, for the first time, an integrated multi-platform approach for mapping the coastal benthic habitat in the Civitavecchia (northern Latium, Italy) coastal area. This approach includes the use of an Unmanned Surface Vehicle (USV), a Remote Operated Vehicle (ROV), and in situ measurements of ecosystem functionality. The echosounder data allowed us to reconstruct the distribution of bottom types, as well as the canopy height and coverage of the seagrass Posidonia oceanica. Our study further involved assessing the respiration (Rd) and net primary production (NCP) rates of P. oceanica and its associated community through in situ benthic chamber incubation. By combining these findings with the results of USV surveys, we were able to develop a preliminary spatial distribution model for P. oceanica primary production (PP-SDM). The P. oceanica PP-SDM was applied between the depths of 8 and 10 m in the studied area and the obtained results showed similarities with other sites in the Mediterranean Sea. Though in the early stages, our results highlight the significance of multi-platform observation data for a thorough exploration of marine ecosystems, emphasizing their utility in forecasting biogeochemical processes in the marine environment.

Quantum Propulsion: Background and Practical Applications

This is the first introduction of new and revolutionary aerospace engines and propulsion methods. Our organization is currently developing quantum propulsion systems and space vehicles that will be capable of flying with enormous speed (potentially reaching and exceeding the speed of light) and will have unseen-before manoeuvrability and lifting capacity. They will provide 100% crew protection from deadly sun and space radiation which is essential for safe deep space travel and manned space exploration. They will also provide spacecraft with protection against space particles. To date, we have managed to crack the main secret of practical quantum engine design and we are ready to develop it further into fully operational aerospace vehicles. Quantum propulsion systems are the only systems that can facilitate realistic prospects of space mining on the industrial scale and deep space colonisation, including colonisation of habitable planets in the future. The cost efficiency of this new technology is going to be enormous. Development and production costs of quantum aerospace vehicles compared to production costs of chemical fuel jet spacecraft allow to reduce price per kilo space launch ratio hundreds of times, making deep space exploration and commercialisation more accessible and practically feasible at last. Manufacturing and maintenance of quantum-propelled flying machines that can reach the age of our solar system within hours will be no more expensive than manufacturing jet planes or helicopters of the same size. Quantum propulsion systems are going to replace outdated chemical fuel rocket and jet engines in the near future and will become the mainstay of air travel and space exploration.

General hospital preparedness in facing flood disasters

Hospitals had a very important function in disaster management, especially in providing health services to reduce the suffering of disaster victims in the form of deceases and injuries. Hospital preparedness in facing disasters was contained in the Hospital Disaster Plan which was prepared based on the Safe Hospital Framework [1], and the Hospital Safety Index[2]. The purpose of this study was to analyze the preparedness of Aceh Tamiang General Hospital in facing flood disasters from 4 (four) aspects or evaluation modules namely, Hazard Affecting, Structural Safety, Non-Structural Safety, Emergency and Disaster Management, specifically analyzing the aspect of “Emergency and Disaster Management” according to the research focus namely, hospital policies, human resources preparedness and hospital infrastructure readiness in facing flood disasters. The research methodology was qualitative with a phenomenological design by 7 (seven) informants. The results of the study showed that the policies of the hospital leadership had been good, with the existence of a Leadership Decree concerning the Formation of a Hospital Disaster Management Team, since 2019 ago. However, there were still hospital personnel who did not know about the organizational structures, goals and functions as team members. Many hospital health workers could not go to work because their homes and access to the hospital were flooded. Besides that, hospital infrastructure, especially motorized vehicles such as ambulances and other operational vehicles, could not operate due to flood conditions that reached up to 1 meter. Therefore it was suggested that the socialization of the Disaster Management Team and Disaster Management Simulation should be carried out periodically, for example, twice a year. It should be suggested that the hospital proposed procuring an ambulance with certain specifications and a rescue boat, so that it could break through the floods that occur almost every year.

The Haidou‐1 hybrid underwater vehicle for the Mariana Trench science exploration to 10,908 m depth

AbstractAn unmanned Autonomous and Remotely Operated Vehicle (ARV), Haidou‐1, visited the Challenger Deep in the Mariana Trench, and performed observation, sampling and bathymetric mapping explorations at the trench bottom. The Haidou‐1 vehicle reached a depth of 10,908 m in the west pool of the Challenger Deep and probed a depth of 10,909 m in the east pool. The 2600 kg underwater robotic vehicle could conduct survey missions with full autonomy and can also be remotely operated through a light fiber tether. Haidou‐1 carries an electric manipulator to implement lightweight intervention tasks. The fiber‐optical tether enables long‐distance real‐time high‐bandwidth communication at full‐ocean depth, thereby providing situational awareness and remote intervention. The hybrid concept we defined for the Haidou‐1 vehicle refers to three typical working modes: Autonomous Underwater Vehicle mode, Remotely Operated Vehicle mode, and ARV mode. There is no need to change any structural configuration at sea to meet the needs of multidisciplinary oceanographic investigation. This paper reports the overview design of Haidou‐1. Practical field trials at the Challenger Deep were conducted to validate the feasibility and performance of the developed system. In the aggregate, eight dives exceeded 10,000 m counting all three operation modes. Some of the initial results are presented including the high‐resolution bathymetric map created by Haidou‐1 onboard sonar, and no similar results have been found yet.

Greenhouse Gasses Inventory on Textile Finishing Industry PT X

The textile industry has the biggest impact on environmental pollution in the world, and is responsible for 10% of global carbon production. Most of the waste in the textile industry, is generated from the dyeing process and textile processing. PT X is a textile finishing industry, that focuses on finishing processes like dyeing and textile processing. In this research, GHG (greenhouse gasses) emission inventory was carried out to see how much GHG generated in the textile finishing industry. The inventory will focus on CO2, CH4, and N2O from generator, curing machine, operational vehicle, and electricity usage. The inventory methodology was based on IPCC 2006, that stated to determine GHG emission, an activity data and emission factor from that source is needed. This emission inventory results on the total emissions of 666.38 tonCO2eq or 258.629 kgCO2eq/tonproduct GHG emission from PT X in 2021. The GHG emission in PT X are dominated by CO2 gas. Which most of comes from electricity usage source. GHG emission produce by PT X are not high compared with similar industries, but can be improved further more with mitigation measures such as installing a solar panel, and constructed wetland.

Adaptive neural network anti-disturbance control of a cable-driven flexible-joint-based underwater vehicle manipulator system with dead-zone input nonlinearities via multiple neural observers

To achieve the requirements of lightweight, low energy consumption, and low inertia of an underwater vehicle manipulator system, a cable-driven manipulator is installed on the underwater vehicle to form a cable-driven flexible-joint-based underwater vehicle manipulator system (CDFJ–UVMS). The CDFJ–UVMS is a complex nonlinear system subject to model uncertainties, complex marine environment disturbances, and actuator dead-zone nonlinearity. To design track controllers, the CDFJ–UVMS dynamics is divided into two parts: known and unknown. Subsequently, a radial basis function neural network is adopted to approximate the unknown nonlinearity. A neural network performance observer is constructed, whose estimation error is then used to design a novel neural disturbance observer (NDO) to estimate the total disturbance. Finally, an adaptive neural network control method is proposed for the CDFJ–UVMS based on the NDO, neural network compensator, and neural performance observer. The stability of the closed-loop system is analyzed using the Lyapunov method. The proposed control algorithm is applied to a CDFJ–UVMS with two cable-driven joints and compared with other control methods to show the effectiveness of the proposed control algorithm.