Fleet Operations Research Articles

Smart Fuel Monitoring for Agricultural Fleet Operations Using Tilt Sensors and Cloud Data Processing

This paper presents a novel Internet of Things (IoT)-based fuel monitoring and tracking system designed to address limitations of traditional fuel gauges and enhance fleet management efficiency. The system leverages an accelerometer and Arduino microcontroller to measure fuel level by detecting tilt angles within the tank. This data, along with real-time location from GPS, is transmitted to a cloud platform for processing and visualization. A mobile application, "Tracer," empowers users with insights into fuel level, location on a map, and distance traveled. Graphical fuel consumption patterns further aid in optimization strategies. This solution offers real-time data for improved fuel efficiency, proactive route planning, and overall fleet management. The proposed system is successfully implemented IOT based technology. This sys in Ada fruit IO cloud issued to provide information about vehicle location, fuel level in tank and distance travelled by the vehicle.

Calculations of Performance Characteristics of Submerged Cargo Pumps with Hydraulic Drive and Constant Torque Controllers, Taking into Account the Energy Efficiency of the Drive Motor

Submerged cargo pumps installed on board tankers are one of the most important components of their cargo system. As they are installed directly in the cargo tanks, they are usually equipped with a hydraulic drive whose power and capacity are controlled by constant-torque controllers. These have a significant impact on the technical and performance characteristics of the cargo pumps. This paper presents a methodology for calculating the performance characteristics of submerged cargo pumps, taking into account the energy efficiency of their hydraulic drive motors. Due to their number and power, the cargo pumps are powered from the ship’s hydraulic central loading system. This paper describes the main parts of the hydraulic power system structure and the functions of the constant torque controller of the STC type. A mathematical model has been developed to use the basic characteristics of submerged cargo pumps made for the base cargo (water) sent by the pump manufacturer for the case of handling liquid cargo with different parameters. The model considers the characteristics of the hydraulic drive, including a Bosch Rexroth A2FM type hydraulic drive motor and a constant torque controller. The results of simulation calculations of the performance characteristics of an example cargo pump are presented and compared with measurements of the characteristics of this pump on a product tanker. The mathematical model presented in this paper is of utilitarian value, enabling calculations to be carried out without the need for time-consuming CFD numerical methods, making it useful for port and fuel terminal logistics services, ship crews and services managing the operation of product tanker fleets.

Strategic deployment of hydrogen fuel cell buses and fueling stations: Insights from fleet transition models

Establishing new hydrogen value chains is challenging, requiring economies of scale and balanced supply-demand dynamics. Municipalities can mitigate this risk through government support and deployment strategies. This study analyzes Edmonton's transition to zero-emission buses (ZEBs), focusing on hydrogen fuel cell electric vehicles (HFCEVs) and hydrogen fueling stations (HFSs). Using scenario-based modeling and S-curve models for technology diffusion, we project the adoption of battery electric vehicles (BEVs) and HFCEVs. Deploying over 1000 ZEBs by 2040 is necessary to meet Net-Zero targets, with 310–760 HFCEVs required for the municipal bus inventory. This results in an estimated hydrogen demand of 6.2–14.5 t-H2/day and a reduction of 0.4–1.0 Mt-CO2 in tailpipe emissions by 2050. We use these scenario projections to develop a phased deployment strategy, optimizing fleet operations to reduce HFS costs by 50–60% from 8 to 9 C$/kg-H2 to 3–4 C$/kg-H2. The study underscores the importance of strategic planning and infrastructure investment in realizing net-zero goals, providing a model applicable globally.

Dynamic Adaptive Charging Network Planning Under Deep Uncertainties

Charging infrastructure is the backbone of electromobility. Due to new charging behaviors and power distribution and charging space constraints, the energy demand and supply patterns of electromobility and the locations of current refueling stations are misaligned. Infrastructure developers (charging point operators, fleet operators, grid operators, vehicle manufacturers, and real-estate developers) need new methodologies and tools that help reduce the cost and risk of investments. To this extent we propose a transport-energy-demand-centric, dynamic adaptive planning approach and a data-driven Spatial Decision Support System (SDSS). In the SDSS, with the help of a realistic digital twin of an electrified road transport system, infrastructure developers can quickly and accurately estimate key performance measures (e.g., charging demand, Battery Electric Vehicle (BEV) enablement) of a candidate charging location or a network of locations under user-specified transport electrification scenarios and constraints and interactively and continuously calibrate and/or expand their network plans as facts about the deep uncertainties about the supply side of transport electrification (i.e., access to grid capacity and real-estate and presence of competition) are gradually discovered/observed. This paper describes the components and the planning support of the SDSS and how these can be used in competitive and collaborative settings. Qualitative user evaluations of the SDSS with 33 stakeholder organizations in commercial discussions and pilots have shown that both transport-energy-demand-centric and dynamic adaptive planning of charging infrastructure planning are useful.

Life cycle management of critical refurbishable parts of ship equipment

To ensure the product life cycle (PLC), foreign and domestic information technologies have been developed that mainly ensure the stages of design and manufacture of products, but they do not allow for automation of the design of technologies for restoration and strengthening of parts. The relevance of restoration of critical parts of ship equipment is due to dependence on foreign supplies of equipment and spare parts (SP), as well as sanctions from unfriendly states, which complicated the acquisition of SP, and the need for import independence arose. The paper shows that life cycle management of a restored part has a significant impact on the efficiency of marine fleet operation, and provides stages and main sub-stages of the life cycle of restored parts of ship equipment. Restoration of parts is considered appropriate if the required durability and savings are ensured compared to manufacturing or purchasing a new part. The concept of life cycle management of restored parts is provided. Life cycle management of restored parts includes planning, control and management of all stages, as well as decision-making to ensure the durability of the part through the use of advanced materials and coating formation technologies. The stage of the life cycle of the restored part, determining the service life of the part, the economic efficiency of its restoration and subsequent operation, is the technological process that ensures the optimal chemical composition, mechanical and structural parameters of the coating. All the properties of the restored part are laid down at the stage of designing the technological process. The prospects of using the life cycle management of the restored part are shown using the example of restoring precision parts of the fuel equipment of marine diesel engines. The use of various technologies for the same type of restored precision parts allows obtaining coatings with different chemical composition, mechanical properties, structure and, accordingly, different values of durability and cost price to ensure the specified service life of the tribological unit at an acceptable price.

Demand-Aware Distributed Pathfinding for Repositioning Vehicles in Shared-use Autonomous Mobility Services

Shared-use autonomous mobility services (SAMS) have the potential to provide accessible and demand-responsive mobility to passengers, while benefitting from autonomous vehicle (AV) technology and bypassing challenges related to supply-side incentives or individual driver goals. SAMS operators typically aim to achieve efficiency and improved service quality in their fleet operations, both of which are further enabled by the use of AVs. Specifically, fleet repositioning decisions in anticipation of future demand can improve service quality, but existing approaches in the literature seldom consider the problem of routing repositioning vehicles in a way that further improves SAMS objectives. This paper presents an approach for demand-aware distributed routing pathfinding for repositioning vehicles, which can supplement existing vehicle repositioning approaches. The problem is formulated with a multi-criteria objective that minimizes the vehicles’ total travel time and maximizes their total demand-serving potential, while distributing that potential equitably among the ride-seeking passengers across the transportation network. We evaluate the proposed approach via numerical experiments using an agent-based simulation of SAMS operations in the network of Manhattan in New York City. The proposed approach is compared to a baseline simple shortest path approach for routing the repositioning vehicles. The results demonstrate that mean passenger waiting times for pick-up can be reduced, while also reducing the total vehicle miles and the empty miles travelled due to repositioning. Thus, the proposed approach can help improve the overall system performance in terms of both service quality and efficiency metrics, relative to the baseline approach.

Cooperative control of multi-vehicle formation based on cooperative game

In this paper, an optimization decision-making method of vehicle fleet queue based on game theory is proposed. By adopting the upper and lower controller structure, the longitudinal motion stability problem of the vehicle fleet is solved. The upper controller utilizes a game control algorithm specially developed for this study. The game payoff function is constructed by considering real-time vehicle information and comprehensively evaluating factors such as expected distance, vehicle safety, and stability. The optimal expected acceleration of the vehicle is determined. Subsequently, the lower controller adjusts the engine throttle opening or brake pressure to regulate the vehicle operation according to the desired acceleration. Simulation results show that the designed game strategy can effectively reduce vehicle spacing and speed errors, thus significantly improving the stability as well as safety of fleet operation.

New Approach on the Development of Operational Fleet Management Systems Using Adaptative AI Techniques: Analysis of Adaptative Goal Weights

New Approach on the Development of Operational Fleet Management Systems Using Adaptative AI Techniques: Analysis of Adaptative Goal Weights

Analysis and directions of development of transport and logistics schemes for the delivery of grain cargoes with the participation of inland waterway transport in Russia

In this article, the authors analyzed the transport and logistics schemes for transporting grain cargoes with the possible participation of water transport in a new geopolitical situation. After the introduction of sanctions by Western countries against the Russian Federation, the existing grain delivery schemes lost their relevance, therefore, the authors proposed a scheme for transporting grain cargoes from grain-producing regions of central Russia to southern ports on the Caspian Sea. Based on the presented scheme, the authors proposed options for the delivery of grain cargoes from the subjects of the Russian Federation, tending to inland waterways to Iranian ports, within the framework of the developing international transport corridor (ITC) "North-South". The proposed delivery options necessarily imply the operation of a river fleet and river-sea vessels to deliver grain raw materials to the countries of the Middle East and Africa during navigation, as well as during the inter-navigation period.

Artificial Intelligence in Maritime Transportation: A Comprehensive Review of Safety and Risk Management Applications

Maritime transportation is crucial for global trade but faces significant risks and operational challenges. Ensuring safety is essential for protecting lives, the environment, and economic stability. This review explores the role of artificial intelligence (AI) in enhancing maritime safety and risk management. Key AI applications include risk analysis, crew resource management, hazardous material handling, predictive maintenance, and navigation systems. AI systems identify potential hazards, provide real-time decision support, monitor hazardous materials, predict equipment failures, and optimize shipping routes. Case studies, such as Wärtsilä’s Fleet Operations Solution and ABB Ability™ Marine Pilot Vision, illustrate the benefits of AI in improving safety and efficiency. Despite these advancements, integrating AI poses challenges related to infrastructure compatibility, data quality, and regulatory issues. Addressing these is essential for successful AI implementation. This review highlights AI’s potential to transform maritime safety, emphasizing the need for innovation, standardized practices, and robust regulatory frameworks to achieve safer and more efficient maritime operations.

Effect of Layout Discretization on the Performance of Zone Control-Based Multi-AGV Traffic Management Systems

Automatic Guided Vehicles (AGVs) are widely used in flexible manufacturing systems for material handling inside the factory. Traffic management strategies, required to guarantee a conflict-free operation of the overall fleet, discretize the workspace of the AGVs and use the resulting graph model for route planning and execution. In zone control approaches, AGVs move from node to node on a permit basis, with limitations on the allowed number of AGVs at a time in each area of the graph to prevent and/or resolve deadlocks and conflicts. Hence, for an optimal implementation of traffic controllers in real manufacturing systems, it is essential to understand how the layout discretization influences the performance of the AGV network. This paper analyzes its effect in grid-like shaped workspaces by using a representative zone control algorithm and a recently developed improvement of it. Realistic numerical experiments on different layouts reveal that denser discretizations do not yield faster executions or increase in throughput, while lower control periods in the permit system entail significant performance uplifts.

Determining demersal fisheries status in fisheries management arena (FMA) 712 under data limited situation

Abstract Demersal fisheries in FMA 712 have been established since the early 1950’s, industrialization in demersal fisheries was started on 1970’s with the operation of trawl fleets in Java Sea. The exploitation continued until the 1980s when the Trawl Ban regulation was enacted. According to historical statical data from 1980 the number of demersal fishing fleets are still dominating and endangered the sustainability of demersal fish stock in FMA 712. This study presented alternatives approaches to determining demersal fisheries status in FMA 712 using the Bayesian surplus production model (cMSY) and Length-Based Spawning Potential Ratio (LBSPR). The cMSY analysis was conducted using time series production data and known CPUE represent the area in FMA 712 and the LBSPR model was conducted using the life-history parameters and the length frequency data. The results show that current demersal fisheries condition is overexploited, points of estimation of the Biomass condition based on 1980-2022 data: B/BMSY 0,803, F/FMSY 1,75 and MSY 323.000 ton. Additionally, the spawning potential ratio (SPR) of the dominant demersal fish species (Lutjanus malabarius and Portunus pelagicus) was lower than the limit reference point (<0,20), indicating overexploited. This study demonstrates that alternatives approaches could be applied to limited data fisheries and provide useful and robust recommendations.

On the impact of co-optimizing station locations, trip assignment, and charging schedules for electric buses

As many public transportation systems around the world transition to electric buses, the planning and operation of fleets can be improved via tailored decision-support tools. In this work, we study the impact of jointly locating charging facilities, assigning electric buses to trips, and determining when and where to charge the buses. We propose a mixed integer linear program that co-optimizes planning and operational decisions jointly and an iterated local search heuristic to solve large-scale instances. Herein, we use a concurrent scheduler algorithm to generate an initial feasible solution, which serves as a starting point for our iterated local search algorithm. In the sequential case, we first optimize trip assignments and charging locations. Charging schedules are then determined after fixing the optimal decisions from the first level. The joint model, on the other hand, integrates charge scheduling within the local search procedure. The solution quality of the joint and sequential iterated local search models are compared for multiple real-world bus transit networks. Our results demonstrate that joint models can help further improve operating costs by 14.1% and lower total costs by about 4.1% on average compared with sequential models. In addition, energy consumption costs and contracted power capacity costs have been reduced significantly due to our integrated planning approach.

Analyzing the flexibility potential of bus fleet operators in Germany

The transition to smart energy systems is a crucial component for ensuring sustainability and reducing carbon emissions. Electrification is a key factor in achieving these goals, with the transport sector being an integral part of the equation. The integration of the transport sector with the electricity sector will facilitate a reduction in carbon emissions. This paper assesses the potential of electric bus depots to function as smart energy infrastructures. Analyzing the energetic system flexibility of the electrified public transport system is at the core. Previous studies emphasize the importance of identifying and managing the optimal operation strategies of electrified transport to achieve system flexibility. This work concentrates on Germany as a reference market for balancing and electricity markets at the center of the EU. The flexibility potential of a bus fleet with 80 electric buses is analyzed under optimal participation in the short-term electricity and balancing market. The bus fleet operator acts as a storage systems aggregator, which combines mobile and stationary storages to enhance energy flexibility. The study measures the potential contribution for the stability of the electricity grid in Germany. The additional battery degradation that arises with the provision of balancing services is part of the economic equation. The analysis is based on historical data from 2020, 2021, and 2022 and investigates hypothetically lower and higher demand for balancing energy in the load-frequency control area of Germany and Denmark. The paper concludes by demonstrating the feasibility of the electrified bus depot as an integral component of smart energy systems. These findings contribute to a better understanding of the electrification of transport, sector integration, and the role of infrastructures in achieving smart energy systems and showcases the attractiveness of this business model.

Electrified fleet and infrastructure aware energy efficient routing

This paper presents an optimization framework to improve the energy efficiency and cost-effectiveness of fleets of commercial trucks operating pickups and deliveries in urban areas. As the electrification of transportation is moving from passenger cars to medium- and heavy-duty vehicles, the proposed analysis considers a fleet of pickup and delivery trucks that includes conventional internal combustion engine vehicles (ICEV), as well as battery electric vehicles (BEV), and plug-in hybrid electric vehicles (PHEV). Given a set of pickups and deliveries, and a fleet including different types of vehicles, the goal is twofold: assign the best vehicle to each task, and solve the vehicle routing problem, i.e., find the optimal route to navigate the vehicle from the origin to the destination(s). To estimate the energy consumption of the different vehicles, vehicle dynamics are considered, together with actual charging infrastructure and road data, including speed limits, road grade, and stop signs. Moreover, the total cost of ownership (TCO) is evaluated to estimate the cost-effectiveness of different fleet compositions and operations. To solve this problem, a hybrid simulated annealing (HSA) heuristic algorithm is proposed. The algorithm is validated against a benchmark exact solver based on mixed integer linear programming (MILP). The proposed methodology achieves optimal results with a 1.2% optimality gap compared to the benchmark, surpassing MILP in computational efficiency. The research findings highlight how fleet composition and operational strategies can vary significantly based on whether the focus is on energy efficiency, total cost of ownership, or a combination of the two, also depending on the number of years of operation. Simulation case studies in the Columbus, OH area demonstrate that integrating fleet and recharging infrastructure information alongside energy savings in vehicle routing problem solutions can achieve 20% to 50% savings in fleet operation costs compared to solely optimizing for minimum energy consumption.

Optimizing quasi-dynamic wireless charging for urban electric buses: A two-scenario mathematical framework with grid and PV-battery systems

This paper presents a mathematical optimization framework for the strategic placement of quasi-dynamic wireless charging (QWC) stations within road networks to address the charging needs of battery electric buses (BEBs). This study evaluates two scenarios for powering the buses. In the first scenario, a grid-connected system is considered. The optimization aims to minimize annual costs related to capital, operation, and energy losses of the electric bus fleet. This involves determining the optimal locations for QWC stations, the length of power transmitters, and the corresponding battery capacities for the BEBs. Using MATLAB-based optimization tools Casadi and Yalmip, with solvers Bonmin and Fmincon, the optimal configuration includes a 13 kWh battery capacity and a 300 m power transmitter distributed across five bus stop areas. The second scenario employs a chance-constrained optimization approach for an isolated solar photovoltaic (PV) and battery energy storage system (BESS). This system is designed to reliably meet the BEBs' energy requirements throughout the day, considering different seasonal data (winter, summer, all seasons/year-round). The optimization results for the PV and BESS capacities vary with the seasons: 394.247 kW and 2012.6 kWh using summer data, 1762.1 kW and 2738.2 kWh using winter data, and 1610.8 kW and 2741.9 kWh using year-round data. Additionally, the paper examines the impact of varying bus fleet sizes on the optimal battery size and power transmitter combination using a real-world example of the bus route between Khalifa City and Abu Dhabi Downtown in the UAE. The findings suggest that larger batteries with fewer or no charging stations are more economical for smaller fleets. Conversely, as the fleet size increases, a combination of smaller battery sizes and a greater number (and length) of QWC (power transmitters) becomes more cost-effective. This research offers significant insights into the efficient deployment of QWC stations and the integration of renewable energy and energy storage for sustainable urban electric bus networks. The proposed optimization models provide a systematic approach to designing and operating charging infrastructure, contributing to sustainable urban transportation systems. Moreover, the study highlights the influence of seasonal data on PV system sizing and costs.

Portside-shipside interaction on shore-power installation: A perspective of tramp shipping deployment

Due to the high initial costs and the uncertain returns of investment, the efficient green technology in shipping industry, shore power (SP), is still in a developmental dark age, especially its installation at bulk terminals and ships. This study examines the factors influencing the SP installation for bulk terminals and ships, elucidates the impacting mechanisms of one party's installation on the investment returns of the other, and reveals the decisive role of fleet operations in the installation decisions of both parties and corresponding carbon emissions. Employing a dataset representing real-world shipping routes and cargo types, the ship-cargo matching and ships' port-of-calls within a planning horizon are optimized with the objective of maximizing the profit of tramp shipping business by taking SP installation and usage cost into account. Portside SP decision-making model is also conducted to estimate the revenue generated by portside SP usage, and guide portside installation decisions based on the cost-benefit ratio. Finally, recommendations are proposed for ship owner, port operator and government to collaboratively navigate through the dark age of SP development, supported by the further discussion regarding fuel-electricity price gap and port loading efficiency.

Features of planning and evaluation of the work of small shipping vessels enterprises at the present stage

The article considers one of the possible approaches to planning and evaluating the fleet operation of small shipping enterprises at the present stage. The existing algorithms for mathematical modeling of fleet operations are universal and can be used for enterprises with a small number of vessels, but at the same time they are complex, costly and therefore inefficient, and therefore unclaimed. In this regard, the article state the problem of developing a system for operational planning and evaluation of the fleet of small shipping enterprises in the context of modern economics and trends in the use of information technology, defines the objectives of the development and implementation of the system, its configuration; reveals the purpose and methods of implementing the components of the system. The methods necessary for the development of the system and also to be developed are called. The importance of substantiating the effectiveness of informatization is emphasized.

Features of railway transport operation in modern conditions

The application of the system of operational indicators, which developed during the years of the planned economy, in modern conditions requires an assessment for the changed working conditions of railway transport. However, it should be noted that any changes in the management of rail transport will have an impact on all logistics chains with the inclusion of rail transport. The emergence of wagon fleet operators and the transfer of almost all wagons of the network to them obviously reflected an increase in empty mileage, loss of versatility of the wagon fleet, an increase in the surplus of wagons on the infrastructure and, as a result, the risk of an increase in the number of ‟abandoned” trains. The analysis of the problems of the surplus of the wagon fleet and the increase in the number of ‟abandoned” trains makes it possible to structure the causes and differentiate the areas of management decisions for their leveling by JSC ‟Russian Railways”, operators of the wagon fleet and large cargo owners. The application of restrictions by JSC ‟Russian Railways” to the withdrawal of wagons on public tracks with obvious advantages in the context of the increasing strategic importance of railway transport may lead to the opposite effect of increasing the turnover of the wagon and the growth of the wagon fleet. The possibility of independent management of the wagon fleet for the largest operators with an analysis of the system of operational indicators with its subsequent improvement would allow solving a number of problems of rolling stock operation.

OBTAINING ADDITIVES USED TO IMPROVE THE CHARACTERISTICS OF DIESEL FUEL

One of the important large-scale petroleum refining products is diesel fuel (DF). It ensures the continuous operation of the transport fleet of various industries, and is also widely used by individual consumers. The chemical and fractional composition of diesel fuel determines the environmental temperature conditions in which diesel fuel (DF) can be used. There are diesel engines for temperate and cold climates. There is a serious shortage in the production of diesel fuel with improved low-temperature properties; the existing demand is covered by less than half [1]. In fact, in 2014, the production of diesel fuel amounted to 2.2% of the total output. The need for low-solidification fuels for our country, taking into account its natural and climatic conditions, is 40%. Thus, the importance of measures aimed at reducing the existing deficit is beyond doubt. The main goal of the article is to develop methods for the production and use of new additives and additives based on domestic petrochemical products. The cetane number of diesel fuel is one of the most important indicators responsible for reliable engine operation. The use of diesel fuel with a cetane number below 40 leads to harsh engine operation, accompanied by increased wear and its gradual destruction [4]. If the cetane number becomes more than 60 points, the power of the internal combustion engine (ICE) decreases, the fuel does not burn completely, fuel consumption increases, and the exhaust gases contain soot [5]. Keywords: diesel fuel, additives, cetane number, dewaxing, low temperature properties.