Transport Operations Research Articles

Improving the Profitability of Public Transport by Daily Forecasting of Passenger Loads and Bus Trip Distribution

The degree of utilization of passenger vehicle capacity affects the economic component of public transport operation. This is due to the fact that it depends on the number of passengers transported, as well as on the capacity of the passenger vehicle used for transportation. One of the tasks formulated in the state program of transport development of the Republic of Belarus is to achieve full self-sufficiency of public transport operation. One of the ways to achieve this goal can be maximizing the degree of use of passenger vehicle capacity by ensuring its compliance with the existing parameters of passenger flow. In this paper, based on the values of passenger flows in one of the cities of Belarus, obtained as a result of field observations in 2019 and 2024, we calculate an indicator that assesses the degree of utilization of passenger vehicle capacity, the factors that determine it, and the regularities of its change. Based on such calculations, the feasibility of creating a new public transport management technology based on daily forecasting of passenger traffic and distribution of passenger vehicles of different capacity to the routes taking this into account is shown.

Performance-Based contracting of urban transport operation Services: Evidence from Porto’s Light-Rail

This paper develops a bonus/malus incentive model for contracting out the provision of urban railroad operation services, and testing parts of its performance using Monte Carlo methods. We also provide evidence on the performance measures of Metro do Porto’s (MdP) light-rail network operation, during the 2010–2016 term of a bonus/malus-based contract, incorporating some features of our model. Results document that the implementation of a performance-based contract with an embedded incentive bonus/malus mechanism may contribute to promoting ridership patronage, increasing the average ride, and ultimately promoting the overall economic operating efficiency of the system. The comparative operating performance analysis of MdP versus Metropolitano de Lisboa, a vertically integrated, governmentally-owned metro network, shows that MdP exhibits higher revenue, cost, and operating efficiency in the 2010–2016 period, and that the bonus/malus mechanism induces the private sub-concessionaire to respond more efficiently to changes in demand.

Planning shared mobility hubs in European cities: A methodological framework using MCDA and GIS applied to Barcelona

In the move towards sustainable urban mobility through seamless intermodality, European cities are faced with the possibility of implementing shared mobility systems. They constitute an opportunity to create new urban hubs, considered as nodes of intermodality and places of urban intensity. In order to effectively plan the future locations of shared mobility hubs, this paper outlines the methodological framework that sustains the design of a new decision-support tool, the so-called Mcda2MobilityHub (M2MHub),11Link to the M2MHub tool, which is available as an open plugin for QGIS: https://github.com/natrouk/Mcda2MobilityHub-desicion-support-tool_QGIS-plugin. using Multi-Criteria Decision Analysis (MCDA) and Geographic Information Systems (GIS). For this purpose, the analysis of existing literature and interviews with local authorities and transport operators, led to the identification of six main location criteria (mobility, compactness, diversity of uses, profile of potential users, spatial configuration and environment). The criteria weights were calculated using the Analytic Hierarchy Process (AHP) and the framework was applied to the case study of the city of Barcelona. The results obtained are presented in the form of heat maps, highlighting the flexibility of the decision-support tool to transform open data into appropriate indicators and detailed maps. This output can be used to support future policies for planning shared mobility hubs as places for convenient multimodal transfers, which also enable social activities and improve the quality of life in European cities.

Key factors for developing freight and passenger integrated transportation systems in Brazil

The intensification of e-commerce increases freight movements in urban areas, which negatively contributes to promoting sustainable cities. Conversely, the spare capacity of the public transport system could reduce the externalities of urban freight transport and then promote sustainable cities. This article identifies and evaluates key factors for developing integrated freight and public transport systems. Key factors were identified with a literature review and then classified into benefits and barriers related to the urban environment, and challenges and strengths related to the transport operation. Subsequently, these factors were evaluated by experts and classified by estimating a Luce model. The results indicate that benefits are related to the fight against climate change by optimising urban space and reducing the movements of freight vehicles. Barriers are associated with the lack of a collaborative culture and the need to change consumer behaviour, which helps to promote collaboration and reduce just-in-time demand. For the transport operation, the integration of people and freight systems can reduce operational costs, increase the efficiency of the transport system, and improve the accessibility for people and goods, while promoting economic development by decentralising economic activity. To achieve these benefits, the main challenges concern the logistic activity and the cooperation of stakeholders.

The flexible airport bus and last-mile ride-sharing problem: Math-heuristic and metaheuristic approaches

Airport buses play a crucial role in addressing the last-mile problem of air travel, especially in cities and countries lacking inner-city rail transit systems. Nevertheless, airport buses are currently witnessing a decline in ridership due to drawbacks such as long departure intervals, inflexible stops, and considerable distances between stops. Consequently, delivering high-quality airport bus services has become a pressing concern for public transport operators. Motivated by new flexible buses and ride-sharing services, this paper explores a flexible airport bus service that integrates ride-sharing services for passengers traveling from bus stops to their destinations. This problem entails integrated decisions involving bus stop selection, passenger assignment to drop-off bus stops, as well as bus and ride-sharing routing. Accordingly, this problem presents more challenges in decision-making than traditional flexible bus or ride-sharing routing problems. We first develop an arc-based mixed-integer linear programming model. Subsequently, we design a double decomposition math-heuristic algorithm that builds upon logic-based Benders decomposition and column generation algorithms to obtain a near-optimal solution within practical computation time limits for practical-scale instances. Additionally, we implement an adaptive large neighborhood search algorithm to evaluate the solution quality of this math-heuristic algorithm and to solve large-scale instances. To validate the effectiveness of both the model and the algorithms, we conduct numerical experiments using instances derived from Shenzhen airport bus lines. The experimental results demonstrate that the flexible service mode offers significant advantages in reducing both passenger ride time and vehicle mileage over traditional airport bus or taxi modes.

How to build a more sustainable passenger air transport system: multimodal experience

A fully integrated passenger multimodal system is a new concept in the transport industry, and consequently, data on system interoperability is lacking. In this paper, a qualitative research method is applied, to get the transport experts’ opinions and information on how the multimodal system should be designed. Although they are aware that the collaboration should result in an increase in the volume of passengers, the most challenging task is to convince transport operators to share the data with each other, due to legal issues. To determine the passengers’ perspective on making multimodal choices in their journeys, the travel demand model is developed, based on online survey data. The proposed (Binary Logistic Regression) model reveals the importance for policymakers and transport operators serving the airport to address access time reliability by carefully considering the passengers’ preferences in terms of their needs and age.

A Study on Challenges being faced by TSRTC Passengers with Special Reference to Dilsukhnagar Bus station Hyderabad

The majority of people in Telangana state travel by public transportation, which plays a crucial role in the country’s socio-economic development. A principal function of public transport industry should be organized around to satisfy the clients. When passengers are pleased, public transportation services are considered to be effective service opportunities. Public transport should become part of a solution for sustainable transport in the future. Public transportation must provide high-quality service to meet a wider range of customer requirements in order to retain and attract more passengers. Efficient operation of public transport is a key factor for the improvement of living condition in Hyderabad city. The environment as well as Bus Transportation in Hyderabad city is poor and can hardly meet the passenger needs. The exploration of service quality of bus is necessary to provide a better in future. In this research challenges faced by TSRTC passengers were analysed based on passenger’s view towards quality, safety and security and services provided by TSRTC at Dilsukhnagar Bus Station. A questionnaire survey was conducted at Dilsukhnagar Bus Station; the result indicated more than half of the responded believed that the present physical facilities of bus station are unsatisfactory, in spite of negative views passengers possessed appositive attitude for buses which is low travel cost.

Anti-ambipolar transport and logic operation in two-dimensional field-effect transistors using in-series integration of GeAs and SnS2

Germanium arsenide (GeAs) from the IV–V semiconductor family has drawn attention for its anisotropic optical and electrical characteristics as a robust p-type semiconductor with high mobility. Despite its potential, the scope of applications for two-dimensional (2D) GeAs remains limited. In this study, we investigate the in-series integration of GeAs and SnS2 for complementary inverter operation, a crucial element in logic circuits. Moreover, the resulting in-series field-effect transistors reveal a previously undocumented anti-ambipolar behavior in this configuration, with a peak-to-valley ratio exceeding 5000 at a drain-source bias of 2 V. This anti-ambipolar characteristic operates regardless of the direction of current flow, which is rarely seen in conventional anti-ambipolar transistors built with hetero-stacked p–n junctions. Moreover, the in-series structure demonstrates stable operation as a complementary inverter, highlighting the versatile potential of p-type 2D GeAs in diverse optoelectronic applications. This work contributes insights into the transport characteristics of GeAs and its interconnected arrangement with SnS2, offering valuable implications for the development of advanced 2D material-based devices.

Predicting energy consumption of zero emission buses using route feature selection methods

This paper reports new insights into how the selection of route based characteristic parameters can influence the predicted energy consumption for next generation battery electric buses. 24 characteristic parameters have been studied to understand their relative importance on vehicle energy consumption and to develop new data-driven prediction models. The parameters are grouped into two scenarios, representative of the varying levels of route information available to a typical bus operator. A combination of feature selection methods was used to determine which characteristic parameters had the greatest influence on energy consumption. Regression based prediction models were developed, and models were then validated using standard and real vehicle drive cycles. The prediction models had a mean absolute percentage difference of 2.10–10.67%. This paper presents a novel methodology to estimate energy consumption of operating zero emission vehicles, which will support public transport operators, policy makers and energy suppliers in the decarbonisation of public transport.

A Model for Electrifying Fire Ambulance Service Stations Considering Practical Service Data and Charging Strategies

Due to concerns with air pollution and climate change, governments and transport operators around the world have engaged in transforming their fossil-fueled vehicles into electric vehicles (EVs). It is essential to build a model for the electrifying process to minimize the operation costs. This paper presents a systematic analytical approach for the electrification of a fire ambulance service station. This approach begins with the selection of suitable EVs to replace the current service vehicles. Subsequently, an in-depth analysis is conducted to determine the practical utilization of EVs at the station. The model proposes two charging strategies: immediate charging upon an EVs’ return and smart charging. Based on the chosen EVs and charging strategies, a comprehensive assessment of the load profiles for the planned EV charging station is performed. In accordance with the load profiles, a mathematical model to minimize the infrastructure and operation costs of the charging station is proposed. Various pricing schemes are compared to identify the most efficient pricing scheme for the charging station, and economic analyses of the EVs and traditional ambulance vehicles are proposed in this paper. The test results indicate that the progressive pricing scheme is well suited for immediate charging strategies, whereas smart charging should opt for the time-of-use pricing scheme. Selecting the appropriate pricing scheme has the potential to significantly reduce electric energy costs.

Chance-Constrained Optimization for a Green Multimodal Routing Problem with Soft Time Window under Twofold Uncertainty

This study investigates a green multimodal routing problem with soft time window. The objective of routing is to minimize the total costs of accomplishing the multimodal transportation of a batch of goods. To improve the feasibility of optimization, this study formulates the routing problem in an uncertain environment where the capacities and carbon emission factors of the travel process and the transfer process in the multimodal network are considered fuzzy. Taking triangular fuzzy numbers to describe the uncertainty, this study proposes a fuzzy nonlinear programming model to deal with the specific routing problem. To make the problem solvable, this study adopts the fuzzy chance-constrained programming approach based on the possibility measure to remove the fuzziness of the proposed model. Furthermore, we use linear inequality constraints to reformulate the nonlinear equality constraints represented by the continuous piecewise linear functions and realize the linearization of the nonlinear programming model to improve the computational efficiency of problem solving. After model processing, we can utilize mathematical programming software to run exact solution algorithms to solve the specific routing problem. A numerical experiment is given to show the feasibility of the proposed model. The sensitivity analysis of the numerical experiment further clarifies how improving the confidence level of the chance constraints to enhance the possibility that the multimodal route planned in advance satisfies the real-time capacity constraint in the actual transportation, i.e., the reliability of the routing, increases both the total costs and carbon emissions of the route. The numerical experiment also finds that charging carbon emissions is not absolutely effective in emission reduction. In this condition, bi-objective analysis indicates the conflicting relationship between lowering transportation activity costs and reducing carbon emissions in routing optimization. The sensitivity of the Pareto solutions concerning the confidence level reveals that reliability, economy, and environmental sustainability are in conflict with each other. Based on the findings of this study, the customer and the multimodal transport operator can organize efficient multimodal transportation, balancing the above objectives using the proposed model.

Features of using ozone for cleaning marine pollution

The subject of the research is issues related to the field of ship power plants and their elements, as well as the operation of water transport and its environmental safety. Studying the processes of ballast water purification and disinfection, as well as oil-containing water that are formed during the ships operation, shows the possibility of increasing the efficiency of these processes. It is proposed to consider these processes, starting from the stage of supplying the ozone-air mixture to the flow of treated water, without limiting ourselves to the study of the actual process of oxidation by ozone of a contaminated, including bacteriologically hazardous, substance. This approach makes it possible to establish the limiting stages of the contaminated water purification and disinfection process, which includes the stage of ozone dissolution in water during its transition from the ozone-air mixture, as well as the stage of subsequent diffusion of ozone dissolved in water into the reaction contact zone. It has been shown that the kinetic characteristics of the limiting stages depend on the conditions of their implementation, which can reduce the efficiency of ozone use due to the limited time of its existence. A technological proposal that makes it possible to increase the efficiency of ozone use and the reliability of ensuring the requirements for the quality of cleaning and disinfection of marine pollution has been developed. Technological proposals provide for the preliminary saturation with ozone of a specially allocated water stream for this purpose, the supply of this stream to the concentration zone of the oxidized and disinfected substance. A device in which the developed technological fragment, including a pump supplying a water flow to a contact column, an ozone generator, a device for supplying an ozone-saturated water flow to a filter, is implemented is also proposed.

IoT based Health Monitoring System

The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real- time remote patient monitoring to improve the quality of people’s lives. This review paper explores the latest trends in healthcare-monitoring systems by implementing the role of the IoT. The work discusses the benefits of IoT-based healthcare systems with regard to their significance, and the benefits of IoT healthcare. We provide a systematic review on recent studies of IoT- based healthcare-monitoring systems through literature review. The literature review compares various systems’ effectiveness, efficiency, data protection, privacy, security, and monitoring. The paper also explores wireless- and wearable-sensor-based IoT monitoring systems and provides a classification of healthcare- monitoring sensors. We also elaborate, in detail, on the challenges and open issues regarding healthcare security and privacy, and QoS. Finally, suggestions and recommendations for IoT healthcare applications are laid down at the end of the study along with future directions related to various recent technology trends. Keywords: IoT, IoWT, healthcare, monitoring, remote

A Georeferenced Dataset for Mapping and Assessing Subgrade Defects in China’s High-Speed Railways

China has the world’s longest high-speed rail (HSR) network, marked by dense transportation and complex operations. However, frequent train use coupled with extreme weather conditions has led to rising subgrade issues. Existing railway defect records suffer from inconsistency, hindering direct applicability. Currently, there is a lack of a relevant dataset dedicated to HSR subgrade defects. To bridge this gap, we developed a comprehensive georeferenced dataset that encompasses defect records extracted from peer-reviewed literature published between 1999 and 2023 in China. Rigorous quality control procedures were implemented to eliminate duplicate data and ensure the accuracy of the dataset. The dataset consists of georeferenced records for eight different defects, spanning across 661 locations and categorized at various scales, ranging from provinces to townships. The most commonly reported defect types include subgrade settlement, frost damage, uplift deformation, and mud pumping. This dataset provides a comprehensive map of historical subgrade defects affecting high-speed railways in China. It could facilitate operational risk assessments and the prediction of subgrade performance.

Monitoring and predicting corn grain quality on the transport and post-harvest operations in storage units using sensors and machine learning models

Monitoring the intergranular variables of corn grain mass during the transportation, drying, and storage stages it possible to predict and avoid potential grain quality losses. For monitoring the grain mass along the transport, a probe system with temperature, relative humidity, and carbon dioxide sensors was developed to determine the equilibrium moisture content and the respiration of the grain mass. These same variables were monitored during storage. At drying process, the drying air and grain mass temperatures, as well as the relative humidity, were monitored. For the prediction of the physical and physical–chemical quality of the grains, the results obtained from the monitoring were used as input data for the multiple linear regression, artificial neural networks, decision tree, and random forest models. A Pearson correlation was applied to verify the relationship between the monitored and predicted variables. From the results obtained, we verified that the intergranular relative humidity altered the equilibrium moisture content of the grains, contributing to the increased respiration and hence dry matter losses along the transport. At this stage, the artificial neural network model was the most indicated to predict the electrical conductivity, apparent specific mass, and germination. The random forest model satisfactorily estimated the dry matter loss. During drying, the air temperature caused volumetric contraction and thermal damage to the grains, increasing the electric conductivity index. Artificial neural network and random forest models were the most suitable for predicting the quality of dry grains. During storage, the environmental conditions altered the moisture contents causing a reduction in the apparent specific mass, germination, and crude protein, crude fiber, and fat contents. Artificial neural network and random forest were the best predictors of moisture content and germination. However, the random forest model was the best predictor of apparent specific mass, electrical conductivity, and starch content of stored grains.

Suitable law-based location selection of high-power electric vehicles charging stations on the TEN-T core network for sustainability: a case of Poland

With the upcoming implementation of the amendment to Regulation (EU) 2019/631 of the European Parliament and of the Council, from 2035 there will be a ban on the registration of new vehicles with internal combustion engines (ICE) in the Member States of the European Union (EU). Consequently, changes in the transportation sector, resulting from the increasing use of electric vehicles, appear to be inevitable. According to the adopted legal acts, the European Union Member States will be obliged to develop, among others, a charging infrastructure and access to public charging stations for electric vehicles. As a result, there will be a need to ensure a significant increase in the power and the number of charging stations and to determine their appropriate location. The article presents the challenges faced by charging station operators and difficulties related to the further development of electric vehicle charging infrastructure in Poland. The still poorly developed public charging infrastructure for electric vehicles, especially in service areas located along the main communication routes, remains the main obstacle to the development of electromobility. In the context of legal, financial, technological, and organizational challenges, the problem of the proper distribution of electric vehicle charging stations along the main communication routes is therefore of particular importance. The aim of the article is to present a new, proprietary method for determining the location of electric vehicle charging stations in Poland within the Trans-European Transport Network (TEN-T), which considers objective location factors: adherence to AFIR requirements, the specificity of the Polish power system and existing parking infrastructure. As a result of using the developed method, a list of 188 recommended locations for the construction of electric vehicle charging stations in Poland along the Trans-European Transport Network (TEN-T) was created. It has been shown in this way that the use of the presented method enables the suitable determination of the location of electric vehicle charging stations along transport routes, considering legal, financial, and technological requirements, which will significantly facilitate the operation of zero-emission transport.

Theoretical basis for development of indicators for improving training and retraining of specialists and passenger road transport personnel

Introduction. The theoretical basis for the development of indicators for improving the training and retraining of road transport personnel is aimed, first of all, at ensuring the results of transportation and technical operation activities corresponding to the output in road transport. The studied indicators should take into account the amount of labor costs of all types of workers ensuring the operation of rolling stock. Training and retraining of personnel largely determine the safety of the transportation process and must comply with the existing operating conditions of rolling stock. The purpose of this article is to theoretically substantiate the indicators for improving the training and retraining of specialists and personnel of road transport, as an element of the “personnel-bus-road-operating environment” (PADS) system to ensure the planned production of rolling stock in accordance with the requirements of the municipal contract for regular passenger transportation and luggage, taking into account operating conditions.Materials and methods. The theoretical basis for the development of indicators for improving the training and retraining of personnel is based on a systematic analysis of professional and qualification requirements, as well as the theory of current planning of the work of motor transport enterprises, taking into account the probabilistic nature of operating conditions under the influence of the external environment. As a result, structural connections between the driver, mechanic and technical condition inspector were identified as elements of the new PADS system.The parameters of the developed mathematical model of personnel activities and the costs of their training and retraining are determined using methods of mathematical statistics and expert assessments. The content of the new approach is to integrate the production of rolling stock with professional and qualification requirements for personnel.Results. This study focuses on fulfilling the municipal contract for regular transportation of passengers and luggage, i.e. to obtain the planned mileage, it is necessary to take into account the joint activities of groups of personnel and in each group of an individual employee.Discussion and conclusion. The scientific novelty and main results of the study consist in the theoretical substantiation of indicators for improving the training and retraining of passenger road transport personnel, as an element of the PADS system, to ensure the planned production of rolling stock, taking into account operating conditions.Based on the results of the study, the indicators of training and retraining of personnel of automobile passenger transport, ensuring the fulfillment of the contract, are grouped in accordance with their levels and periods of formation.A mathematical model that determines the planning of the results of fulfilling the terms of the contract by each employee has been developed. Further research will be aimed at experimentally determining the values of the identified indicators.

Large-scale Wi-Fi and Bluetooth data collection for reconstructing passenger flows

ABSTRACT For a public transport operator, estimating passenger flows is vital to plan inclusive and efficient service. Understanding where and when to optimally allocate resources results in better customer experiences, further shaping and optimizing public transport services. To this end, the project Mobile Data Fusion aims at developing a technique to collect, process, and merge data from different sources. The data are used to inform public transport operators about passenger demand, by combining Wi-Fi and Bluetooth signals from customer devices with time-of-flight counting sensors. The project had access to a large study area in Kassel, Germany, with a fleet of 50 vehicles servicing eight passenger lines, all equipped with automatic passenger counting sensors. In the course of this study, we found out that Bluetooth signals did not offer any significant insight , while Wi-Fi signals could be used to reconstruct a trend, albeit not the absolute occupancy level. In this paper, we present our hardware setup and a subset of our data set to show how the Wi-Fi and Bluetooth signals correlate with the measured occupancy. The ongoing data collection will provide additional material for future studies, and answer some of the pending questions discussed in this work.

Macroscopic modeling of mixed bi-modal urban networks: A hybrid model of accumulation- and trip-based principles

Network-level traffic flow models either assume steady-state urban flows (i.e. accumulation-based models) or track the movement of all vehicles (i.e. trip-based models). The steady-state assumption present in the accumulation-based models may pose a challenge in light of the multi-modal nature of urban flows. It might be indeed a rough assumption for the flow of some transportation modes like buses, cruising-for-parking vehicles, taxis, and on-demand vehicles. Trip-based models address this concern, however, they need significant parameter calibration effort and are not computationally efficient, which substantially reduces the practicality of these models in real-world applications. Nevertheless, despite the critical importance of developing multi-modal traffic flow models, few attempts have been made to investigate these models in network macroscopic fundamental diagram (NMFD)-related literature. This paper bridges this gap by developing a hybrid network-level traffic flow model for mixed bi-modal (i.e. car and bus) networks. The present hybrid model reproduces the dynamics of car flows via accumulation-based model principles while tracking the movement of buses using the trip-based model. This effort also includes the development of a new FIFO-based entrance function to ensure different modes experience the same delay under saturated traffic conditions. Different numerical experiments are conducted to study the hybrid model performance and to compare it with that of accumulation-based and trip-based models in both steady-state and transition periods under different traffic conditions. Our observations reveal that the hybrid model simulates the dynamics of cars and buses by closely following the behavior of its components under free-flow conditions. The model also outperforms the accumulation-based model under saturated traffic conditions while being considerably less demanding than the trip-based model. A further investigation of the model performance is performed for networks with different bus shares in both free-flow and saturated traffic conditions, confirming the results of the initial numerical experiments. The hybrid model’s computational efficiency is demonstrated. The potential real-world applications of the hybrid model in development of bi-modal network-level simulation models, NMFD-based control strategies along with bus space allocation policies, public transport operation problems, modeling of cruising-for-parking vehicles, taxis, and on-demand vehicles, and modeling and application of autonomous modular vehicles are discussed and future research directions are highlighted.

Research on Energy Distribution Strategy of Tandem Hybrid Tractor Based on the Pontryagin Minimum Principle

In order to study the energy distribution of the tandem hybrid tractor and achieve optimal fuel economy under the whole operating condition, an energy distribution strategy based on PMP (Pontryagin minimum principle) is proposed. The performance parameters of the relevant power components are obtained by constructing the test bench of the tandem hybrid tractor. At the same time, the mathematical model of energy distribution is established from the aspects of energy distribution objective function, state variable, and variable constraint. Based on the external characteristic test of the hub motor and the resistance analysis, the transport operation condition of the tractor is selected as the simulation target condition. The ADVISOR2002 and Simulink software are used to jointly simulate the three energy distribution strategies: the thermostat type, the power-following type, and the PMP type. The simulation results show that, compared with the other two, the fuel economy and battery power loss of the PMP-based energy distribution strategy are significantly improved. The fuel consumption per 100 km is decreased by 32.91% and 26.10%, respectively, which verifies the feasibility of the strategy. This study is of great significance for improving the production efficiency and reducing fuel consumption of hybrid tractors.