Search Results (21)

Urban bus fleets worldwide face urgent decarbonization requirements, with Germany targeting net-zero emissions by 2050. Current electrification research often addresses individual components—energy consumption, scheduling, or charging infrastructure—in isolation, lacking integrated frameworks that capture complex system interactions. This study presents “eflips-X”, a modular, open-source simulation framework that integrates energy consumption modeling, battery-aware block building, depot–block assignment, terminus charger placement, depot operations simulation, and smart charging optimization within a unified workflow. The framework employs empirical energy models, graph-based scheduling algorithms, and integer linear programming for depot assignment and smart charging. Applied to Berlin’s bus network—Germany’s largest—three scenarios were evaluated: maintaining existing blocks with electrification, exclusive depot charging, and small batteries with extensive terminus charging. Electric fleets need 2.1–7.1% additional vehicles compared to diesel operations, with hybrid depot-terminus charging strategies minimizing this increase. Smart charging reduces peak power demand by 49.8% on average, while different charging strategies yield distinct trade-offs between infrastructure requirements, fleet size, and operational efficiency. The framework enables systematic evaluation of electrification pathways, supporting evidence-based planning for zero-emission public transport transitions. Full article

This study evaluates four hybrid infrastructure scenarios for supporting battery electric buses (BEBs) and fuel cell electric buses (FCEBs), analyzing different combinations of grid power, solar energy, battery storage, and fuel cell systems. A multi-stage framework—comprising energy demand forecasting, infrastructure capacity planning, and multi-criteria decision-making (MCDM) evaluation incorporating total cost of ownership (TCO), carbon emissions, and energy resilience—was developed and applied to a real-world transit depot. The results highlight critical trade-offs between financial, environmental, and operational objectives. The limited rooftop solar configuration, integrating solar energy through a Solar Power Purchase Agreement (SPPA), emerges as the most cost-effective near-term solution. Offsite solar with onsite large-scale battery storage and offsite solar with fuel cell integration achieve greater sustainability and resilience, but they face substantial cost barriers. The analysis underscores the importance of balancing investment, emissions reduction, and resilience in planning zero-emission bus fleets. Full article

This work develops a scheduling tool for electric buses that accounts for daily disruptions while minimizing the operational costs. The contribution of this study lies in the development of electric bus schedules that consider many factors, such as multiple depots, multiple charging stations, and stochastic travel times, providing schedules resilient to extreme conditions. The developed model is a mixed-integer linear program (MILP) with chance constraints. The main decision variables are the assignment of electric vehicles to scheduled trips and charging events to ensure the improved operation of daily services under uncertain conditions. Numerical experiments and a sensitivity analysis based on the variation in travel times are conducted, demonstrating the performance of our solution approach. The results from these experiments indicate that the variant of the model with the chance constraint produces schedules with lower operational costs compared to the case where the chance constraints are not introduced. Full article

Electric buses (E-buses) are gaining popularity in urban transportation due to their environmental benefits and operational efficiency. However, large-scale integration of E-buses and Vehicle-to-Grid (V2G) technology introduces scheduling complexities for charging and discharging operations arising from uncertainties in energy consumption and load reduction requests. While prior studies have explored electric vehicle scheduling, few have considered robust optimization for E-bus fleets under uncertain parameters such as trip energy consumption and load reduction requests. This paper proposes a robust optimization approach for the charging and discharging scheduling problem at E-bus depots equipped with V2G. The problem is formulated as a robust mixed-integer linear program (MILP), incorporating real-world operational constraints including dual-port chargers, emergency charging, and demand response. A budgeted uncertainty set is used to model uncertainty in energy consumptions and discharging requests, providing a balance between robustness and conservatism. To ensure tractability, the robust counterpart is reformulated into a solvable MILP using duality theory. The effectiveness of the proposed model is validated through extensive computational experiments, including simulation-based performance assessments and out-of-sample tests. Experiment results demonstrate superior profitability and reliability compared to deterministic and box-uncertainty models, highlighting the practical effectiveness of the proposed approach. Full article

With the development of new energy technologies, fuel buses with internal combustion engines are gradually being replaced by electric buses. In order to save on system costs, an optimization model is proposed to jointly design the bus service and charging facilities. Considering the complexity of the original problem, the problem is decomposed into two subproblems, i.e., bus service design and charging facilities design. The bus service design is solved by a genetic algorithm with an embedded enumeration method. The non-linear charging facilities design problem is firstly converted to a linear problem and then solved by existing solving software. Sensitivity analysis of parameters such as passenger flow demand, charging power, and bus stopping time is also conducted to reveal their impact on the optimization of electric bus lines. The results indicate that, compared to the commonly used depot charging strategy, the proposed method reduces the operating cost per unit hour from RMB 16,378.30 to RMB 8677.99, a 47% reduction, and decreases the system cost from RMB 36,386.30 to RMB 29,637.99, an 18.5% reduction. This study addresses the charging and operation problem of electric bus lines. By considering charging vehicles while in operation, a joint optimization model for the operation of electric bus lines and the layout of charging facilities is established. An algorithm based on the combination of a genetic algorithm and enumeration method is designed, combined with a linear programming solver to solve the problem. Full article

Charging piles in the bus depot provide charging services to multiple electric bus (EB) routes operating in the area. As charging needs may overlap between independently operated routes, EB fleets often have to wait in line for charging. However, affected by the ambient temperature, the length of the waiting time will cause the battery temperature to change at the beginning of each charging, thereby influencing the charging performance and charging time of the battery. To this end, this paper considers the influence of ambient temperature on battery charging performance, and collaboratively optimizes the number of charging piles in the bus depot and the scheduling problem of EB charging. Aiming at minimizing the cost of laying charging piles in bus stations and the charging costs of bus fleets, as well as minimizing the empty time of electric bus fleets and waiting time for charging in queues, a mixed-integer nonlinear programming model is established, and the immune algorithm is used to solve it. At last, an actual bus depot and four EB routes are taken as examples for verification. The results show that by optimizing the charging waiting time of the electric bus at the bus station, the rapid decline in charging performance caused by the sharp drop in battery temperature is avoided. Without increasing the charging cost of the electric bus fleet, the established method reduces the charging pile installation cost, improves the bus depot’s service efficiency, and ensures the punctuality and integrity of the regional bus route operation. Full article

The creation of bus rapid transit systems requires significant investments in transport infrastructure. It often requires changes in roadway parameters, building boarding platforms, new bus depots, as well as creating a priority passage system at intersections with individual vehicles flows. In world practice, the routing of bus rapid transit (hereinafter—BRT) corridors is often based on the criterion of an opinion of transport experts who assess passenger flows and the location of main attraction points. This article describes an algorithm for building BRT corridors based on the criterion of economically viable passenger flow. The method is based on an iterative algorithm built on the principle of passenger flows redistribution over the transport network in the event of a change in its characteristics. Specifically, what changes is the speed of transit in certain areas due to inclusion of the area in a BRT corridor when the area reaches the threshold of economically viable passenger flow. A threshold value of passenger flow for different cities, grouped by population size, is determined on the basis of passenger flow statistics in globally operated BRT systems. The condition for exiting the iterative algorithm can be either the absence of new network areas where an economically viable passenger flow is achieved, or the achievement of 90% of the labor commuting share in the city during the time specified in the urban planning standard. This method can be used to identify new and extend existing BRT corridors in cities with populations from 100 to 2000 thousand people. Full article

One of the crucial steps for a successful integration of electric bus fleets into the existing electric power systems is the active and intelligent usage of their flexibility. This is important not only for reducing the eventual negative effects on the power grid but also for reducing energy and infrastructure costs. The first step in the optimal usage of flexibility is its quantification, which allows the maximum provision of flexibility without any negative effects for the fleet operation. This paper explores the available flexibility of large-scale electric bus fleets with a concept of centralized and unidirectional depot charging. An assessment of available positive and negative flexibility was conducted based on the data from two real bus depots in the city of Hamburg, Germany. The analysis shows the biggest flexibility potential was in the period from 16:00 h to 24:00 h, and the smallest one was in the periods from 08:00 h to 16:00 h, as well as from 02:00 h to 08:00 h. The paper also gives an overview of the possible markets for flexibility commercialization in Germany, which can provide an additional economic benefit for the fleet operators. A further analysis of the impact of parameters such as the timeline (working day or weekend), charging concept, ambient temperature, and electrical preconditioning provides an additional understanding of available flexibility. Full article

The city of Tampere in Finland aims to be carbon-neutral in 2030 and wanted to find out how the electrification of public transport would help achieve the climate goal. Research has covered topics related to electric buses, ranging from battery technologies to lifecycle assessment and cost analysis. However, less is known about electric city buses’ performance in cold climatic zones. This study collected and analysed weather and electric city bus data to understand the effects of temperature and weather conditions on the electric buses’ efficiency. Data were collected from four battery-electric buses and one hybrid bus as a reference. The buses were fast-charged at the market and slow-charged at the depot. The test route ran downtown. The study finds that the average energy consumption of the buses during winter was 40–45% higher than in summer (kWh/km). The effect of cabin cooling is minor compared to the cabin heating energy needs. The study also finds that infrastructure needs to have enough safety margins in case of faults and additional energy consumption in harsh weather conditions. In addition, appropriate training for operators, maintenance and other personnel is needed to avoid disturbances caused by charging and excessive energy consumption by driving style. Full article

This work presents three demos, which include Electric Buses (EBs) from four various brands with lengths of 12 m and 18 m and an Electric Truck (E-truck) for refuse collection. The technical operation of these EVs were analyzed to implement further operational cost optimization on the demo vehicles. The Electric Vehicles (EVs) were tested against superfast-charging solutions based on Pantograph (Type A & Type B) on the route lines (and depots) and based on Combined Charging System Type 2 (CCS2, Combo2) from various brands to validate the interoperability among several vendors and support further EV integration with more affordable solutions. The optimization includes the calculation of the EBs’ consumption at various seasons and under various operating conditions in order to use optimum battery system design, heating system, optimum EB fleet operation and size and to find the charging solutions properly. The results showed that the EB consumption increases in some cases by 64.5% in wintertime due to heating systems, and the consumption in urban areas is more than that on the route lines outside cities. In the E-truck demo, where the electric heater was replaced with a heat-pump to optimize the energy consumption, it was found that the consumption of the heat-pump is about half of the electric heater under certain operating conditions. Under strict EB schedule, Pantograph charging solutions with power ratings of 300–600 kW have been adopted to charge the batteries of the EBs within 4–10 min. In order to minimize the cumulative costs of energy, (pantograph) charging infrastructure depreciation and battery degradation, as well as depot charging (at the bus operator’s depot), was adopted with a power level of 50–350 kW based on CCS2 and pantograph. Full article

Electric buses (e-buses) demonstrate great potential in improving urban air quality thanks to zero tailpipe emissions and thus being increasingly introduced to the public transportation systems. In the transit operation planning, a common requirement is that long-distance non-service travel of the buses among bus terminals should be avoided in the schedule as it is not cost-effective. In addition, e-buses should begin and end a day of operation at their base depots. Based on the unique route configurations in Shenzhen, the above two requirements add further constraint to the form of feasible schedules and make the e-bus scheduling problem more difficult. We call these two requirements the vehicle relocation constraint. This paper addresses a multi-depot e-bus scheduling problem considering the vehicle relocation constraint and partial charging. A mixed integer programming model is formulated with the aim to minimize the operational cost. A Large Neighborhood Search (LNS) heuristic is devised with novel destroy-and-repair operators to tackle the vehicle relocation constraint. Numerical experiments are conducted based on multi-route operation cases in Shenzhen to verify the model and effectiveness of the LNS heuristic. A few insights are derived on the decision of battery capacity, charging rate and deployment of the charging infrastructure. Full article

This paper provides a comprehensive overview of the state-of-the-art related to the implementation of battery electric buses (BEBs) in cities. In recent years, bus operators have started focusing on the electrification of their fleet to reduce the air pollutants in cities, which has led to a growing interest from the scientific community. This paper presents an analysis of the BEB powertrain topology and the charging technology of BEBs, with a particular emphasis on the power electronics systems. Moreover, the different key technical requirements to facilitate the operation of BEBs are addressed. Accordingly, an in-depth review on vehicle scheduling, charger location optimization and charging management strategies is carried out. The main findings concerning these research fields are summarized and discussed. Furthermore, potential challenges and required further developments are determined. Based on this analysis, it can be concluded that an accurate energy consumption assessment of their BEBs is a must for bus operators, that real-time, multi-objective smart charging management strategies with V2X features should be included when performing large bus fleet scheduling and that synchronized opportunity charging, smart green depot charging, and electric bus rapid transit can further reduce the impact on the grid. This review paper should help to enable a smarter and more efficient integration of BEBs in cities in the future. Full article

This work presents a real-life demonstration of 23 heavy-duty (HD) public electric buses (e-buses) in Jaworzno, Poland, with three lengths: 8.9 m, 12 m, and 18 m. The e-bus demo is based on the development of baseline e-buses to optimize the operational cost based on technical optimization. The demo aims to switch public transportation from internal combustion engine vehicles (ICEVs) to electric ones to minimize CO₂ emissions. The e-buses are equipped with standard charging solutions, which are plug-in charging with Combined Charging System Type 2 (CCS2, Combo 2) and pantograph-up (Type B). The CCS2 solution is used for overnight slow/normal charging (NC) in the depot of the e-bus operator, whereas the pantograph charging solutions are installed along the e-buses routes and used for fast charging (FC) when the e-buses are stopped for a short time. In Jaworzno, there are 20 chargers with CCS2 in the depot of the e-bus operator and 12 pantograph-up (Type B solution) fast-charging stations. This work studies the technical operations and operational costs of the e-bus fleet, and the impact of the NC and FC solutions on the Li-ion battery packs and on the grid. The uncoordinated/standard and coordinated charging (smart charging) based on load shifting were investigated to study the impact of e-bus fleet integration on the distribution grid. The exploited data in this study were collected from the data logger devices, which are installed on the e-buses and record over 46 signals. Data from over one year were collected, and some sample data were processed and analyzed to study the technical and economic operations of the e-bus fleet. Full article

The present paper proposes a new methodology to aid the electrification process of local public transport (LPT). In more detail, real drive cycles of traditional buses currently in use are evaluated together with other data to simulate the consumption of equivalent e-buses (electric buses) with similar characteristics. The results are then used in order to design the best charging infrastructure. The proposed methodology is applied to the case study of Algeciras Bay, where a specific line of LPT is considered. Real measurements are used as data for the simulation model, and the average consumption of an equivalent e-bus is obtained for different operating conditions. Based on these results, different sizes and locations for fast-charging infrastructure are proposed, and the size of the depot charging system is defined trying to maintain the current buses timetable. Finally, some future developments of the present work are presented by considering other bus lines that may benefit from the introduction of the defined charging systems. Full article

Bus operators around the world are facing the transformation of their fleets from fossil-fuelled to electric buses. Two technologies prevail: Depot charging and opportunity charging at terminal stops. Total cost of ownership (TCO) is an important metric for the decision between the two technologies; however, most TCO studies for electric bus systems rely on generalised route data and simplifying assumptions that may not reflect local conditions. In particular, the need to reschedule vehicle operations to satisfy electric buses’ range and charging time constraints is commonly disregarded. We present a simulation tool based on discrete-event simulation to determine the vehicle, charging infrastructure, energy and staff demand required to electrify real-world bus networks. These results are then passed to a TCO model. A greedy scheduling algorithm is developed to plan vehicle schedules suitable for electric buses. Scheduling and simulation are coupled with a genetic algorithm to determine cost-optimised charging locations for opportunity charging. A case study is carried out in which we analyse the electrification of a metropolitan bus network consisting of 39 lines with 4748 passenger trips per day. The results generally favour opportunity charging over depot charging in terms of TCO; however, under some circumstances, the technologies are on par. This emphasises the need for a detailed analysis of the local bus network in order to make an informed procurement decision. Full article