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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. [ABSTRACT FROM AUTHOR]

There is no doubt that traffic noise has become one of the main sources of urban noise, and the electric bus, as an important means of transport frequently used by people in daily life, has a direct impact on the psychological and auditory health of passengers due to its interior noise characteristics. Consequently, studying electric bus sound quality is an important way to improve vehicle performance and comfort. In this paper, eight electric buses were selected and 64 noise samples were measured. Acoustic comfort was taken as an evaluation index, professionals were organized to complete the subjective evaluation tests for all noise samples based on rank score comparison (RSC). And nine psycho-acoustic objective parameters such as loudness, sharpness and roughness were calculated using Artemis software to establish the sound quality database of electric buses. Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. Finally, the calculation results of three indexes of average relative error, square root error and correlation coefficient indicate that the proposed PSO-XGBoost model is significantly better than GS-XGBoost and standard XGBoost, with its prediction accuracy as high as 97.6 %. This model is determined as the evaluation model of interior acoustic comfort for this case, providing a key technical support for future sound quality optimization of electric buses. [ABSTRACT FROM AUTHOR]

The emergence of battery electric buses (BEBs) can alleviate environmental problems caused by tailpipe emissions in transit system. However, the high cost of on-board batteries and range anxiety hinder its further development. Recently, the advent of dynamic wireless power transfer technology (DWPT) has become a potential solution to promote the development of BEBs. Hence, this study focuses on the application of DWPT in flex-route transit system. A mixed integer non-linear model is proposed to simultaneously optimise the bus routing and the selection of corresponding bus types considering the constraints of passengers’ travel time, battery size and bus capacity. The objective is to minimise both transit agency cost and passengers’ travel time cost. A tangible hybrid variable neighbourhood search (HVNS) consisting of simulated annealing (SA) and variable neighbourhood search (VNS) is developed to solve the proposed model efficiently. Compared with GAMS (DICOPT solver) and VNS, the proposed algorithm can considerably improve computational efficiency. The results suggest that the proposed model can effectively determine the BEBs’ routing and bus type for flex-route transit system powered by DWPT through a case study in Xi’an China. A comparative analysis shows the proposed model takes 12.97% less total cost than the alternative model with terminal charging technology (TCT).

Electric drive systems in mobility solutions are increasingly being used by the manufacturers in the global automotive industry. The European strategy to reduce greenhouse gas emissions to zero by 2050 is also transposed into Romania's Energy Strategy. An important part of this strategy is the use of electricity in public passenger transport to significantly reduce pollution in urban areas. The rapid pace in terms of the renewal of conventional urban transport with modern electrified solutions requires, at the same time, an analysis of the pressure that this new consumer can exert on the national energy system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the initial steps taken in analysing the benefits of connected autonomous vehicles (CAVs), especially Modular Autonomous Vehicles (MAVs), in search of sustainable solutions for reducing energy consumption per passenger in air transport. For this particular case, a Mobility-as-a-Service (MaaS) solution is proposed, correlating airside transport with landside transport, as an urban mobility alternative. To better understand the benefits of the proposal, this paper studies the impact on energy consumption conceptual differences between a conventional public transport fleet using Battery Electric Buses (BEBs) and an MAV fleet. Simulations for simple public transport tasks are performed to highlight the advantages of the modular vehicle concept, in which routes are assigned dynamically based on the requested passenger carrying capacity and travel distance, aiming to optimize the efficiency of the entire system. With a proven reduction in energy consumption due to better use of available passenger capacity and reduced travel times in which the vehicle is driving with a number of passengers less than half of its capacity, the concept can be addressed further in developing a predictive system that processes public transport data and delivers an optimized schedule for the entire fleet. The main goal being to improve overall operational efficiency and total cost of ownership, the second part of the paper studies the impact of weight distribution on efficiency parameters such as energy consumption, range, and overall performance of an electric bus. The impact on dynamic elements such as acceleration, braking, and cornering performance is analyzed, to assess the viability and safety of all types of electric bus operations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Inductive power transfer (IPT) systems offer a promising solution to multiple major hurdles associated with electric vehicles, such as the lack of widespread charging infrastructure, driving range anxiety, and significant charging time. With the aid of IPT systems, dynamic wireless charging enables electric vehicles to be charged when running over the IPT power pads. The objective of this study is to minimise the overall cost of charging infrastructure by optimising the deployment of IPT transmitters and the battery size required to support charging for electric buses. A mixed-integer linear programming model is proposed and solved using the commercial solver Gurobi. Bus route information and the characteristics of electric buses, such as weight, drag coefficient and frontal area, are used as input to run the traffic simulation in SUMO to get time-varying velocity and acceleration data during bus operations. A bus route in Auckland, New Zealand, is used as a case study in the presented numerical experiments. A strong correlation between the velocity of the bus and the state of charge is identified. The largest cost component is the charging pad, followed by the battery. [ABSTRACT FROM AUTHOR]

Intelligent transportation systems enhance the potential for sustainable, user-friendly, and efficient transport. By eliminating driver costs, autonomous buses facilitate the redesign of networks, timetables, and fleet structure in a cost-effective manner. The electrification of bus fleets offers the opportunity to further improve the environmental sustainability of transportation networks, but requires adjustments to vehicle schedules due to the limited range and charging requirements. This paper examines the intricate relationship between electrification and autonomous buses. To this end, timetables for autonomous electric buses of different sizes were developed for a real bus route in Aachen, Germany. The resulting electric vehicle scheduling problem was then solved using an adaptive large neighborhood search to determine the number of vehicles needed and the total cost of ownership. By eliminating driver costs, vehicles with lower passenger capacity become much more attractive, albeit at a slightly higher cost. In comparison, the incremental costs of electrification are low if the right approach is taken. Fluctuations in typical passenger numbers can be used to modify timetables and vehicle schedules to accommodate the charging needs of autonomous electric buses. In particular, electric bus concepts with fewer charging stations and lower charging power benefit from adapting the timetable to passenger numbers. The results demonstrate that the specific requirements of electric buses should be considered when adapting networks and timetables in order to design a sustainable transport network. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The energy efficiency was determined of the energy storage buffer of the traction power unit of an electric bus taking into account the degradation of the lithium battery. A simulation model of the energy system of an electric bus was synthesized in MATLAB/Simulink, and the results of simulation of the energy system without a buffer storage and with a buffer of various capacities based on a lithium titanate battery were compared. The implementation of an energy storage buffer with 14.47% of the total capacity of the storage will increase the battery lifetime by 32.7%. [ABSTRACT FROM AUTHOR]

Rapid growth in the electrification of bus fleets, driven by substantial environmental benefits, is facing challenges such as range anxiety, prolonged charging durations, and reduced flexibility compared to combustion engine buses. This study first conducts a comprehensive bibliometric analysis of diverse publications to identify key research trends in electric buses (E-buses). It then offers a thorough comparison of charging technologies, encompassing topologies, power flow capabilities, costs, grid impacts, and efficiency, along with an examination of existing standards, norms, and challenges. With a classification of nearly 150 references, the study aims to illuminate the strengths and weaknesses of each charging technology, providing a solid background for selecting optimal topologies and strategies for specific applications. Emphasizing the importance of a nuanced trade-off between the quantity and type of chargers and E-bus battery capacity in each scenario, the research goes beyond technical considerations to explore potential future trends in the field. The information gathered in this review is a helpful guide for policymakers, industry experts, and researchers dealing with the complexities of E-bus charging infrastructure.

Current electric bus has become an important public transport for people in China, and its interior sound quality directly affects the driver's physical and mental health for a long working time and the comprehensive performance of the vehicle. Therefore, it is an inevitable and urgent trend to research electric bus interior sound quality. Aiming at the problem of subjective uncomfortable auditory sensation caused by different speeds, the noise signals near the driver's ears were collected under two constant speed conditions. On the basis of principle analysis of feed-forward adaptive control system, the primary and secondary path transfer functions were presented using Simulink module in MATLAB to construct three active noise control models for an electric bus based on least mean square (LMS), normalized LMS (NLMS) and filtered-x LMS (FxLMS). Numerical simulation results indicate that the established control models are convergent, and four acoustic parameters are effectively reduced after controls to achieve the effect of improving the sound quality. [ABSTRACT FROM AUTHOR]

The development of public transportation is considered a vital issue in reducing traffic as well as urban pollution. City buses play an important role in the city transportation system. In Iran, due to the high average age of city buses, it is necessary to replace the old buses with new ones, To replace the old buses, diesel and CNG, hybrid, and electric buses are proposed as the main alternatives. Global warming and the energy crisis are now considered as two potential serious threats for the world. Therefore, energy consumption and CO2 emissions are examined as two outstanding criteria for comparing candidate buses in this paper. To make an accurate comparison, the amount of energy consumption and CO2 emissions have been calculated based on the well-to-wheel approach. The electric bus well-to-wheel analysis has been done for both electricity generation mix and renewable generation. To perform more accurate calculations and simulations, as a case study, a real driving cycle has been constructed for Tehran. For this approach, a modified micro trip method as a novel solution is presented to synthesize the driving cycle. The results show that due to the high share of fossil power plants (about 92%) in Iran, the use of electric buses in the bus fleet may not have much effect on reducing energy and CO2 eq emissions. By using renewable power plants, the amount of well-to-wheel energy consumption and CO2 emissions decrease significantly (about 56% and 93%, respectively) compared to that for the generation mix. [ABSTRACT FROM AUTHOR]

This study explores the feasibility of integrating battery technology into electric buses, addressing the imperative to reduce carbon emissions within the transport sector. A comprehensive review and analysis of diverse literature sources establish the present and prospective landscape of battery electric buses within the public transportation domain. Existing battery technology and infrastructure constraints hinder the comprehensive deployment of electric buses across all routes currently served by internal combustion engine counterparts. However, forward-looking insights indicate a promising trajectory with the potential for substantial advancements in battery technology coupled with significant investments in charging infrastructure. Such developments hold promise for electric buses to fulfill a considerable portion of a nation's public transit requirements. Significant findings emphasize that electric buses showcase considerably lower emissions than fossil-fuel-driven counterparts, especially when operated with zero-carbon electricity sources, thereby significantly mitigating the perils of climate change. [ABSTRACT FROM AUTHOR]

Aiming at the consensus problem of slow convergence for the active noise control (ANC) model based on standard FxLMS algorithm that leads to performance degradation, this paper takes the error signal and its variation as the inputs of fuzzy logic control, and proposes an improved FxLMS algorithm by fuzzy control mechanism with two-input-two-output TSK fuzzy rules (TSK-FxLMS); In addition, the four-channel ANC models based on standard FxLMS and TSK-FxLMS are constructed using the noise signals from four measuring points inside an electric bus under uniform and variable speed conditions, respectively. Ultimately, the offline simulation and acoustic parameter calculation results indicate that the A-weighted sound pressure level (ASPL) and loudness of the two FxLMS models within the low and middle frequencies are significantly reduced, whereas the TSK-FxLMS model has faster convergence rate, higher average reduction percentage of ASPL and loudness, which proves that the established four-channel TSK-FxLMS model has a better sound quality improvement effect than the standard FxLMS. [ABSTRACT FROM AUTHOR]

Copyright of Notaire is the property of Universitas Airlangga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Electric buses have been vigorously promoted and implemented in major countries worldwide and have generated a huge demand for charging stations. Optimizing the daily charging experience of electric buses, adapting the daily operation scheduling, improving the utilization rate of charging stations, reducing the load on the power grid, and improving the operation efficiency of electric bus line networks require the reasonable layout of the charging stations. In this study, public transportation charging station layout and siting is the research object. We summarize the progress of analysis methods from the charging station and vehicle sides; introduce related research on the planning and layout of charging stations based on optimization models, including cost analysis and siting and layout for electric bus systems; summarize the data-driven station planning and siting research; and provide an overview of the current charging demand estimation, accuracy, and charging efficiency. Finally, we address the problems of the charging demand estimation accuracy, the mismatch between the charging station layouts for electric buses, and the charging demand on a long time scale. We suggest that research be conducted on data fusion for the temporal and spatial refinement of charging demand prediction in the context of the electrification of public transportation systems and the big data of telematics. [ABSTRACT FROM AUTHOR]

The study aimed to assess the performance of electric buses that are used in public transportation, and produced and sold in Türkiye. To achieve this, multi-criteria decision-making techniques, the Entropy and WASPAS methods, were employed. The Entropy method was used to calculate the weights of the criteria, and the WASPAS method was used to rank the performance of the electric buses. During the analysis, the most important performance criteria were identified to be maximum torque and battery capacity, while the lowest performance criterion was found to be maximum speed. According to the results, the Otokar Kent Electra was the highest performing electric bus in terms of entropy weights, and the Temsa MD9 ElectriCITY was the best performer according to equal weights. On the other hand, the Otokar Doruk Electra was found to be the worst performing bus in both weight calculations. [ABSTRACT FROM AUTHOR]

An essential part of electrifying bus networks is deciding on the appropriate charging strategy among the many available alternatives, such as opportunistic (rapid) charging techniques and overnight (slow) charging. The broad usage of electric buses in public transportation networks and the increasing demand for environmentally friendly transportation options have elevated the significance of this step. This research establishes a multi-criteria decision-making (MCDM) fusion method for choosing the optimal electric bus charging strategy by considering various variables, including operational, quality-of-service, social, environmental, and economic factors. To determine what matters most for making decisions in this field, we surveyed electric bus specialists and reviewed the literature extensively. We used the TOPSIS method as an MCDM fusion method to combine the criteria and alternatives. We compute the weights of criteria by the average method. Then, the TOPSIS fusion method selects and ranks the alternatives. We collected the 20 criteria and five alternatives in this study. We show that overnight is the best charging strategy in the electric bus system. We performed a sensitivity analysis to show the different cases in criteria weights, then ranked the alternatives under different weights to establish the stability of the results. [ABSTRACT FROM AUTHOR]

A cleaner transportation sector requires the implementation of a variety of measures, such as the use of electric vehicles. Electric mobility has seen increasing use in public transportation, even though it still faces significant challenges. Electric bus fleets require high‐performance batteries to minimize the cost and weight of the buses. This paper investigates the energy consumption of an electric bus in urban and interurban transit using two methods: forward‐facing and backward‐facing approaches. The obtained findings have shown that the energy consumption of a bus depends on the road and its characteristics, ranging between 0.98 and 1.39 kWh/km. Furthermore, a regenerative braking analysis has been performed, and it has been found that this factor plays a significant role in reducing energy consumption by 21%. Finally, a life cycle assessment and an environmental analysis have been conducted. The obtained results have shown that the total cost of ownership of the buses in this project will be around 1.76 $/km. The use of electric buses could eliminate the greenhouse gas emissions produced by public transportation in the investigated province. [ABSTRACT FROM AUTHOR]

Steering systems with an electromechanical amplifier (EMA) are a modern design solution compared to hydraulic and electro-hydraulic steering systems. Hydraulic steering amplifiers are used in the steering drives of modern trolleybuses and electric buses. If an electric motor powered from the power grid is used to drive the hydraulic pump in trolleybuses, then in electric buses, the source of electrical power is rechargeable batteries. Energy consumption to ensure the operation of the hydraulic power steering reduces the mileage of the electric bus between charging the batteries. Therefore, conducting research and substantiating the possibility of using EMA in electric buses is relevant and has important practical significance. Considering the design features of the electromechanical steering amplifier and the design of the steering axle of the Electron 19101 electric bus, a dynamic model of the drive for turning the controlled wheels of the electric bus was built on the spot. Based on the dynamic model of the drive for turning the controlled wheels of an electric bus with an electromechanical steering amplifier, a mathematical model of the drive and a stimulation model were developed in the MathLab Simulink environment for the study of oscillatory processes in the drive links when the wheels turn on a horizontal plane. The nature of the change of elastic torques in the links of the steering control drive of an electric bus with an electromechanical steering amplifier, the frequency of rotation of the rotor of the electric motor, the current strength in the windings of the rotor and stator of the electric motor, the angle of rotation of the steered wheels as a function of time was studied. It was found that the change in the moment of resistance to the rotation of the steered wheels increases smoothly, and the load on the drive links of the electromechanical power steering depends on the total gear ratio of the drive and its distribution between the gearbox and the steering rack. A decrease in the total transmission ratio of the drive leads to an increase in the speed of rotation of the driven wheels and an increase in elastic moments in the drive links. Transient processes in the electric part of the drive correspond to the characteristics of such electric motors in terms of the nature of the change and do not exceed the permissible values in terms of magnitude. It was established that the power characteristics of the electromechanical steering amplifier with the selected parameters and the electric motor can ensure the control of the wheels of the electric bus following the established requirements.

From Shenzhen to Philadelphia and Izmir to Delhi, public bus operators around the world are increasingly using electric buses. Their choice is not only justified by support for the green transition or the reduction of background traffic noise: economic calculations regarding the entire life cycle cost also support the need for technological change. The article points out that the inclusion of electric vehicles in the service requires a complex approach and can bring a revolutionary change in our operation. The transport company can become a community service provider that occasionally provides balancing energy for energy supply systems (Vehicle-to-grid, i.e. V2G) or provides a virtual power plant service to the operators of photovoltaic power plants. The bus company can become a producer with independent network power generation capacity, which can sell the excess capacity it produces on the market to the owners of electric cars. The article presents the operating model that connects the transport, energy and battery industrial systems. Last but not least, batteries that have lost their capacity but are still usable can be resold for “storage” or other secondary purposes, even as uninterruptible power supplies. In order to implement the operation according to the model, Volánbusz Zrt. started building its data-driven ecosystem, which enables cost-optimized operation based on the data of an ever-growing electric bus fleet and the solutions of Industry 4.0 technology.

This study shows the concept of an innovative road and rail vehicle as a new form of public transport. Our literature review shows that the idea of a “smart city” contains not only new tools but also vehicles or infrastructure. The new vehicle is proposed based on the observed development of urban public transport means and other novel solutions. A slight innovation proposed here could allow the use of typical and operated tram routes for modified buses. A new type of vehicle could use both the existing tram routes and newly constructed sections with no tracks. It is assumed that new vehicles would drive with trams on the same, shared tracks. All of the conditions should reduce the costs of developing public transport networks in many cities where tram networks already exist. This paper contains a description of the idea and a potential case study location. The implementation conditions are outlined in the Discussion section. The title’s question is also considered there: “Should smart cities introduce a new form of public transport vehicles?” In addition, the potential benefits as well as threats are presented. Conclusions define the next steps for the research. So, this paper is an introduction to the wider research. It will popularize the idea of a new vehicle and could motivate the industry to construct a prototype. At this stage, no models or detailed calculations were conducted.

Auto-oscillations may occur in moving vehicles in the area where the tire interacts with the support base. The parameters of such oscillations depend on the sliding velocity in the contact patch. As they negatively affect the processes occurring in the electric drive and the mechanical transmission, reducing their energy efficiency, such processes can cause failures in various elements. This paper aims to conduct a theoretical study into the peculiarities of oscillatory processes in the nonlinear system and an experimental study of the auto-oscillation modes of an individual traction drive. It presents the theoretical basis used to analyze the peculiarities of oscillation processes, including their onset and course, the results of simulation mathematical modeling and the experimental studies into the oscillation phenomena in the movement of the vehicle towards the supporting base. The practical value of this study lies in the possibility to use the results in the development of algorithms for the exclusion of auto-oscillation phenomena in the development of vehicle control systems, as well as to use the auto-oscillation processes onset and course analysis methodology to design the electric drive of the driving wheels. [ABSTRACT FROM AUTHOR]

The research on vehicle sound quality is an emerging and highly promising field. This paper proposes a solution for sound quality improvement based on sensitivity analysis of psycho-acoustic parameters, in which the main acoustic techniques involved include noise signal acquisition, subjective and objective evaluations, sound quality modelling and prediction, parameter sensitivity and spectral analysis, and fuzzy comprehensive evaluation. In addition, taking 64 noise samples of electric bus as an application case, the presented sound quality analysis steps are implemented successively, and the obtained test results of improving the whole vehicle sound quality verify the feasibility and effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The electric bus is an extremely important part of urban public transportation and has a huge impact on the ecosystem. However, the battery capacity is still a tough problem, and electric buses often face a booming demand for charging during peak periods. This paper focuses on the problem of electric bus battery swapping station (BSS) location. Based on the traffic flow assignment theory, this paper proposes a hybrid traffic assignment method based on GA and Frank–Wolfe algorithm, which has proved to be closer to the global optimum than the traditional method. This paper proposes a BSS selection model considering service quality as an evaluating indicator and a simulation is made based on a virtual road network. Compared with the traditional method, the result from the hybrid method is more suitable for electric buses when considering the situation at peak hours. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Transit electrification has emerged as an unstoppable force, driven by the considerable environmental benefits it offers. However, the adoption of battery electric buses is still impeded by their limited flexibility, a constraint that necessitates adjustments to current bus scheduling plans. Consequently, this study aspires to offer a thorough review of articles focused on battery electric bus scheduling. Moreover, we provide a comprehensive review of 42 papers on electric bus scheduling and related studies, with a focus on the most recent developments and trends in this research domain. Despite this extensive review, our findings reveal a paucity of research that takes into account the robustness of electric bus scheduling. Furthermore, we highlight the critical areas of considering diverse charging modes in electric bus scheduling and integrated planning of electric buses, which have not been adequately explored but hold the potential to greatly boost the effectiveness of electric bus systems. Through this synthesis, we hope that readers could acquire a thorough comprehension of the studies in this field and be motivated to address the identified research gaps, thus propelling the progress of transit electrification.

This paper presents the initial steps taken in analysing the benefits of connected autonomous vehicles (CAVs), especially Modular Autonomous Vehicles (MAVs), in search of sustainable solutions for reducing energy consumption per passenger in air transport. For this particular case, a Mobility-as-a-Service (MaaS) solution is proposed, correlating airside transport with landside transport, as an urban mobility alternative. To better understand the benefits of the proposal, this paper studies the impact on energy consumption conceptual differences between a conventional public transport fleet using Battery Electric Buses (BEBs) and an MAV fleet. Simulations for simple public transport tasks are performed to highlight the advantages of the modular vehicle concept, in which routes are assigned dynamically based on the requested passenger carrying capacity and travel distance, aiming to optimize the efficiency of the entire system. With a proven reduction in energy consumption due to better use of available passenger capacity and reduced travel times in which the vehicle is driving with a number of passengers less than half of its capacity, the concept can be addressed further in developing a predictive system that processes public transport data and delivers an optimized schedule for the entire fleet. The main goal being to improve overall operational efficiency and total cost of ownership, the second part of the paper studies the impact of weight distribution on efficiency parameters such as energy consumption, range, and overall performance of an electric bus. The impact on dynamic elements such as acceleration, braking, and cornering performance is analyzed, to assess the viability and safety of all types of electric bus operations.

AbstractSustainability orientation is increasingly becoming a focus in companies’ top management. In addition to social, environmental, and economic impacts, a sustainability-based strategy can be a source of excellence for the company in the future. Using the Network for Business Sustainability model as a lens, this study examines how companies are involved in the challenge of forming an ecosystem that is still not mature when developing the electric bus business. It includes how companies change their business orientation, identify and collaborate with stakeholders, and encourage the acceleration of regulatory existence. The company and new business’ top management were interviewed to understand the company’s orientation as part of a group of companies. A total of six interviews were conducted for this purpose. The factor of reconceptualizing the business’s purpose and influencing the ecosystem through strategy, linkages, and learning was explored as the determining factor. Flexibility in business models, influential partners in global supply chains, and good relations with government agencies were also crucial factors. This study contributes to research on sustainability-oriented innovation, and corporate entrepreneurship. This study provides a comprehensive and general framework for sustainability-oriented innovation, highlighting the guiding principles of any ecosystem approach to innovation management.

Considering the proposed strict new constraints of public authorities, decarbonization has become a key trend in recent years. Although several countries have started the process of decarbonization through the introduction of electric vehicles in their public services, for many countries, especially developing countries, transportation is still a hard sector to decarbonize. The presence of obsolete and polluting vehicles discourages citizens from using public transport and thus incentivizes the use of private vehicles, which create traffic congestion and increase emissions. Based on these considerations, this paper aimed to implement a simulation for a public service in Eritrea, evaluating whether it is possible to take a long trip using an electric minibus. A case study is implemented highlighting the barriers of electrifying transportation in this area, producing results on fuel consumption and service reliability. In the case study, four scenarios are presented to estimate the service. The scenarios evaluate the possibility to perform from three to five recharges. Fewer charges mean longer charging time, leading to a 2 h charging phase in Scenario 1, while recharging more than twice along the route will lead to shorter 30 min charges, as in Scenario 3. The case study also highlights the relevance of the slope in electric vehicle performance, as reported for the case of Asmara–Massawa travel ( E c o n s = 6.688 kWh). Finally, an environmentally sustainable solution, such as a 92 kWh/day photovoltaic plant, is proposed to power the service. [ABSTRACT FROM AUTHOR]

Electric buses (EBs) are gaining popularity worldwide as a more sustainable and eco-friendly alternative to diesel buses (DBs). Electricity-saving driving plays a crucial role in minimizing an EB's energy consumption, subsequently leading to an extended driving range. This study proposes a machine learning–based framework for identifying electricity-saving EB driving behaviors during various driving stages, including running on road segments, entering bus stops/intersections, and exiting bus stops/intersections. The proposed random forest (RF) model effectively evaluates the energy consumption level using EB drivers' historical driving data under different scenarios. Specifically, the electricity consumption factor (ECF), as the evaluation index, is divided into three categories to determine the implicit relationship between driving behavior and energy consumption. The results indicate that the classification accuracy of RF models surpasses 90%, which highlights the effectiveness in accurately identifying energy-efficient EB driving behaviors. In addition, the Shapley additive explanations (SHAP) and partial dependency plots (PDPs) are utilized to visualize and interpret the results of RF models. A speed interval of 30–40 km/h is identified as the most energy-efficient range for EB running on a road segment. Findings from this study can be applied to targeted optimization of electricity-saving driving strategies in different driving scenarios to improve the overall efficiency and sustainability of the transportation system. [ABSTRACT FROM AUTHOR]

The orography of the terrain is a key factor for the electrification of vehicles, especially regarding public transport and electric buses. This work deals with the analysis of the use of mobile laser scanning, both terrestrial and aerial, for the evaluation of the orography of urban areas. First, the minimum point density required is evaluated to estimate the slope. The results show that point densities of 1 point/m2, measured with aerial laser scanning, are adequate for the task. Based on this, the design of a route for public transport is presented including the requirements concerning key transit points, maximum slope, and others. Based on the proposed route design, the transformation to an electrified route is analyzed from an economic and environmental point of view. The results show that the implementation of electric buses vs. diesel buses in cities with steep slopes (up to 7%) reduces greenhouse gas emissions (32.59%) as well as economic costs (18.10%). [ABSTRACT FROM AUTHOR]

Modern manufacturers of electric vehicles everywhere introduce regenerative braking control using the accelerator pedal. One of the difficulties in implementing regenerative braking is the interaction of the service braking system and the auxiliary one using a traction motor. In this regard, the concept of regenerative braking control with one pedal – the accelerator pedal. Currently, a similar concept is presented on many modern electric cars, such as the Tesla Model S, Tesla Model X, Hyundai Kona. The aim of study is the creation and subsequent debugging of an algorithm for controlling regenerative braking using the accelerator pedal in relation to urban public electric transport. The developed algorithm is implemented in the MATLAB/Simulink simulation environment. Using the available blocks and subsystems, a mathematical model of the movement of an electric vehicle has been compiled. A mathematical model of the movement of electric vehicle has been developed that allows testing and debugging of the algorithms being developed. Simulation methods have confirmed the operability of the proposed method of regenerative braking control by the accelerator pedal. The scientific novelty of the research lies in the synthesis of an algorithm for controlling regenerative braking in relation to the operation of public electric transport in an urban environment with frequent stops, traffic on roads with slopes and starting to climb. The practical utility (value) of this research lies in the possibility of using the proposed control algorithm in urban public electric transport with on-board energy storage, for example, in electric buses.

Despite rapid advances in urban transit electrification, the progress of systematic planning and management of the electric bus (EB) fleet is falling behind. In this research, the fundamental issues affecting the nascent EB system are first reviewed, including charging station deployment, battery sizing, bus scheduling, and life-cycle analysis. At present, EB systems are planned and operated in a sequential manner, with bus scheduling occurring after the bus fleet and infrastructure have been deployed, resulting in low resource utilization or waste. We propose a mixed-integer programming model to consolidate charging station deployment and bus fleet management with the lowest possible life-cycle costs (LCCs), consisting of ownership, operation, maintenance, and emissions expenses, thereby narrowing the gap between optimal planning and operations. A tailored branch-and-price approach is further introduced to reduce the computational effort required for finding optimal solutions. Analytical results of a real-world case show that, compared with the current bus operational strategies and charging station layout, the LCC of one bus line can be decreased significantly by 30.4%. The proposed research not only performs life-cycle analysis but also provides transport authorities and operators with reliable charger deployment and bus schedules for single- and multi-line services, both of which are critical requirements for decision support in future transit systems with high electrification penetration, helping to accelerate the transition to sustainable mobility.

Electric vehicles (EVs) have positive impacts on reducing oil dependence and exhaust emissions. However, the range problem of EVs is a factor that raises concerns for individual users and bus operators. For this reason, studies on increasing the range of the electric buses in public transportation is extremely important to ensure optimum operation. In this study, a novel energy consumption model, MTECM (Malatya Trolleybus Energy Consumption Model), is developed using the multi-parameter linear regression method. The real-time big data was collected on the field of Trolleybus vehicles, which have been operated for 8 years in Malatya / Türkiye. Firstly, by calculating the correlation of the parameters affecting this model, the parameters that are suitable for the purpose of our study are determined and regression analysis is performed on the original Trolleybus dataset. A total of 75.497.472 data are analyzed for this model. The RMSE (Root Mean Square Error) of MTECM is calculated as 0.29996. The trained model is applied to the 10 busiest routes in Malatya in terms of passenger density. The RMSE value on these routes is calculated between 0.30299 and 0.31421. Based on the results, with lower error rates, the proposed novel model is more efficient than other studies in the literature. In addition, energy consumption can be calculated for any route planned to establish an electric bus operation with MTECM. Therefore, according to the consumption obtained, the correct determination and selection of parameters that significantly affect the investment cost such as route, vehicle length, engine power, and battery capacity can be made.

The progressive conversion of conventional bus fleets into full-electric fleets have gained focus in recent years, instilled by awareness about the environment and significant trends of urbanization. Public transport operators in major cities worldwide have put efforts into fulfilling this change. However, an efficient electrification process is still a challenge for most operators. This paper aims to propose an E-Bus vehicle model that estimates the actual energy consumption. The proposed model is implemented on the case study of a real bus line for Local Public Transport (LPT) and considers all technical characteristics of the vehicle. Real-time input data are represented by real driving cycles of the actual bus fleet and slope profile of the line. Real-time input data allow to establish directly the influence on the energy consumed during real operations. As simulation results, the global energy consumption and battery State of Charge (SOC) are then computed for the whole daily service operations. The simulation results are validated with the real data available and several scenarios are then considered within the simulations. Based on the results obtained, further improvements are proposed and discussed aiming to optimize the utilization of bus fleet, regarding both vehicles scheduling and new charging solutions.

The radical increase in the popularity of electric vehicles (EVs) has in turn increased the number of associated problems. Long waiting times at charging stations are a major barrier to the widespread adoption of EVs. Therefore, battery swapping stations (BSSs) are an efficient solution that considers short waiting times and healthy recharging cycles for battery systems. Moreover, swapping stations have emerged as a great opportunity not only for EVs, but also for power systems, with regulation services that can be provided to the grid particularly for small networks, such as microgrid (MG) systems. In this study, the optimum location and size that maximize the revenue of a swap station in an MG system are investigated. To the best of our knowledge, this study is first to solve the placing and sizing problem in the MG from the perspective of a BSS. The results indicate that bus 23 is the BSS’s optimal location and is crucial for maximizing revenue and addressing issues like the provision of ancillary services in microgrid system. Finally, the swap demand profile of the station serving electric bus public transportation system was obtained using an analytical model based on public transportation data collected in Berlin, Germany.

The use of electric buses has a great effect on reducing traffic and air pollution. The purpose of this article was to examine the challenges facing the country to produce and benefit from this product and solutions to solve these challenges. In this research, data was collected through documentary studies and in-depth semi-guided interviews and analyzed through qualitative content analysis. The target community was the experts of electric bus manufacturing companies and related institutions. The number of 72 propositions were categorized into 10 sub-categories and finally 6 main categories, the main categories of which were empowerment, cost, technological cooperation and cultural alignment. Then, action was taken to form a focus group and the extracted challenges and solutions were validated and finalized. Among the important challenges are the dependence on foreign electric propulsion, the unaffordability of bus operations, the high price of electric buses, the infrastructure for conducting some specialized tests to obtain the standard, and the lack of culture for using this new product. Some important solutions include the domestication of electric motors and accessories with government support from domestic companies, the creation of a joint supply chain for bus manufacturing companies, the preparation of a business model based on public-private partnership, and the implementation of Article 12 of the law on removing barriers to production, cultural measures and promotion based on new product and technology requirements, design of night charging system for bus batteries and design of electric base buses

This study explores the feasibility of integrating battery technology into electric buses, addressing the imperative to reduce carbon emissions within the transport sector. A comprehensive review and analysis of diverse literature sources establish the present and prospective landscape of battery electric buses within the public transportation domain. Existing battery technology and infrastructure constraints hinder the comprehensive deployment of electric buses across all routes currently served by internal combustion engine counterparts. However, forward-looking insights indicate a promising trajectory with the potential for substantial advancements in battery technology coupled with significant investments in charging infrastructure. Such developments hold promise for electric buses to fulfill a considerable portion of a nation’s public transit requirements. Significant findings emphasize that electric buses showcase considerably lower emissions than fossil-fuel-driven counterparts, especially when operated with zero-carbon electricity sources, thereby significantly mitigating the perils of climate change.