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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]

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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]

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.

Battery states are very important for the safe and reliable use of new energy vehicles. The estimation of power battery states has become a research hotspot in the development of electric buses and transportation safety management. This paper summarizes the basic workflow of battery states estimation tasks, compares, and analyzes the advantages and disadvantages of three types of data sources for battery states estimation, summarizes the characteristics and research progress of the three main models used for estimating power battery states such as machine learning models, deep learning models, and hybrid models, and prospects the development trend of estimation methods. It can be concluded that there are many data sources used for battery states estimation, and the onboard sensor data under natural driving conditions has the characteristics of objectivity and authenticity, making it the main data source for accurate power battery states estimation; Artificial neural network promotes the rapid development of deep learning methods, and deep learning models are increasingly applied in power battery states estimation, demonstrating advantages in accuracy and robustness; Hybrid models estimate the states of power batteries more accurately and reliably by comprehensively utilizing the characteristics of different types of models, which is an important development trend of battery states estimation methods. Higher accuracy, real-time performance, and robustness are the development goals of power battery states estimation methods. [ABSTRACT FROM AUTHOR]

Battery electric vehicles (BEVs) are one of the most promising new energy models for industrialization and marketization at this stage, which is an important way to solve the current urban haze air pollution, high fuel cost and sustainable development of the automobile industry. This paper takes pure electric buses as the research object and relies on the operation information management platform of new energy buses in Nantong city to propose an electric bus cycle construction method based on the mixed interpolation method to process sparse data. Three different interpolation methods, linear interpolation, step interpolation and mixed interpolation, were used to preprocess the collected data. The principal component analysis method and K-means clustering algorithm were used to reduce and classify the eigen parameter matrix. According to the clustering results, different categories of moving section and idle section libraries were established. According to the length of time and the correlation among various types, several moving sections and idle sections were selected to form a representative driving cycle of Nantong city buses. The results show that the mixed interpolation method, based on linear interpolation and cubic spline interpolation, has a good processing effect. The average relative error between the synthesized working conditions and the measured data are 15.71%, and the relative error of the seven characteristic parameters is less than 10%, which meets the development requirements. In addition, the comparison and analysis with the characteristic parameters of the world typical cycle conditions (NEDC, WLTC) show that the constructed cycle conditions of Nantong city are reasonable and reliable to represent the driving conditions of pure electric buses in Nantong city, which can provide a reference for the optimization of the bus energy control strategy. [ABSTRACT FROM AUTHOR]

Among the activities that cities are taking to reduce the emissions of harmful substances emitted by conventional engine-powered vehicles is replacing the fleet with electric vehicles in public transport that can operate in urban areas. Fleet conversion is a process in which one of the decisions that must be made is the choice of lines that should be served in the first place by electric buses. Due to the specificity of the battery charging process, the routes of lines serviced by electric vehicles should run through sections that are as little exposed to disruptions as possible, which can adversely affect the travel time of these sections. The main goal of the article was to develop a method that supports the search for bus lines that are characterized by the highest level of reliability and punctuality and therefore also by the stability of the travel time between stops. The proposed method makes it possible to indicate critical interstop sections that have the greatest impact on the sensitivity of the line to disturbances. It was assumed that the more critical sections of the route, the greater the risk of bus delay, which may be disadvantageous in the case of electric vehicles due to the need to reach the battery charging station in time. The method was implemented on the example of selected lines in the Upper Silesian region (Poland) for data covering four years (2016–2019). The proposed approach allowed for the development of the ranking of lines, corresponding to the order in which the conventional fleet should be changed to electric. [ABSTRACT FROM AUTHOR]

This paper presents the problem of public transport planning in terms of the optimal use of the available fleet of vehicles and reductions in operational costs and environmental impact. The research takes into account the large fleet of vehicles of various types that are typically found in large cities, including the increasingly widely used electric buses, many depots, and numerous limitations of urban public transport. The mathematical multi-criteria mathematical model formulated in this work considers many important criteria, including technical, economic, and environmental criteria. The preliminary results of the Mixed Integer Linear Programming solver for the proposed model on both theoretical data and real data from urban public transport show the possibility of the practical application of this solver to the transport problems of medium-sized cities with up to two depots, a heterogeneous fleet of vehicles, and up to about 1500 daily timetable trips. Further research directions have been formulated with regard to larger transport systems and new dedicated heuristic algorithms. [ABSTRACT FROM AUTHOR]

Considering the battery-failure-induced catastrophic events reported frequently, the early fault warning of batteries is essential to the safety of electric vehicles (EVs). Motivated by this, a novel data-driven method for early-stage battery-fault warning is proposed in this paper by the fusion of the short-text mining and the grey correlation. In particular, the short-text mining approach is exploited to identify the fault information recorded in the maintenance and service documents and further to analyze the categories of battery faults in EVs statistically. The grey correlation algorithm is employed to build the relevance between the vehicle states and typical battery faults, which contributes to extracting the key features of corresponding failures. A key fault-prediction model of electric buses based on big data is then established on the key feature variables. Different selections of kernel functions and hyperparameters are scrutinized to optimize the performance of warning. The proposed method is validated with real-world data acquired from electric buses in operation. Results suggest that the constructed prediction model can effectively predict the faults and carry out the desired early fault warning. [ABSTRACT FROM AUTHOR]

Battery-Electric Buses (BEBs) are expensive compared to diesel buses and the biggest problem in the battery operated electric vehicle is always the range. The electric consumption is very high during extreme cold and extreme hot climates. Around the world, the developing economies are deploying BEBs on a large scale with the idea of sustainable green mobility. In this context it is required to reduce the energy consumption required for BEBs during extreme cold and hot weather. For this purpose, it is required to implement energy conservation procedures to prevent the heat entry and heat loss in the HVAC system of the BEBs. For simulating the transient effect of external solar load on the air-conditioning system of the vehicle, commercial Computational Fluid Dynamics software is used. In this project, simulation of energy consumption in a BEB is carried out using ANSYS FLUENT software. An energy conservation parametric study with different types of glass and wall materials has been carried out. There is a reduction in energy consumption of 20.52 % when using hard-coated solar glass and 26.07 % reduction when polyethylene insulation is used. [ABSTRACT FROM AUTHOR]

The technological development of buses among the new alternative concepts is evaluated in this paper. Bus transportation is an important system in the public transportation, which is cheap, flexible and, in many cases, in terms of capacity and speed. But increasing car traffic in the city centre and increasing the emission such as Carbon Dioxide (CO2) in the air are some of the dangerous problems for urban life. Therefore, it is needed the public transportation to stop increasing car traffic and needed the cleaner technology for air and environmental quality. Electric Buses (EBs) can play an important role for resident's life quality with improving the urban air quality. However, planners and managers have difficulty in decision-making due to diversified EBs together with the developing technology. Multi-criteria decision-making (MCDM) methods that are analytic decision processes, prepare a good solution for this problem. In this study, 5 EBs are assessed under the special criteria with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Optimization on the basis of the Ratio Analysis (MOORA) methods. These 2 methods are MCDM methods that are used to aim of ranking of alternatives in the complex decision problem. These methods are applied to select the best EB under the 6 criteria. Finally, E5-Bus is selected as the best option that rank of the 1st at all the 3 methods. Besides, MOORA and TOPSIS methods were compared. The results are shown alongside the best bus selection for public transportation that MOORA method is also a strong tool for solving vehicle selection problems in transportation. The proposed model has been validated using existing real applications. The proposed multi-criteria analysis can be used for advising decision-makers in their decision-making process for Electric Vehicles (EVs) in the area of clean transportation. [ABSTRACT FROM AUTHOR]

The uneven distribution of public charging infrastructure poses significant challenges for private electric vehicles (EVs). Many Chinese city bus depots have abundant chargers for electric buses (EBs), often unused during daytime operations. This study proposes an innovative mechanism to utilize bus depot chargers for private EVs, prioritizing the charging demands of EBs. Uncertainty in EB and EV charging demand, EV arrival time are considered. The objective is to maximize bus company revenue through a two-stage stochastic model. Practical applicability is demonstrated through a real-world bus depot case in Shanghai with 127 EBs and 376 private EVs. The results show that allocating 58% of the charging power and 30% of the chargers to the public from 10:00 to 24:00 meets 97.54% of the private EVs' charging demand. The bus operator faced a charging cost of 10,747 CNY, while now it expects a profit of 1733 CNY with the project running. [ABSTRACT FROM AUTHOR]

Most of the transportation in Indonesia still uses oil as their fuel, thus Indonesia is currently facing one of the Energy Security issues which are oil availability. Nowadays, Indonesia doesn’t have sufficient oil production, consequently, Indonesia must import oil to meet its daily demand. Furthermore, Indonesia also dealing with an environmental issue from the transportation sector, which is air pollution. Air pollution is one of the non-military threats that threaten the lives of many people in Indonesia. The non-military defense is an effort made to ward off non-military threats. One of the ways to fight air pollution is to reduce the use of oil in the transportation sector. Currently, the development of innovative technology in the field of transportation is increasingly oriented to electric vehicles (EV). This is due to EVs that do not produce gas emissions, increase energy efficiency, and reduce oil consumption. In August 2018, a one-week trial runs on an electric bus at Soekarno-Hatta Airport conducted to looking for responses from passengers when boarding an electric bus as an airport shuttle bus. Therefore, this study will be further determining the strategies of electric bus implementation at Soekarno-Hatta Airport. The method used is a qualitative method using a case study approach and Strength-Weakness-Opportunity-Threat Analysis with Quantitative Strategic Programming Matrix. This study concludes that the strategy that has to be implemented first for electric bus implementation in Soekarno-Hatta Airport is Strength-Opportunity 3 (SO3) strategy, which is collaborating with Bus Companies to become a pioneer in electric bus implementation in Indonesia’s Airport and improve the Eco Airports Status.

The increasing number of electric vehicles induces a new relationship between the electric vehicles, transportation network and electric network. The deployment of the charging infrastructure is a prerequisite of the widespread of electric vehicles. Furthermore, the charging process and energy management have a significant influence on the operation of both the transportation and electric networks. Therefore, we have elaborated novel operational methods that support the deployment of charging infrastructure for electric cars and buses operating in public bus service, and the energy management. Weighted sum-models were developed to assess candidate sites for public charging stations. The mathematical model of public bus services was elaborated that supports the optimization of static charging infrastructure at bus stops and terminals without schedule adjustments. The flexibility and predictability of charging sessions were identified as the main differences between charging infrastructure deployment for cars and buses. Furthermore, the flows of energy, information and value have been revealed among the components of charging with a focus on commercial locations, which is the basis of energy flow optimization on the smart grid. [ABSTRACT FROM AUTHOR]

As the progress of electrification for the public transportation sector is accelerated, it becomes more and more important to integrated planning charging infrastructure for public transportation, while emerging technologies such as distributed renewable generation and energy storage system should be accounted. Here, an integrated resource planning framework is proposed where both planning investment cost and operational cost are considered. An aggregation strategy is also proposed to optimise the charging decisions for electric bus on different routes, which could effectively improve the planning and operation efficiency. To address the uncertainties involved in this process, a scenario‐based chance‐constrained programming approach is adopted. A numerical case study is also included to demonstrate the effectiveness of this proposed resource planning model. [ABSTRACT FROM AUTHOR]

Highlights • A novel efficient braking energy recovery system for electric bus is proposed. • The models of blend braking and eddy-current heating are established. • The blend braking control strategy of braking & heating system are established. • The performance of system is tested by the simulation platform and vehicle tests. • The proposed system can offer higher regeneration efficiency. Abstract This paper proposes the eddy-current braking & heating system, which is a novel efficient braking energy recovery system for electric bus. The system is designed to solve two problems: one is the low recovery efficiency of regenerative braking energy, another is the driving range dramatic decline of electric bus when heating the bus cabin in winter. The system converts braking energy into heating energy directly by the principle of eddy-current braking and heating. It greatly improves the recovery efficiency of braking energy. The layout scheme of system is designed by considering the vehicle drive structure. The mathematical models of friction braking, regenerative braking, eddy-current braking & heating are established respectively. A blend braking control strategy considering braking strength, State of Charge, and supply air temperature is proposed. The energy-saving evaluation parameters of the system are presented. A simulation platform is built in the MATLAB/Simulink environment. The simulation and vehicle tests show that the calculated temperature and driving range agree well with the measured results and the models are validated. Compared with Positive Temperature Coefficient heating, the recovery efficiency of braking energy of the system increases from 23.8% to 65.3%, and the improvement rate of driving range reaches 81.4%. The system can satisfy the braking requirement of electric vehicle by blend braking control strategy. The system can effectively increase energy recovery of the regenerative braking. It can solve the reduced driving range problem of electric buses while heating in winter. [ABSTRACT FROM AUTHOR]

Abstract The uncertainty of operating conditions such as weather and payload cause variations in the energy demand of electric city buses. Uncertain variation in energy demand is a challenge in the design of charging systems and on-board energy storages. To predict the energy demand, a computationally efficient model is required for real-time applications. We present a novel approach to predict energy demand variation with a wide range of uncertain factors. A factor identification is carried out to recognize the range of variation in the operating conditions. A computationally efficient surrogate model is generated based on a previously developed numerical simulation model. The surrogate model is shown to be 10 000 times faster than the numerical model. The surrogate model output corresponds with the numerical model with less than 1% error. The energy demand of the surrogate model varied from 0.43 to 2.30 kWh/km, which is realistic in comparison to previous studies. Successful sensitivity analysis of the surrogate model revealed the most crucial factors. Uncertainty in temperature, rolling resistance and payload contributed most to the variation in energy demand. Variation in these factors should be taken into account when predicting energy consumption and while planning schedules for a bus network. Highlights • Novel surrogate modeling approach for energy demand prediction. • Uncertainty margins of 14 noise factors are identified. • Performing a sensitivity analysis of electric bus energy demand and regeneration. • Computational efficiency is improved significantly with high prediction accuracy. • Consumption depends mainly on the ambient temperature, rolling resistance and mass. [ABSTRACT FROM AUTHOR]

Abstract Electrification of public bus transport services is currently being explored in various demonstration projects around the world. The objective of this paper is to (i) gather insights from electric bus demonstration projects with a focus on charging technologies (conductive, inductive) and strategies (slow, fast); and explore the role these factors may play as upscaling of electric bus deployment is considered. The focus is on the Nordic region. A survey with stakeholders involved with electric bus demonstration projects is performed for understanding the benefits and drawbacks of each solution, and identifying the main themes emerging from project implementation and upscaling. Advantages of the conductive charging include the maturity of the technology and its higher maximum charging power compared to currently available inductive alternatives. On the other hand, inductive technology entails other benefits, such as the lack of moving parts which could reduce the maintenance costs for infrastructure, as well as minimal visibility of the equipment. The main issues likely to impact the upscaling of electric bus use are related to the maturity, cost-effectiveness, compatibility, and charging efficiency of the available technologies. [ABSTRACT FROM AUTHOR]

The pressure to the environment protection within the concept of sustainable development and many national initiatives is constantly rising. This is also reflected in the field of transport. Currently, the issue of electro mobility is often discussed. Acquisition of eco-friendly cars or electric buses has the potential for improving the environment and greenhouse gas production situation. However, the acquisition cost and the operating costs of the electric vehicles generate a certain cost structure that is different compared to the diesel vehicles. The amount of state aid as well as possibility of such aid for purchasing electric bus still remains uncertain. The aim of this paper is to highlight the possibility of using life cycle cost analysis to quantify the support for the acquisition of electric buses against diesel buses with respect to the different structure of costs and the time value of money. This difference was set at the level Difference set to 22%, which is a required level for the co-financing from the government, self-governance or EU structural funds. In monetary terms, that means the amount of 132 000 € for an electric bus. [ABSTRACT FROM AUTHOR]

Highlights • Monte Carlo, RBF-NN and Markov-chain are employed for the future passenger amount forecast on a bus. • A model predictive control based air-conditioning system energy management strategy is established for electric buses. • A comprehensive comparison is performed in terms of cabin temperature, energy consumption and computation. Abstract Air-conditioners (AC) usually consume the most electricity among all of the auxiliary components in an electric bus, over 30% of the battery power at maximum. On-board passengers carried by the electric bus are important but random heat sources, which are obsessional disturbances for the cabin temperature control and energy management of the AC system. This paper aims to improve the AC energy efficiency via passenger amount variation analysis and forecast in a model predictive control (MPC) framework. Three forecasting approaches are proposed to realize the passenger amount variation prediction in real-time, namely, stochastic prediction based on Monte Carlo, radial basis function neural network (RBF-NN) prediction, and Markov-chain prediction. A sample passenger number database along a typical bus line in Beijing is built for passenger variation pattern analysis and forecast. A comparative study of the above three prediction approaches with different prediction lengths (bus stops in this case) is conducted, from both the energy consumption and temperature control perspectives. A predictive AC controller is developed, and evaluated by comparing with Dynamic Programming (DP) and a commonly used rule-based control strategy. Simulation results show that all the three forecasting methods integrated within the MPC framework are able to achieve more stable temperature performance. The energy consumptions of MPC with Markov-chain prediction, RBF-NN forecast and Monte Carlo prediction are 6.01%, 5.88% and 5.81% lower than rule-based control, respectively, on the Beijing bus route studied in this paper. [ABSTRACT FROM AUTHOR]

An integrated chassis control framework that consists of a basic chassis controller and a torque vectoring controller is designed for a three-axle electric bus with distributed motor-driven and active rear steering subsystems. In the basic chassis controller, the active speed limiting control is integrated for antisideslip and antirollover purposes, and the interaxle torque distribution ratio is optimized for energy economy. Meanwhile, the active rear steering control is designed for the tire-wear coordinating purpose. In the torque vectoring controller, the model-based motion control algorithm based on the holistic cornering control method is designed, by which a torque increment is generated at each wheel to change the plane motion states of the vehicle. To solve the optimal torque increment vector, a real-time constrained quadratic programming problem is formulated. The constraints related to the wheel torque limits, the tire friction limits, and the anti-wheel-slip requirements are constructed and converted as the upper and lower bounds of the increments of the longitudinal tire forces. To verify the performance of the control framework, a Trucksim-Simulink cooperative test platform is established. The test results show satisfactory performances on energy economy, anti-wheel-slip, and the safety and stability of the motion control. [ABSTRACT FROM PUBLISHER]

We investigate the economic and technological potential for adoption of Electric Vehicles (EVs) in Abu Dhabi through a parametric assessment, a public attitude survey, and a diffusion model. Abu Dhabi, similar to fossil-fuel-rich countries in its region, features a car-dependent society and energy subsidies while being situated in hot, desert environment challenging to EVs. We compare conventional vehicles and EVs in the region accounting for the higher use of air-conditioning (AC) in the actual climatic and driving pattern conditions of Abu Dhabi developing an EV AC consumption penalty model. Average annual AC penalty in fuel consumption over normal testing conditions is 16% for conventional vehicles and 25% for EVs based on hourly weather and vehicle utilization patterns. For 250 days per year, the expected EV range is higher than 75% of the nominal value. During the five hottest days of the recorded year, it can drop to 60% but still covering the average daily driving of the majority of users with a single charge with a 25kWh battery. With partial subsidies offered for both fuel and electricity, EV adoption impacts the state in terms of opportunity costs for these fuels in addition to environmental externalities. We calculate the state and user benefits in a parametric analysis dependent on driving distance and battery costs. If the battery cost is $325/kWh, direct and internalized benefits and costs are balanced when the EV is driven 60 km/day. A diffusion scenario of 5% by 2030 results in cumulative net savings of 6.4 million barrels of oil, a reduction of 517.000 tonnes of CO2, and a cumulative net benefit of $127 million. [ABSTRACT FROM AUTHOR]

Rapid but unplanned urban development coupled with economic growth has resulted in congestion and pollution concerns in Indian cities. This forced India consider taking concrete steps towards design policies that would help stir the nation towards a more sustainable future. India, along with other bigger Asian economies like China, needs to address the growing global concerns over climate change and design their framework and policies to help cut down the greenhouse gas emissions. Transportation is a major source of pollution. A shift towards a pro-public transport policy would solve the traffic congestion problems and address the emission concerns. India has a significantly higher modal share of public transportation in its major cities. Public bus transport system acts as a lifeline to the India's poor and middle class citizens. The following study focuses on the need for a replacement of conventional fossil fuel dependent buses with Electric buses in the existing public transport bus fleet in the city of Bengaluru. A design has been developed to utilize wireless charging technologies to realize electric bus migration in Bengaluru. [ABSTRACT FROM AUTHOR]

• Approach to solve the integrated electric vehicle and crew scheduling problem. • Influence of vehicle and crew scheduling on the design of electric buses. • Comparing electric bus concepts taking into account local conditions. • Case study investigation for a real-world bus route. • Most cost-effective electric bus concept depends on the crew scheduling assumptions. Encouraged by international efforts to reduce greenhouse gases and local emissions, many public transport operators are converting their fleets to battery-powered electric buses. Public transport operators can choose between different electric bus concepts, with the total cost of ownership being the most important decision criterion. The associated strategic decisions regarding charging strategy, vehicle concept, and charging infrastructure have a significant impact on the operational planning of the electric buses. Motivated by this, this paper aims to analyze the interactions between electrification and operational planning, especially vehicle scheduling and crew scheduling. This allows us to make a more comprehensive comparison of different electrification concepts. Prior work has addressed the impact of electrification on vehicle scheduling but has neglected the interactions with crew scheduling. Crew scheduling dominates operational costs and planning for many public transport operators and must therefore be considered in all strategic decisions. For this reason, in this work we focused on integrated electric vehicle and crew scheduling problem. This allows us to calculate the total cost of ownership of different electric bus concepts under better representation of local conditions. We deal with the electric vehicle and crew scheduling problem with a metaheuristic based on Adaptive Large Neighborhood Search. We tested the developed methodology for a real-world bus route. Our results indicate that the constraints for crew scheduling significantly impact the total cost of ownership and the required number of vehicles of the different electrification concepts. Our case study suggests that the choice of the most cost-effective concept depends significantly on crew scheduling constraints. These findings imply that crew scheduling constraints should be considered as part of the local framework for bus fleet electrification. [ABSTRACT FROM AUTHOR]

This article analyzes various configurations of Hybrid Energy Storage Systems consisting of batteries only, combinations of batteries and supercapacitors, and supercapacitors only. For the presented configurations, mathematical models that were used in research in terms of energy consumption and carbon dioxide emissions were developed, employing a 12-m city bus as a test bed. The tests were carried out using standard test cycles for heavy vehicles as well as routes developed on the basis of actual road conditions. The obtained test results confirmed that the lowest energy consumption is characterized by the system supplied exclusively by batteries (855 Wh/km), followed by a hybrid system of a large battery with a small supercapacitor (941 Wh/km), a hybrid system with a large supercapacitor and a small battery pack (1087 Wh/km), and finally a system with a supercapacitor only (1091 Wh/km). In comparison with the conventional diesel power system (3967 Wh/km), the CO2 emission reductions ranged from 27% to 43%, depending on the source of electrical energy.

Automated manual transmissions (AMT) play an important role in reducing energy consumption in electric vehicles. However, a major concern that limits the usage of AMTs is their poor gear shifting quality that reduces the driving comfort. In this study, a new pneumatically driven robotized gearbox without clutch and synchronizer is introduced and a gear shifting control scheme is developed for an electric city bus. A six speed manual transmission has been robotized (automated) by using two pneumatic double acting cylinders, four three position double solenoid air control valves and a transmission control unit. The speeds of the electric motor and the output shaft of the gear mechanism are well synchronized during shifting process. Experimental study carried out on a prototype electric bus revealed that the new design improves the gear shifting quality such that the shift speed is quite fast and the shift jerk is within the acceptable. The performance of the proposed gearbox has been also compared with that of fixed ratio gearbox and the comparative test results showed that, thanks to the proposed gearbox system, the electric motor is operated efficiently within rated torque limits and the energy consumption is reduced to a large extent. [ABSTRACT FROM AUTHOR]

In view of severe changes in temperature during different seasons in cold areas of northern China, the decay of battery capacity of electric vehicles poses a problem. This paper uses an electric bus power system with semi-active hybrid energy storage system (HESS) as the research object and proposes a convex power distribution strategy to optimize the battery current that represents degradation of battery capacity based on the analysis of semi-empirical LiFePO4 battery life decline model. Simulation results show that, at a room temperature of 25 °C, during a daily trip organized by the Harbin City Driving Cycle including four cycle lines and four charging phases, the percentage of battery degradation was 9.6 × 10-3%. According to the average temperature of different months in Harbin, the percentage of battery degradation of the power distribution strategy proposed in this paper is 3.15% in one year; the electric bus can operate for 6.4 years until its capacity reduces to 80% of its initial value, and it can operate for 0.51 year more than the rule-based power distribution strategy. [ABSTRACT FROM AUTHOR]

This paper describes an integrated chassis control framework for a novel three-axle electric bus with active rear steering (ARS) axle and four motors at the middle and rear wheels. The proposed integrated framework consists of four parts: (1) an active speed limiting controller is designed for anti-body slip control and rollover prevention; (2) an ARS controller is designed for coordinating the tyre wear between the driving wheels; (3) an inter-axle torque distribution controller is designed for optimal torque distribution between the axles, considering anti-wheel slip and battery power limitations and (4) a data acquisition and estimation module for collecting the measured and estimated vehicle states. To verify the performances, a simulation platform is established in Trucksim software combined with Simulink. Three test cases are particularly designed to show the performances. The proposed algorithm is compared with a simple even control algorithm. The test results show satisfactory lateral stability and rollover prevention performances under severe steering conditions. The desired tyre wear coordinating performance is also realised, and the wheel slip ratios are restricted within stable region during intensive driving and emergency braking with complicated road conditions. [ABSTRACT FROM PUBLISHER]

The battery capacity of electric buses (EB) used for public transportation is greater than that of electric cars, and the charging power is also several times greater than that used in electric cars; this can result in high energy consumption and negatively impact power distribution networks. This paper proposes a framework to determine the optimal contracted power capacity and charging schedule of an EB charging station in such a way that energy costs can be reduced. A mathematical model of controlled charging, which includes the capacity and energy charges of the station, was developed to minimize costs. The constraints of the model include the charging characteristics of an EB and the operational guidelines of the bus company. A practical EB charging station was used to verify the proposed model. The financial viability of this EB charging station is also studied in this paper. The economic analysis model for this charging station considers investment and operational costs, and the operational revenue. Sensitivity analyses with respect to some key parameters are also performed in this paper. Based on actual operational routes and EB charging schemes, test results indicate that the EB charging station investment is feasible, and the planning model proposed can be used to determine optimal station power capacity and minimize energy costs. [ABSTRACT FROM AUTHOR]

Evidence suggests that the role of electric buses in public transit is important if we are to take steps to reduce climate change and the environmental impacts of fossil fuels. Several electric alternatives are currently operationalized, and the debate about which is most suitable is attracting considerable attention. This article provides a detailed review of various performance features for three categories of electric buses: hybrid, fuel cell, and battery. Economic, operational, energy, and environmental characteristics of each technology are reviewed in detail based on simulation models and operational data presented by various scholars in different contexts. The study develops a holistic assessment of electric buses based on side-by-side comparison of 16 features that best inform the decision making process. The review indicates that the selection process of electric technology is highly sensitive to operational context and energy profile. In addition, it highlights that hybrid buses will not provide a significant reduction in GHG and would be suitable only for short-term objectives as a stepping-stone towards full electrification of transit. Battery and fuel cell buses are arguably capable of satisfying the current operational requirements, yet initial investment remains a major barrier. Overnight Battery Electric Bus is advocated as the most suitable alternative for bus transit contexts given the expected improvements in battery technology and the trend to utilize sustainable sources in electricity generation. [ABSTRACT FROM AUTHOR]

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China is facing serious issues involving energy sufficiency, greenhouse gas (GHG) emissions and air pollution caused partly by the rapid growth of vehicles. In order to relieve those problems, new energy vehicles are introduced into the bus and car market. We adopt life cycle analysis to evaluate the well-to-wheels (WTW) energy consumption, CO 2 emissions and pollutant emissions from the traditional diesel bus and new energy buses, including diesel hybrid electric vehicles (HEVs), compressed natural gas vehicles (CNGVs) and battery electric vehicles (BEVs). This study reports the current situation and projects future scenarios for the BEV bus for several regions in China due to significant regional differences in the power generation mix. Compared to the diesel bus, the HEV bus can reduce petroleum, fossil fuel use and CO 2 emissions by about 20%, and, at the same time, produce stable reduction benefits for all air pollutants. The CNG bus achieves reductions of WTW primary PM 2.5 emissions by 70% over its diesel counterpart and, of course, uses little petroleum; but increases fossil fuel consumption moderately and has no benefit in GHG emissions. The BEV bus can deliver a substantial petroleum consumption advantage and greatly reduce the WTW NO X , VOC and CO emissions; but, if the electricity is generated from burning coal, the BEV bus has no PM 2.5 emission benefit compared to the conventional diesel bus. Currently, the BEV bus increases fossil energy use and CO 2 emissions in the coal-dominated regions; but, in the future, it can achieve substantially lower fossil energy use and CO 2 emissions with more penetration of clean electric energy. To reach the win–win strategy, a city’s initial reliance on diesel buses for the public fleet has to give way to a mixture of these new energy buses; and the fleet mix should be diversified over the region and modified over time to accommodate changes in these energy and environmental parameters. [ABSTRACT FROM AUTHOR]

The transportation sector accounts for a significant share of greenhouse gas emissions. Hence, the electrification of this sector is a crucial contributor to the mitigation of global warming. Recent studies suggest that electric vehicles will be economically paired with internal combustion engine vehicles in the near future. However, relying on private vehicle decarbonization only cannot deliver comprehensive space management efficiency solutions in urban environments. Therefore, it is essential to invest in the technological development and deployment of electric buses for public transportation, directly enhancing the quality of life in large cities. From this perspective, this review examines a wide range of scientific literature on electric bus research using science mapping methods and content analysis to support critical thinking unveiling the main research streams, methods, and gaps of the field. The analysis indicates that future research on electric buses will be mainly devoted to sustainability (encompassing economic, environmental and quality of service dimensions), energy management strategies, and fleet operation. • Electric bus research is assessed using science mapping and content analysis. • The main electric bus research streams are recognized. • Content analysis of relevant articles is carried out to assess the methods used. • Future research is mainly aimed at energy management strategy and fleet operation. • Recent research gaps are identified. [ABSTRACT FROM AUTHOR]

Globally, the use of electric vehicles, and in particular the use of electric buses, has been increasing. The city of Nanjing leads China in the adoption of electric buses, supported by city policies and infrastructure. To lower costs and provide a better service, vehicle selection is crucial, however, existing selection methods are limited. Accordingly, Nanjing Bus Company developed a test method based on road tests to select a bus. This paper presents a detailed description of the test method and a case study of its application. The method included an organization structure, selection of eight test vehicles (four 10 m length, four 8 m length) from four brands (a total of 32 test vehicles), selection of indicators and selection of routes. Data was collected from repeated drives by 65 drivers over an 8-week period. Indicators included power consumption, charging duration, failure duration and driving distance. It is concluded that the road test method designed and conducted by the Nanjing Bus Company provides a good framework for the selection of pure electric buses. Furthermore, subsequent experience with selected buses supports the validity and value of the model. [ABSTRACT FROM AUTHOR]

• The scheduling problem of EBs for multiple vehicle types is proposed and defined as the MVT-E-VSP. • Differences in technical characteristics of various EV types are considered in the modeling. • The insertion of recharging trips and the substitution between EV types are considered. • The findings provide some guidance on the scheduling of EBs for multiple vehicle types and the deployment of chargers. The effective scheduling of electric buses (EBs) for multiple vehicle types is essential for the sustainable practice of public transport. This paper proposes a new methodology for the electric vehicle scheduling problem with multiple vehicle types (MVT-E-VSP) in public transport based on a given multi-vehicle-type timetable. First, with explicit consideration of differences in driving range, recharging duration and energy consumption of EBs for multiple vehicle types, an optimization model is established to minimize annual total scheduling costs, including the purchase costs of EBs and chargers, the operating costs of deadheading and timetabled trips, etc. Then, a heuristic procedure is developed to find the optimal solution considering recharging trips and the substitution between electric vehicle (EV) types. Finally, the proposed methodology is validated using a real-world transit network in Daxing District, Beijing. The optimization result provides transit agencies with guidance on the purchase and schedule of EBs for multiple vehicle types, as well as the deployment of chargers. Comparative analysis indicates the proposed method considering the substitution between EV types reduces annual total scheduling costs by 15.93% compared with the conventional method. Sensitivity analysis reveals that the current recharging power (240 kW) and discharging depth (80%) are approximately economical. [ABSTRACT FROM AUTHOR]

The market for electric vehicles (EVs) has grown with each year, and EVs are considered to be a proper solution for the mitigation of urban pollution. So far, not much attention has been devoted to the use of EVs for public transportation, such as taxis and buses. However, a massive introduction of electric taxis (ETs) and electric buses (EBs) could generate issues in the grid. The challenges are different from those of private EVs, as their required load is much higher and the related time constraints must be considered with much more attention. These issues have begun to be studied within the last few years. This paper presents a review of the different approaches that have been proposed by various authors, to mitigate the impact of EBs and ETs on the future smart grid. Furthermore, some projects with regard to the integration of ETs and EBs around the world are presented. Some guidelines for future works are also proposed. [ABSTRACT FROM AUTHOR]