Battery Electric Buses Research Articles

A cyberattack resilient model for battery electric bus transit fleets using real-time adaptive system information

This paper aims to assess and tackle the cyber–physical security threats stemming from vulnerabilities of battery-based electric bus (BEB) fleets to cyberattacks. An optimization model is adopted for scheduling the battery swapping in BEB fleets and is utilized for cybersecurity assessments. New methods are proposed for detection of false data injection attacks (FDIAs) against the information of the BEB scheduling model. A supervised machine learning-based method is used for identification of potential cyberattacks against the system parameters that govern the operation of the BEB transit fleet. The proposed cybersecurity model is integrated with the BEB scheduling model to form a cyberattack-resilient scheduling framework for the BEB transit fleet. Two categories of data are considered for the simulation of attack scenarios and assessment of the proposed cybersecurity framework: Type 1 – Signals that are received from sources local to the battery swapping station (BSS), and Type 2 – Signals that are received from sources external to the BSS which can be intercepted and tampered by the attacker. The simulation results are presented to evaluate potential disruptions in the BEB transit operation due to FDIAs against the system’s operating parameters. It is demonstrated that a soft cyberattack mildly deviating the fleet operating parameters, e.g., the bus arrival time by up to 10 min or battery SoC by 5%, does not cause a considerable impact on the scheduling parameters or the financial metrics. A moderate or aggressive attack, however, affecting the fleet operating parameters considerably, can adversely impact the scheduling information and the fleet financial metrics.

An assessment of the energy performance of battery-electric buses in hot environments

Battery Electric Buses (BEBs) are drawing increasing interest as a viable option for sustainable heavy-duty vehicles with reduced emissions. However, their widespread adoption is facing several obstacles, including significant operational limitations engendered by their driving range and the availability of charging infrastructure. Addressing these challenges requires a comprehensive evaluation of BEBs’ energy consumption (EC), accounting for factors like charging requirements, mileage, and battery specifications. This work analyzes the actual EC of four BEB types in Qatar through a real-world testing campaign involving an extensive testing program assessing the EC of the various subsystems, i.e., heating, ventilation, and air conditioning, driveline, and auxiliary, under diverse operating conditions using on-board telematics. In addition, a forecasting simulation model is developed to account for Qatar’s distinctive weather and climate conditions, providing a useful comparison with the real-world case study. Specifically, the study examines how the region’s soaring temperatures will impact on BEBs’ driving range, while the comparative analysis presents a fascinating exploration of the disparities between the actual on-road scenario and the meticulously simulated environment.

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

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

Comparative Life Cycle Assessment of Battery and Fuel Cell Electric Cars, Trucks, and Buses

Addressing the pressing challenge of global warming, reducing greenhouse gas emissions in the transportation sector is a critical imperative. Battery and fuel cell electric vehicles have emerged as promising solutions for curbing emissions in this sector. In this study, we conducted a comprehensive life cycle assessment (LCA) for typical passenger vehicles, heavy-duty trucks, and city buses using either proton-exchange membrane fuel cells or Li-ion batteries with different cell chemistries. To ensure accuracy, we supplemented existing studies with data from the literature, particularly for the recycling phase, as database limitations were encountered. Our results highlight that fuel cell and battery systems exhibit large emissions in the production phase. Recycling can significantly offset some of these emissions, but a comparison of the technologies examined revealed considerable differences. Overall, battery electric vehicles consistently outperform fuel cell electric vehicles regarding absolute greenhouse gas emissions. Hence, we recommend prioritizing battery electric over fuel cell vehicles. However, deploying fuel cell electric vehicles could become attractive in a hydrogen economy scenario where other factors, e.g., the conversion and storage of surplus renewable electricity via electrolysis, become important.

Environmental Impact Reduction of a Trolleybus System in the City of São Paulo, Brazil

Several cities worldwide are studying the replacement of their trolleybus systems with diesel buses or battery electric buses, due to their flexibility and lower operational costs. Diesel buses are considered a major cause of gas emissions in cities, while battery electric buses employ cutting-edge technology, but there is still discussion around the topic due to their technology costs, autonomy, and the sustainability of battery packs. In this study, we evaluated the trolleybus system’s potential for reducing emissions, noise pollution, and greenhouse gases (GHGs) when compared to diesel buses. Furthermore, we compared the trolleybus system with battery electric buses in terms of cost and environmental benefits. To do so, a case study was conducted in São Paulo, Brazil, the largest city in Latin America, which operates the second-highest trolleybus system on the American continent. Our results show that the trolleybus system is a feasible alternative to diesel buses when considering environmental aspects. It can be seen as a complementary service for urban transport systems in the city’s transition to clean energy. Finally, the study implications indicate the need for further investigation of the benefits of in-motion-charge technology to generate flexibility in trolleybus systems, and the involvement of stakeholders in the transition matrix energy process in urban bus systems beyond the direct costs.

An Investigation into the Viability of Battery Technologies for Electric Buses in the UK

An Investigation into the Viability of Battery Technologies for Electric Buses in the UK

Subsidy policies towards zero-emission bus fleets: A systematic technical-economic analysis

We establish a bus market evolution model to explore the implications of subsidy policies in Hong Kong (HK) for the transition to a zero-emission bus (ZEB) fleet using an unsubsidized case as the benchmark scenario. Using the system dynamics (SD) approach, we capture the intricate feedback mechanisms among market share dynamics, cost considerations, consumer preferences, and competitive interactions within the bus market. These interactions are encapsulated within three pivotal feedback loops: scale economy, public acceptance, and bus market competition. We systematically integrate the HK-specific features of hydrogen buses (H-buses), battery electric buses (E-buses), and diesel buses (D-buses) from technical and economic perspectives and compare them to the benchmark scenario. The results show that only 66% of the bus fleet would be ZEBs by 2050, and this underscores the necessity for governmental financial incentives to expedite the transition to a fully zero-emission fleet. Furthermore, we evaluate various ZEB subsidy policy alternatives in terms of timing, intensity, and recipients. The analysis suggests that policies offering long-term and low-intensity subsidies are most beneficial, taking into account the cumulative effects and inherent delays associated with policy implementation. Importantly, the study highlights the critical balance that policymakers must achieve between short- and long-term objectives, especially given the counter-intuitive outcomes observed in the early stages of policies favoring H-buses exclusively. This study provides valuable policy insights for policymakers and upstream energy companies in HK, with potential applicability in wider real-world contexts.

Energy Efficiency Analysis of a Fuel Cell Bus Model Using Real Scenarios Generated by Data Collection

Modernizing public transportation is crucial, given the ongoing call for sustainable mobility. Growing concerns about climate change and the increasingly stringent emissions standards have compelled public transport operators to embrace alternative propulsion vehicles on a broader scale. For the past years, the Battery Electric Buses (BEBs) have been the vehicle of choice for public transportation. However, an emerging contender in this sector is the Fuel Cell Electric Bus (FCEB). This paper aims to evaluate the way one such vehicle would perform in terms of energy efficiency while being exploited in an urban scenario generated from collected data.

Charging facility planning and scheduling problems for battery electric bus systems: A comprehensive review

The adoption of battery electric buses (BEBs) has gained significant momentum in the public transportation sector due to their environmental and energy-saving merits. Nonetheless, challenges such as limited driving range and battery degradation, to some extent, hinder the extensive deployment of BEBs. This paper provides a comprehensive review of BEB adoption and utilization over the past decade, categorizing the state-of-the-art development and our discussion on BEB charging facility planning (BEB-CFP) and BEB charging scheduling (BEB-CS). In this review paper, we first survey the prevailing charging technologies in the BEB market and evaluate their applicability and limitations. Subsequently, the paper synthesizes the development and application of these technologies in terms of related infrastructure planning and charging scheduling operation, focusing on their unique considerations, modeling approaches, solution algorithms, and practical applications. Last, the paper concludes by identifying avenues for future research. Our findings contribute to the literature by providing a holistic revisit of BEB-CFP and BEB-CS with different types of charging technologies, offering selection recommendations and insights for both practitioners and policymakers aiming to optimize the utilization and sustainability of BEB fleets.

Electrification of Transit Buses in the United States Reduces Greenhouse Gas Emissions.

The transportation sector is the largest emitter of greenhouse gas emissions (GHGs) in the United States. Increased use of public transit and electrification of public transit could help reduce these emissions. The electrification of public transit systems could also reduce air pollutant emissions in densely populated areas, where air pollution disproportionally burdens vulnerable communities with high health impacts and associated social costs. We analyze the life cycle emissions of transit buses powered by electricity, diesel, gasoline, and compressed natural gas and model GHGs and air pollutants mitigated for a transition to a fully electric U.S. public transit bus fleet using transit agency-level data. The electrification of the U.S. bus fleet would reduce several conventional air pollutants and has the potential to reduce transit bus GHGs by 33-65% within the next 14 years depending on how quickly the transition is made and how quickly the electricity grid decarbonizes. A levelized cost of driving analysis shows that with falling capital costs and an increase in annual passenger-kilometers of battery electric buses, the technology could reach levelized cost parity with diesel buses when electric bus capital costs fall below about $670 000 per bus.

Empirical analysis of battery-electric bus transit operations in Portland, OR, USA

This study aims to understand the difference in operational performance between electric, hybrid, and diesel buses in Portland, OR. We estimated a running time model, and a distance until a breakdown occurs model using ordinary least squares and multilevel regression frameworks. The results of the running time model suggest that electric buses are faster than diesel buses while controlling for all other operating characteristics. Whilst electric buses do break down sooner if the ramp is used more often, more stops made along the route served by the electric buses increase the distance traveled by the electric buses until a breakdown occurs. Public transport operators are encouraged to continue deploying electric buses, especially along shorter routes with numerous stops, and to undergo preventive maintenance every two weeks. It is also recommended to deploy electric buses to routes where the ramp use is known to be historically infrequent in the short term.

E-Bus Scheduling


 
 
 The following Review Articles aims at reviewing available literature regarding the introduction of E-Buses in urban public transport networks, with particular focus on the scheduling constraints of both vehicles and crews. 
 Battery Electric Buses (BEBs) are the type of E-Buses taken into consideration in this review through the lens of the Electric Vehicle Scheduling Problem (E-VSP). 
 By introducing the planning processes and scheduling objectives that the implementation of e-buses requires, covering then the most impactful constraints that emerge with their adoption (both complete and partial), and concluding with the illustration of the five solution approaches to the scheduling problem deemed more relevant by the authors on the basis of information availability and frequency of use, the article attempts to provide the reader with holistic level information regarding the topic. 
 
 

Impact of Ambient Temperature, Passenger Load, and Delay on the Consumption of Battery Electric Buses

The operation of state-of-the-art battery electric buses (BEBs) has started recently, and their consumption model is unknown. Therefore, the service providers are lenient regarding the energy used. Our aim was to reveal the effects of ambient temperature and bus service characteristics, such as passenger load and delay, on the energy consumption. Real-time consumption data of BEBs were analyzed in Nyíregyháza, Hungary, and the functional relationships among the aforementioned variables were revealed. We found that while ambient temperature is negatively correlated with consumption in the cold winter periods, the consumption surplus is positively correlated with passenger load and generally positively correlated with the delay on the trip because of road traffic. In the case of delay, the consumption increase is caused by more frequent acceleration and the greater consumption of auxiliary systems due to longer running times. Accordingly, the energy consumption can be estimated if the characteristics data are available. The results can be used by bus service operators to plan the daily schedule and predict the energy consumption of a BEB.

Life cycle assessment of lithium iron phosphate and electrochemical recuperator cells for city buses in Finland

The study investigates the environmental impacts of electric city buses based on the storage technologies applied and the degree of electrification within the Finnish context. Lithium iron phosphate (LFP) and electrochemical recuperator (ECR) were selected as storage technologies. ECR can be an alternative to the lithium-ion battery; however, little is known regarding its environmental performance when applied to electrify city buses. The study focused on diesel buses, battery electric buses (BEB) and plug-in hybrid buses. Life cycle assessment (LCA) was used to assess the potential environmental impacts between storage technologies and the degree of electrification. Primary data from the industry was used to assess the impacts of manufacturing ECR. The results showed that manufacturing a kWh of ECR generated a global warming potential (GWP) of 178 kg CO2-eq, higher than LFP. However, its application indicated that ECR performed better. The impacts of using ECR and LFP in BEB were 385 g CO2-eq/km and 441 g CO2-eq/km, respectively. The hybrid system generated 652 g CO2-eq/km and 670 g CO2-eq/km for ECR and LFP, respectively. The study also showed no consistent pattern between the degree of electrification and environmental benefits. Scenario analysis revealed that BEB provided the best GWP when assessed using a Finnish and Norwegian electricity mix, while the hybrid system performed the best when Polish electricity was applied. This study demonstrated that storage technologies, degree of electrification, fuel consumption, and electricity sources affect environmental performance. Careful assessment is needed before deciding to electrify the city's transport system.

Towards Efficient Battery Electric Bus Operations: A Novel Energy Forecasting Framework

As the adoption of battery electric buses (BEBs) in public transportation systems grows, the need for precise energy consumption forecasting becomes increasingly important. Accurate predictions are essential for optimizing routes, charging schedules, and ensuring adequate operational range. This paper introduces an innovative forecasting methodology that combines a propulsion and auxiliary energy model with a novel concept, the environment generator. This approach addresses the primary challenge in electric bus energy forecasting: estimating future environmental conditions, such as weather, passenger load, and traffic patterns, which significantly impact energy demand. The environment generator plays a crucial role by providing the energy models with realistic input data. This study validates various models with different levels of model complexity against real-world operational data from a case study of over one year with 16 electric buses in Göttingen, Germany. Our analysis thoroughly examines influencing factors on energy consumption, like altitude, temperature, passenger load, and driving patterns. In order to comprehensively understand energy demands under varying operational conditions, the methodology integrates data-driven models and physical simulations into a modular and highly accurate energy predictor. The results demonstrate the effectiveness of our approach in providing more accurate energy consumption forecasts, which is essential for efficient electric bus fleet management. This research contributes to the growing body of knowledge in electric vehicle energy prediction and offers practical insights for transit authorities and operators in optimizing electric bus operations.

Electrification of public buses in Jakarta, Indonesia: A life cycle study

Indonesia plans to mitigate the environmental emissions, particularly the carbon emissions, from the transport by replacing conventional buses with battery electric buses (BEBs). However, there are limited studies on the potential environmental benefits of BEBs and mostly focused on carbon emissions. In this study, the environmental impacts of adopting BEBs in Jakarta's public transportation system were examined using Life Cycle Assessment (LCA) to better understand its potential environmental impacts. Using LCA, the environmental impacts of BEBs were also compared with conventional buses across their life cycles, which included raw materials extraction until the end of life stages. The results showed diesel buses have generally lower environmental impacts than BEBs due to the high share of fossil fuels in the electricity generation in Indonesia. Scenario analysis showed that extending the life cycle, using different battery disposal methods, and using battery reuse could lead to higher environmental benefits in using BEBs. Among the scenarios considered in the study, prolonging the lifespan of the bus to 32 years, using electricity mix with a higher share of renewable energy and reusing the lithium-ion batteries, BEBs would have lesser environmental impact per kilometre. In particular, the particulate matter formation (PM2.5) dropped 21 %, while the overall life cycle of BEB using the highest renewable scenario showed an average of 25 % improvement compared to the baseline scenario regarding environmental impact.

Planning dynamic wireless charging infrastructure for battery electric bus systems with the joint optimization of charging scheduling

To address the battery-related shortcomings of battery electric buses (BEBs), dynamic wireless charging (DWC) technology that allows BEBs to charge while in motion has emerged, thereby extending the driving range and reducing the size of onboard batteries. The introduction of DWC technology raises a critical problem, namely, the deployment of DWC facilities. To resolve the infrastructure planning problem, this study first proposes a (higher-level) strategic planning model that optimizes the deployment of DWC facilities and battery capacity of BEBs, and then establishes a (lower-level) tactical planning model of optimal charging scheduling under the time-of-use (TOU) tariff mechanism considering the interdependence between infrastructure design and charging activities of BEBs. Mixed-integer nonlinear programming (MINLP) is proposed to optimize the model, aiming to minimize the overall cost associated with charging facilities, batteries, and charging. The proposed optimization model is tested and evaluated using a real-world bus system network, and the results demonstrate that the model effectively determines the DWC facility locations and battery sizes and optimizes the charging scheduling considering the TOU tariff for BEBs. The proposed model in this study provides a comprehensive guideline for relevant practitioners and further promotes the application of DWC technology in BEBs.

Optimization of Electric Bus Scheduling and Charger Location

In the pursuit of sustainable urban transportation, the transition from traditional fossil fuel-powered buses to battery electric buses (BEBs) presents a significant leap forward. However, this shift introduces a critical challenge in the form of the BEB scheduling and charger location (EBSCL) problem. The limited driving range of BEBs necessitates the strategic reassignment of buses for service trips, known as the electric vehicle scheduling problem. Simultaneously, the optimal placement of charging infrastructure adds complexity to the overall transit electrification process. Our study addresses this challenge by proposing an integrated model that optimizes both BEB scheduling and charger location. The source code is available at https://gitlab.com/AmirDavatgari/etcp.

Optimal structure selection and integrated optimization of parameters of a dual-motor-driven system in battery electric bus

Optimal structure selection and integrated optimization of parameters of a dual-motor-driven system in battery electric bus

Decarbonization with induced technical change: Exploring the niche potential of hydrogen in heavy transportation

Fuel cells and electric batteries are competing technologies for the energy transition in heavy transportation. We explore the conditions for the survival of a unique technology in the long term. Learning by doing suggests focusing on a single technology while differentiation and decreasing return to scale (cost convexity) favor diversification. Exogenous technical change also plays a role. The interaction between these factors is analyzed in a general model. It is proved that in absence of convexity and exogenous technical change, only one technology is used for the whole transition. We then apply this framework to analyze the competition between fuel-cell electric buses (FCEBs) and battery electric buses (BEB) in the European bus sector, considering both learning by doing and exogenous technical change. The model is calibrated and solved. It is shown that the existence of a niche for FCEBs critically depends on the speed at which cost reductions are achieved. The speed depends both on the size of the niche and the rate of learning by doing for FCEBs. Public policies to decentralize the socially optimal trajectory in terms of carbon tax and subsidies to learning by doing are derived.