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The option of decarbonizing urban freight transport using Battery Electric Vehicle (BEV) seems promising.However, there is currently a strong debate whether Fuel Cell Electric Vehicle (FCEV) might be the bettersolution. The question arises as to how a fleet of FCEV influences the operating cost, the Greenhouse Gas(GHG) emissions and primary energy demand in comparison to BEVs and to Internal Combustion EngineVehicle (ICEV). To investigate this, we simulate the urban food retailing as a representative share of urbanfreight transport using a multi-agent transport simulation software. Synthetic routes as well as fleet size andcomposition are determined by solving a Vehicle Routing Problem (VRP). We compute the operating costsusing a total cost of ownership (Total Cost of Ownership (TCO)) analysis and the use phase emissions as wellas primary energy demand using the Well To Wheel (WTW) approach. While a change to BEV results in 17 -23% higher costs compared to ICEV, using FCEVs leads to 22 - 57% higher costs. Assuming today’s electricitymix, we show a GHG emission reduction of 25% compared to the ICEV base case when using BEV. Currenthydrogen production leads to a GHG reduction of 33% when using FCEV which however cannot be scaled tolarger fleets. Using current electricity in electrolysis will increase GHG emission by 60% compared to the basecase. Assuming 100% renewable electricity for charging and hydrogen production, the reduction from FCEVsrises to 73% and from BEV to 92%. The primary energy requirement for BEV is in all cases lower and forhigher compared to the base case. We conclude that while FCEV have a slightly higher GHG savings potentialwith current hydrogen, BEV are the favored technology for urban freight transport from an economic andecological point of view, considering the increasing shares of renewable energies in the grid mix.

To enable the deployment of battery-electric vehicles (BEV) as passenger cars in the private transport sector, a suitable charging infrastructure is crucial. In this paper a methodology for efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a market penetration of BEVs of 100 percent (around 1.3 million vehicles). It aims towards the development of various charging infrastructure scenarios - including public and private charging - which are suitable to cover the charging demand. Therefore, these scenarios are investigated in detail with focus on number of public charging points, their spatial distribution, the available charging power and the necessary capital costs. For the creation of those charging infrastructure scenarios a placement model is developed. It uses the data of a MATSim (Multi-Agent Transport Simulation) traffic simulation of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital cost of the charging points and the mean detour car drivers must cover additionally are used as optimization criteria. Using these criteria should lead to cost efficient infrastructure solutions which provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found and suitable solutions can be selected by using other criteria subsequently. The optimized charging infrastructure solutions show capital costs between 624 and 2950 million euro. Users must cover an additionally mean detour of 254m to 590m per charging process to reach an available charging point. According to the results a suitable ratio between charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50kW) of less than ten percent seems to be sufficient, if it is situated at main traffic routes and highly frequented places.

Sustainable products are becoming increasingly important for companies in order to succeed. However, the development of sustainable products poses a complex challenge, because alongside the classical product development requirements, additional social, economic and ecologic requirements arise. Despite the increasing relevance of this topic, sustainability is not yet fully integrated into the product development processes and mindsets within companies. Simultaneously, the integration of sustainability into engineering education is still insufficient and traditional teaching formats seem to be inadequate to teach such complex and multifaceted topics. Within this publication, the development, the contents and the implementation of two different university engineering courses for sustainability and environmentally compatible product development are described and compared. The different approaches to develop and incorporate sustainability into the engineering education and the usage of innovative teaching concepts are demonstrated to encourage and inspire other universities.

Requirements engineering and requirements management are essential sub-processes of product development and are an integrated part of virtually all product development models and industrial process descriptions. Proprietary and context specific processes for working with requirements are used in industrial design practice. However, these are not appropriately reflected in existing process models for product development. Existing standards describe the content and generation of requirements documents but not their integration in the product development process.The study is based on a retrospective analysis of a set of representative real-world product development projects from automotive industry and rail industry. Comparing the processes downstream the milestone “release of PRD”, it was found that subsequent processes to manage requirements and specifications do not differ much with regard to industrial context. Based on this, a model for the product requirements specification (PRS) process is proposed which addresses the gap.

In electric buses, the heating, ventilation and air conditioning (HVAC) system is responsible for up to 50% of the energy consumption, thereby significantly affecting the efficiency. It is therefore necessary to identify improved thermal settings for the bus cabin to minimize the energy consumption, while guaranteeing good thermal comfort. To achieve this goal, this paper presents the results of climatic measurements in an electric bus in Berlin, Germany. These measurements were performed for outer temperatures between 5.3 °C and 7.8 °C and four cabin temperature settings. During the measurements, several climatic parameters and the energy consumption were measured, whereas the thermal comfort (TC) was evaluated via 71 passengers' surveys. The results show that the climatic conditions in the bus vary greatly depending on the position (up to 3 K difference in mean air temperature) and height (up to 8 K/m temperature-to-height ratio). Additionally, the surveys show that the mean value of the thermal comfort parameter TC is minimized to a value of 0.15 (corresponding to "comfortable" thermal perception) for a set temperature of 21 °C, whereas the thermal conditions are perceived as acceptable even with heating off.

Future transport will change drastically with the introduction of automated vehicles. Here, Autonomous Mobility on Demand (AMoD) will play a major role, requiring a radical change of vehicle design, with many different conceivable concepts. This technology shift holds high potentials and high risks. Uncertainties about future usage profiles, operator and customer requirements have to be dealt with. An approach to elicit initial requirements for future vehicle concepts considering the entire ecosystem is introduced. The applicability is shown for a specific urban mobility scenario.

A major part of urban private vehicles needs to be electrified in order to meet the German climate protection goals in the transport sector. Therefore, charging strategies must be developed and the geographical distribution of infrastructure has to be planned accordingly. We propose a new method to combine a multi agent traffic simulation (MATSim) with real-world vehicle distribution and measured charging behavior. The results of our simulation were analyzed for the exemplary use case of Berlin’s private passenger cars. Three different charging strategies were developed and analyzed: charging at home, at work and during leisure activities. Charging at home was suitable to serve all agents’ charging demand with low charging power (7.4 kW). Charging at work only served 56.23 % of the agents with a charging power of 11 kW, but required fewer charging points. Charging during leisure activities served from 46.36 % to 81.92 % of the agents, depending on the chosen charging power and user behavior.

To support power grid operators to detect and evaluate potential power grid congestions due to the electrification of urban private cars, accurate models are needed to determine the charging energy and power demand of battery electric vehicles (BEVs) with high spatial and temporal resolution. Typically, e-mobility traffic simulations are used for this purpose. In particular, activity-based mobility models are used because they individually model the activity and travel patterns of each person in the considered geographical area. In addition to inaccuracies in determining the spatial distribution of BEV charging demand, one main limitation of the activity-based models proposed in the literature is that they rely on data describing traffic flow in the considered area. However, these data are not available for most places in the world. Therefore, this paper proposes a novel approach to develop an activity-based model that overcomes the spatial limitations and does not require traffic flow data as an input parameter. Instead, a route assignment procedure assigns a destination to each BEV trip based on the evaluation of all possible destinations. The basis of this evaluation is the travel distance and speed between the origin of the trip and the destination, as well as the car-access attractiveness and the availability of parking spots at the destinations. The applicability of this model is demonstrated for the urban area of Berlin, Germany, and its 448 sub-districts. For each district in Berlin, both the required daily BEV charging energy demand and the power demand are determined. In addition, the load shifting potential is investigated for an exemplary district. The results show that peak power demand can be reduced by up to 31.7% in comparison to uncontrolled charging.

To enable the deployment of battery electric vehicles (BEVs) as passenger cars in the private transport sector, suitable charging infrastructure is crucial. In this paper, a methodology for the efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a 100% market penetration of BEVs of (around 1.3 million vehicles) in Berlin, Germany. The goal of the evaluated methodology is the development of various charging infrastructure scenarios—including public and private charging—which are suitable to cover the entire charging demand. Therefore, these scenarios are investigated in detail with a focus on the number of public charging points, their spatial distributions, the available charging power, and the necessary capital costs. For the creation of these charging infrastructure scenarios, a placement model is developed. As input, it uses the data of a multi-agent transport simulation (MATSim) scenario of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital costs of the charging points and the mean detour car drivers must undertake are used as the optimization criteria. Using these criteria, we expect to generate cost-efficient infrastructure solutions that provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found, and suitable solutions can be selected by subsequently using other criteria. Besides the generated charging scenarios for Berlin, the main goal of this paper is to provide a valid methodology, which is able to use the output data of an agent-based, microscopic transport simulation of an arbitrary city or area (or even real driving data) and calculate different suitable charging infrastructure scenarios regarding the different optimization criteria. This paper shows a possible application of this method and provides suggestions to improve the significance of the results in future works. The optimized charging infrastructure solutions for the Berlin scenario show capital costs of between EUR 624 and 2950 million. Users must cover an additional mean detour of 254 m to 590 m per charging process to reach an available charging point. According to the results, a suitable ratio between the charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50 kW) of less than ten percent seems to be sufficient if it is situated at the main traffic routes and highly frequented places.

Electric moped scooter sharing services have recently experienced strong growth rates, particularly in Europe. Due to their compactness, environmental-friendliness and convenience, shared e-mopeds are suitable for helping to reduce the environmental impact of urban transport. However, its traffic-related, economic and environmental effects are merely represented in academic research. Therefore, this study investigates the ability of an e-moped sharing system to substitute passenger car trips, and the resulting economic and environmental effects. First, we model fleets of 2500, 10,000 and 50,000 shared e-mopeds in Berlin, based on a passenger car scenario generated by the multi-agent transport simulation framework MATSim. Afterwards, the total cost of ownership and a life cycle assessment are conducted. The results indicate that a substantial part of all passenger car trips in Berlin can be substituted. The larger the fleet, the more and longer trips are replaced. Simultaneously, the efficiency in terms of fleet utilization decreases. The scenario with 10,000 e-mopeds offers the lowest total distance-based costs for sharing operators, whereas a fleet consisting of 2500 vehicles exhibits the lowest environmental emissions per kilometer. Already with today���s grid mix, the use of shared e-mopeds results in a significant reduction in environmental impact compared to conventional and battery-electric passenger cars.

Many cities have announced ambitious plans to introduce zero-emission electric bus systems. The transformation process to electric bus systems opens up a vast design space as different charging strategies, charging technologies and battery types are available. Therefore, a profound assessment strategy is necessary to find a “most suitable system solution” under given strategic and operational requirements.In this study, we present a new methodology for conceptual design of urban electric bus systems. First, the available e-bus technologies are analysed with a special focus on charging systems, battery technology and aging. Relational functional analysis is used to derive a suitable simulation model. Based on the operational requirements, an energetic simulation of the e-bus is carried out, and the required battery capacity is obtained. Subsequently, the design space is reduced by applying a qualitative cost- technology compatibility matrix taking cost and battery aging into account. The applicability of the model is shown for an exemplary realistic operational scenario to identify three most expedient concepts, which are finally validated with an in-depth analysis.

This paper presents a new methodology to derive and analyze strategies for a fully decarbonized urban transport system which combines conceptual vehicle design, a large-scale agent-based transport simulation, operational cost analysis, and life cycle assessment for a complete urban region. The holistic approach evaluates technical feasibility, system cost, energy demand, transportation time, and sustainability-related impacts of various decarbonization strategies. In contrast to previous work, the consequences of a transformation to fully decarbonized transport system scenarios are quantified across all traffic segments, considering procurement, operation, and disposal. The methodology can be applied to arbitrary regions and transport systems. Here, the metropolitan region of Berlin is chosen as a demonstration case. The first results are shown for a complete conversion of all traffic segments from conventional propulsion technology to battery electric vehicles. The transition of private individual traffic is analyzed regarding technical feasibility, energy demand and environmental impact. Commercial goods, municipal traffic and public transport are analyzed with respect to system cost and environmental impacts. We can show a feasible transition path for all cases with substantially lower greenhouse gas emissions. Based on current technologies and today&rsquo, s cost structures our simulation shows a moderate increase in total systems cost of 13&ndash, 18%.

Submitted to ABMTRANS'21 – 10th International Workshop on Agent-based Mobility, Traffic and Transportation Models, Methodologies and Applications The decarbonization of transport is one major challenge in the upcoming years. One possible solution is the use of battery electric vehicles (BEV). While electric passenger cars and their charging strategies are already in series production, battery electric trucks and their charging strategies are still mostly in the prototype stage. The range limitations of battery electric trucks represent a new challenge for logistics. Therefore, we introduce a methodology for determining charging strategies for freight transport vehicles based on transport simulation results. We analyze the results of an agent-based transport simulation (MATSim) and evaluate different settings of normal and fast charging points. We found for a case study dealing with the food retailing in Berlin, that for a fleet with 279 vehicles in 16 depots 214 normal and 61 fast charging points are sufficient to complete approx. 90% of the tours with BEV. If the vehicles share their charging points, only 71 fast charging points with 400 kW are sufficient. With higher charging power the share of charged vehicles hardly increases. With 29 additional high performance opportunity chargers within the city, all tours can be operated by battery electric trucks.

This paper establishes a prognosis of the long term environmental impact of various car subsidy concepts. The CO2 emissions of the German car fleet impacted by the purchase subsidies are determined. A balance model of the CO2 emissions of the whole car life cycle is developed. Consideration of production-, use- and End-of-Life processes are taken into account. The implementation of different subsidy scenarios directly affects the forecasted composition of the vehicle population and therefore the resulting life cycle assessment. All scenarios compensate the additional emissions required by the production pull-in within the considered period and hence reduce the accumulated CO2 emissions until 2030. The exclusive funding of BEVs is most effective with a break-even in 2025.

The transport sector in Germany causes one-quarter of energy-related greenhouse gas emissions. One potential solution to reduce these emissions is the use of battery electric vehicles. Although a number of life cycle assessments have been conducted for these vehicles, the influence of a transport system-wide transition has not been addressed sufficiently. Therefore, we developed a method which combines life cycle assessment with an agent-based transport simulation and synthetic electric-, diesel- and gasoline-powered vehicle models. We use a transport simulation to obtain the number of vehicles, their lifetime mileage and road-specific consumption. Subsequently, we analyze the product systems&rsquo, vehicle production, use phase and end-of-life. The results are scaled depending on the covered distance, the vehicle weight and the consumption for the whole life cycle. The results indicate that the sole transition of drive trains is insufficient to significantly lower the greenhouse gas emissions. However, sensitivity analyses demonstrate that there is a considerable potential to reduce greenhouse gas emissions with higher shares of renewable energies, a different vehicle distribution and a higher lifetime mileage. The method facilitates the assessment of the ecological impacts of complete car-based transportation in urban agglomerations and is able to analyze different transport sectors.

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

Decarbonisation is a major challenge for the coming decades, for all industries, including the transport sector. Battery electric vehicles are a potential solution for the transport sector to reduce its carbon impact. Asides from the question whether there is sufficient supply of electric vehicles for freight transport, it is also unclear whether battery-powered trucks meet the practical requirements, especially in terms of their driving range. To investigate this, synthetic tours were generated by solving a Vehicle Routing Problem (VRP). This also generates the fleet size and composition depending on a set of different vehicle types. The network with underlying traffic conditions comes from an publicly available transport model. The generated tours are then simulated with an open-source transport simulation (MATSim), for both diesel and battery electric vehicles (BEVs). In a sensitivity study, two different purchase prices were considered for calculating vehicle costs. The case study uses a model of the food retailing industry for the city of Berlin. 56% of the tours can be driven without recharging. When recharged one time, 90% of the tours are suitable for BEVs. The costs for transporting the goods will increase by 17 to 23% depending on the assumption for the purchase prices for the BEVs. Using a well-to-wheel calculation, the electrification of all tours leads to a reduction of greenhouse gas (GHG) emissions by 26 to 96% depending on the assumed electricity production. DFG, 398051144, Analyse von Strategien zur vollständigen Dekarbonisierung des urbanen Verkehrs

We introduce the concept of social sustainability, intertwined with ecological and economic aspects, to the field of service robots and comparable automation technology. It takes a first step towards a comprehensive guideline that operationalizes and applies social sustainability. By applying this guideline to the project MURMEL we offer a concept that collects and rates social key issues to visualize their individual importance. Social sustainability is an important and often overlooked aspect of sustainable technology development which should be considered in the early development phase.

In den vergangenen Jahren hat sich das Lasersintern im Bereich der medizintechnischen Forschung als aussichtsreiches AM-Verfahren zur zeitnahen Herstellung von patientenspezifischen Implantaten mit entsprechender Bioaktivitat etabliert. Aufgrund mangelnder Prozesssteuerbarkeit und zu groser Bauvolumina kommerzieller Lasersintermaschinen wird diesbezuglich am Fachgebiet Methoden der Produktentwicklung und Mechatronik in Zusammenarbeit mit dem Fachgebiet Keramische Werkstoffe und dem 3D-Labor der Technischen Universitat Berlin eine modulare Lasersintermaschine neuentwickelt, die in Zukunft zur Fertigung von Implantatmatrizen aus bioresorbierbareren Polymeren verwendet werden soll. Ein kleiner Bauraum, hohe Fertigungsgenauigkeit, parametrische Steuerung und die Moglichkeit der Integration geeigneter Sensorik waren die Hauptanforderungen an die Forschungsmaschine. Die Prozesskammer ist durch die Verwendung FDA-konformer Werkstoffe fur die Fertigung von Medizinprodukten unter inerter Gasatmosphare geeignet. Der im Rahmen der Konzipierungsphase erarbeitete Modularisierungsansatz unterteilt die Lasersintermaschine in Maschinengestell, Baustempel-, Pulverzufuhr-, Pulverauftrags-, Prozessgas-, Heiz- und Lasermodul. Im Rahmen der materialspezifischen Prozessentwicklung wird das Lasermodul mit entsprechenden Spezifikationen erganzt.

Electric vehicles with a distributed drive train configuration provide great possibilities for the improvement of the vehicle dynamics, handling, safety as well as efficiency. In this paper, an energy-efficient torque allocation scheme is proposed for the improvement of traction efficiency and braking energy recovery. In traction conditions, the traction distribution is developed using an objective function of minimizing power loss of four electric motors. In braking conditions, aiming at guaranteeing the braking stability and recapturing the braking energy as much as possible, the changeable distribution of braking torque is obtained based on the ideal front-rear braking force distribution curve, while complying with braking regulations of Economic Commission for Europe. The proposed allocation scheme does not rely on the complex online computation. It is obtained via an offline optimization procedure and utilized for online allocation by simple interpolation. The low calculation effort makes it easy to implement the algorithm on real vehicles. Additionally, a conventional torque allocation is introduced as a contrasting approach. Finally, the simulations are conducted in CarSim and MATLAB/Simulink environment. The results demonstrate that the energy-efficient torque allocation scheme considerably improves the vehicle efficiency and increases the braking energy recovery compared with the conventional approach.

The performance of an airborne wind energy system crucially depends on the aerodynamic, structural dynamic and flight dynamic properties of the tethered wing. In the scope of this paper, flight dynamic properties are determined against reproducible steering inputs. Current design methods for highly flexible membrane wings have achieved a mature product level by combining iterative testing with empirical and intuitive variation of wing parameters. However, for significant further improvements, experimental data of high quality is indispensable. We have developed a tow test setup for reproducible measurement of the dynamic properties of different types of tethered membrane wings. The test procedure is based on repeatable automated maneuvers with the entire kite system under realistic conditions. By measuring line forces and line angles, we determine the aerodynamic coefficients and the lift-to-drag ratio as functions of the length ratio between power and steering lines. This non-dimensional parameter characterizes the angle-of-attack of the wing and is varied automatically by the control unit on the towed test bench. During each towing run, several test cycles are executed such that mean values can be determined and errors can be minimized. We can conclude from this study that an objective measurement of specific dynamic properties of highly flexible membrane wings is feasible. The presented tow test method is suitable for quantitatively assessing and comparing different wing designs. The method represents an essential milestone for the development and characterization of tethered membrane wings as well as for the validation and improvement of simulation models. On the basis of this work, more complex maneuvers and a full degree of automation can be implemented in subsequent work. It can also be used for aerodynamic parameter identification.

For the purpose of utilizing electric bus fleets in metropolitan areas and with regard to providing active energy management at depots, a profound understanding of the transactions between the market entities involved in the charging process is given. The paper examines sophisticated charging strategies with energy procurements in joint market operation. Here, operation procedures and characteristics of a depot including the physical layout and utilization of appropriate charging infrastructure are investigated. A comprehensive model framework for a virtual power plant (VPP) is formulated and developed to integrate electric bus fleets in the power plant portfolio, enabling the provision of power system services. The proposed methodology is verified in numerical analysis by providing optimized dispatch schedules in day-ahead and intraday market operations.

\ud \ud This paper proposes a fast model predictive control allocation (MPCA) approach to minimize the tire slip power loss on contact patches for distributed drive electric vehicles (DDEV). In this strategy, two assumptions are set up from a practical focus: (1) the vehicle acceleration and yaw rate are measurable by global position system (GPS)/ inertial navigation system (INS) and inertial measurement unit (IMU), respectively; (2) the longitudinal velocity, road adhesion factor, and vehicle yaw rate are arranged to be “already known” by advanced estimators. For the strategy design, a CarSim-embedded driver model and a linear quadratic regulator (LQR) based direct yaw moment controller, are respectively applied to calculate the desired longitudinal traction and yaw moment as a virtual input first. Then, a MPCA method is proposed to reasonably distribute the virtual input among four in-wheel motors in order to optimize the tire slip power loss and vehicle stability performance. To accurately characterize tire slip power loss in MPCA, a tire slip estimator is established for tire slip information acquirement. Moreover, addressing on the heavily computational challenge in MPCA, a modified continuation/generalized minimal residual (C/GMRES) algorithm is employed. Since the traditional C/GMRES algorithm cannot directly solve the inequality constraint problem, the barrier functions are applied for transforming the inequality constraints to equivalent cost. According to Pontryagin’s minimum principle (PMP) conditions, the existence and uniqueness for solution of the modified C/GMRES algorithm are strictly proved. Subsequently, a Karush–Kuhn–Tucker​ (KKT) condition based approach is developed to fast gain the optimally initial solution in C/GMRES algorithm for extending application. Finally, numerical simulation validations are implemented and demonstrate that the proposed MPCA can ensure the compatibility between the tire slip power loss reduction and vehicle stability in a computationally efficient way.

The Sequencing of product DSMs has been proposed for the identification of interdependencies and for product development planning (PDP) including components and subsystems. But, due to little exploitable outcome, this approach is hardly used in practice. A new method using an augmented DSM Sequencing algorithm with a gradient based optimizer is presented. The method considers Product Architecture Drivers to derive a suggestion for an efficient planning process and is integrated in a DSM software. Furthermore, it is validated using a combustion engine as a typical engineering product.

Many public transport authorities have a great interest in introducing zero-emission electric buses. However, the transformation process from diesel to electric bus systems opens up a vast design space which seems prohibitive for a systematic decision making process. We present a holistic design methodology to identify the ‘most suitable system solution’ under given strategic and operational requirements. The relevant vehicle technologies and charging systems are analysed and structured using a morphological matrix. A modular simulation model is introduced which takes technical and operational aspects into account. The model can be used to determine a feasible electric bus system. The technology selection is based on a detailed economic analysis which is conducted by means of a total cost of ownership (TCO) model. To cope with uncertainties in forecasting, a stochastic modelling of critical input parameters is applied and three different future scenarios are evaluated. The applicability of the model was verified in a pilot project in Berlin and the methodology was applied to a realistic operational scenario. Our results indicate that electric bus systems are technically feasible and can become economically competitive from the year 2025 under the conditions examined.

The air-conditioning and heating of the passenger cabin in an electric bus leads to a significant increase of the auxiliaries’ energy consumption. Due to limited battery capacity, the daily operating range of electric buses depends considerably on the ambient climate. In particular, heating is an energy-intensive process since no waste heat from the IC engine is available. Energetic simulations show drastic range reductions when the interior is heated by an electric resistance heater. In contrast, the range reduction can be limited noticeably if a heat pump is utilised. Therefore, the selection of heating and air-conditioning (HVAC) systems has a significant impact not only on the range but also on the operating costs of an electric vehicle. The aim of this study is to conduct a cost analysis for different HVAC systems of an electric city bus. The economic assessment is based on comprehensive energy consumption simulation and a life-cycle costing approach considering all expenses of the operation period. The examination reveals that the heat pump systems feature significant energy savings compared to conventional HVAC systems. However, over a life span of twelve years, the current high acquisition cost of a heat pump system is not compensated when only considering direct cost.