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A key factor in limiting global warming is the conversion of conventional electricity generation to renewable energy sources. However, a major obstacle is that renewable energy generation and energy demand often do not coincide in time, and energy must therefore be stored temporarily. Vehicle to grid (V2G) can be used to store excess renewable energy in battery electric vehicles (BEVs) and feed it back into the electric grid when needed. For effective V2G operation, the grid may have to be expanded, as the energy needs to be transported to BEVs. However, the grid should only be strengthened where renewable energy demand exceeds current grid capacity due to high grid expansion costs. This requires a method that determines the spatial distribution of V2G potential at a high resolution. Since such a method has not yet been reported in the existing literature, and so is developed in this paper. The method is demonstrated for the city of Berlin and its 448 sub-districts. For each sub-district, the method allows determining the percentage of residential and BEV energy demand that can be met by renewables if V2G is deployed, and answers the question of whether a full renewable supply is possible. The results show that BEVs can be effectively used as intermediate storage for renewable energy. If 30% of the BEVs participate in V2G, more than 99% of the energy demand of households and BEVs in Berlin can be covered by renewables on certain days. On the other hand, V2G deployment increases the average peak load in the districts by up to 100% and results in a nearly double load on vehicle batteries. High shares of renewable energy can be observed in districts with a high degree of motorization, which are predominantly found in the outskirts of the city.

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 (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.

Lithium-ion (Li-ion) batteries are currently the preferred choice among energy storage systems for a wide range of applications due to their high energy density, long life span and cost effectiveness. However, in several high-power applications such as electric vehicles, the heat generation of Li-ion battery cells can cause several problems such as accelerated aging and thermal runaway. Although cooling systems are typically utilized to overcome these issues, they suffer from drawbacks such as uneven cooling of the battery cells as well as cumbersome architectures and high energy consumption. In this paper, we propose an active cell balancing (ACB) strategy to mitigate the impact of the temperature gradient on divergent aging of the cells with the goal of increasing the life span of a battery module. We explore balancing architectures dedicated to this goal and study their effectiveness via a simulation framework based on an electrochemical cell model, a computational fluid dynamics (CFD) cooling model and a battery aging model. The experiments show that the life extension of the module is proportional to the amount of ACB circuit, which points toward cost-effective solutions for battery manufacturers. In addition, the results indicate further cost reduction from relaxed cooling system requirements. Our investigation on a 40-cell battery module with standard thermal gradient shows that the life span can be prolonged by about 2.8%. Finally, our extended analysis shows that a life cycle extension of 19.8% is possible with ACB if a relaxed thermal gradient constraint of 12.4 °C is assumed.

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.

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.

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.

This paper presents a methodology that addresses the challenges of designing a depot for electric vehicle fleets. The wide variety of possible solutions are structured using a morphological matrix. A modular simulation and planning tool is introduced which takes technical and operational aspects into account. The tool can be used to determine the effects of depot layouts and processes. Different from most existing works, the charging process is integrated into main depot operations, which consist of daily service, maintenance, parking and vehicle dispatch. In a real-world case study, the developed algorithms for dispatching and price-oriented charging are applied. The results show the depot processes of 74 electric buses over a week and a charging profile in low-cost electricity price intervals as well as a 56.6 % reduction in peak load compared to charging without management.

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.

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.

Electric vehicles mainly work in urban conditions. Due to frequent acceleration and deceleration, the driving and braking torques vary in a large range as well as the motor efficiency. Distributed drive electric vehicles allow for an independent and accurate torque control of each wheel. Based on that, a novel driving and regenerative braking regulation (DRBR) with respect to energy-saving is developed. Firstly, economy-based objective function is established to optimize the vehicle efficiency under driving conditions. Its solutions, traction distribution coefficient, are derived under the constraints of desired driving torque, current RPM and motor property. Then according to the ideal braking force distribution curve and ECE regulations, the regenerative braking regulation is proposed combining friction brake and motor brake. Therefore it can guarantee both the braking stability and the energy recovery. Finally, the driving and braking regulation is verified with computer simulations based on the worldwide harmonized light vehicles test procedures. The simulation results indicate that the presented approach improves vehicle efficiency significantly.

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