The electrification of the transportation sector leads to an increased deployment of lithium-ion batteries in vehicles. Today, traction batteries are installed, for example, in electric cars, electric buses, and electric boats. These use-cases place different demands on the battery. In this work, simulated data from 60 electric cars and field data from 82 electric buses and six electric boats from Germany are used to quantify a set of stress factors relevant to battery operation and life expectancy depending on the mode of transportation. For this purpose, the open-source tool SimSES designed initially to simulate battery operation in stationary applications is extended toward analyzing mobile applications. It now allows users to simulate electric vehicles while driving and charging. The analyses of the three means of transportation show that electric buses, for example, consume between 1 and 1.5 kWh/km and that consumption is lowest at ambient temperatures around 20 °C. Electric buses are confronted with 0.4–1 equivalent full cycle per day, whereas the analyzed set of car batteries experience less than 0.18 and electric boats between 0.026 and 0.3 equivalent full cycles per day. Other parameters analyzed include mean state-of-charges, mean charging rates, and mean trip cycle depths. Beyond these evaluations, the battery parameters of the transportation means are compared with those of three stationary applications. We reveal that stationary storage systems in home storage and balancing power applications generate similar numbers of equivalent full cycles as electric buses, which indicates that similar batteries could be used in these applications. Furthermore, we simulate the influence of different charging strategies and show their severe impact on battery degradation stress factors in e-transportation. To facilitate widespread and diverse usage, all profile and analysis data relevant to this work is provided as open data as part of this work.
The electrification of transportation modes such as cars, buses, and boats offers the potential of providing vehicle-to-X services during idle times. Pools of vehicles can provide balancing power, trade on the electricity market, or be used for load peak shaving. In this work, the usage patterns of electric cars, electric buses, and electric boats are investigated, and the provision of vehicle-to-X with these vehicles is simulated using an open-source simulation tool. A data analysis and a vehicle usage pattern assessment show that especially private electric cars behave predictably at night. It also reveals that the vehicle-to-X availability varies over the week for all vehicle types and is highest at night for cars and buses. During the day on weekdays, private cars are available for vehicle-to-X 30 to 70% of the time, the analyzed buses 5 to 50% of the time, and the availability of the boats depends on their primary use as ferries or private boats. If the three transportation modes provide vehicle-to-X during idle times, the equivalent full cycles that the lithium-ion batteries complete increase at different rates depending on the vehicle pool size, while the mean charging rates decrease. Furthermore, an exemplary aging analysis shows that the additional load of vehicle-to-X provision slightly increases the capacity loss of the car batteries compared to a paused unidirectional charging strategy.