TRAFFIC FLOW CONTROL OF VEHICLES AND MOBILE EV FUEL CHARGING STATIONS

Description

[0001] Road traffic, primarily caused by cars and trucks, is increasingly reaching its capacity limits, not only in Germany but worldwide. Capacity limits mean that too many vehicles are participating in traffic for the existing infrastructure, especially the roads, resulting in frequent and lengthy traffic jams that lead to wasted time and additional energy expenditure. Particularly at certain "hotspots," smooth traffic flow is unfortunately more the exception than the rule. It is expected that these conditions will worsen rather than improve in the future. One of the reasons for this is the steadily increasing volume of traffic over the years and the influx of people into cities.Improving this situation by adding infrastructure, especially by building new roads and / or parking lots, is expensive, time-consuming and not always possible due to construction limitations.

[0002] A common cause of such traffic jams is hard braking, hard acceleration, insufficient or excessive distances between vehicles, poor anticipation of other vehicles' behavior, lane changes, and / or speed differences between vehicles. Even minor disruptions to the traffic flow can lead to waves of congestion during periods of high traffic volume, which then often develop into larger traffic jams – seemingly out of nowhere. Each of the actions described above disrupts traffic flow for following vehicles, and in the worst-case scenario, these disruptions can be compounded. Individual car and truck drivers are therefore often the biggest disruptive factor and thus the cause of the traffic jams. Studies show that the existing infrastructure would be capable of handling a significantly higher volume of traffic without the disruptive factor of "human" drivers. To make matters worse, every driver has their own individual "destinations."For example, if a driver has to cover the route from Cologne to Düsseldorf 10 minutes faster than other drivers, this inevitably leads to a difference in their speed.

[0003] Even if drivers were to improve in this respect and drive more smoothly, there are still limits to such improvement, as a single driver, for example, is unable to grasp the overall situation of a potential traffic jam. They can only focus on their immediate surroundings and have no overview or consideration of what is happening, for example, ten vehicles in front or behind them.

[0004] Due to environmental concerns and the finite nature of resources, vehicles will also undergo a shift in drive technology from conventional fuels to electric alternatives (e-mobility). Mobility and logistics are crucial aspects of our economic system and therefore of paramount importance. In the coming years, passenger cars with combustion engines will be gradually replaced by alternative drive technologies. Currently, electric cars are relegated to the sidelines due to their limited range and the incomplete charging infrastructure. With the anticipated and, in some cases, already available new battery technologies, electric cars with a range of approximately 600 km and a battery weight of 250 kg with a capacity of 75 kWh can be expected in the medium to long term. However, the question remains: how can an electric car's depleted battery be charged as efficiently and quickly as possible?

[0005] While fast charging stations exist for electric cars, their limited number means they must first be available, and charging takes significantly longer (approximately 30 minutes) than at a conventional petrol pump. In this regard, DE 10 2018 118 945 A1 describes a quick-swap system for electric car batteries.

[0006] Intelligent driver assistance systems, such as adaptive cruise control, are already well-established "precursors" to autonomous driving. It is generally accepted that it is only a matter of time before fully autonomous vehicles are available. Autonomous vehicles are already being used in public transport, specifically minibuses. It is already possible to send control commands to vehicles, which they then execute correctly. The current challenge lies in taking dynamic traffic situations into account in real time.

[0007] US Patent 2019 / 0164418 A1 discloses a method and system for maximizing traffic flow by combining classical machine learning to predict traffic flow minimization before it occurs and to optimize future vehicle positions. Vehicles are rerouted to minimize travel time for each vehicle, taking into account other vehicles on the road network.

[0008] US 2019 / 0351783 A1 describes a system for organizing mobile charging services for electric vehicles with a central "charging control server" that manages profiles / locations of charging units, monitors transactions, and communicates wirelessly with EVs. The doctrine mentions both stationary and mobile charging stations that can come to stranded vehicles or dynamically plan / coordinate rendezvous between EVs in motion and mobile charging stations.

[0009] The object of the invention is to provide a method, a system, a refueling unit and a vehicle that optimizes the driving time for vehicles.

[0010] This task is solved using the characteristics of independent claims.

[0011] According to a first aspect of the invention, a method for controlling the flow of traffic of vehicles, in particular passenger cars, on public roads is specified. The method comprises the following steps: Providing a central traffic flow control unit within a communication network and storing road infrastructure information on this central traffic flow control unit. This central traffic flow control unit can be, in particular, a cloud platform on the internet, designed to centrally collect information and evaluate it using an associated computing unit. The road infrastructure information can be stored, for example, using road maps, informing the central traffic flow control unit of where roads may have multiple lanes, where features such as roundabouts are present, and / or which traffic regulations apply at a given location.Furthermore, the infrastructure information can include details indicating the maximum number of vehicles that should be on the road per unit of distance without adversely affecting traffic flow. It is advantageous for this infrastructure information to be updated regularly. Establishing a data connection between vehicles traveling on the road and the central traffic flow control unit via the communication network; the vehicles being equipped to communicate with the communication network.

[0012] Within the scope of all aspects of this invention, a communication network is preferably a mobile communication network, particularly preferably a 5G-capable network.

[0013] The core idea of ​​the invention is that the vehicles transmit parameters, target and / or status parameters, to the central traffic flow control unit, and that an algorithm implemented on the central traffic flow control unit calculates an optimized traffic flow for all vehicles and an individual driving profile for each vehicle based on these parameters and infrastructure information. The individual driving profile is extracted from the optimized traffic flow. The individual driving profiles thus complement each other to form the optimized traffic flow. In particular, the vehicles can transmit their own target and / or status parameters. These status parameters include the current speed and / or the vehicle's position.

[0014] When calculating a model for optimal traffic flow, each vehicle, especially those with available status parameters, is considered a variable in the optimized traffic flow model. These variables can be assigned to different road options during model optimization. Particular attention is paid to the destination parameters—that is, where the vehicle wants to travel—so that the vehicle can only be assigned to other roads within the optimization process that increase the travel time and / or distance by no more than 10%, preferably no more than 5%. Furthermore, road infrastructure information is taken into account, allowing for simulations of the maximum number of vehicles that should travel on a given road length and their typical speeds.

[0015] Optimization can be performed using an algorithm to minimize the total travel time of all vehicles involved. This optimization can be calculated, for example, using a simulated annealing method. Simulated annealing provides a termination criterion for the optimization process when the total travel time of all vehicles involved has been minimized. One approach to this optimization process is to randomly regroup at least a subset of vehicles on the roads and examine whether this results in a reduction of the total travel time. If such a regrouping of a subset yields an improvement exceeding a predefined improvement threshold, the regrouped vehicles remain on their newly assigned roads, and the optimization continues with the remaining vehicles based on further subsets.

[0016] The idea behind the Simulated Annealing method can be visualized as follows: Imagine searching for the (global) lowest point in a two-dimensional landscape. The landscape itself consists of many depressions of varying depths. The simple search strategy (finding the nearest lowest point) corresponds to the behavior of a ball placed in this landscape. It rolls to the nearest local minimum and remains there. During the simulated cooling, the ball is repeatedly subjected to a push, which weakens as the "cooling" progresses. Ideally, this push is strong enough to move the ball out of a shallow depression (local minimum), but not strong enough to propel it out of the global minimum.

[0017] Since each vehicle is simulated as an object within the optimized traffic flow, the simulation of the object – i.e., its route – can be easily extracted and sent to the corresponding vehicle as an individual driving profile.

[0018] A vehicle within the scope of the invention can be, in particular, a passenger car or a truck. The parameters that the vehicle transmits to the central traffic control unit can, for example, be destination parameters indicating the location the road user wants to travel to and the desired arrival time. The status parameters can include the vehicle's position and speed vector, as well as those of other vehicles on the road. With this information, the algorithm of the central traffic control unit can gain a comprehensive overview of the traffic situation for all vehicles, or all vehicles participating in the process, and proactively calculate an optimal traffic flow for all vehicles. One possibility is to minimize the travel time for all vehicles.This can also be weighted in relation to the total distance, since a time loss of, for example, 10 minutes over 100 km is less significant than over 10 km. A 5G network can be advantageously used as the communication network, as it can be particularly well adapted to the requirements of the system and offers low latency. This predictive traffic management system preferably takes place on highways and expressways, as vehicles can travel at more consistent speeds in this scenario. The driver's individual driving profile can be displayed on their vehicle's screen as control commands. These commands could include, for example, how fast the driver should travel and which lane they should be in.

[0019] This method offers several advantages, including the generation of a smooth flow of traffic, which increases road capacity and allows vehicles to move faster on average.

[0020] A direct consequence of this is improved environmental protection through reduced traffic congestion and the resulting energy savings. Individual drivers, who are unable to oversee the entire traffic situation, can therefore use the control commands to drive as if they did.

[0021] Preferably, the individual driving profile is transmitted as a control command from the central traffic flow control unit to the vehicle assigned to it via the communication network.

[0022] This offers the advantage that the existing communication network can be used effectively to communicate control commands to the vehicles.

[0023] In one embodiment, the vehicle has an on-board computer that is configured to control the vehicle at least semi-automatically and that the on-board computer executes the control command.

[0024] This offers the advantage that the human factor, which is usually unable to follow the control commands 100%, can be replaced by the on-board computer, which controls the vehicle automatically. The more such on-board computers are installed in vehicles, the higher the compliance of the process, resulting in a better traffic flow.

[0025] The algorithm preferentially recalculates the optimized traffic flow when infrastructure information and / or parameters change. Such a change can occur, for example, when new vehicles join the traffic or when a vehicle already participating wants to change its destination.

[0026] This offers the advantage that the process can dynamically respond to and take into account changing traffic situations. An optimized traffic flow will therefore typically only have a limited validity period. In one implementation, the optimized traffic flow is recalculated in real time.

[0027] According to a second aspect of the invention, a traffic flow control system is provided, wherein the system is configured to carry out the previously described method. The system has the following features: a central traffic flow control unit, wherein the central traffic flow control unit is embedded in a communication network and wherein the central traffic flow control unit is configured to store infrastructure information and to establish data connections with vehicles; vehicles, wherein the vehicles are configured to establish a data connection with the central traffic flow control unit and to transmit parameters to the central traffic flow control unit, wherein an algorithm is implemented in the central traffic flow control unit which is configured to create an optimized traffic flow for the vehicles and an individual driving profile for each vehicle based on the parameters and the infrastructure information and to send this to the vehicles via the data connection.

[0028] According to a third aspect of the invention, a method for mobile refueling of vehicles, in particular passenger cars, with an electric drive is specified, comprising the following steps: Provision of the aforementioned system for controlling the flow of vehicles; provision of at least one mobile refueling unit on the roads, wherein the mobile refueling unit is equipped with charged, in particular standardized, battery modules. The mobile refueling unit is preferably a truck capable of charging and transporting several tons of exchangeable battery modules; transmission of a refueling request from a vehicle to the central traffic flow control unit.The refueling request can be actively submitted by the driver of a vehicle and / or the vehicle automatically monitors the charge level of its battery modules and can automatically submit the refueling request if predefined thresholds are undershot; creation of an initial individual refueling driving profile for the vehicle to be refueled by the algorithm implemented on the central traffic flow control unit and transmission of the initial refueling driving profile to the vehicle to be refueled; guiding the vehicle to be refueled to the mobile refueling unit using the initial individual refueling driving profile and initiating a refueling process by supplying / charging the vehicle's depleted battery modules with energy from the battery modules of the mobile refueling unit.

[0029] The mobile refueling unit can preferably exchange its depleted battery modules at central battery exchange stations, e.g., as described in DE 10 2018 118 945 A1. The central traffic flow control unit can determine the location of the vehicle to be refueled relative to the mobile refueling unit and the speed and direction of travel of both. Preferably, the central traffic flow control unit extracts the relevant data from the individual driving profiles of the vehicle and the mobile refueling unit. The algorithm then calculates the refueling driving profile such that, in a first step, the vehicle to be refueled approaches the refueling unit, preferably as quickly as possible, and in a second step, aligns its speed vector with that of the mobile refueling unit, thus enabling the vehicle to connect to the mobile refueling unit and for the charging process to begin.

[0030] This offers the advantage of avoiding lengthy charging processes and waiting times at stationary charging stations when the electric car's battery is depleted, allowing the vehicle to be charged efficiently and quickly while driving. Additionally, the mobile charging unit can carry standardized, charged battery modules for the electric car, which can be exchanged for the depleted battery modules at a meeting point, such as a parking lot.

[0031] Since the vehicle being refueled adapts to the optimized driving profile of the mobile refueling unit, the mobile refueling unit integrates seamlessly into the optimized traffic flow and avoids disrupting other road users, which could lead to a traffic jam. Within the scope of this invention, the terms mobile refueling unit and mobile refueling unit are to be understood as synonyms.

[0032] Preferably, the central traffic flow control unit creates a second refueling driving profile for the mobile refueling unit, in particular for a mobile refueling unit designed as a mobile e-charging station.

[0033] This offers the advantage that the vehicle to be refueled and the mobile refueling unit can approach each other even faster, as the vehicle is brought to the mobile refueling unit by the first refueling driver and the mobile refueling unit is brought to the vehicle by the second refueling driver.

[0034] Furthermore, it is possible to create a third charging profile for a second electric vehicle. These three charging profiles can then be optimized to minimize charging time, at least for the two electric vehicles and the mobile charging station. Parameters such as the desired charging amounts and / or the respective distance of the electric vehicles to the mobile charging station can be used to calculate this optimization.

[0035] According to a fourth aspect of the invention, a mobile refueling unit for mobile electric refueling of vehicles is specified, which is equipped to carry out the method described above.

[0036] According to a fifth aspect of the invention, a vehicle, in particular an e-car, is specified that is equipped for mobile electric refueling by the mobile refueling unit described above and / or that is suitable for carrying out one of the methods described above.

[0037] Preferred embodiments of the present invention are explained below with reference to the accompanying figures: Fig. 1: schematically shows the method for controlling the flow of vehicles in traffic. Fig. 2: schematically shows the method for mobile refueling of an electric car.

[0038] Numerous features of the present invention are explained in detail below with reference to preferred embodiments. The present disclosure is not limited to the specific combinations of features mentioned. Rather, the features mentioned here can be combined arbitrarily to form embodiments according to the invention, unless expressly excluded below.

[0039] Fig. 1 The diagram schematically illustrates the procedure for controlling the flow of vehicles in traffic. The procedure is described below and placed in its technical context.

[0040] With the technical possibilities of a 5G network, the increasing connectivity of new passenger cars and their intelligent assistance systems, up to and including autonomous vehicles, the technical foundations for the automation of traffic flow control have been laid.

[0041] Such vehicles 10 can be optimally controlled in road traffic 15. Furthermore, relevant vehicle data, such as position or speed, can be made transparent and transmitted on the network. Current concepts often still view the driver of the vehicle 10 as the determining factor, although analyses show that the driver is frequently the biggest disruptive factor in road traffic 15 ("Today everyone wants to achieve their individual goals on the road, and almost all those involved miss their goals precisely because of this!").

[0042] This is where automated traffic flow control comes in: Each vehicle 10 is connected to a cloud platform 20 that controls the traffic flow 15. This control system is preferably used on highways or multi-lane roads, but is also conceivable for more regional infrastructure. The driver can specify their route or destination and the desired average travel speed to the vehicle 10. The driver's request is one of many parameters that the cloud platform 20 uses to optimize and control the traffic flow 15.

[0043] The following parameters can also be used to calculate an optimized traffic flow 15 by an algorithm implemented on the cloud platform 20: • Traffic volume and density on the respective roads; • Inflow and outflow at on- and off-ramps; • Route infrastructure (e.g., number of lanes, speed limits); • Disruptions; • Traffic flow; • Use of respective lanes; • Requests of road users; • Average speed; • Position of vehicles; • Distances;

[0044] Stable traffic flows occur when many vehicles 10 travel at approximately the same speed, with optimally low distances on the traffic lanes, and preferably form groups 25 of several vehicles 10.

[0045] To ensure that traffic flow in the group 25 remains stable even during disruptions (e.g., on- or off-ramps), the group 25 should be controlled proactively. Since the cloud platform 25 for traffic flow control has access to almost all data from the vehicles 10, the groups 25 can be optimally controlled with a comprehensive overview (using the parameters described above).

[0046] This means that the traffic flow control intervenes in the control of individual vehicles 10 or cars 10 in order to optimally organize the groups 25. The driver thus relinquishes some control over the car 10 to the traffic flow control and benefits from the more optimal control of overall traffic, as congestion can be almost completely avoided.

[0047] Passenger cars 10 with fully automated assistance systems, which control the passenger car 10 after receiving control commands from the cloud platform 20 and taking driver wishes into account, therefore have the following advantages: A smoother traffic flow 15 is created, thereby creating more capacity on the roads and allowing the passenger cars 10 to move faster overall. Energy consumption is reduced, thus making a significant contribution to environmental protection. Driving on the roads is considerably more relaxed, which leads to greater road safety.

[0048] Depending on the traffic flow, the 25 traffic groups are intelligently assembled at various speeds (e.g., 80 km / h, 100 km / h, 120 km / h, 130 km / h) and sizes (number of vehicles) to ensure they complement each other optimally on the roadways and minimize mutual interference. The goal is to utilize the roadways with optimal high-flow conditions. The traffic flow control system modifies these configurations in real time, reacting to changes in relevant parameters. One possible parameter change is a significant increase in traffic volume, particularly during rush hour. A potential response is to proactively break up higher-speed groups (even if drivers want to travel faster) and merge them into slower groups (e.g., 80 km / h).Even if the car driver doesn't get his way at the moment to drive faster, he benefits "in the long term" because the optimized traffic flow brings all cars to their destination 10 times faster and with less congestion.

[0049] Since providers and users of the transport infrastructure benefit from this traffic flow control, it would be advantageous if as many or all vehicles as possible participated in the procedure.

[0050] Traffic flow management with intelligent assistance systems, up to and including autonomous vehicles, enables orderly, anticipatory driving in convoys. This, in turn, opens up new application possibilities within the convoy (> a "protected area" through traffic flow management). One of these is the one in Fig. 2 The "mobile e-charging station" shown is designed for charging electric cars on long journeys. Charging an electric car at a stationary fast-charging station is currently an unacceptable time commitment (30-60 minutes) for many drivers on long journeys. Therefore, the mobile e-charging station described below provides a technical solution that enables charging of an electric car while driving, thus eliminating the aforementioned time loss. In addition to the technical solution, this also represents a potential new business model for selling charging electricity and the associated special service.

[0051] The mobile e-charging station 50 is an autonomously controlled vehicle that travels on highways, preferably in a group at 80 km / h. Within this speed group, the mobile e-charging station 50 communicates with the cloud platform 20, allowing e-cars 55 to book charging time slots for fast charging (approx. 30 minutes while driving) in advance.

[0052] The following is a specific example: In this version, the e-charging station 50 can charge two e-cars 55 simultaneously.

[0053] According to German traffic regulations (StVO), the e-charging station 50, coupled with the e-cars 55, constitutes an articulated vehicle with a maximum overall length of 18.75 meters. The e-cars 55 should not exceed a maximum length of 5 meters and should have a ground clearance of at least 12 centimeters. The mobile e-charging station 50 is designed as a 7.5-ton vehicle and carries approximately 4 tons of swappable battery cells with a total capacity of approximately 1200 kWh. This allows the e-charging station 50 to recharge 12 vehicles (standard next-generation e-cars with a capacity of over 75 kWh, a 250 kg battery, and a range of approximately 600 km) in about 3 hours while driving, covering a distance of approximately 240 km. Subsequently, the e-charging station 50 must exchange its empty exchangeable battery cells for charged exchangeable battery cells during an intermediate stop at a service station (decentralized structures to recharge later exchanged batteries with renewable energies) and can then return to the motorway.

[0054] The battery replacement can be implemented technically as taught in DE 10 2018 118 945 A1.

[0055] With daily use of the autonomous e-charging station 50 from 5:00 to 21:00 (core hours), up to sixty e-cars 55 can be charged while driving.

[0056] One possible sequence of an e-refueling procedure is as follows: The e-refueling station 50 rolls in a pack at 80 km / h (see Fig. 1 ) and waits for customers to come to the store while driving.

[0057] Via the cloud platform 20, which can also control the charging stations 50 and is constantly in contact with them, electric cars 55 book charging time slots in advance for a fast charge (approx. 30 minutes while driving) along their route. The cloud platform 20 guides the electric cars 55 into the correct group of 80 during their journey, and the electric car 55 positions itself at a safe distance behind the charging station 50. Ideally, this is coordinated so that two electric cars 55 line up behind the charging station 50 in quick succession.

[0058] At charging station 50, both drawbars (A + B) are on the road and roll behind the charging station. Charging station 50 takes control of the electric car 55 by sending control commands for the charging process to the electric car's assistance systems via the 5G network – preferably using a secure and predefined protocol. Charging station 50 thus controls the docking process (including acceleration, deceleration, and direction).

[0059] The first electric car, 55a, is slowly moved towards the charging station, 50, and the drawbars. Monitored by sensors, the first electric car, 55, moves over a mechanical / electrical connection point on the drawbar, which is then automatically locked (secure mechanical and electrical connection). The electric car, 55a, is no longer moving under its own power but is being pulled by the drawbar. The charging process begins. Since the charging station, 50, still has full control over the electric car, 55a, the braking system is also coupled, resulting in a safe, controlled combination.

[0060] The same procedure is then carried out with the second e-car 55b, which is docked at the drawbar B. After approximately 30 minutes of fast charging (batteries charged to approximately 80%), during which both vehicles were towed as trailers (approximately 40 km), the automated docking maneuvers are performed in reverse order of undocking.

[0061] As soon as each e-car 55 is back at a safe distance from the e-charging station 50, full control is transferred to e-car 55 and the charging process is complete. The payment process is also fully automated. Once both e-cars 55a and 55b have regained control, the next charging cycle can begin with a new pair of e-cars.

[0062] While the electric cars are automatically locked to drawbars A and B, the drawbars retract due to the locking mechanism against the underbody of the electric cars, thus losing contact with the ground. This makes the combination even safer, as only the cars function as trailers. Drawbar A can be hydraulically retracted into the charging station 50 when the vehicle is empty or only one electric car is being used as a customer. In this case, only the shortened drawbar B remains on the road as a "small trailer" (approximately 3 meters long).

[0063] In the case of electric cars, in addition to intelligent assistance systems, a simple standardized locking mechanism and an electrical connecting element are preferably provided on the underbody of the vehicle to participate in the refueling procedure.

[0064] The e-Tank cloud platform plans the optimal connection point between the electric car and available charging stations along the route, taking into account the customer's journey and planned charging time window. This ensures that the charging process is initiated and completed relatively quickly. The actual time lost during a 30-minute fast charge at 80 km / h is roughly equivalent to a conventional refueling session for a combustion engine vehicle at a typical gas station (approximately 10 minutes). During the fast charging time, the electric car driver can, for example, read a newspaper and relax.

[0065] Another embodiment involves a short connecting unit that can be extended from the charging station to the electric car without ground contact. This would allow an electric car to be coupled and towed for fast charging. However, this also requires a standardized docking mechanism in the front of the electric car.

Claims

1. A method for mobile refueling of vehicles, in particular passenger cars, with an electric drive, comprising the following steps: Providing a system for controlling a traffic flow of vehicles, wherein the system comprises: a central traffic flow control unit (20), wherein the central traffic flow control unit (20) is embedded in a communication network (30), wherein the central traffic flow control unit (20) is configured to store infrastructure information and to establish data connections with vehicles (10); vehicles (10), wherein the vehicles (10) are configured to establish a data connection with the central traffic flow control unit (20) and to transmit parameters to the central traffic flow control unit (20), wherein the vehicles are configured to transmit destination and / or status parameters, namely a current speed and a position of the vehicle, to the central traffic flow control unit (20), wherein the central traffic flow control unit (20) comprises an algorithm configured to generate, based on the parameters and the infrastructure information, an optimized traffic flow (15) for the vehicles (10) and an individual driving profile for each vehicle (10), and to transmit these to the vehicles (10) via the data connection, wherein the algorithm is configured to calculate the optimization using a simulated annealing method that provides a termination criterion for the optimization process with respect to minimizing the total travel time of all participating vehicles, wherein the optimization is limited to an increase in the travel time and / or travel distance of any of the vehicles to no more than 5%; providing at least one mobile refueling unit (50), in particular a mobile e-refueling station (50), wherein the mobile refueling unit (50) is equipped with charged, in particular standardized, battery modules, Sending a refueling request from a vehicle (10) to the central traffic flow control unit (20), wherein the algorithm implemented on the central traffic flow control unit (20) creates a first refueling driving profile for the vehicle (10) to be refueled and transmits it to the vehicle to be refueled, wherein the first individual refueling driving profile guides the vehicle (10) to be refueled to the mobile refueling unit (50) and enables an electrical refueling process at the mobile refueling unit (50).

2. The method according to claim 1, characterized in that the central traffic flow control unit creates a second refueling driving profile for the mobile refueling unit (50).

3. The method according to any one of claims 1 to 2, characterized in that a plurality of vehicles are refueled simultaneously.

4. A mobile refueling unit for the mobile electric refueling of vehicles, configured to perform a method according to any one of claims 1-3.