METHOD FOR PREPARING TO REFUEL A VEHICLE

Abstract

The invention relates to a method for preparing to refuel a tank in a vehicle with hydrogen, for which purpose the tank pressure is lowered in preparation for driving to a filling station, wherein the filling station is informed of the pending refueling. The method according to the invention is characterized in that the refueling takes place with liquid hydrogen, wherein the maximum achievable pressure level of the tank during refueling, the expected pressure level of the tank when the filling station is reached, and the expected refueling quantity are transmitted to the filling station.

Claims

1. A method for preparing to refuel a tank in a vehicle with hydrogen, for which purpose the tank pressure is lowered in preparation for driving to a filling station, wherein the filling station is informed about the pending refueling, wherein the refueling takes place with liquid hydrogen, wherein the maximum achievable pressure level of the tank during refueling, the expected pressure level of the tank when the filling station is reached, and the expected refueling quantity are transmitted the filling station.

2. The method according to claim 1, wherein specifications of the filling station are transmitted to the tank system of the vehicle from the filling station to the vehicle.

3. The method according to claim 1, wherein the selection of the filling station takes place on the basis of a route pre-planned on a vehicle-external server in a driving and refueling strategy module and is transmitted to the filling station and the vehicle-external server.

4. The method according to claim 3, wherein the driving and refueling strategy module is formed by a cloud.

5. The method according to claim 3, wherein the driving and refueling strategy module calculates different variants for refueling on the basis of a model-supported prediction of the tank state, which consists of pressure, temperature, and refueling quantity, and creates an optimized strategy with regard to the pressure in the tank and the selection of filling station.

6. The method according to claim 5, wherein in the case of the optimized strategy, future use of the vehicle on the pre-planned route after refueling is also taken into account.

7. The method according to claim 5, wherein further external data on states of the route from at least one additional external module is taken into account in the optimal strategy.

8. The method according to claim 5, wherein the optimized strategy is transmitted to the vehicle, the vehicle-external server, and the filling station.

9. The method according to claim 1, wherein the pressure reduction takes place by consumption of hydrogen, for which purpose drive energy is made available primarily from the hydrogen and/or a traction battery is recharged and/or secondary consumers of the vehicle are operated.

10. The method according to claim 1, wherein the pressure reduction is carried out at least partially by the generation and grid feed-in of electrical energy when the vehicle is at a standstill.

11. The method according to claim 2, wherein the selection of the filling station takes place on the basis of a route pre-planned on a vehicle-external server in a driving and refueling strategy module and is transmitted to the filling station and the vehicle-external server.

12. The method according to claim 4, wherein the driving and refueling strategy module calculates different variants for refueling on the basis of a model-supported prediction of the tank state, which consists of pressure, temperature, and refueling quantity, and creates an optimized strategy with regard to the pressure in the tank and the selection of filling station .

13. The method according to claim 6, wherein further external data on states of the route from at least one additional external module is taken into account in the optimal strategy.

14. The method according to claim 6, wherein the optimized strategy is transmitted to the vehicle, the vehicle-external server, and the filling station.

15. The method according to claim 7, wherein the optimized strategy is transmitted to the vehicle, the vehicle-external server, and the filling station.

16. The method according to claim 2, wherein the pressure reduction takes place by consumption of hydrogen, for which purpose drive energy is made available primarily from the hydrogen and/or a traction battery is recharged and/or secondary consumers of the vehicle are operated.

17. The method according to claim 3, wherein the pressure reduction takes place by consumption of hydrogen, for which purpose drive energy is made available primarily from the hydrogen and/or a traction battery is recharged and/or secondary consumers of the vehicle are operated.

18. The method according to claim 4, wherein the pressure reduction takes place by consumption of hydrogen, for which purpose drive energy is made available primarily from the hydrogen and/or a traction battery is recharged and/or secondary consumers of the vehicle are operated.

19. The method according to claim 2, wherein the pressure reduction is carried out at least partially by the generation and grid feed-in of electrical energy when the vehicle is at a standstill.

20. The method according to claim 3, wherein the pressure reduction is carried out at least partially by the generation and grid feed-in of electrical energy when the vehicle is at a standstill.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Further advantageous designs of the method according to the invention also result from the exemplary embodiment, which is described in more detail hereinafter with reference to the figure.

[0019] FIG. 1. is a block diagram of a system on which the method is based.

DETAILED DESCRIPTION

[0020] A possible detailed sequence of the method according to the invention is described below with reference to this block diagram, without restricting the method to this. A first step in this case is logistics planning in the box labeled 1 here, which is carried out by a fleet operator of a fleet of vehicles, in particular commercial vehicles. In general, this logistics planning 1 is carried out in a so-called transport management system. Transport orders are linked to individual vehicles 2 and their drivers in this case. Furthermore, time and route planning is carried out for the respective vehicle 2. The data packet created in this way in logistics planning 1 typically contains the route data, i.e. the coordinates of the individual sections, a schedule with departure times, loading and unloading times, break times, and the like. In addition, information about the vehicle 2, for example various vehicle parameters, its equipment, its vehicle identification number, and the like, is stored in the data packet. The data packet also contains data on the driver and the vehicle's cargo, and here in particular its weight.

[0021] This data packet is transmitted to a driving and refueling strategy module 3 via the communication labeled la and received there via a data interface 3.1. It is then further processed in a driving prediction module 3.3. Consistent with the information about the vehicle 2 from the data packet transmitted via communication la, data about the vehicle 2 is requested via communication 2a/2b, via a further interface module 3.2, or read out using a communication module 2.1 of the vehicle 2. This includes, for example, physical measured values of the liquid gas tank 2.3, for example pressure, temperature, and refueling quantity, which are recorded by a tank control module 2.4, as well as the state of charge of any traction batteries 2.8 or other energy storage devices that may be present. Using the logistics planning data 1a and the vehicle data 2a, the driving prediction module 3.3 of the driving and refueling strategy module 3 then calculates the energy requirement and other vehicle states on the planned route with the planned vehicle, its cargo, the measured values of its liquid gas tank 2.3, and the like. In this case, the traffic influences, such as possibly the driver, the topography, the weather, and the traffic infrastructure, are also taken into account accordingly. Via additional modules 4, this information can be requested as data packets via path 4b and/or retrieved via path 4a, for example, in the form of weather information 4.1 and/or traffic information 4.2. With the calculated results of the driving prediction module 3.3, a tank state prediction module 3.4 can calculate the consumption of the liquid hydrogen in the liquid gas tank 2.3 and, furthermore, also estimate the future state of the liquid gas tank 2.3 with regard to pressure, temperature, and fill level.

[0022] These results of the tank state prediction module 3.4 are then supplied to a refueling strategy module 3.5, which uses them to determine an optimal refueling strategy. In this case, the refueling strategy comprises the determination of the times or the appropriate filling stations 5 based on the planned route, the vehicle and time planning, as well as the precalculated energy consumption or the resulting range of the remaining energy available in the liquid gas tank 2.3 and possibly other energy storage devices 2.8. In addition, an availability or reservation of a time slot at a filling station 5 can be carried out by asking the filling station operator according to communication 5a/5b.

[0023] If an optimal refueling strategy has then been determined, if necessary by calculating and evaluating several strategies accordingly, then this is communicated accordingly to the fleet operator or dispatcher in logistics planning 1, to the vehicle 2, or to its driver, and to the operator of the selected filling station 5. In addition to displaying the determined refueling strategy, for example, in the vehicle 2 to inform the driver, in particular via a navigation device and an associated display, the refueling strategy, i.e. the time and route information, is forwarded to a central drive control unit 2.2 of the vehicle in advance of the planned refueling via the interface 2.1. The control unit specifies an operating strategy for the vehicle 2. Knowing the point in time at which the filling station 5 is reached for refueling and the calculated power requirement on the known route to get there, the operating strategy can then increase the consumption of liquid hydrogen in advance of the planned refueling in such a way that the pressure in the tank 2.3 drops as much as possible before the filling station 5 is reached. This can be done, for example, by a timely increase in fuel consumption by a fuel cell 2.6 in the vehicle 2, wherein the expected secondary consumers or their energy requirements and the energy requirements of the trip itself can be considered while taking into account the state of charge of an electric battery 2.8. Boxes 2.5 and 2.7 show the control units assigned to the fuel cell 2.6 and the battery 2.8.

[0024] In addition, it is the case that a pressure drop in the tank 2.3 can also take place via other consumers and in particular also when the vehicle is parked, or it can be initiated by the driver of the vehicle 2. The vehicle can be influenced either directly or via a remote control or an app or indirectly via logistics planning 1. Hydrogen can then be used, for example, to charge the battery 2.8 even while it is stationary, to precondition the cabin temperature of the vehicle 2, to cool the battery 2.8, or to cool the cargo in a refrigerated body. Other secondary consumers such as air compressors can also be controlled in order to fill compressed air tanks and thereby consume energy and lower the pressure in the tank 2.3. Of course, these aspects can also be implemented while the vehicle 2 is being driven.

[0025] A further alternative, and this is only possible when the vehicle 2 is stationary, is to connect it, via a corresponding charging plug, to a charging station, which in turn is connected to a power grid. This charging station, which enables a return of the charge from the vehicle 2 or its fuel cell 2.6 and/or battery 2.8 back to the power grid, can then be used to generate electricity from hydrogen with the fuel cell 2.6 and to supply it to the stationary power grid. This also allows the pressure in the tank 2.3 to be lowered, for example, immediately before a filling station 5 that is being approached as the trip continues, in order to optimize the refueling process. The electricity fed in can be reimbursed accordingly. If the fueled gas was generated regeneratively, this electricity can also be classified as regeneratively generated “green” electricity, fed in, and billed accordingly.

[0026] To determine the actual refueling strategy in the refueling strategy module 3.5, various optimization methods are then conceivable, since various options with filling stations at different distances corresponding to the consumption and states to be expected up to that point can be used according to the tank state prediction module 3.4 and/or the driving prediction module 3.3. The aim of the optimization must be to enable the most efficient strategy possible with the lowest possible energy and time losses and optimal costs. Therefore, prices for the fuel which have previously been obtained, for example, from the filling station operator and/or logistics planning 1 can also possibly be included in the strategy. In the case of feeding electrical energy into a grid as described above, the level of feed-in reimbursement that can be achieved can also be included in this strategy.

[0027] As already mentioned, the refueling strategy determined to be optimal is then communicated accordingly to the participants, i.e. the scheduler in logistics planning 1, the vehicle 2 or the driver, and the selected filling station operator. The information can be transmitted directly or indirectly, for example in that the vehicle itself only communicates with logistics planning 1 or the module 3 and all other steps are initiated from there.

[0028] The data, which are then transmitted from the vehicle 2 to the filling station 5 of the selected filling station operator, contain the feasible pressure level of the tank 3.2, i.e. the maximum pressure possible during refueling, and the expected tank quantity, which is communicated via the communication between the module 3 and the vehicle 2, as well as the transmission of the data to the filling station 5, so that preparation can already be made for the refueling process at the filling station 5. In addition, transmission in the opposite direction is also conceivable, for example in order to transmit specifications from the filling station 5 to the vehicle 2, which also contributes to optimizing the refueling.