DE102018210766A1 - Generation of a fuel demand map using a remaining vehicle range - Google Patents

Abstract

The invention relates to a method for generating a fuel requirement map using a remaining vehicle range, and to using the method for estimating regional energy requirements and a computer program product for executing the method. In the first step 100 of the method, motor vehicles 3 are selected on the basis of a first tank fill level X; In the second step 200, specific points 13 are determined on a road map 1 using a second tank fill level Y; In the third step 300, the specific points 13 are weighted by means of probability of occurrence; In the fourth step 400, the road map 1 is tiled; in the fifth step 500, the fuel demand map 2 is generated by weighting each tile 21; In the sixth step 600, the fuel demand map 2 is completed. The method enables infrastructure planning for the fuel supply of motor vehicles with different types of drive in a predetermined area in a simple and inexpensive manner.

Description

The invention relates to a method for generating a fuel demand map using a remaining vehicle range and to using the method for estimating regional energy requirements and a computer program product for executing the method.

Road traffic, or more precisely motor vehicle traffic, is of central economic importance among the various traffic systems. In order to do justice to this importance, in addition to suitable local, regional and supraregional road networks, an appropriate infrastructure for the fuel supply of vehicles equipped with different types of drive is required.

While the petrol and diesel fuel available today is largely guaranteed by today's petrol stations in most industrialized countries, there are so far only comparatively few petrol stations that offer alternative liquid fuels such as ethanol, liquid gas or liquid hydrogen, or gaseous fuels such as natural gas or gaseous hydrogen , offer, or have charging stations for refueling or charging electric vehicles.

Not least because of the stricter legal requirements for the release of pollutants by conventional diesel and petrol engines in all industrialized countries, the demand for the alternative fuels and drive technologies mentioned is growing and in the meantime vehicles with these drives are also available to serve this demand at competitive conditions. On the one hand, a need-based fuel supply for these new vehicle fleets must be ensured and, on the other hand, a change in demand for petrol and diesel fuel must be taken into account.

New service stations are usually planned based on traffic flows and population densities. To do this, the vehicle density in a target area is estimated. Based on this estimate, possible locations on sections of the route with the highest traffic densities are determined, from which a location is then determined for the construction of a new petrol station. Planning procedures, which mainly focus on traffic flows and population densities, leave unanswered questions about optimal plant utilization and the number of fuel and charging stations required in detail. In this respect, these methods are only suitable for rough planning and, due to the limited database, are not suitable for detailed infrastructure planning of petrol stations and charging stations.

However, planning based on tank information that is transmitted to a backend server during the refueling process and that, over a longer period of time, provides an exact picture of the fuel demand at a particular location is only of limited use for the infrastructure planning of fuel supply systems. On this basis, the tank behavior can be predicted with sufficient accuracy at the location in question. However, it is questionable whether this location is an optimal location with regard to the development of fuel demand within a target region.

Furthermore, the vehicle and personal data obtained from the operation of test fleets, which in individual cases can include several hundred vehicles, can be used for the planning of petrol stations and charging stations. Although the individual data relevant for fuel demand forecasts can be filtered out from the existing data stock, this method has a decisive cost disadvantage, not only in the type of data collection, but in particular also in the effort required for the transfer, storage and evaluation of the collected data is justified.

Further methods for providing data for energy demand planning for motor vehicles are known in detail from the following published documents.

After one in the DE 10 2015 221 292 A1 disclosed data collection method, vehicle data is transmitted in real time via a wireless network in that not every vehicle transmits all data over the wireless network, but rather by distributing it over several alternative data collection vehicles, so that network congestion is avoided. The vehicle data collected in this way are linked in a data collection server and made available, for example, in the form of a position and route information for a vehicle. Although the data available in this way are suitable for fuel requirement planning, this method is also very complex and cost-intensive, due to the high computing requirements for the selection of the data collection vehicles and the necessary data linkage on the backend server.

A method in which the position data of a large number of vehicles is recorded over a period of up to several months and evaluated in a data center is in the DE 10 2015 008 968 A1 described. Using a location unit, communication unit and digital Road maps are used to generate traffic load statistics in a data center based on the position information of each vehicle recorded and a route planning optimized for consumption is provided using the vehicle consumption values recorded. With the vehicle data obtained and provided according to this method, average consumption values for routes defined according to departure and destination are available.

The creation of an energy demand forecast for an energy network with locally distributed charging stations for electric vehicles based on a driving profile of an electric vehicle is from DE 10 2010 027 726 A1 known. According to the method disclosed therein, position information, travel distances, travel speeds and consumption values, possibly taking into account the current state of charge of the battery, are recorded in a driving profile, on the basis of which the respective service life periods with the possibility of charging are determined. From the recorded driving profiles of a vehicle fleet, an energy demand forecast is then created in a central data center, according to which a power provider can control the energy required for the operation of the vehicle fleet in terms of space and time, and in particular while avoiding peak loads in the power grid. This method therefore only enables the efficient provision of electricity for electric vehicles in an existing power grid.

From the DE 10 2013 202 059 A1 Finally, a method for optimizing a charging infrastructure for electric vehicles is known, which enables the optimal number of locations for charging stations to be selected within an area. For this purpose, the data from vehicle sensors, navigation systems, on-board diagnostic sensors, the individual call verification data from cell phones as well as the signals from cell phone masts, GPS units and induction loops within a target area are evaluated and classified according to vehicle types in a map adaptation module with route, time and area information Estimation of the spatial-temporal charging requirements mapped. With further consideration of geographic, economic and regulation-related boundary conditions, possible locations for charging stations are then determined. This method is therefore limited to the operation of electric vehicles. In addition, the extensive data acquisition places considerable demands on the transmission and processing of the data obtained and is therefore also associated with considerable costs.

Overall, none of the known methods enables an efficient and cost-effective recording of the fuel requirement of vehicles within a certain area that require different fuels due to different types of drive. It is also not possible with any of the known methods to forecast the regional total energy requirement required for the operation of motor vehicles with different types of drive. In particular, the known prior art does not provide any clue as to how appropriate infrastructure planning for a reliable fuel supply for such motor vehicles can be ensured in an area in the most efficient manner.

So that all motor vehicles within an area can be reliably supplied with the required fuel if necessary, the locations of petrol stations should be located so that they can be reached by as many vehicles as possible before the fuel runs out. On the other hand, all the fuels that are required to operate vehicles with different types of drive within the area should be offered at the petrol stations. It is therefore desirable to take into account not only the actual traffic flows, but also the type of fuel, in addition to the actual traffic flows, when planning the infrastructure for the fuel supply of motor vehicles within an area.

The aim of the present invention is to provide a method which is suitable for overcoming the disadvantages of the prior art and which enables infrastructure planning for the fuel supply of motor vehicles with different types of drive in a predetermined area in a simple and inexpensive manner.

The object of the invention is achieved by the subject matter of the independent claims. Preferred developments are the subject of the dependent claims.

A first aspect of the present invention relates to a method for generating a fuel demand map for a motor vehicle using a remaining vehicle range, which has the method steps described below. The term fuel is to be understood in the broadest sense to mean all fuels that are carried by a motor vehicle to drive it in a suitable storage or tank.

Suitable fuels for carrying out the method according to the invention thus include all liquid fuels, in particular gasoline, diesel, ethanol, liquid gas or liquid hydrogen, just like all gaseous fuels, in particular natural gas or gaseous hydrogen, but also those by means of an accumulator Operation of an electric vehicle provided electricity. The term vehicle range denotes the maximum distance that a motor vehicle can travel with a currently carried amount of fuel without refueling. A fuel demand map thus designates a map which, in addition to the road courses to be traveled by a motor vehicle, also contains information on the tank or charging requirements.

In a first method step, vehicles are selected whose tank level falls below a first tank level X. A tank level X therefore stands for an incomplete tank filling or for a fuel tank that is no longer completely filled, and can e.g. Amount to 10 I.

In a second method step, all concrete points on possible route sections are determined on a road map, at which each of the vehicles selected in the first method step still has a second tank level Y in relation to its current position and its current tank level, which is reduced compared to the first tank level X , A specific point is thus to be understood as a precisely ascertainable geographical position of a motor vehicle on a road, which forms or can potentially form at least part of the route of the vehicle. A tank level Y stands for a fuel tank that has not yet been completely emptied and can e.g. 7 liters.

In a third method step, each of the specific points previously determined for a selected vehicle is then weighted in that it is assigned an occurrence probability with which the vehicle is likely to reach each of the specific points assigned to it. The travel route of a vehicle that leads into a region via a road that branches off at several points in the further course can potentially extend at each of these branch points or nodes via one of the branching roads. There is therefore a certain probability for each of these continuing roads to become part of the vehicle's route. If the route selection is not subject to any other criteria and a total of N further roads are available, the probability that the vehicle will continue on one of these roads is 1 / N.

In the context of the method according to the invention, this probability is referred to as the probability of occurrence with which a specific point is weighted.

The road map is then tiled in a fourth method step, as a result of which all weighted concrete points are assigned to the respective corresponding tiles. With the subdivision of a target area encompassed by the road map into tiles, there is a clear regional assignment of all determined concrete points according to their respective geographical location or position. Through the fourth process step, the total fuel requirement of the target area is broken down according to its regional origin. Since both the scale of the road map and the size of the tiles are freely selectable and can be optimally adapted to the accuracy required when determining the fuel requirements, tiling a target area is of particular advantage when planning and optimizing petrol stations and charging stations ,

In a further, fifth method step, each tile is now weighted by summing the probability of occurrence of the vehicles assigned to it. The weighting of each tile, or each of the grid fields placed on the road map, is thus carried out by adding up the probability of occurrence of all concrete points placed in the respective tile, which have been previously determined for a particular vehicle. By tiling and stating the weight of each tile, the road map becomes a fuel demand map. This fuel demand map generated according to the invention enables, in addition to a problem-free and unambiguous identification of regions with fuel demand, in particular also a quantitative differentiation of the regions according to the amount of the existing fuel demand on the basis of the given weights.

Finally, in a sixth process step, the fuel demand map is completed by displaying all weighted tiles on the road map, preferably stating the number of vehicles on which the fuel demand illustrated by the weighted tiles is based. This type of labeling confirms the validity of the data collection and ensures that relevant regions or tiles can be identified quickly and easily using the fuel demand map. The completed fuel demand map is preferably provided as a computer program product on a backend server, on a computer readable storage medium or in paper form.

The method according to the invention thus advantageously makes it possible to provide maps from which the fuel requirement for motor vehicle traffic, that is to say the energy requirement for the operation of motor vehicles, can be found broken down by region, without being restricted to a special type of drive. To this extent, these maps are immediately suitable as a basis for planning new fuel supply systems for Motor vehicles or petrol stations as well as for the optimization of an existing petrol station network. The tiled representation of the fuel requirements in the maps enables potential target regions to be identified quickly and easily and, moreover, can be easily adapted to the respective requirements by simply selecting the map scale and the tile size accordingly.

The vehicle data otherwise required for carrying out the method according to the invention are preferably recorded using suitable sensor means in the motor vehicle and forwarded via a communication unit to a back-end server for carrying out the required calculations with the aid of maps. Although this type of vehicle data determination and processing is preferred within the scope of the invention, it is nevertheless not absolutely necessary for successful process management; all required input data can also be easily recorded in the conventional way using the usual on-board means of a vehicle, such as a distance and tank level indicator on a display on the dashboard.

Further preferred embodiments of the invention result from the other features mentioned in the subclaims. The various embodiments mentioned in this application can be advantageously combined unless otherwise stated in the individual case.

According to the method according to the invention, the fuel demand map is generated in a first particularly preferred embodiment for a motor vehicle with an internal combustion engine. The first and second tank fill levels X, Y correspond to a first and a second residual amount of a liquid fuel which is carried in a fuel tank of a respective motor vehicle with such a drive. The liquid fuel is preferably gasoline, diesel, ethanol, liquid gas or liquid hydrogen. In addition, it can be a gaseous fuel, preferably natural gas or gaseous hydrogen. The internal combustion engine is in any case suitably adapted for operation with the respective liquid or gaseous fuel. In this respect, a first tank level X can correspond, for example, to a first remaining amount of a liquid fuel of 10 l and a second tank level Y, a second remaining amount of this fuel, e.g. 7 l.

In a second particularly preferred embodiment of the method according to the invention, the fuel demand map for a motor vehicle with an electric motor is generated. In this case, a first tank fill level X corresponds to a first remaining amount of a current, while a second tank fill level Y corresponds to a second remaining amount of a current, which is removably carried in an accumulator included in the vehicle for the operation of the electric vehicle. The tank fill level is specified in kWh, corresponding to the energy still available in the accumulator.

In a further preferred embodiment of the method according to the invention, the first tank fill level X is preferably dimensioned such that it is highly likely that a fuel supply will be necessary either during the current or at least during the next trip of a vehicle. A fuel supply, or refueling or reloading, is considered necessary if a tank level Y is reached during the current or at least during the next trip of the vehicle. Whether there is a high probability of this is preferably determined using the data on the previous tank behavior stored for the respective motor vehicle.

Alternatively, it is possible and preferred to determine the first and second tank fill levels X, Y in a navigation system of a motor vehicle in question. In this case, fuel is supplied when it is signaled by the vehicle's navigation system. The current point at which refueling or reloading is required is defined in this case using the vehicle's on-board navigation system.

In a very particularly preferred embodiment of the method, each specific point is weighted in the third method step in that the sum of all possible route sections or route variants that were determined for the vehicle in the second method step is formed and the reciprocal value is then determined therefrom. 1 / N thus indicates the probability of occurrence for a specific point of a vehicle, where N denotes the number of all possible route sections or route variants on a road map on which a selected vehicle, based on its current position and its current fuel level, at a respective specific point has the second tank level Y. Each concrete point defined in this way represents a place where a fuel supply or refueling is required. The explanations already given in connection with the third method step, regarding the probability of occurrence, are still valid for this advantageous method.

Furthermore, it is preferred to weight those determined after the third method step and weighted according to the number of possible route variants Weighting the probability of occurrence even further by taking into account the traffic route category, or road class, of each of the possible route variants. For this purpose, the probability of occurrence is multiplied by a key figure, which is dimensioned according to the category of the traffic route in question, over which a respective route section leads with a specific point. A categorization of the traffic routes used according to the road construction load, and thus a differentiation according to federal highways, federal highways, state highways, district highways and municipal highways, is particularly preferred to weight the procedural probability of occurrence. Obviously, the likelihood that a vehicle will turn off a larger road, such as a freeway or a main road, after a short drive is significantly less than is the case with a smaller road, such as a municipal road. The street classes mentioned can use the numbers, for example 1 to 5 assigned, where 5 for a federal highway and 1 stands for a community road.

In addition, it is preferred to further weight the entry probabilities determined after the third method step and weighted according to the number of possible route variants by taking into account the tank information available for the respective vehicle. In this case, the probability of occurrence is multiplied by the percentage of the current amount of fuel. If, for example, the tank is still a third full at a specific point, the further weighting is carried out by multiplying the probability of occurrence by a factor of 0.3.

In a likewise preferred embodiment of the method according to the invention, the second tank level Y determined in the second method step is determined as the mean value of the tank levels of all selected vehicles with a fuel supply, on the basis of which the specific points for the individual vehicles are then determined. For this purpose, the mean value calculation is carried out in the known advantageous manner on a back-end server which, as described at the beginning, communicates with each of the vehicles via a suitable data connection. Since this method variant therefore takes into account the actual tank behavior of a large number of different vehicles, the mean value derived therefrom for the second tank level Y is particularly suitable for the fuel requirement analysis according to the invention. However, it must be taken into account here that this averaged tank fill level relates to locations at which a fuel suitable for the respective motor vehicle is already available and which as such need not necessarily be optimally located.

In a further preferred embodiment of the method according to the invention, the second tank level Y determined in the second method step is determined on the basis of available tank information of the respective selected vehicle as the mean value of the tank levels when this vehicle is supplied with fuel. This limitation of the database to the vehicle in question obviously reduces the validity of the second tank level Y thus determined for the fuel demand forecast according to the invention in comparison with the previously described method variant. However, this restriction has an advantageous effect with regard to the procedural costs. The above information regarding the location of the data collection also applies in the same way if the data collection is restricted to the vehicle in question.

In a further preferred method variant, the determination of the specific points on possible route sections based on the two tank fill level Y at the route section actually traveled by the vehicle in question, based on the position detected by a navigation system of the vehicle, is carried out according to the two aforementioned preferred embodiments of the method according to the invention which is followed by a fuel supply. It is therefore unnecessary to use the second tank level Y when determining the specific point for the current route section.

In a further, particularly preferred embodiment of the method, the specific points on the road map at which the second tank level Y is reached are determined on the basis of available tank information of all vehicles using a probability density function. The specific points at which a fuel supply is required and the respective position of which is defined by reaching the second tank fill level Y in accordance with the advantageous method variants described above are replaced by a probability density function for the fuel supply in this method variant. Compared to the discrete tank levels X, Y, the recorded tank and charging events are shown in a continuous function. Compared to the forecasts made on the basis of discrete tank fill levels, the fuel demand forecasts created using this method are characterized by their higher accuracy, which, however, goes hand in hand with a significantly increased data processing effort on a backend server. If the method according to the invention is carried out according to this variant, the subsequent method steps have to be adapted accordingly.

In a further preferred embodiment of the method according to the invention, the first tank fill level X in the first and second process step and the second tank fill level Y in the second process step are replaced as process parameters by a first or second remaining range. According to this method variant, the vehicles are selected in the first method step and all specific points are determined in the further method steps and preferred embodiments on the basis of the remaining ranges of the vehicles. The criterion for the selection of a vehicle in the first method step is that the first remaining range X is undershot, which is predetermined, for example, as 50 km. The criterion for determining the specific points in the second method step is the achievement of a second, predetermined, remaining range Y, which is reduced compared to the first remaining range X. Starting from the above-mentioned definition of the term vehicle range, a remaining range is a maximum travel distance that a motor vehicle can cover with a currently carried amount of fuel before refueling is required. The process parameters tank level and range are therefore to be regarded as equivalent with regard to their respective effect in the process according to the invention. The use of both features to define the method according to the invention takes into account the customary use of the language, according to which tank fuel levels are usually referred to in connection with internal combustion engines, while it is customary to speak of ranges in connection with electric motors.

In a further preferred embodiment of the method according to the invention, the fuel demand map is generated at different times of the day. With this time of day-specific data acquisition, the tank and / or charging requirements that change over the course of the day can be recorded even more precisely in a target area, which further increases the forecast quality for the fuel requirement that can be achieved with the method according to the invention.

According to a last preferred embodiment of the method according to the invention, the resolution of the road map and the size of the tiles are determined in the fourth method step in accordance with a desired regional breakdown of the fuel requirements of an area. These adaptations enable a further increase in the forecast quality to be achieved with the invention, since in particular the tank and charging requirements in small target areas can be predicted in this way.

Another aspect of the invention relates to the use of the method according to the invention for the assessment of regional energy requirements, in particular for the assessment of regional energy transports via a power grid. Each tile in the fuel demand map created according to the invention represents a region within a larger geographical area with the associated tank and charging requirements of all motor vehicles with different drive types and thus enables the energy requirement of all vehicles with different drives within a region to be estimated. In addition, with the fuel demand map drawn up according to the method according to the invention, it is also possible to make a statement about a partial energy requirement, and in particular about the electricity requirement, within a region which arises from the operation of the respective motor vehicles. The estimation of the electricity demand or charging energy requirement is of particular importance for an electricity supplier, who is thus given a simple and efficient means to provide the charging energy required within his electricity network in an economical and needs-based manner.

Finally, a further aspect of the invention relates to a computer program product which comprises commands, when executed by a computer, the computer is caused to carry out a method according to the invention as described above. Yet another aspect of the invention relates to a computer-readable storage medium, comprising a computer program product, which comprises commands, when executed by a computer, the computer is prompted to carry out a method according to the invention, as described above. The storage medium can be volatile memory or non-volatile memory.

• 1 ein schematisches Ablaufdiagramm eines erfindungsgemäßen Verfahrens;
• 2 eine Straßenkarte mit drei Fahrzeugen, ausgewählt nach einem ersten Verfahrensschritt;
• 3 eine Straßenkarte gemäß 2 mit konkreten Punkten für ein Fahrzeug, ermittelt nach einem zweiten Verfahrensschritt;
• 4 eine Straßenkarte gemäß 2 mit konkreten Punkten für drei Fahrzeuge, jeweils gewichtet nach einem dritten Verfahrensschritt;
• 5 eine Treibstoffbedarfslandkarte mit drei Fahrzeugen und Kacheln, jeweils gewichtet nach einem fünften Verfahrensschritt;
• 6 eine Treibstoffbedarfslandkarte gemäß 5 mit einer Vielzahl von Fahrzeugen und Kacheln, jeweils gewichtet nach einem fünften Verfahrensschritt.

The invention is explained in more detail below in exemplary embodiments with reference to the associated drawings. Show it:

• 1 a schematic flow diagram of a method according to the invention;
• 2 a road map with three vehicles selected after a first process step;
• 3 a road map according to 2 with specific points for a vehicle, determined after a second process step;
• 4 a road map according to 2 with specific points for three vehicles, each weighted according to a third procedural step;
• 5 a fuel demand map with three vehicles and tiles, each weighted according to a fifth process step;
• 6 a fuel demand map according to 5 with a large number of vehicles and tiles, each weighted according to a fifth process step.

1 shows a schematic flow diagram of a method according to the invention, which is preferably carried out with an electronic data acquisition and communication unit in a motor vehicle, which is connected to a back-end server via a mobile communication network. In the 1 Process steps shown to generate a fuel demand map 2 are to be described below with reference to the in the 2 to 6 illustrated examples are explained in more detail.

In a first step 100 become the motor vehicles 3 within a target area on a road map 1 selected, the current tank level of which falls below a first tank level X, for example 10 I. The target area is predetermined here and includes the region for which a fuel demand map is provided 2 should be created. The specification of a fuel quantity of e.g. 10 1 as a selection criterion for a motor vehicle, depending on the size of the target area, it is preferably determined such that a refueling stop must still be made during the current trip, but at least during the next trip within the target area. On the basis of the current GPS position data and tank information transmitted from each vehicle to a back-end server in a known manner via a mobile communication network, the back-end server is used to select the map for creating the fuel requirement map 2 suitable vehicles according to the specifications. Only the vehicles selected in this way will be taken into account in the further process. By restricting the vehicle collective to be taken into account for recording the fuel requirement on the basis of the two selection criteria, the vehicle collective can be used to compile the fuel requirement map 2 required data traffic between the individual vehicles and the back-end server can be reduced to a minimum. The method according to the invention is also characterized in particular by the fact that its requirements with regard to bandwidth for data transmission and storage requirements on the back-end server are minimal, which also applies to the costs for creating the fuel demand map 2 has an advantageous effect. In 2 is a road map 1 with multiple streets 11 and with three vehicles 31 . 32 . 33 shown in one of the street map 1 enter the enclosed region. Each of the vehicles 31 . 32 . 33 has a first tank fill level <X and is therefore in the first process step 100 for the creation of a fuel demand map 2 selected. The details of the street map 1 covered streets 11 branch to nodes 12 , which each have a turning option for the vehicles 31 . 32 . 33 offers while maintaining your respective direction of travel.

In a second step 200 are all concrete points on the backend server 13 on possible route sections on a road map 1 determined on each of the selected vehicles 3 in relation to its current position and its current tank level still has a second tank level Y, reduced compared to the first tank level X, for example 7 l. First, the amount of fuel currently available for a selected vehicle 3 , which corresponds to its current tank level, subtracts the second amount of fuel, which corresponds to the predetermined second tank level Y. Then the maximum driving distance is calculated, which the vehicle 3 with the remaining amount of fuel. Starting from the vehicle position at which the vehicle 3 is selected in the first process step, all possible route variants are then on a road map 1 determined that can be reached while maintaining the original direction of travel, with every branch or node 12 opens up at least two route variants. The remaining fuel quantity of 7 l, for example, is determined in such a way that a tank or charging station can or should be reached. In the in 3 illustrated example for process step 200 arise for vehicle 31 due to four branching options at the nodes 12 in connection with the maximum distance that can still be covered until the second tank level Y is reached, a total of four specific points 13 on each route section of one of the possible route variants.

In turn, the backend server will be in a further step 300 all after the second step 200 determined specific points 13 weighted by assigning a probability of occurrence. This is done in detail for each of the for a particular vehicle 3 determined specific points 13 it is determined what the probability is that the route of the vehicle 3 actually passed him.

According to a first preferred procedure, the probability of occurrence is determined by forming the sum of all possible route variants, which have been determined for the vehicle in the second procedure step, and then determining the reciprocal. In 4 , as an example of the third process step 300 , the entry probabilities calculated in this way for the in 2 three vehicles selected after the first process step 31 . 32 . 33 and the specific points determined for this after the second procedural step 13 specified. So there is for each of the four specific points 13 same probability of 25%, from vehicle 31 to be reached. Vehicle also reached 32 with the same probability of 25% the four concrete points assigned to him 13 , Because the maximum driving distance from vehicle 33 only a single node due to the amount of fuel remaining 12 , which allows a total of two route variants, the two specific points 13 of vehicle 33 achieved with a probability of 50% each.

In the fourth step 400 becomes the road map 1 tiled on the backend server based on the previous steps 100 to 300 the vehicles 3 selected the specific points 13 have been determined and weighted with probability of occurrence. With the subdivision of the from the road map 1 included target area in tiles 21 , there is a clear regional allocation of all determined specific points 13 according to their respective geographical location or position. Through the fourth step 400 the total fuel requirement of the target area is broken down according to its regional origin. Because both the scale of the road map 1 as well as the size of the tiles 21 are freely selectable, and to the extent that they can be optimally adapted to the accuracy required when determining fuel requirements, tiling of a target area is of particular advantage when planning and optimizing petrol stations and charging stations. 5 shows the road map 1 the 2 to 4 with a regional subdivision by tiles 21 ,

In a next step 500 will be any that in the previous process step 400 generated tiles 21 weighted. On the backend server, all occurrence probabilities are within a tile 21 summed. The result of this weighting is in 5 by rendering the summed probability of occurrence of each tile 21 shown. By tiling and specifying the weight of each tile, the road map 1 a fuel demand map 2 , This fuel demand map generated according to the invention 2 enables, in addition to a problem-free and unambiguous identification of regions with fuel requirements, in particular also a quantitative differentiation of the regions according to the amount of the existing fuel requirements based on the given weights. In the example after 5 show the weighted tiles 21 the regional distribution of the fuel requirements as they are for the three vehicles shown 31 . 32 . 33 results. The region with the highest fuel demand is included 0.75 weighted and immediately on a dark shade in the fuel demand map 2 to recognize. The same applies to those with 0.50 and 0.25 weighted regions that are immediately recognizable by their lighter shading.

In a final, sixth step 600 will eventually become the fuel demand map 2 completed. This happens because each tile 21 the fuel demand map 2 is marked on the backend server in accordance with the fuel demand in the target area encompassed by it, preferably by means of color highlighting or screening. In addition to this, the number of vehicles 3 on which this demand is based. This type of labeling confirms the validity of the data collection and ensures that relevant regions or tiles 21 quickly and easily using the fuel demand map 2 are to be identified. 6 shows an example of a fuel demand map 2 , which was created according to the inventive method on the basis of the tank requirements of several hundred motor vehicles.

LIST OF REFERENCE NUMBERS

1

road map

11

road

12

node

13

concrete point

2

Fuel demand Map

21

tile

3

motor vehicle

31

first motor vehicle

32

second motor vehicle

33

third motor vehicle

100

first process step

200

second process step

300

third step

400

fourth step

500

fifth step

600

sixth step

QUOTES INCLUDE IN THE DESCRIPTION

This list of documents listed by the applicant has been generated automatically and is only included for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent literature cited

• DE 102015221292 A1 [0009]
• DE 102015008968 A1 [0010]
• DE 102010027726 A1 [0011]
• DE 102013202059 A1 [0012]

Claims (15)

Method for generating a fuel demand map (2) for a motor vehicle (3) using a remaining vehicle range, comprising the method steps: Selecting (100) the vehicles (3) whose tank level falls below a first tank level X; Determination (200) of all specific points (13) on possible route sections on a road map (1) at which each of the selected vehicles (3) has a second, reduced compared to the first tank level X, with respect to its current position and its current tank level Has tank level Y; Weighting (300) each concrete point (13) by assigning a probability of occurrence for reaching a specific point (13) by the respective vehicle (3); Tiles (400) of the road map (1) and allocation of all weighted concrete points (13) to the respective corresponding tiles (21); Weighting (500) each tile (21) by summing the probability of occurrence of the vehicles (3) assigned to it; Completion (600) of the fuel demand map (2) by displaying all weighted tiles (21) on the road map (1). Procedure according to Claim 1 , The fuel demand map (2) for a motor vehicle (3) with an internal combustion engine is generated and the first and second tank fill levels X, Y of a first and second residual amount of a liquid fuel, in particular gasoline, diesel, ethanol, liquid gas or liquid hydrogen, or one corresponds to gaseous fuel, in particular natural gas or gaseous hydrogen, or the fuel demand map (2) for a motor vehicle (3) is generated with an electric motor and the first and second tank fill levels X, Y correspond to a first and second residual amount of electricity from an accumulator. Procedure according to Claim 1 or 2 , The first tank fill level X being determined such that a fuel supply during the current or the next trip of a vehicle (3) is highly likely, or that such a signal is signaled by a navigation system of a vehicle (3). Procedure according to one of the Claims 1 to 3 , wherein the weighting step (300) of each concrete point (13) determines the probability of occurrence with 1 / N, and where N denotes the number of all possible route sections of a selected vehicle (3) on a road map (1), starting from which from its current position and its current tank level, the second tank level Y has. Procedure according to Claim 4 , the probability of occurrence for reaching a specific point (13) being determined by the respective vehicle (3) taking into account road classes, and the probability of occurrence being multiplied by a road class code which is set higher for a main road than for a secondary road, and on the basis of which each possible route section of a selected vehicle (3) is identified. Procedure according to Claim 4 , the probability of occurrence for reaching a specific point (13) being determined by the respective vehicle (3) taking into account the available tank information, and the probability of occurrence being multiplied by the percentage of the current fuel quantity. Method according to one of the preceding claims, wherein in the method step determining (200) all concrete points (13) the second tank level Y is determined on the basis of available tank information of all selected vehicles (3) as the mean value of the tank levels of all vehicles (3) when a fuel is supplied. Method according to one of the preceding Claims 1 to 6 , In the method step of determining (200) all the specific points (13), the second tank level Y is determined on the basis of available tank information from a selected vehicle (3) as the mean value of the tank levels when this vehicle (3) is supplied with fuel. Procedure according to Claim 7 or 8th The position detected by a navigation system of a selected vehicle (3), at which the vehicle (3) is supplied with fuel, is used as a specific point (13) for this route section on the road map (1). Method according to one of the preceding Claims 1 to 6 , the specific points (13) at which the second tank level Y is reached being determined on the basis of available tank information of all vehicles (3) with the aid of a probability density function. Method according to one of the preceding claims, wherein the method steps selecting (100) the vehicles (3) and determining (200) all concrete Points (13) are carried out on the basis of the remaining ranges of the vehicles (3), and wherein a vehicle (3) is selected when the first remaining range X is undershot, and wherein each of the selected vehicles (3) at each specific point on a possible route section in With respect to its current position and its current remaining range, a second remaining range Y is reduced compared to the first remaining range X. Method according to one of the preceding claims, wherein the fuel demand map (2) is generated on a time-of-day basis. Method according to one of the preceding claims, wherein in the tile step (400) of the road map (1) the resolution of the road map (1) and the size of the tiles (21) are determined according to a desired regional breakdown of the fuel requirements of an area. Use of the procedure according to Claim 13 for the assessment of regional energy requirements, in particular for the assessment of regional energy transports via a power grid. A computer program product comprising instructions that cause the computer to execute the program, a method according to one of the Claims 1 to 13 perform.

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