Method for creating route calculations for a fleet of vehicles and route calculation system

Abstract

The present invention provides a method for creating route calculations for a fleet of vehicles and a corresponding route calculation system. The method comprises: a) an initial vehicle-destination assignment, b) an estimate of a first total number M1 of required charging stops for the vehicles, taking into account a distance to the initial destination and one or more vehicle parameters, c) identification of vehicles for which no or at least one charging stop is required to reach the initial destination, (d) a pairwise exchange of the initial destination between a vehicle that does not require a charging stop to reach the initial destination and a vehicle that requires at least one charging stop to reach the initial destination, in order to assign a changed destination, (e) an estimate of a second reduced total number M2 of required charging stops for the vehicles, taking into account a respective distance to the initial or changed destination and one or more vehicle parameters, f) a repetition of steps d) and e) g) a calculation of the route for the vehicles to reach the respective initial and modified destinations.

Description

State of the art

[0001] The present invention relates to a method and operating system for calculating a number of route calculations for a fleet of vehicles and a corresponding route calculation system.

[0002] Electric vehicles (EVs) have a limited range based on the amount of electrical energy that can be stored on board. The time required to charge an EV can be much longer than the time required to refuel a combustion engine vehicle. Furthermore, there is currently less public infrastructure available for charging EVs than for refueling combustion engine vehicles.

[0003] Such constraints have led to various solutions for optimizing the costs and charging time of vehicles in a fleet. For example, DE 10 2020 103102 A1 discloses a fleet charging system with a plurality of chargers and a controller for predicting charging demand and charging time intervals for a fleet.

[0004] DE 10 2018 131452 A1 discloses systems and methods that optimize driving routes by minimizing battery charging time using high-power charging stations. Disclosure of the invention

[0005] According to the invention, a method for creating route calculations for a fleet of n vehicles with the features of patent claim 1 and a computer-assisted route calculation system for creating route calculations for a fleet of n vehicles with the features of patent claim 8 are therefore provided. n is a natural number greater than 1.

[0006] The method according to the invention for creating route calculations for a fleet of n vehicles, where n is a natural number greater than 1, comprises the steps: a) initially assigning a respective initial destination from a number of n predetermined destinations to the n vehicles; b) estimating a first total number M1 of required charging stops for the n vehicles to reach the respective initial travel destinations, taking into account a respective distance to the initial travel destination and one or more vehicle parameters, where M1 is a natural number or equal to 0; c) determining vehicles (F2, F5) for which no charging stop is required to reach the respective initial travel destination (Z5, Z2) and vehicles (F1, F3, F4) for which at least one charging stop (MF1, MF3, MF4) is required to reach the respective initial travel destination; d) swapping the initial destination of one vehicle in each case, for which no charging stop is required to reach the respective initial destination, and one vehicle in each case, for which at least one charging stop is required to reach the respective initial destination, in order to assign a respective changed destination; (e) estimating a second reduced total number M2 of required charging stops for the n vehicles to reach the respective initial or changed destinations, taking into account a respective distance to the initial or changed destination and the one or more vehicle parameters, where M2 is a natural number or equal to 0; f) repeating steps d) and e) until the total number M2 is below a predefined limit or cannot be reduced further; and g) Calculating a respective route for the n vehicles to reach the respective initial and changed destinations.

[0007] The present invention overcomes the limitations mentioned above, which lead to additional costs and / or time losses for companies, by using a method and a route calculation system that calculate routes for a fleet of vehicles with relatively reduced computational effort.

[0008] One idea of the invention lies in a simple algorithm that iterates the calculation of vehicle-destination assignments before performing a complex route calculation. Said route calculation takes the aforementioned constraints into account, but is typically time-consuming, generates data traffic, and incurs additional costs (e.g., costs for certain API calls). Reassigning the vehicle-destination assignments before the complex route calculation enables the optimization of route planning for a fleet of vehicles. Furthermore, the algorithm according to the invention is significantly faster, avoids data traffic, and incurs additional costs (e.g., costs for certain API calls).

[0009] Furthermore, the computerized route calculation system implementing the algorithm allows the target user easy access to the procedure for generating route calculations for a fleet of n vehicles through a user-friendly interface.

[0010] Preferred further training is the subject of the subclaims.

[0011] After a preferred further training, the following further steps are included: - Determining the respective energy consumption of the n vehicles for the respective calculated route, - comparing the respective energy consumption of the n vehicles with a respective state of charge of the n vehicles, - Determine the vehicles that require at least one charging stop for the respective calculated route.

[0012] The additional steps mentioned above make it possible to determine the number of charging stops for vehicles more precisely and in a more complex way than if the distance to the destination and one or more vehicle parameters were taken into account.

[0013] According to a further preferred development, energy consumption is determined taking into account a specific vehicle weight and / or a weather forecast and / or a specific route profile and / or a specific driver profile. Taking these parameters into account allows for a precise and accurate determination of energy consumption. Subsequently, the number of expected charging stops is determined with even greater certainty, taking into account possible uncertainties in vehicle operation.

[0014] After further preferred training, the following further steps are included: - Identifying suitable charging stations along the route for vehicles that require at least one charging stop for the respective calculated route; - Incorporation of required charging stations as intermediate stops along the route for vehicles that require at least one charging stop for the respective calculated route, based on one or more predefined optimization criteria; and - Defining a final route for the vehicles that require at least one charging stop for the respective calculated route.

[0015] The steps mentioned allow to determine optimized routes for vehicles that require a charging stop.

[0016] According to a further preferred development, the respective distance and the respective range are taken into account when estimating the first total number M1 of required charging stops and the second reduced total number M2 of required charging stops. By taking these two parameters into account, the calculation of the required charging stops M1 and M2 is quick and cost-effective.

[0017] According to a further preferred development, a corresponding safety margin is applied when estimating the first total number M1 of required charging stops and the second reduced total number M2 of required charging stops. Such a safety margin is used to account for all incidents that may occur during vehicle operation. If the number of charging stops is calculated quickly and cost-effectively, for example, by only considering the distance to the destination and the respective range of the n vehicles, such a safety margin makes the result of the algorithm more robust.

[0018] According to a further preferred refinement, the optimization criteria include a required detour to reach the respective charging station. Including a detour to reach the charging station in the route calculation allows the route calculation to be adapted in the event of a lack of charging stations along the road, especially when public infrastructure for charging vehicles is not so common. Furthermore, including a detour can offer further interesting options for the calculated route. For example, a detour to charge at a high-power charging station may be more worthwhile than stopping at a conventional charging station along the road.

[0019] The present invention is explained in more detail below with reference to the exemplary embodiments shown in the schematic figures.

[0020] They show: Fig. 1 is a schematic flow diagram of a method for creating route calculations for a fleet of n vehicles according to one embodiment of the present invention; Fig. 2a-e are schematic diagrams of the steps of the method for creating route calculations for a fleet of n vehicles according to the embodiment of the present invention; Fig. 3 is a schematic representation of a method for creating route calculations for a fleet of n vehicles according to another embodiment of the present invention; and Fig. 4 is a schematic representation of a method for creating route calculations for a fleet of n vehicles according to another embodiment of the present invention.

[0021] The accompanying figures are intended to provide a further understanding of embodiments of the invention. They illustrate embodiments and, in conjunction with the description, serve to explain principles and concepts of the invention. Other embodiments and many of the noted advantages will be apparent upon consideration of the drawings. Elements of the drawings are not necessarily shown to scale relative to one another.

[0022] In the figures of the drawing, identical, functionally identical and acting elements, features and components are provided with the same reference symbols, unless otherwise stated.

[0023] In addition, selected terms used herein are defined below. These definitions are also intended to aid further understanding of the disclosure itself and the preferred manner of use. The definitions may include various, unlimited examples.

[0024] A vehicle fleet refers to a group or collection of vehicles owned or operated by a single organization, company, government agency, or other entity. This grouping may include various types of vehicles, such as cars, trucks, vans, buses, motorcycles, or specialized vehicles, all of which serve a common purpose for the entity that owns or manages them. Vehicle fleets are common in various sectors, including commercial businesses, transportation and logistics companies, government agencies, rental services, and delivery services.

[0025] As used herein, the term "vehicle" refers to a vehicle capable of carrying one or more people and powered in whole or in part by one or more electric motors powered by an electric battery. The vehicle may include battery-powered vehicles and plug-in hybrid vehicles. Such a vehicle includes, but is not limited to, cars, trucks, vans, SUVs, motorcycles, and scooters. Further, the term vehicle may refer to autonomous vehicles and / or self-driving vehicles powered in whole or in part by one or more electric motors powered by an electric battery. The autonomous vehicle may carry one or more human occupants.

[0026] The term "range" used here refers to the maximum distance a vehicle can travel on a full battery charge before the battery is depleted and the vehicle needs to be recharged. Inherent characteristics of a vehicle, such as battery capacity and model, affect the vehicle's range.

[0027] The term "battery capacity" used here refers to how much electrical energy the battery can store. Vehicles with higher battery capacities generally have a longer range. Battery capacity may decrease over time and with regular use.

[0028] The term "state of charge" used here refers to how much energy is currently in the vehicle's battery. It is often displayed as a percentage or as remaining range. A high state of charge means the battery is close to its maximum capacity, while a low state of charge indicates that the battery needs to be recharged.

[0029] The term "vehicle consumption" used here refers to the energy consumed per distance traveled. This value is often expressed in kilowatt-hours per kilometer (kWh / km). Energy consumption per kilometer indicates how many kilowatt-hours of energy the vehicle needs to cover a distance of one kilometer.

[0030] Fig. 1 shows a schematic flowchart of a method V for creating route calculations for a fleet of n vehicles according to an embodiment of the present invention.

[0031] In a first method step a, a respective initial destination from a number of n predetermined destinations is assigned to n vehicles.

[0032] In a second method step b, a first total number M1 of required charging stops for the n vehicles to reach the respective initial travel destinations is estimated, taking into account a respective distance to the initial travel destination and one or more vehicle parameters.

[0033] In a third method step c, vehicles for which no charging stop is required to reach the respective initial travel destination and vehicles for which at least one charging stop is required to reach the respective initial travel destination are determined.

[0034] In a fourth method step d, the initial destination of one vehicle each requiring no charging stop to reach the respective initial destination and one vehicle each requiring at least one charging stop to reach the respective initial destination are swapped in pairs to assign a respective changed destination.

[0035] In a fifth method step e, a second reduced total number M2 of required charging stops for the n vehicles to reach the respective initial or changed destinations is estimated, taking into account a respective distance to the initial or changed destination and the one or more vehicle parameters.

[0036] In a sixth process step f, steps d and e are repeated until the total number M2 is below a predefined limit or cannot be further reduced. Fig. 1, the dashed arrows indicate the repetition of steps d and e.

[0037] In a seventh method step g, a respective route is calculated for the n vehicles to reach the respective initial and changed destinations.

[0038] Fig. 2a-e show a schematic graphical representation of the method for creating route calculations for a fleet of n vehicles according to the embodiment of the present invention

[0039] Figure 2a shows step a of method V, wherein, for example, five vehicles F1, F2, F3, F4, and F5 are assigned a respective initial destination, Z1, Z2, Z3, Z4, Z5 from a number of five predetermined destinations.

[0040] For example, vehicle F1 is assigned to the initial destination Z3, as shown by the double-headed arrow. Similarly, F2, F3, F4, and F5 are assigned to the initial destinations Z5, Z4, Z1, and Z2, respectively. The initial vehicle-destination assignment is performed, for example, by a human dispatcher. This initial assignment can be done manually or with the assistance of software. For example, the dispatcher can assign a vehicle to an initial destination based on a comparison between the vehicle's electric range and the distance to the destination. This criterion is not restrictive, and the vehicle-destination assignment can also be performed differently.

[0041] The following parameters can also be considered in combination or individually: - the driver's skills and type of driving licence, - the type, condition and load capacity of the vehicle, - the type, capacity and condition of the battery, - traffic regulations and traffic conditions, - the type of roads, the geographical area, - additional costs on the road, which vary depending on the type of vehicle (e.g. due to a toll booth), - the expected weight, size and type of cargo.

[0042] The vehicle-destination assignment must be carried out individually in each individual case, as the parameters mentioned can be difficult to determine.

[0043] Fig. 2b shows steps b and c of method V, wherein a first total number M1 of required charging stops M1 F1, M1 F2, M1 F3, M1 F4, M1 F5 is determined for the five vehicles F1, F2, F3, F4, F5 in order to reach the respective initial destinations Z3, Z5, Z4, Z1, Z2.

[0044] Then the total number M1 of required charging stops, M1F1, M1F2, M1F3, M1F4, M1F5 is estimated by comparing the vehicle's range and the distance to the destination. The range is represented here by an arrow associated with a fully charged battery. This range varies depending on the vehicle model and expresses the distance a vehicle can travel with a full battery. Note that the range varies depending on the battery capacity but is not represented here. The distance to the destination is indicated by an arrow associated with an arrival flag. The distance to the destination is estimated using a route calculation that takes constraints into account. These constraints relate, for example, to the vehicle type (e.g., the weight and dimensions of the vehicles) and associated traffic regulations, which may affect the calculated route.For example, certain vehicles are prohibited in certain urban areas due to their weight or emissions class.

[0045] In another example, the total number M1 of required charging stops M1F1, M1F2, M1F3, M1F4, M1F5 could be estimated by comparing the vehicle's state of charge and the distance to the destination. This could have the advantage of allowing method V to be applied while the vehicle is in operation or when the vehicle is parked at a location without charging facilities before departing for the assigned destination.

[0046] In Fig. In Figure 2b, the total number M1 of required charging stops M1F1, M1F2, M1F3, M1F4, M1F5 is 5 for the five vehicles F1, F2, F3, F4, and F5. The number of charging stations per vehicle is also specified. Vehicle F4 requires 3 charging stops (M1F4=3), vehicles F1 and F3 require one charging stop (M1F1=1, M1F3=1), while vehicles F2 and F5 do not require a single charging stop (M1F2=0, M1F5=0).

[0047] Optionally, a corresponding safety margin is applied when estimating the initial total number M1 of required charging stops M1F1, M1F2, M1F3, M1F4, M1F5. Vehicle F4 could reach the initially assigned destination Z1 with only two charging stops. However, a safety margin was applied, and vehicle F4 therefore requires three charging stops M1F4=3. The safety margins depend on various parameters and can be applied both as a percentage and in absolute terms.

[0048] Example parameters are: - Battery charge level, - weather conditions, - planned route - Driver profile (reserved, sporty) - Traffic (traffic jam) - User “well-being”, a factor that determines how willing the user is to take risks.

[0049] Fig. 2c shows steps d and e of method V, wherein a pairwise swap is performed to assign a respective changed destination and a second reduced total number M2 of required charging stops M2F1, M2F2, M2F3, M2F4, M2F4, M2F5 is estimated.

[0050] Vehicles F1 and F4 have swapped their original destination Z3 and Z1 with the original destination Z5 and Z2 of the respective vehicles F2 and F5, since F1 and F4 require at least one charging stop, while F2 and F5 do not require a charging stop.

[0051] Consequently, vehicles F2 and F5 have also exchanged their original destinations Z5 and Z2 for destinations Z3 and Z1. This exchange is indicated by the double arrows between the different vehicle-destination assignments, expressed as Fi;Zi (i is a number from 1 to 5). In this way, the pair exchange between a destination and a vehicle is performed.

[0052] Vehicle swapping does not disrupt the fleet's normal production processes. Pair swapping also takes into account the characteristics of the vehicle and / or the load and / or the route and / or the driver.

[0053] As mentioned above, vehicle, load, route and / or driver characteristics may include: - the driver's skills and type of driving licence, - the type, condition and load capacity of the vehicle, - the type, capacity and condition of the battery - traffic regulations and traffic conditions, - the type of roads, the geographical area, - additional costs on the road, which vary depending on the type of vehicle (e.g. due to a toll booth), - the expected weight, size and type of cargo.

[0054] The first exchange between the original destinations Z3 and Z5 of the respective vehicles F1 and F2 can, for example, be carried out taking into account traffic regulations and / or the geographical delivery area, since both vehicles are of a similar type and size.

[0055] The second exchange between the original destinations Z1 and Z2 of the respective vehicles F4 and F5 can be carried out taking into account the type of load, since both have a high loading capacity.

[0056] For the five vehicles F1, F2, F3, F4, F5, a total number M2 of required charging stops, M2F1, M2F2, M2F3, M2F4, M2F5, is determined to reach the respective initial or changed travel destinations Z5, Z3, Z4, Z2, Z1.

[0057] Then, the total number M2 of required charging stops, M2F1, M2F2, M2F3, M2F4, M2F5, is estimated by comparing the vehicle's range and the distance to the destination. The range is represented here by an arrow connected to a fully charged battery. This range varies depending on the vehicle model and expresses the distance a vehicle can travel with a full battery. Again, it should be noted that the range varies depending on the battery capacity, but is not represented here.

[0058] The distance to the destination is indicated by an arrow connected to an arrival flag. The distance to the destination is estimated using a route calculation that takes constraints into account. These constraints relate, for example, to the vehicle type (e.g., the weight and dimensions of the vehicles) and the associated traffic regulations, which may affect the calculated route.

[0059] In another example, the total number M2 of required charging stops M2F1, M2F2, M2F3, M2F4, M2F5 could be estimated by comparing the vehicle's state of charge and the distance to the destination. This could have the advantage of allowing method V to be applied while the vehicle is in operation or when the vehicle is parked at a location without charging facilities before departing for the assigned destination.

[0060] In Fig. In Figure 2c, the total number M2 of required charging stops M2F1, M2F2, M2F3, M2F4, M2F5 is 3 for the five vehicles F1, F2, F3, F4, and F5. Furthermore, the number of charging stations per vehicle is specified. Vehicles F3, F4, and F5 require one charging stop (M2F3=1, M2F4=1, M2F5=1), while vehicles F1 and F2 do not require a single charging stop (M2F1=0, M2F2=0).

[0061] Again, an appropriate safety margin is optionally applied when estimating the initial total number M2 of required charging stops M2F1, M2F2, M2F3, M2F4, M2F5. Vehicle F4 could reach the modified assigned destination Z2 without charging stops. However, a safety margin was applied, and vehicle F4 requires one charging stop M2F4=1.

[0062] Fig. 3 shows a schematic representation of a method for creating route calculations for a fleet of n vehicles according to another embodiment of the present invention.

[0063] According to Fig. 3, an energy consumption Ei is determined for the calculated route estimated in step f of the method V for the 5 vehicles F1, F2, F3, F4 and F5.

[0064] Energy consumption Ei is determined by considering at least one of the following parameters: the vehicle's current weight, the weather forecast, the route profile, and the driver profile. These parameters are not exhaustive. For example, the load, regenerative braking, the vehicle's condition, and the expected traffic (congestion) can also affect energy consumption.

[0065] A heavy vehicle and / or a heavy load would result in high energy consumption. Worn tires on a vehicle can also lead to an increase in energy consumption. Adverse weather conditions, such as low temperatures combined with the use of the vehicle's internal heat, would increase energy consumption.

[0066] If the destination is in rough terrain, such as the mountains or a city with numerous traffic lights, energy consumption would also increase. Driving during rush hour with possible traffic jams would also increase energy consumption. The driving style, whether aggressive or relaxed, would also affect energy consumption. Regenerative braking allows the battery to be recharged during operation and would therefore reduce energy consumption.

[0067] The data sources of the parameters mentioned for determining the energy consumption Ei come from vehicle data sheets, weather data, vehicle utilization data from the fleet operator's system, driver profiles from historical data, in particular consumption data from the past.

[0068] The energy consumption Ei is compared with the respective state of charge Si of the five vehicles F1, F2, F3, F4, and F5. The state of charge SoCi of the vehicles can be recorded using a telemetry unit in the vehicle and transmitted to a backend system. Additionally or alternatively, an algorithm can be used to estimate the vehicle's state of charge SoCi based on datasheet values and historical data.

[0069] In Fig. Figure 3 shows the energy consumption Ei and the state of charge SoCi expressed in % relative to a full charge of the respective battery. Energy consumption and state of charge are symbolically represented by battery charge levels.

[0070] Vehicle F1 has a state of charge of 75%, while the estimated energy consumption to reach destination Z5 is 50%. As already estimated in the procedural steps before route calculation ( Fig. ), no charging stop is required for vehicle F1: M3F1=0 ( Fig. ). Vehicle F2 has a state of charge of 60%, while the energy consumption is 100% to reach destination Z3. Here, vehicle F2 requires a charging stop, M3F2=1. In comparison, vehicle F2 does not require a charging stop, M2F2=0 ( Fig. 2c) when the distance to the destination and the range are compared. In this example, the current state of charge SoCi is comparable to the energy required to reach the destination Z3 when only the distance is taken into account. This can be seen from Fig. 2c. However, a potentially aggressive driving style and / or the condition of the vehicle (depleted battery or worn tires) may lead to an increase in energy consumption to 100%.

[0071] Vehicle F3 has a state of charge of 100%, while the estimated energy consumption to reach destination Z4 is 150%. In comparison, vehicle F3 required a charging stop M2F3=1 ( Fig. 2c) when the distance to the destination and the range are compared. In this example, the estimated energy consumption for reaching the destination Z4 is higher than one would expect if only the distance to the destination is considered. This can be seen from Fig. 2c. However, possible traffic conditions and / or the delivery area, such as the city, may increase energy consumption.

[0072] Vehicle F4 has a state of charge of 80%, while the estimated energy consumption to reach destination Z2 is 120%. In comparison, vehicle F4 required a charging stop M2F4=1 ( Fig. 2c) when the distance to the destination and the range are compared. In this example, the estimated energy consumption for reaching the destination Z2 is higher than one would expect if only the distance to the destination is considered. This can be seen from Fig. 2c. However, a loaded vehicle and / or a road with a steep gradient may lead to higher energy consumption.

[0073] Vehicle F5 has a state of charge of 90%, while the estimated energy consumption to reach destination Z1 is 140%. In comparison, vehicle F5 required a charging stop M2F5=1 ( Fig. 2c) when the distance to the destination and the range are compared. In this example, the estimated energy consumption for reaching the destination Z5 is higher than one would expect if only the distance to the destination is considered. This can be seen from Fig. 2c. However, a heavy vehicle with a heavy load can lead to higher energy consumption.

[0074] Fig. 4 shows a schematic representation of a method for creating route calculations for a fleet of n vehicles according to another embodiment of the present invention.

[0075] In particular, Fig. 4 shows a schematic city map with various streets, whose names are shown in italics and by straight lines. Routes are calculated on the city map based on Method V for generating route calculations for a fleet of vehicles according to the embodiments described above.

[0076] The calculated route is represented by lines with arrows for the five vehicles F1, F2, F3, F4, F5. Here, the vehicles depart from the same location, which is referred to as "departure," but the vehicles could start from different locations. The travel destinations Z1, Z2, Z3, Z4, and Z5 for the five vehicles F1, F2, F3, F4, and F5 are assigned to initial or changed travel destinations according to the invention. The travel destinations Z1, Z2, Z3, Z4, and Z5 are marked with crosses. The charging stations S1, S2, S3, S4, and S5 are represented by filled rectangles. The locations and characteristics of the charging stations are known and can be easily implemented when calculating the final route according to the third embodiment.

[0077] Vehicle F1 reaches the assigned, modified destination Z5 without a charging stop. The route for vehicle F1 is calculated using method V for creating route calculations for a fleet of vehicles according to the invention or the first, second, fourth, or fifth embodiments.

[0078] The vehicle F4 reaches the assigned changed destination Z2 with a charging stop and stops at the charging station S1.

[0079] The route for vehicle F4 is calculated as the final route according to the third, fourth, or fifth embodiments. Charging station S1 represents a suitable charging station located along the calculated route according to the third embodiment. A charging station may be considered suitable based on one or more parameters, such as the type of charging stations, such as high-power charging stations, the number of available spaces at the expected charging time, suitability for the vehicle, or charging costs. These parameters are not limited.

[0080] Charging station S1 was selected as an intermediate stop along the calculated route for vehicle F4 based on one or more predefined optimization criteria. The optimization criteria can be specified by the dispatcher. These optimization criteria are essentially defined to save time and money. For example, the time to reach the charging station and the time to charge the vehicles are taken into account. Additionally or alternatively, the charging costs are also taken into account. Fast charging stations are generally more expensive, so it depends on the individual case whether you want to save time or money. Integration into the daily routine is also taken into account. A charging stop can be scheduled for the lunch break even though you can continue driving. This saves time and money. These examples of optimized criteria are not restrictive.

[0081] Vehicle F2 reaches the assigned modified destination Z3 with a charging stop and stops at charging station S2. The route for vehicle F2 is calculated as the final route according to the third, fourth, or fifth embodiment. Charging station S2 represents a suitable charging station located along the calculated route according to the third embodiment. Charging station S2 was selected as an intermediate station along the calculated route for vehicle F2 based on one or more predefined optimization criteria.

[0082] Vehicle F3 reaches the assigned modified destination Z4 with a charging stop and stops at charging station S4. The route for vehicle F3 is calculated as the final route according to the third, fourth, or fifth embodiments. Charging station S4 represents a suitable charging station located near the calculated route according to the third embodiment. Charging station S4 was selected as an intermediate station near the calculated route for vehicle F3 according to the sixth embodiment. This resulted in a detour. Such a detour should be defined to save time and costs. Given various options for a detour, the dispatcher can select the most suitable one based on the optimization criteria mentioned above. In this case, the charging station is closest to the calculated route, so less time is lost due to the detour.

[0083] Vehicle F5 reaches the assigned modified destination Z1 with a charging stop and stops at charging station S3. The route for vehicle F5 is calculated as the final route according to the third or fifth embodiment. Charging station S3 represents a suitable charging station located near the calculated route according to the third embodiment. Charging station S3 was selected as an intermediate station near the calculated route for vehicle F5 according to the sixth embodiment. This resulted in a detour. Given the possibility of taking two different detours to charging stations S3 and S2, the dispatcher selects the most suitable charging station based on the optimization criteria mentioned above. In this case, charging station S3 can be a rapid charging station or the costs are reduced compared to charging station S2.Additionally or alternatively, the charging station S2 may be unsuitable for the vehicle F5 and / or is not likely to have enough charging spaces. QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2020 103102 A1

[0003] DE 10 2018 131452 A1

[0004]

Claims

[1] Method for creating route calculations for a fleet of n vehicles, where n is a natural number greater than 1, comprising the steps: a) initially assigning a respective initial destination from a number of n predetermined destinations (Z1, Z2, Z3, Z4, Z5) to the n vehicles (F1, F2, F3, F4, F5); b) estimating a first total number M1 of required charging stops (M1F1, M1F2, M1F3, M1F4, M1F5) for the n vehicles (F1, F2, F3, F4, F5) to reach the respective initial travel destinations (Z1, Z2, Z3, Z4, Z5) taking into account a respective distance to the initial travel destination and one or more vehicle parameters, where M1 is a natural number greater than or equal to 0; c) determining vehicles (F2, F5) for which no charging stop is required to reach the respective initial travel destination (Z5, Z2) and vehicles (F1, F3, F4) for which at least one charging stop (MF1, MF3, MF4) is required to reach the respective initial travel destination; d) swapping the initial destination (Z5, Z2) of one vehicle (F2, F5) in each case, for which no charging stop is required to reach the respective initial destination, and one vehicle (F1, F3, F4) in each case, for which at least one charging stop (M1F1, M1 F3, M1 F4) is required to reach the respective initial destination (Z3, Z4, Z1), in order to assign a respective changed destination; e) estimating a second reduced total number M2 of required charging stops (M2F1, M2F2, M2F3, M2F4, M2F5) for the n vehicles (F1, F2, F3, F4, F5) to reach the respective initial or changed travel destinations (Z1, Z2, Z3, Z4, Z5) taking into account a respective distance to the initial or changed travel destination and the one or more vehicle parameters, where M2 is a natural number greater than or equal to 0; f) repeating steps d) and e) until the total number M2 is below a predefined limit or cannot be further reduced; and g) Calculating a respective route for the n vehicles (F1, F2, F3, F4, F5) to reach the respective initial and changed destinations. [2] The method of claim 1, further comprising the steps of: Determining a respective energy consumption (E1, E2, E3, E4, E5) of the n vehicles (F1, F2, F3, F4, F5) for the respective calculated route; comparing the respective determined energy consumption (E1, E2, E3, E4, E5) of the n vehicles (F1, F2, F3, F4, F5) with a respective state of charge (SoC1, SoC2, SoC3, SoC4, SoC5) of the n vehicles (F1, F2, F3, F4, F5); and Determine the vehicles (F2, F3, F4, F5) that require at least one charging stop (M3F2, M3F3, M4F4, M5F5) for the respective calculated route. [3] Method according to claim 2, wherein the respective energy consumption (E1, E2, E3, E4, E5) is determined taking into account a respective vehicle weight and / or a weather forecast and / or a respective route profile and / or a respective driver profile. [4] The method of claim 2 or 3, further comprising the steps of: Determining suitable charging stations (S1, S2, S3, S4) along the route for the vehicles that require at least one charging stop for the respective calculated route; Incorporating required charging stations as intermediate stops along the route for vehicles that require at least one charging stop for the respective calculated route, based on one or more predefined optimization criteria; and Defining a final route for the vehicles that require at least one charging stop for the respective calculated route. [5] Method according to one of the preceding claims, wherein the respective distance and the respective range are taken into account when estimating the first total number M1 of required charging stops and the second reduced total number M2 of required charging stops. [6] The method of claim 5, wherein a corresponding safety margin is applied when estimating the first total number M1 of required charging stops and the second reduced total number M2 of required charging stops. [7] Method according to claim 4, wherein the optimization criteria comprise a required detour to reach the respective charging station. [8] Computer-aided route calculation system for creating route calculations for a fleet of n vehicles, where n is a natural number greater than 1, for carrying out the method according to one of the preceding claims.

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