LU500994B1 - VEHICLE AND DRIVER SPECIFIC ROUTING - Google Patents

Abstract

The present invention relates to the field of route optimization. For the first time, mass data from vehicles and vehicle drivers is continuously evaluated, predictions for the vehicle used and the vehicle driver are derived and included in the optimization.

Description

Vehicle and driver specific routing

technical field

The present invention relates to a method for optimizing travel routes

Device and a computer program product for recording, reading out and transmitting consumption and charging data on the vehicle

State of the art

During the introduction of the first vehicles with internal combustion engines, the

Fuels can only be purchased in pharmacies. Since motor vehicles were not widespread at that time anyway, the drivers were usually familiar with the detours. In the

The picture has changed over the decades. Almost every place and on a regular basis

There are petrol stations at intervals along the motorways. Today's vehicles with

Combustion engines achieve greater ranges with one tankful, with which they often have to be refueled less than once a week in everyday use.

For about half a decade, due to an increasing number of

Consumers who are concerned about the environment are also considering vehicles with an electric drive train and an accumulator.

In contrast to the existing infrastructure at filling stations for internal combustion engines, charging stations for electric vehicles are still sparsely distributed. Since the energy density of known accumulators is significantly lower than the energy density of commonly used ones

fuels, the range of an electric vehicle falls compared to that of a

usually significantly lower.

A further complication is that the possible charging currents are known

Accumulators from the so-called State of Charge (SoC), i.e. the filling level of the

depend on the accumulator and drop disproportionately with a higher SoC. It is therefore advantageous to move the vehicle until the remaining range and thus the SoC is as small as possible. For example, many vehicle drivers try to use a charging station with around 10%

To reach the SoC in order to then charge up to about 80% SoC as quickly as possible, since from about 80% onwards only a small fraction of the maximum charging power is usually available.

In addition, not all charging stations can provide the same amount of power to charge the vehicle. In inner-city areas there are often only charging stations with alternating current with a maximum charging capacity of 11 kW, sometimes also 22 kW, with only a few

allow the vehicle to be charged with 22 kW.

CLVR-0003-P-LU 12/12/2021 Luxembourg patent application

On the other hand, so-called LU500994 are usually found on motorways and trunk roads

fast charging stations. These usually include a so-called CCS connector, sometimes also a so-called CHAdeMO connector, and offer charging capacities from 50 kW to several hundred kilowatts.

The maximum charging power of the possible charging stations and the maximum charging power of the

vehicle are also taken into account in corresponding calculations in the prior art.

The field becomes all the more complex when it is considered that charging stations are known in the prior art that only provide the maximum designated charging power for the vehicle if another charging station is not occupied. This often happens because the

Charging stations away from the mains connection also via built-in charging stations

Accumulators have the ability to convert correspondingly high charging capacities without overloading the mains connection. Such charging complicates the prediction of the times needed to charge the vehicle, since it must be known which others

Charging stations at the same main connection of the energy supply will be occupied at the time of charging.

Due to the circumstances mentioned, the journey from a starting point À to a known destination B is often planned by the vehicle driver, who usually takes into account the SoC at the start of the journey and usually the vehicle model.

Planning tools such as the EVcalc (EV: electric vehicle) from eCalc.ch were quickly published. These allow the route to be planned on the basis of vehicle-dependent

Parameters such as tire pressure, payload, type of tire, charging curve (charging current depending on the

SoC), degradation of the accumulator and the SoC upon departure, user preferences such as the SoC upon arrival at a charging station and at the destination, and weather data such as

Wind speed, air temperature and condition of the route such as the elevation profile and

dampness of the road.

These tools also allow, for example, an overview of how often the driver drives the vehicle in

has to reload/refuel depending on its chosen cruising speed.

US20210180970A1 discloses a similar method for so-called plug-in hybrids, for example to be able to estimate whether they can completely cross a so-called environmental zone in which the emission of gases from a combustion process is restricted.

Those skilled in the art know plug-in hybrids as vehicles with two powertrains, one of which is designed to be powered by an internal combustion engine, while the second powertrain is designed to be powered by an electric motor.

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Other providers such as 'A Better Route Planner' offer similar functionality in a LU500994

App on a mobile device (e.g. smartphone), whereby by connecting a

Device that reads vehicle data via a diagnostic port (OBD, on-board diagnostics), transmits information about the vehicle, in particular the SoC, to the app and thus enables recalculation in the event of a deviation from the expected consumption.

The app also allows use without a device plugged into the OBD port. In this case, the app offers the same functionality, but does not tell the user what speed is being calculated, so that there are always deviations between the predicted SoC and the actual SoC and charging stations that are reachable according to the calculation are not reached can become. Similar kind

Methods are also disclosed in US20210213844A1 and EP3798579A1.

Other technologies known from the state of the art also try to predict the state of the vehicle in the future in whole or in part. So revealed

US20210373082A1, for example, a method and one suitable for implementing the method

Device to determine and predict the so-called state of health (in German: degree of degradation) on the basis of a large number of parameters collected.

Some manufacturers of electric vehicles, such as VW or Tesla, offer the im

Vehicle integrated navigation already a navigation with the planning possible

Charging pillars, although here too there is a lack of transparency with which vehicle driver profile, i.e. with which acceleration and braking behavior and with which selected ones

speeds is calculated. In addition, vehicle drivers are advised not to exceed a certain speed in order to reach the planned charging stations, so the vehicle driver must follow the vehicle's specifications.

On the other hand, the vehicle manufacturers' navigation systems often have information about the occupancy status of a charging station and can take this into account during navigation.

The statements made so far on the state of the art are limited in particular to problems of mobility with electric vehicles, in particular electric cars.

The problems themselves are basically universal and also apply, for example, to vehicles with a natural gas engine or to vehicles with fuel cells (Fuell Cell Electric

Vehicles, FCEV), since corresponding filling stations are not widespread.

Furthermore, the problems with regard to range, for example, also apply in particular to aircraft with electric motors. Although these are particularly efficient as a

World record flight from Switzerland to Norderney 2020 showed (the plane needed only

CLVR-0003-P-LU 12.12.2021 Luxembourg patent application approximately % of the energy of a conventional aircraft), these aircraft have LU500994 had to make multiple stopovers so far.

During this flight, it also turned out that not all airfields were sufficiently

adequate house connections to charge the aircraft's accumulator as quickly as possible. In addition, the planning was extremely lengthy, as it had to be clarified in advance with the airfields whether they had the appropriate charging facilities. Even if the latter problem can be solved by adding charging options to the existing registers of airports, the problem of planning remains, which is analogous to planning for others

electric vehicles is highly dependent on the weather. Furthermore, the range also depends on the extent to which the pilot in the ark uses thermals, for example, so consumption here also depends on the behavior of the pilot.

Most of the well-known methods for calculating the consumption of a

Route planning proceed as follows: First, calculate one or more routes

Basis of a primary optimization strategy such as "shortest route" or "shortest travel time" using conventional routing algorithms such as Dijkstra or A*. Consumption and, if necessary, charging options are then planned for the calculated routes.

At this point it makes sense to talk about route calculations in general.

This requires graph theory. In graph theory, there are so-called edges and nodes. The nodes are connected to each other by the edges. In reality, intersections become nodes in the route calculation

Graphs, the roads connecting the intersections, are represented by edges.

The edges have so-called weights, i.e. numbers that describe the edge in more detail. In the case of a routing graph, for example, the lengths of the

Road sections between the intersections are written on the edges representing the road. For the route calculation, the

Sums of the weights of the edges along the path are formed and then, as a rule, the smallest value is formed. Thus, the shortest route would be calculated. For the fastest route, the calculation would take place analogously, except that instead of the lengths of the road segments, the average driving time on the road segment would be used as the weight for the edge.

To further optimize the calculation speed, virtual edges can be

Routing graphs are added. One speaks here of so-called contraction

hierarchies. Routing algorithms can be improved by adding multiple virtual edges, which store information about the shortest path between two points

CLVR-0003-P-LU 12/12/2021 Luxembourg patent application can be significantly accelerated, since the algorithm used in each case has to check significantly fewer LU500994 potential paths before it finds one or more connections between the starting point A and the destination point B.

Due to their complexity, such virtual edges have so far only been determined for static routing graphs. However, until a few years ago, this methodology was the only way to calculate the routes in a reasonable time, since the ones used for it

Computers, navigation systems or smartphones were comparatively slow.

For a few years now, there has been enough computing power, especially on modern servers, to use route calculation without such optimizations on static graphs. Although this greatly increases the computing power required for a similarly fast route calculation, it enables dynamic calculation

Changing the weights on the edges depending on the travel time, e.g. based on

Traffic jam data, time access restrictions or even weather events.

Task

The present invention is therefore based on the technical task of providing a method in which the properties of the vehicle, the route, the

Weather conditions, traffic and the vehicle driver are taken into account to create a

Route and, if necessary, breaks according to at least one target variable such as the

Optimizing consumption, charging costs or driving time.

Since the problems solved, as described above, represent general problems for all vehicle types, all means of transport that have an energy carrier that is in

Depending on the design and the way the driver controls the vehicle,

Vehicles within the meaning of this invention.

Energy sources within the meaning of this invention are both classic energy sources, in particular for chemical energy such as natural gas, crude oil and fuels produced from this or

Hydrogen, but also forms of energy such as electrical ones stored in an accumulator

Energy. Energy stored in other ways, such as nuclear energy stored in nuclear fuel, would also be conceivable.

In particular, within the meaning of the invention, the term "vehicle" includes cars, bicycles and pedelecs, insofar as they have an auxiliary motor, scooters, motorcycles,

Small motor vehicles, trucks, but also airplanes, drones, helicopters,

Multicopters, flying taxis, rockets or anything else designed for transport in space

vehicle included.

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Accordingly, vehicle drivers are users who drive the vehicle (e.g. car, plane, E-LU500994

scooters).

Furthermore, all data processing devices, comprising at least one

Processing unit and a possibility for interaction by a user, whereby the interaction can also take place indirectly, as with a server, through another terminal, computer within the meaning of this patent. In particular, this also includes smartphones, navigation devices or devices for connection to a diagnostic port in a vehicle.

Solution

According to the invention, this object is achieved by a method for optimizing travel routes and drive type-related breaks based on the vehicle and vehicle driver profile, comprising the following steps: a. Identifying (S01) the vehicle to be used, b. Sensory collection (S02) of vehicle data of the vehicle, the

allow conclusions to be drawn about the consumption and/or the behavior of the filling process, c. Defining (S03) the starting point A and the target point B as well as the

Start time t1 or the target time ta, i. Optimizing (S04) the route from A to B using a primary

Optimization strategy (e.g. fastest connection) as well as under

Consideration of the vehicle data and the estimated consumption, determined using sensor-based vehicle data and the historical one

Driving behavior of the driver, solved.

What is special here is the consideration of the historical driving behavior in step S04.

Therefore, if the user of the method is not also the driver of the vehicle, the driver of the vehicle must optionally be determined.

The route can be calculated and optimized in various ways.

Description

In a first embodiment, initially one route or preferably several

Alternative routes are calculated based on the primary optimization strategy.

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Subsequently, the static information about the edges, such as the route, the LU500994 average time, the altitude information, etc., within the determined routes can be supplemented with data that changes over time, such as weather data, current or predicted traffic data,

Driving speeds, permitted speeds along a route section, etc. are enriched. In the case of vehicles for locomotion in space are even

Constellations of various celestial bodies such as satellites, moons, planets, asteroids,

comets, stars and black holes for so-called swing-by maneuvers and possibly also solar winds and the so-called solar weather.

Subsequently, the consumption of the primary energy carrier, i.e. electrical energy in the

in the case of an electric vehicle (BEV, English: Battery Electric Vehicle) or kerosene in the case of a conventional airplane or hydrogen in the case of a vehicle with

fuel cell, to be appreciated along the route. According to what has happened

Estimation and the filling level of the vehicle identified in S01 before the start of the journey can be used to estimate the intervals at which the vehicle would have to be filled with the primary energy source.

As a result, the filling devices would have to be found along the route. A so-called bounding box can be drawn around the entire route for this purpose. This describes a geographic region that is defined by a minimum and a maximum geographic latitude and a minimum and a maximum geographic longitude, whereby a spherical rectangle is spanned. The bounding box can then go to

Query of all filling devices within the bounding box can be used.

Within the meaning of the invention, a filling device is understood to mean a device which is suitable for filling or loading the vehicle with a primary energy carrier. In the case of electric vehicles, this would be, for example, a charging station or a

Power outlet. In the case of vehicles with internal combustion engines, under a

Filling example. Understood a gas station.

For further optimization, especially with long routes, individual

Route sections, preferably each individual section between two turns,

Bounding boxes are raised, so that, for example, on a route from Berlin to

Bodensee is not taken into account half of Germany, but only small corridors between two waypoints. All curves, or preferably only locations at which the driver of the vehicle has to change from the course of the road to another road, can be used as turns for determining the route sections.

The query on the basis of bounding boxes is also particularly preferred because, with corresponding indices on databases, it enables a particularly quick and simple query in the databases of the directories for filling devices.

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Based on the filling devices found along the route, all possible LU500994 or at least the most probable combinations of the routes with those along the

Routes found filling devices and different filling strategies are calculated / calculated or estimated in terms of additional travel time and filling time or, for example, in terms of costs.

Different filling strategies can be particularly relevant because some

Vehicles move particularly quickly when they are driven very quickly (and thus in a comparatively energy-intensive manner) and are then always filled when the level of the primary energy carrier is low, while other vehicles are faster when they drive through at a constant and slower speed.

In addition, the historical driving behavior of the vehicle driver can also be taken into account.

It is optionally provided that the application of the primary optimization strategy and the

Considering the vehicle data includes: Training the primary

Optimization strategy depending on all sensory collected and stored

Vehicle data and the determined consumption, and the historical driving behavior of the

vehicle driver to obtain a trained primary optimization strategy.

In a last step, a selection of the combination of alternative routes and

Filling strategies are communicated to the vehicle driver so that he can select a suitable route for him.

From a technical point of view, this first variant for optimization has the advantage that all known

Strategies for optimizing the local routing can first be used, whereby the calculation of the alternative routes itself on a computing power and / or the

device with limited main memory, such as a smartphone, can also run within a few seconds over longer distances and the following steps can also run extremely quickly due to the significantly limited options.

One way to optimize in step S04 is to first determine all features that affect consumption, such as elevation profiles, features that change over time, such as

Apply weather data and typical driver consumption to the graph.

Thus, the weighting of the edges is directly based on the consumption and the primary

Optimization strategy is calculated and based on the weighting of the appropriate

Routing algorithm applied.

In a further step, analogously to the first embodiment of step S04

Filling devices determined along the route and with a selection of the possible ones

Charging strategies the filling time, driving time extension and the costs incurred for the filling

CLVR-0003-P-LU 12.12.2021 Luxembourg patent application is calculated and subsequently a selection of combinations of LU500994

Alternative routes communicated to the vehicle driver so that he can make a selection.

The considerable amounts of data on the vehicle used (such as type, model, gof.

Series/year of construction, etc.), which are required for implementing the method, advantageously allow extremely accurate predictions of the consumption of the vehicle and the behavior of its filling.

For example, the charging behavior of an accumulator in an electric vehicle depends heavily on the cell chemistry used, the structure of the electrodes, its degree of degradation, the

cell temperature etc. Therefore, in every electric vehicle there is a so-called

Battery Management System (BMS). The BMS regulates, for example, the extent to which which cell is loaded so that all cells are worn down to about the same extent. Furthermore, the BMS heats or cools the accumulator in many vehicle models. This is done in order to choose a suitable operating point for the accumulator, at which it can call up a particularly large amount of power or be charged with a particularly large amount of power without the

To load the accumulator too much so that its degradation is minimized as much as possible.

It was also found that new vehicles of the same vehicle model in the same configuration, for example due to fluctuations in quality, are significantly different

Have differences of up to 10% in the net capacity of the battery. The — net capacity designates the part of the physically available capacity (so-called gross capacity) that is available to the vehicle in normal operation.

Similarly, some vehicles with combustion engines, e.g.

Protective mechanisms that have an impact on driving behavior and thus also on the

consumption of the vehicle. For example, the speed limiter of some vehicles is set more restrictively on the vehicle side when the vehicle is new, in order to advantageously

Damage to the vehicle's engine during the first few thousand trips

kilometers to avoid. Vehicles of the "Audi R8" model have such a restrictive

Rev limiter in the version with a so-called V10 engine or a so-called V12 engine even permanently depending on the oil temperature. For example, the rev limiter only allows around 6,000 revolutions for low oil temperatures, while up to 8,500 revolutions are permitted for high oil temperatures.

Due to the necessary amount of data from many similar vehicles, at least of an identical type, preferably a model, preferably a series, preferably equipped with components (such as accumulators) of the same series and the same state of degradation and also preferably equipped with the same

software version and the same tires and rims, the collection of the data of the

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Vehicle in step S02 preferably implemented by a device in the vehicle. The LU500994

Data includes a selection of vehicle type, model, primary fuel,

Degradation of the vehicle and relevant components, etc.

This device is preferably suitable for acquiring all the necessary data and transmitting it to a system for processing large amounts of data. The transmission, in turn, can be direct, e.g. via a mobile phone connection (GPRS, EDGE; UMTS, LTE, 5G), or indirectly via a sporadic connection, e.g. W-LAN, Zigbee or LoRaWAN, or indirectly via a mobile device, e.g. a smartphone take place, to which the device connects, for example, via Bluetooth or the like.

A mobile phone connection is advantageous because it allows data to be exchanged in a plannable manner and does not require any further setup/adjustment by the vehicle driver or a third party.

A transmission via W-LAN would also be advantageous because the data for the

Application purpose does not necessarily have to be transmitted immediately and W-LAN is now widely used both at home and in the business context and thus costs for mobile communications can be saved.

A transmission via Zigbee or LoRaWAN would be advantageous in that the Zigbee has significantly higher ranges than W-LAN thanks to the mesh network and LoRaWAN based on the standard and at the same time also save mobile phone costs.

The transmission via a mobile device is advantageous in that for the regular comparison of the predicted/estimated consumption of the primary

Energy carrier during the navigation already continuously recorded data on the level of the primary energy carrier and this must be reported to the mobile device that is used for navigation, so that the same device can be used for this.

The data recorded in this way, e.g. data that allows conclusions to be drawn about consumption and behavior during the filling process, is sent to a system for

Data processing, preferably transmitted to a server on the Internet. This system for

Data processing involves a medium for storing the data, as well as a

Arithmetic unit and it implements a computer program product. This

Computer program product receives the data and evaluates them. The data is then stored on a computer-readable medium in such a way that it is available for later use in route calculation and optimization.

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This computer program product preferably aggregates the data in accordance with LU500994

Vehicle parameters such as degradation, battery temperature,

Air resistance or similar in the form that as many of these parameters as possible are similar. If this is not possible because there is not enough data for a specific design of a

vehicle are available, data on similar vehicle types, models, years etc. can be selected, provided that the data taken into account suggest that the ones taken into account

Vehicles can be expected to have similar properties in terms of consumption and filling.

Analogous to the considerations regarding the vehicle, the influence of the

vehicle driver on the consumption and the charging strategy are taken into account. For example, historical consumption data and data on the

Filling behavior of the vehicle driver with the selected vehicle is taken into account. If no data is available, historical consumption data and historical data on the

Filling behavior of the vehicle driver can be used with other vehicles. In addition, historical consumption data from other vehicle drivers can be used with the same

Vehicle used and, if necessary, also correlated with corresponding data of the vehicle driver with other vehicles in order to determine his personal influence on consumption and his preferred charging strategy.

All of this data is preferably also recorded by a device in the respective vehicle and, analogously to the device described above, to the system for evaluating the

data are transferred.

Furthermore, the method according to the invention optionally enables the determination of further ones

Boundary conditions for route calculation and optimization. In addition to usual

Conditions such as the exclusion of motorways, toll roads or similar can also apply

Requirements are placed on the filling device. For example, the user could request that only filling devices with an accessible toilet, near a restaurant, with lighting or similar be proposed in order to advantageously meet the safety needs of the user

to meet the needs of the vehicle driver.

If the method is used sufficiently, the occupancy status of the corresponding filling devices can be predicted on the basis of the planned routes and planned breaks for filling the primary loading carrier. This information can be included in the calculation of the loading times. The expediency is again on

Example of electromobility explained: Since in many charging parks, for example, the fully available

If the charging power of a charging station is distributed over several connections for charging two electric cars, occupancy away from a possible traffic jam at the driveway can lead to a reduced charging power and thus to a longer downtime.

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Using this data can also advantageously improve the utilization of the fewer LU500994 filling devices that are approached and thus continue to advantageously expand the

infrastructure are stimulated. In addition, through a corresponding

Fleet management, if necessary, congestion on the way to the filling device can be completely or at least partially avoided.

But even without a corresponding distribution, the current occupancy status of the

charging stations are taken into account and displayed to the user. This is via public

Directories of corresponding filling devices, e.g. charging station directories, queried. In addition, based on historical occupancy of the filling devices, their expected future occupancy can be modeled using statistical methods and this possible occupancy can be included in the calculation of the additional time for loading.

Furthermore, it happens again and again that filling devices are completely or partially defective. If such defects are stored in the appropriate directories, this information can be used when selecting the filling device. Also in this

case there is the possibility based on historical data on the technical availability of a

Filling device the technical availability of a charging station to the expected possible

Predict the time of use and include this in the calculation.

In a further refinement, the user can specify the strategy according to which routes are to be calculated and preferred. Conceivable would be the shortest combination of driving and loading time, the maximum driving time between consecutive breaks, the shortest

Consumption on the route, the fewest breaks on the route, or a number

Combinations in which the driving time and fuel consumption are weighed against each other so that the right route is determined for every preference of the vehicle driver.

This setting, as well as the display of possible route alternatives with the

A preferred route can be selected on any end device.

Especially with the mass of data taken into account, which for the better

Planning on a tablet computer, a

Laptop or a desktop computer with the largest possible screen size is particularly preferred.

Alternatively, an embodiment as an app on a mobile device such as a

Smartphone implemented, which advantageously with a possibility to drive off the planned

Route can be equipped by keeping the remaining to be driven while driving

displays route and displays corresponding navigation instructions or by a

outputs voice output. In addition, the same smartphone app can be used to transfer the

CLVR-0003-P-LU 12.12.2021 Luxembourg patent application data recorded by the device in the vehicle for the device for evaluating the data LU500994. Furthermore, an application on a mobile device allows a

Comparing the calculated consumption with the real consumption while driving, so that the route or the planning with regard to filling with the primary energy source can be changed accordingly.

In a further embodiment, there is also the possibility of optimizing the

Filling behavior of the vehicles in a fleet. For example, a company with private

Filling devices and access to its field workers' calendars which calculate routes for the field workers to their off-premises appointments. This calculation can be used to determine whether the filling device is sufficient to fill the vehicle sufficiently for the destination to be reached.

Again, the problem can be explained using electric cars: house connections are in the

Usually designed according to the maximum load expected in the past. DIN 18015-1 "Planning electrical systems in residential buildings" takes one for a residential unit

Power requirement of 14.5 kW. Insofar as the need for an electric

water heating exists, a power requirement of 34 kW is calculated. Even if the house connection of a company were designed to be five times stronger (power of 170 kW), the house connection would already be overloaded with 8 charging stations with 22 kW each. To avoid this, the charging stations can communicate with each other and reduce the charging power. Through the above planning based on the dates of

Employees can now prioritize the vehicles of employees who have to drive particularly early or particularly far. In addition, vehicles for which it is foreseeable that they will not be able to reach their destination by charging at the house connection can be discriminated against, since they have to be charged at a fast charging station on the way anyway.

Similarly, filling stations that have a supply line, e.g. for natural gas or hydrogen or other liquid or gaseous energy carriers (e.g. kerosene or

rocket fuels such as liquid hydrogen, oxygen or liquid methane) may be limited by physical conditions in the maximum inflow of the primary energy carrier. If this inflow has to be divided between several filling devices, one is

Prioritization and/or discrimination of the vehicles to be filled based on those planned

Routes and departure times preferred.

Correspondingly, the inflows to the individual vehicles can be controlled on the basis of the route planning method for limited, divided inflows of the primary energy carrier in the case of a distribution among several vehicles.

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Further advantageous refinements and developments can be found in LU500994

Subclaims and from the embodiments.

exemplary embodiments

The present invention is explained in more detail on the basis of the following figures and exemplary embodiments, without restricting the invention to these.

while showing

Fig. 1: A schematic representation of the interaction of the components involved in a

embodiment

Fig. 2: A schematic representation of a planned route (16) with a scheduled

charging station (17)

Fig. 3: A possible course of the method in a flowchart

Fig. 1 shows a schematic representation of the interaction of the components involved.

To explain the interaction is an electric vehicle (5) with a charging station (3) as

Filling device shown. The connection between the two is via a cable (4).

To enable the charging process, the charging station (3) builds a connection (11) to a

Billing server, which is part of the infrastructure (2) of the charging station operator. If the

Server confirms that payment for the charge is approved, charging begins.

In this case, the vehicle's BMS (5) reports the charge and relevant parameters such as charging current, battery level, etc. on the vehicle's internal CAN bus. The

Connection unit (6) plugged into a diagnostic port of the vehicle (5), for example an OBD port, learns the relevant data and transmits them to the device for

Capture (7). The recording of consumption data during the works in the same way

Drive. The device for recording the charging and consumption data (7) regularly transmits (13) the recorded information to a system for evaluating the recorded data (8).

In this case, the system for processing the data collected (8) is identical to that

Route calculation system (8). This system communicates (9) with a charging station register (1) in order to calculate the routes. Frequently, charge point operators (CPO) or providers of RFID cards operate to unlock

Charging stations and their billing (MSPs, mobility service providers) own

Directories of charging stations. In that case, the charging station list (1) could be part of the

infrastructure of the charging station operator (2). As a rule, the system becomes

Calculation of the routes (8) communicate with several charging station directories (1) (9).

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The charging station directory (1) also communicates (10) with the infrastructure of the LU500994

charging station operator (2). For example, the changed occupancy status of the

Device for filling the vehicle (3) reported with the primary energy source if a filling starts or ends. In addition, for example, defects or

Changes in the flow of the primary energy carrier, ie in the case of the charging station (3) the maximum charging power to be delivered, are transmitted.

2 is a schematic representation of a planned route (16) from a starting point À (14) to a destination B (19) on a mobile terminal (smartphone) (15). The route runs along the roads (18) and shows the shortest way from the starting point A (14) to the destination point B (19). In addition, on route (16) a

Charging station (17) planned to enable the vehicle (5) to reach the destination.

3 shows a possible course of the method. Identifying (20) the

driver is the first step. This can also be done implicitly, assuming that the user of the method is the vehicle driver himself. In a further step, the vehicle (5) to be used is identified (21). This is necessary to, as in

1 to determine from which vehicle (5) the data is to be collected (22) by the device for collecting the data (7) in step S02 (22). In step SO3 (23), the starting point A (14) and the destination B (19) and optionally the departure time t i or the destination time t i are defined. The route (16) is then calculated in step S04 (24) and optimized according to the historical and current data on the vehicle (5) and vehicle driver and, if necessary, supplemented by breaks (17) at suitable filling devices (3).

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List of reference numbers LU500994 1 Publicly accessible directory with filling devices such as a

Charging station (3) 2 Digital infrastructure of the operator of the filling devices, e.g. for operating the

Invoice. 3 filling device for filling the vehicle with the primary energy source in which

Case a charging station 4 element for establishing a connection between the filling device (3) and

Vehicle (5), in this case a charging cable 5 vehicle, in this case an electric car 6 connection between a device for detecting the charging and

Consumption data of the vehicle (7) and a diagnostic port of the vehicle (5), in this case wirelessly connected to the device. 7 Device for recording the charging and consumption data of the vehicle (5) 8 System for processing the charging and consumption data recorded by the

Device of charging and consumption data (7) and for calculating and

Optimization of routes 9 Exchange of data between the system for calculating and optimizing routes (8) and the publicly accessible directory of filling devices (1), for example to update the charging stations used for the routing. 10 Exchange of data between the digital infrastructure of the operator of

Filling devices (2) and the public directory for filling devices 11 exchange of data between the digital infrastructure of the operator (2) and the

Filling device (3) e.g. for the purpose of billing or for transferring the

Occupancy status or similar 12 Exchange of vehicle data between the device for detecting the

Load and consumption data (7) by means of the connection (6) of the device to

Recording of charging and consumption data. 13 Exchange of data between the device for collecting charging and

Consumption data in the vehicle (7) realized in this case by a direct

Connection e.g. via mobile radio

CLVR-0003-P-LU 12/12/2021 Luxembourg patent application

14 Starting point A of a route (16) LU500994 15 Schematic of a smartphone used to plan a route (16) from starting point A (14) to destination B (19) 16 Route from starting point A (14) to destination B (19) 17 In the route (16) planned filling device, in this case a charging station for a

Electric vehicle 18 Schematically indicated streets 19 Destination point B of the route (16) 20 Process step of vehicle driver identification 21 Process step of vehicle identification 22 Process step of sensory collection of vehicle data 23 Process step of defining starting point, destination and, if necessary, planned

Arrival and departure time 24 process step of optimizing the route

CLVR-0003-P-LU 12/12/2021 Luxembourg patent application

Claims (41)

Patent claims LU500994 1. A method for optimizing travel routes and possibly also breaks in vehicles, comprising the steps a. | identify (S01) a vehicle to be used, b. Sensory collection (S02) of vehicle data that allows conclusions to be drawn about its consumption and/or its filling process behavior, c. Defining (S03) a starting point A and a destination B and a starting time to and/or a destination time ti, i.e. Optimizing (S04) the route from A to B using a primary optimization strategy, taking into account the vehicle data and the estimated consumption, determined using vehicle data collected by sensors and the historical driving behavior of the vehicle driver. 2. The method as claimed in claim 1, wherein the vehicle driver is optionally determined in step S04 if the user of the method is not the vehicle driver. 3. The method according to claim 1 or 2, wherein the method for optimizing the route (S04) comprises the following steps a. Calculate (S04a) at least one route, but preferably more than one alternative route, according to the primary optimization strategy, b. Extending (S04b) edges of the calculated route(s) to include features that change over time and/or static features that affect consumption, c. Estimating (S04c) the consumption of the energy carrier along the edges based on the data with which the edges were expanded in the previous step (S04b), i.e. Determine (S04d) suitable filling devices along the route/s/edge/s, e. Calculating (S04e) the filling time and/or travel time extension and/or costs of all relevant filling strategies along the route(s), f. Communicating (S04f) a selection of the calculated alternatives for selection to the user. CLVR-0003-P-LU 12/12/2021 Luxembourg patent application 4. The method according to any one of claims 1 or 2, wherein the method for optimizing the route (S04) LU500994 comprises the following steps a. Calculating (S05a) at least one route, but preferably at least one alternative route, according to the primary optimization strategy, taking into account the estimated consumption on the basis of variable and/or static features of the possible route sections b. Identifying (S05b) suitable filling devices along the route, c. Calculating (S05c) the filling time and/or travel time extension and/or costs of all relevant filling strategies along the routes, i.e. Communicating (S05d) a selection of the calculated alternatives for selection to the user. 5. The method according to any one of claims 1 to 4, wherein consumption data from at least two vehicles are collected by means of devices in the vehicles and corresponding sensors for the estimation of the consumption in step S04, a. whereby consumption data is collected from at least two, but preferably from as many vehicles as possible, of an identical type, and/or b. Consumption data from at least two, but preferably from as many vehicles as possible, are collected with the same configuration of consumption-determining properties. 6. The method according to any one of claims 1 to 5, wherein for the estimation of the consumption in step S04 consumption data from at least two vehicle drivers are collected via a corresponding device and sensors in the vehicles and a. the driver's historical consumption data and/or b. Consumption data is collected from at least two vehicle drivers and aggregated or compared with one another via vehicles of one type, and/or c. historical consumption data of the same vehicle driver over different types of a vehicle are used. 7. The method according to any one of claims 1 to 6, wherein in step S04 optionally other characteristics of the vehicle influencing the consumption or the filling process are taken into account after they are activated by a device in the vehicle under LU500994 Use of appropriate sensors were collected. 8. The method according to claim 1 one of claims 1 to 7, wherein in step S04 optionally unchangeable properties of the possible routes influencing the consumption of the vehicle, such as road surface or height profile of a road, are taken into account. 9. The method according to any one of claims 1 to 8, wherein in step S04 optionally temporally variable environmental data, in particular weather data, in particular air pressure, temperature and wind speed and direction or the position of the sun are taken into account 10. The method according to any one of claims 1 to 9, wherein further boundary conditions such as local conditions are optionally taken into account in step S04. 11. The method according to any one of claims 1 to 10, wherein in the optimization in step S04, average and chronologically current traffic data from routes relevant to the vehicle are taken into account (live traffic). 12. The method according to any one of claims 1 to 11, wherein future occupancy of the routes relevant to the vehicle is determined using other users of the method. 13. The method according to claim 1, wherein the average and current occupancy of the energy carrier for filling devices is taken into account. 14. The method according to any one of claims 1 to 13, wherein the historical reliability of filling devices for the primary energy carrier is taken into account. 15. The method according to any one of claims 1 to 14, wherein the future assignments of the filling devices for the primary energy carrier of the vehicle is determined using other users of the method. CLVR-0003-P-LU 12/12/2021 Luxembourg patent application 16. The method according to any one of claims 1 to 15, wherein in step S04 characteristics of the vehicle are used to fill the energy carrier. 17. The method according to any one of claims 1 to 16, wherein the user can influence the optimization of the route according to subjective standards. 18. The method according to any one of claims 1 to 17, wherein a filling device is provided, wherein the filling device comprises an inflow for a primary energy carrier, the inflow of which is limited, and at least two outflows, wherein the filling device can optionally be expanded in a modular manner with further outflows, wherein the outflows can each be coupled to a vehicle, and wherein, if at least two vehicles are coupled to the filling device via the outflows, the outflows of the primary energy carrier to the vehicles according to the routes planned for their vehicle drivers using the method according to one of claims 1 to 17 be adjusted in order to optimally distribute the inflow of the energy source for all coupled vehicles. 19. Computer program product comprising instructions which, when the method according to one of claims 1 to 18 is executed by a computer, cause the computer to record and read consumption and charging data on the vehicle side and to transmit the vehicle data necessary for step S01 to a server. 20. Computer-readable medium on which the computer program product according to claim 19 is stored. 21. Data acquisition device for acquiring, reading out and transmitting the consumption and charging data in the vehicle, comprising a computer-readable medium according to claim 20. 22. The device according to claim 21, comprising a cellular modem for the communication of the device to a server. CLVR-0003-P-LU 12/12/2021 Luxembourg patent application 23. The device as claimed in claim 21, comprising a radio interface suitable for directly establishing a connection to a network with Internet access, such as a W-LAN 24. The device as claimed in claim 21, comprising a radio interface for transmission to a further device which can collect recorded data and transmit it to a server. such as Zigbee, LoRaWAN or Bluetooth. 25. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to execute the method according to any one of claims 1 to 18 in order in this way to plan a route by a user and optionally to set boundary conditions and optimization parameters. 26. Computer program product according to claim 25, comprising instructions which, when the program is executed by a computer, cause the latter to guide the user along the planned route. 27. Computer program product according to claim 25 or 26, comprising instructions which, when the program is executed by a computer, cause the computer to compare the estimated consumption of the primary energy carrier by the vehicle with the actual consumption of the primary energy carrier by the vehicle while driving. 28. Computer program product comprising instructions which, when the program is executed by a computer, cause the computer to transmit the data recorded by the device according to one of claims 21 to 24 from the device to a mobile terminal and from there to a server. 29. Computer-readable medium on which at least one of the computer program products from one of claims 25 to 28 is stored. 30. Computer comprising at least one computer-readable medium according to claim 29. 31. Computer program product, comprising instructions which, when the program is executed by a computer, cause it to implement a CLVR-0003-P-LU 12.12.2021 Luxembourg patent application Method according to one of Claims 1 to 18, for receiving and processing the LU500994 consumption and charging data recorded on the vehicle side. 32. Computer-readable medium on which a computer program product according to claim 31 is stored. 33. Computer, comprising a computer-readable medium according to claim 32 for processing all consumption and charging data recorded on the vehicle side. 34. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to execute the method according to any one of claims 1 to 17 in such a way as to determine the optimal route according to one of the data collected therein. 35. Computer-readable medium on which a computer program product according to claim 34 is stored. 36. A computer comprising a computer-readable medium according to claim 35. 37. Filling device, comprising an inflow for a primary energy source and at least two outflows, wherein the filling device is set up in such a way that when the outflows are coupled to a plurality of vehicles that are filled at the same time, the primary energy source is divided between the coupled vehicles according to claim 18. 38. A computer program product comprising instructions which, when the program is executed by a computer, cause the latter to control the filling device according to claim 34 or to carry out a method according to claim 18. 39. Computer-readable medium on which a computer program product according to claim 38 is stored. 40. Computer comprising a computer-readable medium according to claim 40, preferably installed in the filling device according to claim 37. CLVR-0003-P-LU 12/12/2021 Luxembourg patent application 41. Network comprising at least two of the computers or Apparatus according to claims 21, 30, 33, 36 and 40, wherein a computer can fulfill several of claims 30, 33 and 36. CLVR-0003-P-LU 12/12/2021 Luxembourg patent application