DE102019109561A1 - Method for route planning in a navigation system of a vehicle, navigation system for a vehicle and vehicle with the same - Google Patents

Abstract

The present disclosure relates to a method for route planning in a navigation system of a vehicle, in particular an electric vehicle. The method comprises: a) dividing a route from a starting point to an end point (or route destination) into a plurality of route sections; b) assigning an individual speed to each route section of the plurality of route sections; c) determining a charging time for at least one (planned ) Charging point along the route; d) determining an initial total travel time for the route based on the individual speeds assigned to the plurality of route sections and the charging time; and e) determining a minimum total travel time by varying the variables used for determining the initial total travel time relating to the individual speeds and the at least one charging point.

Description

The disclosure relates to a method for route planning in a navigation system of a vehicle, in particular an electric vehicle, a navigation system for a vehicle and a vehicle with such a navigation system. The disclosure relates in particular to the optimization of route planning in a navigation system of an electric vehicle.

State of the art

Navigation systems are generally used to recommend a route to a driver from a current position to a route destination, the route being able to be displayed on a navigation map as a map track, for example. The travel route can be determined, for example, based on the shortest time or shortest distance between the current position and the route destination.

Alternatively, energy-optimized routes can be determined and suggested to the driver. From the DE 10 2017 119 453 A1 For example, a method for generating energy-optimized driving routes with a vehicle navigation system is known. The method includes generating candidate driving routes between a route starting point and one or more route destinations, and then dividing each candidate driving route into a plurality of route segments. The method further comprises estimating the expected travel speeds along each section using cloud information and calculating an expected energy efficiency over each of the candidate travel routes using one or more vehicle-specific energy efficiency models. The routes are displayed on the navigation system.

Disclosure of the invention

It is an object of the present disclosure to provide a method for route planning in a navigation system of a vehicle, in particular an electric vehicle, a navigation system for a vehicle and a vehicle with such a navigation system that enable a route destination to be reached more quickly and / or more efficient route guidance. In particular, it is an object of the present disclosure to enable faster achievement of the destination by minimizing the travel time.

This object is achieved by the subject matter of the independent claims. Advantageous refinements are given in the subclaims.

1. a) Unterteilen einer Fahrtstrecke von einem Anfangspunkt zu einem Endpunkt (bzw. Routenziel) in eine Vielzahl von Streckenabschnitten;
2. b) Zuordnen einer individuellen Geschwindigkeit zu jedem Streckenabschnitt der Vielzahl von Streckenabschnitten;
3. c) Bestimmen einer Ladezeit für wenigstens einen z.B. basierend auf einer Energieprognose geplanten Ladepunkt entlang der Fahrtstrecke (die Planung des Ladepunkts kann beispielsweise eine Einplanung und/oder Berücksichtigung eines Umweges, möglicher Wartezeiten an Ladestationen etc. umfassen);
4. d) Bestimmen einer initialen Gesamtreisezeit für die Fahrtstrecke basierend auf den der Vielzahl von Streckenabschnitten zugeordneten individuellen Geschwindigkeiten und der Ladezeit; und
5. e) Ermitteln einer minimalen Gesamtreisezeit durch Variieren, und insbesondere Optimieren wenigstens einer für das Bestimmen der initialen Gesamtreisezeit verwendeten Variable betreffend die individuellen Geschwindigkeiten und den wenigstens einen Ladepunkt.

According to embodiments of the present disclosure, a method for route planning in a navigation system of a vehicle, in particular an electric vehicle, is specified. The procedure includes:

1. a) dividing a route from a starting point to an end point (or route destination) into a plurality of route sections;
2. b) assigning an individual speed to each route section of the plurality of route sections;
3. c) Determining a charging time for at least one charging point planned, for example, based on an energy forecast along the route (the planning of the charging point can include, for example, planning and / or taking into account a detour, possible waiting times at charging stations, etc.);
4. d) determining an initial total travel time for the route based on the individual speeds assigned to the plurality of route sections and the loading time; and
5. e) Determining a minimum total travel time by varying, and in particular optimizing at least one variable used for determining the initial total travel time relating to the individual speeds and the at least one charging point.

To determine the minimum total travel time in step e), at least some of steps a) to d) can be repeated at least partially with the varied variables.

According to the invention, the total travel time, which corresponds to a sum of travel time and charging time, is minimized. In particular, two aspects are equally taken into account for determining the minimum or optimal total travel time for a given route, namely driving and charging or their influencing variables. In other words, a holistic view of the total travel time takes place through dual consideration of driving and charging, whereby a global optimum of the total travel time can be ensured by taking into account the set system limits and / or boundary conditions (e.g. a remaining charge to be kept at the route destination).

To determine the minimum total travel time, the individual speeds of the route sections can be adjusted in order to enable a shorter travel time. Furthermore, as part of the determination of the minimum total travel time, a charging stop can be saved, for example, and / or a different charging station can be selected for a planned charging stop, which enables a shorter charging time. A Saving a charging stop can correspond to a charging time of zero. The shortening of the travel time and / or the loading time leads in turn to a reduction in the total travel time, which is made up of the travel time and the loading time.

In some embodiments, by adapting the individual speeds of the route sections, energy consumption can be reduced and a charging stop can be saved, thereby reducing the overall travel time. For example, the optimization according to the invention can save an originally planned charging stop, so that no charging stop is required for the journey from the starting point to the end point. In such a case, the charging time is zero, so the total travel time corresponds to the travel time.

In some embodiments, the load time includes a physical load time and a setup time. The physical charging time indicates the time that the actual charging process of a drive energy storage device of the vehicle takes. The set-up time includes the time required for preparation and follow-up of the charging process, e.g. Plugging in, paying, etc.

For example, the at least one charging point can be scheduled based on individual information from the charging point along the route. The individual information can be selected from the group that includes a route, in particular a detour to the charging point, a waiting time at the charging point, and the set-up time at the charging point.

The minimum total travel time is based on specific individual speeds for the sections of the route and loading parameters, such as a location of a charging station and / or a charging hub and / or a time of a charging stop. The corresponding driving information and / or charging information can be output to a driver and / or a driver assistance system for automated driving. The travel information can include information relating to the specific individual speeds for the individual route sections of the route. Similarly, the charging information can include information relating to a location of a charging station and / or a charging hub and / or a time of a charging stop.

The corresponding driving information and / or charging information is typically output to a driver, for example visually on a display and / or by means of voice output. In particular, a target speed corresponding to the minimum total travel time can be displayed to the driver. The target speed can be output individually for each route section of the multiplicity of route sections. The target speed is a recommendation or a suggestion for an optimal speed to achieve the minimum total travel time.

Alternatively, the driving information (e.g. the target speed) and / or charging information can be output to a driver assistance system for automated driving. The driver assistance system for automated driving can be set up for partially autonomous or fully autonomous driving and control the vehicle according to the driving information and / or charging information.

The subdivision of a route from a starting point to an end point into a plurality of route sections preferably comprises subdividing the route based on at least one criterion. The at least one criterion is selected from the group comprising a route section speed, a road type, a structural route section property and a charging point. A single criterion can be used for a given route, or two or more criteria can be used. Typically, at least some of the route sections are of different lengths.

With regard to the criterion of the route section speed, the route sections can be subdivided in such a way that a speed within a route section is essentially constant (e.g. sections or zones with 30 km / h, 50 km / h, 100 km / h etc.).

The subdivision of the route into road types can be, for example, a subdivision into motorway, country road, local road etc. The subdivision of the route into structural route section properties can include, for example, a subdivision into driveways, exits, construction sites, etc. With the subdivision by charging points, the route can be divided into the route sections by the charging points or charging stations arranged along the route. In other words, two adjacent route sections can be separated by a charging point or charging station.

In other embodiments, the route is divided into a plurality of equidistant route sections.

Each route section of the plurality of route sections is assigned an individual speed, which can be constant or variable. In the latter case, the individual speed is a speed profile over the course of the route section, ie a location-dependent one Speed. The speed profile can be determined by suitable forecast models, for example based on navigation data and / or real-time traffic information and / or a driver-specific behavior.

In some embodiments, forecast probabilities are used within the framework of the forecast model, which indicate a probability of a respective speed profile. In particular, some speed profiles may be more likely than others. Preferably that speed profile is used for a route section which is most likely. Improbable solutions can be discarded.

In some embodiments, the initial total travel time for the route is determined using initial individual speeds for the route sections. The initial individual speeds can be determined, for example, from the aforementioned forecast models and / or real-time traffic information. The initial individual speeds can in particular be expected speeds (in sections) that can be obtained, for example, from the real-time traffic information. The real-time traffic information can be, for example, “Real Time Traffic Information” (RTTI) from BMW.

The method of the present disclosure comprises determining the minimum total travel time by varying the variable used for determining the initial total travel time relating to the individual speeds, such as the aforementioned initial individual speeds of the route sections. In other words, the initial individual speeds of the route sections can be varied in order to determine the minimum total travel time. For example, by reducing the speed (e.g. in sections), a charging stop can be saved, which can shorten the total travel time.

The minimum total travel time is also determined by varying the variable used for determining the initial total travel time relating to the at least one charging point. For example, a charging hub and / or a location of the at least one charging point can be varied along the route in order to determine the minimum total travel time. For example, the total travel time can be shortened by using a different charging station, for example because there is less utilization and thus the waiting time at the other charging station.

The determination of a charging time for at least one charging point along the route preferably includes determining a first charging time for a first charging point or a first charging station, the initial total travel time being determined based on the first charging time for the first charging point. Varying at least one variable used to determine the initial total travel time relating to the at least one charging point to determine the minimum total travel time can then include replacing the first charging point with a second charging point or second charging station and determining a second charging time for the second charging point.

The first charging point and the second charging point can be different. In particular, the first charging point and the second charging point can be arranged spatially separated along the route. For example, if the charging time, i. the physical charging time and / or the set-up time for the second charging point is smaller than for the first charging point, the total travel time can be shortened by selecting the second charging point for a charging process. This assumes that the second charging point can be reached with the vehicle's charge level. This can be derived from a suitable energy forecast.

A minimum total travel time is preferably determined by means of dynamic programming, for example using a cost function. The term “dynamic programming” is generally understood to mean a method for the algorithmic solving of an optimization problem by dividing it into sub-problems. In some embodiments, the method of the present disclosure can use a dynamic programming-based algorithm for solving an optimization problem segment by segment, i. to minimize the total travel time. For this purpose, forecast models can be integrated, for example, for a speed profile of the route or route sections of the route. In particular, the forecast models can data the algorithm, that is, supply input variables.

In some embodiments, the cost function can be given as follows: $$mi{n}_{u\left(k\right)}{\displaystyle \sum _{k=0}^{N-1}{t}_{k,\mathrm{L.}aden}\left({\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="DE102019109561A1\_0004.png"\; state="\{\{state\}\}">u</figure-callout>}}_{\mathrm{1,}k},k\right)+t_{k,\mathrm{F.}aHren}\left({\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="DE102019109561A1\_0004.png"\; state="\{\{state\}\}">u</figure-callout>}}_{\mathrm{2,}k},k\right)}$$

In the above formula, t indicates a time. u ₁ specifies a first control variable (“charging”) that relates to the at least one charging point, such as a charging stroke for a specific charging point. u ₂ specifies a second control variable (“driving”) which relates to the individual speeds or vehicle speeds of the route sections of the route. The summation takes place over the multitude of route segments k that form the route.

The second control variable u ₂ or the vehicle speed can be used for an energy forecast for the individual route sections. Typically, additional parameters can be used in the energy forecast, such as vehicle data. The vehicle data can include, for example, a state of charge (SoC) of a drive energy storage device, a remaining range (remaining range), a load status of the vehicle, a driver profile (e.g. driver-specific consumption), an incline, a remaining distance, etc. The energy forecast can be used to plan the charging stops, i.e. whether and when a charging stop is necessary. The method according to the invention can optimize the planning of the charging stops, taking into account the energy forecast, so that the total travel time is minimized.

The procedure, such as the above-mentioned solution algorithm, can take into account both aspects of “driving” and “charging” within the framework of the cost function. The sum of travel time (via the realizable vehicle speed) and charging time (controlled via defined charging strokes) can thus be minimized, for example by specifying a remaining charge level at the route destination.

The method preferably further comprises specifying a target state at the end point (e.g. a route destination) of the route, the initial total travel time and / or the minimum total travel time being determined based on the target state. The target state can be taken into account as a state variable in the cost function. The target state can e.g. can be specified by the driver. The target status can be, for example, a (desired) remaining range (“RRW”) at the route destination or a remaining charge status (“remaining SoC”) of a drive energy storage device of an electric vehicle.

According to a further aspect of the present disclosure, a storage medium is described. The storage medium can comprise a software program which is set up to be executed on a processor and thereby to execute the route planning method described in this document in a navigation system of a vehicle.

According to a further aspect of the present disclosure, a navigation system for a vehicle is specified. The navigation system comprises at least one processor which is set up to execute the route planning method described in this document in a navigation system of a vehicle.

The driver can enter the end point of the route, i.e. a route destination, into the navigation system. The navigation system can then determine a minimum travel time to the route destination using the method according to the invention.

In some embodiments, the navigation system can include at least one output unit which is set up to output the route (that is, route guidance) and / or driving information and / or charging information. The at least one output unit can include an optical output unit, such as a display for displaying a navigation map with a map track, and / or an acoustic output unit for outputting voice instructions.

According to a further aspect of the present disclosure, a vehicle, in particular an electric vehicle, comprising the aforementioned navigation system is specified.

According to embodiments, the electric vehicle can be a purely electric vehicle. However, the present disclosure is not limited to this and the vehicle can be, for example, a hybrid vehicle such as a plug-in hybrid vehicle (PHEV), a (partially) electric vehicle with an electrical storage device of any size, a vehicle with a fuel cell, etc. The term vehicle includes cars, trucks, buses, mobile homes, motorcycles, etc. that are used to transport people, goods, etc. In particular, the term includes motor vehicles for passenger transport.

Figure list

• 1 schematisch ein Flussdiagram eines Verfahrens zur Routenplanung in einem Navigationssystem eines Fahrzeugs gemäß Ausführungsformen der vorliegenden Offenbarung, und
• 2 schematisch ein Unterteilen einer Fahrtstrecke von einem Anfangspunkt zu einem Endpunkt in eine Vielzahl von Streckenabschnitten gemäß Ausführungsformen der vorliegenden Offenbarung.

Exemplary embodiments of the disclosure are shown in the figures and are described in more detail below. Show it:

• 1 schematically a flow diagram of a method for route planning in a navigation system of a vehicle according to embodiments of the present disclosure, and
• 2 schematically dividing a route from a starting point to an end point into a plurality of route sections according to embodiments of the present disclosure.

Embodiments of the disclosure

Unless otherwise noted, the same reference symbols are used below for elements that are the same and have the same effect.

1 schematically a flow diagram of a method 100 for route planning in a navigation system of a vehicle according to embodiments of the present disclosure.

The procedure 100 includes in the block 110 dividing a route from a starting point to an end point or route destination into a plurality of route sections; in the block 120 assigning an individual speed to each route section of the plurality of route sections; in the block 130 determining a charging time for at least one charging point along the route; in the block 140 determining an initial total travel time for the route based on the individual speeds assigned to the plurality of route sections and the loading time; and in the block 150 determining a minimum total travel time by varying variables used for determining the initial total travel time relating to the individual speeds and the at least one charging point.

For determining the minimum total travel time in the block 150 can the blocks 110 to 140 repeated once or several times with the varied variables. In particular, the method 100 , and especially the blocks 110 to 150 , take place iteratively until the total travel time is optimized or minimized.

The vehicle can be an electric vehicle. The electric vehicle includes an electrical energy storage device (a drive energy storage device such as batteries) that can be connected to a charging station and charged. Various charging technologies can be used to charge the electrical energy storage device of such electric vehicles. With AC charging, the charger that converts the direct current to charge the electrical energy storage device is located in the vehicle. With DC charging, the charger, which converts the direct current to charge the electrical energy storage device, is located in the charging station. However, the present disclosure is not limited to this, and the DC converter may also be provided in the vehicle.

2 schematically shows a subdivision of a route from a starting point to an end point into a plurality of route sections according to embodiments of the present disclosure.

The starting point ("Start") can be a current position of the vehicle and / or a e.g. be the starting point for the journey predetermined by a driver. The current position of the vehicle and the starting point specified by a driver can, but need not, match. The specified starting point can be entered, for example, before the start of the journey to the end point, so that an initial minimum total travel time can be determined. In some embodiments, the method of the present disclosure is carried out continuously (repeatedly) during the trip to the end point, the starting point for the method corresponding to the current position of the vehicle, so that a current minimum total travel time, that is, in real time during the trip, can be determined . The end point (“destination”) can be a route destination that is entered into a navigation system by a driver, for example.

In the example of 2 the route is divided into N route sections. In some embodiments, at least some of the route sections are of different lengths. However, the present disclosure is not limited to this, and in other embodiments the travel route can be subdivided in such a way that the route sections are approximately the same length.

In some embodiments, the route can be subdivided based on one or more criteria, such as, for example, based on a route section speed, a road type, a structural route section property and a charging point. A single criterion can be used for a given route, or two or more criteria can be used in combination.

Each route section of the plurality of route sections is assigned an individual speed, which can be constant or variable. In the latter case, the individual speed is a speed profile over the course of the route section, i.e. a location-dependent speed.

The speed profile can be determined using suitable forecast models. Here, forecast probabilities can be used which indicate a probability of a respective speed profile for a specific route section. For example, the forecast model can determine several possible speed profiles for a route section, each of the several possible speed profiles having a forecast probability. The speed profile is preferably used for a route section that is most likely. Improbable solutions can be discarded.

Referring to the 1 is in the block 130 determines a charging time for a charging stop planned based on an (initial) energy forecast for the route. The loading time is suspended a physical charging time for the drive energy storage and a set-up time together.

In the block 140 the initial total travel time is determined using the N (initial) individual speeds or speed profiles of the N route sections and the charging time of the (initially) planned charging stop. The individual speeds for determining the initial total travel time can be determined, for example, by the aforementioned forecast models and / or from real-time traffic information.

The one in the block 140 certain initial total travel time is now in the block 150 minimized by varying variables as part of the dual approach for driving and charging until a minimum is reached. In particular, the (initial) individual speeds of the route sections can be varied. For example, by reducing the speed in sections, a charging stop can be saved, which can shorten the total travel time. In addition, a charging hub and / or a location of the planned charging point can be varied along the route. For example, the total travel time can be shortened by using a different charging station than the initially planned charging station, for example because the utilization and thus the waiting time at the other charging station is lower.

In some embodiments, the method of the present disclosure uses dynamic programming to determine the minimum total travel time, for example using a cost function. In particular, the method can use an algorithm based on dynamic programming for the segment-wise solution of an optimization problem, i.e. to minimize the total travel time. For this purpose, forecast models can be integrated, for example, for a speed profile of the route or route sections of the route. In particular, the forecast models can data the algorithm, that is, supply input variables.

In some embodiments, the cost function can be given as follows: $$mi{n}_{u\left(k\right)}{\displaystyle \sum _{k=0}^{N-1}{t}_{k,\mathrm{L.}aden}\left({\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="DE102019109561A1\_0004.png"\; state="\{\{state\}\}">u</figure-callout>}}_{\mathrm{1,}k},k\right)+t_{k,\mathrm{F.}aHren}\left({\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="DE102019109561A1\_0004.png"\; state="\{\{state\}\}">u</figure-callout>}}_{\mathrm{2,}k},k\right)}$$

In the above formula, t indicates a time. u ₁ specifies a first control variable (“charging”) that relates to the at least one charging point, such as a charging stroke for a specific charging point. u ₂ specifies a second control variable (“driving”) which relates to the individual speeds or vehicle speeds of the route sections of the route. The summation takes place over the multitude of route segments k that form the travel route.

In the cost function explained above, a target state at the end point or route destination can be specified. The target state can, for example, be taken into account as a state variable in the cost function. The target status can be, for example, a (desired) remaining range (“RRW”) at the route destination or a remaining charge status (“remaining SoC”) of a drive energy storage device of an electric vehicle.

The minimum total travel time determined by minimizing the cost function, for example, is based on specific individual speeds for the route sections of the route and loading parameters, such as a location of a charging station and / or a charging hub and / or a time of a charging stop. The corresponding driving information and / or charging information can be output to a driver and / or a driver assistance system for automated driving. The travel information can include information relating to the specific individual speeds for the individual route sections of the route. Similarly, the charging information can include information relating to a location of a charging station and / or a charging hub and / or a time of a charging stop.

The corresponding driving information and / or charging information is typically output to a driver, for example visually on a display and / or by means of voice output. In particular, a target speed corresponding to the minimum total travel time can be displayed to the driver. The target speed can be output individually for each route section of the multiplicity of route sections. The target speed is a recommendation or a suggestion for an optimal speed to achieve the minimum total travel time.

Alternatively, the driving information (e.g. the target speed) and / or charging information can be output to a driver assistance system for automated driving. The driver assistance system for automated driving can be set up for partially autonomous or fully autonomous driving and control the vehicle according to the driving information and / or charging information.

According to the invention, the total travel time, which corresponds to a sum of travel time and charging time, is minimized. In particular, two aspects are equally taken into account for determining the minimum or optimal total travel time for a given route, namely driving and charging or their influencing variables. Different In other words, a holistic view of the total travel time takes place through dual consideration of driving and charging, whereby a global optimum of the total travel time can be ensured by taking into account the set system limits and / or boundary conditions (e.g. a remaining charge at the route destination).

QUOTES INCLUDED IN THE DESCRIPTION

This list of the documents listed by the applicant was generated automatically and is included solely 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 102017119453 A1 [0003]

Claims (11)

Method (100) for route planning in a navigation system of a vehicle, in particular an electric vehicle, comprising: Dividing (110) a route from a starting point to an end point into a plurality of route segments; Assigning (120) an individual speed to each route segment of the plurality of route segments; Determining (130) a charging time for at least one charging point along the route; Determining (140) an initial total travel time for the route based on the individual speeds assigned to the plurality of route sections and the loading time; and Determining (150) a minimum total travel time by varying the variables used for determining the initial total travel time relating to the individual speeds and the at least one charging point. The method (100) according to Claim 1 wherein dividing (110) a route from a starting point to an end point into a plurality of route segments comprises: dividing the route segment based on at least one criterion selected from the group consisting of: a route segment speed; a type of road; a structural route section property; and a charging point, or dividing the route into a plurality of equidistant route sections. The method (100) according to Claim 1 or 2 wherein the variable relating to the at least one charging point is selected from the group consisting of a charging hub and a location of the at least one charging point. The method (100) according to one of the Claims 1 to 3 , wherein the at least one charging point is planned based on at least one individual piece of information from the charging point along the route, and wherein the at least one individual piece of information is selected from the group consisting of a route, in particular a detour to the charging point, a waiting time at the charging point, and there is a set-up time at the charging point. The method (100) according to one of the Claims 1 to 4th wherein determining (130) a charging time for at least one charging point along the route comprises: determining a first charging time for a first charging point, the initial total travel time being based on the first charging time for the first charging point, the varying of the for determining the Initial total travel time variable used regarding the at least one charging point to determine the minimum total travel time comprises: replacing the first charging point with a second charging point that is different from the first charging point, and determining a second charging time for the second charging point. The method (100) according to one of the Claims 1 to 5 wherein the determination (150) of a minimum total travel time takes place by means of dynamic programming using a cost function. The method (100) according to one of the Claims 1 to 6th , wherein determining (150) a minimum total travel time is performed using the following formula: $$mi{n}_{u\left(k\right)}{\displaystyle \sum _{k=0}^{N-1}{t}_{k,\mathrm{L.}aden}\left(u_{\mathrm{1,}k},k\right)+t_{k,\mathrm{F.}aHren}\left(u_{\mathrm{2,}k},k\right)}$$

The method (100) according to one of the Claims 1 to 7th , further comprising: specifying a target state at the end point of the route, wherein the minimum total travel time is determined based on the target state. A storage medium, comprising a software program which is set up to be executed on a processor and thereby to carry out the method (100) according to one of the Claims 1 to 8th execute. Navigation system for a vehicle, comprising: at least one processor which is configured to carry out the method (100) according to one of the Claims 1 to 8th execute. Vehicle, in particular an electric vehicle, comprising the navigation system according to Claim 10 .

Images