Control Device and Method for the Predictive Operation of an On-Board Power Supply System

Abstract

A control device for operating an on-board power supply system of a motor vehicle includes an input unit which is configured to determine operating parameters of the on-board power supply system of the motor vehicle and/or one or more environment parameters of the motor vehicle and to forward them to a processing unit of the control device. At least one environment parameter is a probability of an operating action of a third-party vehicle.

Claims

1.-10. (canceled)

11. A control device for operating an on-board power supply system of a motor vehicle, the control device comprising: a processing unit; and an input unit which is configured to ascertain at least one of operating parameters of the on-board power supply system of the vehicle or one or more environmental parameters of the motor vehicle, and to forward the at least one of the operating parameters of the on-board power supply of the vehicle or the one or more environmental parameters of the motor vehicle to the processing unit, wherein: at least one of the environmental parameters is a probability of a third-party vehicle operating action, the probability is linked to a georeference point, and the processing unit is configured to determine an on-board network operating action based on a characteristic indicator of the georeference point as a function of: the probability of the third-party vehicle operating action, or one or more other environmental parameters known at the georeference point.

12. The control device according to claim 11, wherein the processing unit is configured: to determine the on-board network operating action depending on a plurality of probabilities of the third-party vehicle operating action, wherein the probabilities are ascertained for successive georeference points along an expected route of the motor vehicle.

13. The control device according to claim 12, wherein a set of the consecutive georeference points is limited by a prediction horizon.

14. The control device according to claim 12, wherein the on-board network operating action is determined based only on a subset of the georeference points, the ascertained probability value of which for the third-party vehicle operating action meets at least one relevance threshold.

15. The control device according to claim 11, wherein the third-party vehicle operating action for which the probability is ascertained is at least one of: a regeneration operation of an electric drive unit of the third-party vehicle, and/or a temporary shutdown of an internal combustion engine of the third-party vehicle followed by a restart, or a consumer power demand in the on-board power supply system that is above a high-power limit or below a low-power limit.

16. A method for operating an on-board power supply system of a motor vehicle, the method comprising: determining at least one of each of a plurality of operating parameters of the on-board power supply system of the vehicle or one or more environmental parameters of the vehicle, wherein at least one of the environmental parameters is a probability of a third-party vehicle operating action, and the probability is linked to a georeference point, and determining an on-board network operating action based on a characteristic indicator of the georeference point as a function of: the probability of the third-party vehicle operating action, or one or more other environmental parameters known at the georeference point.

17. The method according to claim 16, wherein at least one of: the on-board network operating action is determined based on a learned operating strategy, or the on-board network operating action is verified based on a predefined verification strategy.

18. A central database device, wherein the central database device is configured: to receive an indicator value for an operating action at or near a georeference point from a plurality of third-party vehicles, to ascertain a probability for a presence of the operating action at the georeference point from the indicator values, and to transmit the probability to the control device according to claim 11.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0118] FIG. 1 shows a diagram of the interaction of a control device according to an embodiment of the invention with a central database device according to an embodiment of the invention, and a third-party vehicle fleet.

[0119] FIG. 2 shows a schematic view of the control device from FIG. 1 when carrying out a method according to one embodiment of the invention.

[0120] FIG. 3 shows a schematic view of a map with which the control device and the database device from FIG. 1 interact, having a plurality of georeference points at which values for parameters are used when carrying out the method according to FIG. 6.

[0121] FIG. 4 shows a schematic view of the central database device from FIG. 1 when carrying out the method according to FIG. 6.

[0122] FIG. 5 shows a schematic view of ascertaining a probability of an operating action for relevant third-party vehicles in the context of carrying out the method according to FIG. 6.

[0123] FIG. 6 shows a flowchart for carrying out a method according to an exemplary embodiment of the invention in an arrangement according to FIG. 1.

DETAILED DESCRIPTION OF THE DRAWINGS

[0124] FIG. 1 shows a diagram of the interaction of a control device 10 of a vehicle 1 according to an exemplary embodiment of the invention with a central database device 20 according to an exemplary embodiment of the invention and with a third-party vehicle fleet 30 with a plurality of third-party vehicles. The diagram also shows a map 2, the underlying navigation data records of which—and in particular the georeference points P.sub.ref specified on the map—are available both to the vehicle 1 and its control device 10, as well as to the central database device 20.

[0125] The vehicle 1 has a communication device 11, which is also connected to the control device 10 of the vehicle 1 and is designed to exchange data with a communication device 21 of the central database device 20. In particular, this data exchange takes place over a mobile communication network 3. The vehicle 1 supplies the central database device 20, in particular, with values of the operating parameters available in the on-board network (i.e. an operating state BZ) for each georeference point P.sub.ref the vehicle has passed, and receives values for environmental parameters for the georeference points P.sub.ref to be passed in the near future, and also values of the probabilities (in the exemplary embodiment at least a probability of a regeneration operation W.sub.REKU, and possibly a probability of an automatic start/stop operation W.sub.SSA) of specific third-party vehicle operating actions, such as a regeneration operation REKU (and possibly an automatic start/stop operation SSA).

[0126] The control device 10 has an input unit 12, a processing unit 13 and an output unit 14, and is designed to control an on-board network 15 of the motor vehicle 1 using this topology.

[0127] The processing unit 13 in the exemplary embodiment is designed as a learning system, having a learning unit 16 for decision-making regarding possible on-board network operating actions B, and a reflex unit 17 for verifying the decision proposals of the learning unit 16.

[0128] Each of the vehicles of the third-party vehicle fleet 30 also has a communication device, which also transfers the current values of the operating parameters (summarizing the operating state) to the central database device 20 at each georeference point P.sub.ref that is passed and stores them there in a database memory 22.

[0129] In addition to communication device 21 and database memory 22, the database device 20 has a computing server 23 which controls the database device 20 and manages the data inputs and data outputs in response to requests from vehicles 1.

[0130] The database memory 22 maintains for each georeference point P.sub.ref a georeference point data record, which contains the values of the environmental parameters of the point (the environmental state) as well as the plurality of stored operating states of the third-party vehicles from the fleet 30 as they each pass the respective georeference point, wherein each operating state is defined by the total set of values of the individual operating parameters. In addition, each of the georeference point data records for the relevant point P.sub.ref contains a value—updated continuously or at predetermined intervals—of a probability of a specific on-board network operating action (in the implementation example REKU and/or SSA) in relation to the operating states of the previously stored passages of the various third-party vehicles at the georeference point.

[0131] Specifically, such a georeference point data record in the exemplary embodiment contains values for some or all of the following parameters: [0132] (1) Spatial definition of the georeference point: P.sub.ref [0133] (2) Operating parameters of the vehicles that have passed the georeference point in the past: [0134] vehicle class: K [0135] vehicle speed: v [0136] time of day: t [0137] type of day: d [0138] direction of travel: R [0139] indicator for regeneration operation during the passage: i.sub.REKU [0140] if applicable, an indicator of whether stop/start device is activated during passage: i.sub.SSA; [0141] if applicable, indicator for an atypical consumer output of at least one consumer connected to the on-board network during passage: i.sub.VL [0142] (3) Environmental parameters: [0143] probability of REKU during the passage: W.sub.REKU [0144] if applicable, probability of SSA during the passage: W.sub.SSA [0145] if applicable, probability of VL during the passage: W.sub.VL [0146] characteristic indicator I.sub.C [0147] direction of travel: R [0148] road type: S [0149] slope of the road: G

[0150] Based on FIGS. 2 to 6, an exemplary embodiment of a method according to the invention for operating the on-board network 15 in the infrastructure described in FIG. 1 is explained in more detail below.

[0151] FIG. 2 also shows details of the information processing in the control device 10. FIG. 3 shows an example of the role of the map 2 in determining the on-board network operating action B. FIG. 4 shows details of the information processing of the data supplied by the vehicles of the fleet 30 in the central database device 20. FIG. 5 shows an example of how the probability W.sub.REKU of a third-party vehicle operating action REKU can be ascertained and used in the vehicle 1. Finally, FIG. 6 shows an exemplary flowchart for important method steps of the exemplary method.

[0152] FIG. 2 shows how the input unit 12 can use the communication device 11 of the control device 10 to ascertain the required parameter values for describing a current or future relevant operating state BZ and environmental state UZ.

[0153] Firstly, a higher-level vehicle control system, not shown, provides an expected route 4 (compare FIG. 3), which for the purpose of the exemplary embodiment of the invention is defined by a path of successive georeference points P.sub.ref.

[0154] The environmental status UZ with the corresponding values of the respective associated parameters refers to a specific georeference point, which was determined as relevant by way of the left-hand data of the map 2 in the navigation system (see FIG. 6, S110), in the typical case, because this point will lie on the expected route 4 in the near future. The expected route 4 is indicated by a path of adjacent georeference points P.sub.ref,n to P.sub.ref,n+x. In FIG. 2, dotted lines are used to indicate symbolically the georeference point P.sub.ref,n to which the displayed information processing refers. In FIG. 3, this reference to the expected route 4 is entered symbolically on the map 2.

[0155] The operating mode BZ with the corresponding values of the respective associated parameters refers in the exemplary embodiment to the current status of the vehicle 1 or its on-board network 15.

[0156] A value for each of the operational parameters BZ and environmental parameters UZ (at P.sub.ref,n) entered in FIG. 2 is thus now available to the input unit 12 and is forwarded to the processing unit 13.

[0157] For each relevant georeference point P.sub.ref, the processing unit 13 can thus now access the current operating status BZ of the on-board network 15 and the vehicle 1, as well as the environmental status UZ of the relevant georeference point P.sub.ref for decision-making about possible on-board network operating actions B. In the exemplary embodiment the latter contains in particular a value W.sub.REKU for the probability of the third-party vehicle operating action REKU.

[0158] On the basis of this information, a learning unit 16 of the processing unit 13 proposes a suitable operating action B which corresponds to a predefined operating strategy, possibly supplemented and/or replaced by previous learning processes. A reflex unit 17 of the processing unit 13 verifies the proposed operating action B for compatibility with a predetermined strategy and sends a reward or penalty to the learning unit 16 depending on the result of the check. If the action B is rejected by the reflex unit 17, the reflex unit 17 can also forward a modified, permitted operating action B′ to the output unit 14. The task of the output unit 14 is to activate an operating action B (or B′) that has been decided upon (see FIG. 6, S160) in the on-board network 15.

[0159] The resulting change in the operating state BZ can be fed back directly to the input unit 12, or to the learning unit 16 in abstracted form as a delayed reward/penalty.

[0160] In the exemplary embodiment described here, a typical possible on-board network operating action B is a conditioning of the energy storage unit E of the motor vehicle, in particular in the sense of a deliberate discharge if a charge contribution is expected (indicator: high probability of regeneration for the next georeference point or points) or in the sense of a deliberate recharging in the case of an expected discharge contribution (indicator: high start/stop probability for the next georeference point or points).

[0161] FIG. 3 shows which information is stored in the database memory 22 depending on an associated georeference point P.sub.ref, and the logic which is used to query this information by the control device 10 of the motor vehicle 1.

[0162] Due to the integration of the navigation system with its stored map 2, the control device 10 has knowledge of an expected route 4, which is defined by a path 5 in successively adjacent georeference points P.sub.ref. In order to obtain information about the environmental status UZ of the georeference points P.sub.ref soon to be passed, the control device 10 uses the communication device 11 to query the central database device 20 for the information stored for the corresponding points P.sub.ref. These may be parameters of the operating state of third-party vehicles from the fleet 30, if necessary, but are normally at least the parameters of the environmental state UZ. In this case, therefore, in particular also the probability of a regeneration operating action B in those third-party vehicles that have already passed the relevant georeference point earlier and have deposited a data record to this effect in the central database facility 20.

[0163] As can be seen from FIG. 4, for each georeference point P.sub.ref on the map 2 the database memory 22 thus stores a data record which contains the definition of the point and its environmental state UZ, as well as a plurality of operating states of those vehicles of the fleet 30 that have already passed the georeference point P.sub.ref at an earlier point in time.

[0164] FIG. 5 shows how a probability of the presence of a specific third-party vehicle operating action, in this case a probability for the presence of a regeneration operating action REKU, can be ascertained from this data.

[0165] This probability can optionally be ascertained by way of the computing server 23 of the database device 20 and transmitted pre-determined to the control device 10 of the vehicle 1, or the stored bases for the calculation are transferred to the control device 10 and the calculation itself is carried out there. In both cases, the calculation can be carried out as shown in FIG. 5.

[0166] The vehicle 1 uses its control device 10 (not shown in FIG. 5) to query the data records for the associated georeference point(s) P.sub.ref, taking into account the expected route 4.

[0167] The respective data record stores how many vehicles have passed the corresponding georeference point in the past. In FIG. 5, as a rough simplification, ten vehicles are shown. The data record shows that for eight vehicles the indicator i.sub.REKU for the presence of a regeneration operating action REKU is set (dark background icons), but for two other vehicles it is not (light background icons).

[0168] In an additional step, on the basis of the operating status BZ of the vehicle 1, those “historical” third-party vehicles for which the operating state is not sufficiently similar are removed from the analysis.

[0169] In the exemplary embodiment, seven relevant vehicles remain, six of which have set the indicator i.sub.REKU.

[0170] This results in a probability W.sub.REKU for the presence of a regeneration at the observed georeference point P.sub.ref of 6 out of 7, i.e. of 0.857.

[0171] This probability W.sub.REKU is then compared with a predefined relevance threshold W.sub.rel, which in the exemplary embodiment has the value 0.75 (see FIG. 6, S130). As the probability is higher than the relevance threshold, it is taken into account in the decision about possible on-board network operating actions B.

[0172] In the exemplary embodiment, the decision is taken in particular on the basis of expected (dis)charge quantities or (dis)charge amounts, which are determined depending on the ascertained probabilities W.sub.REKU and/or, if applicable, W.sub.SSA to be taken into account.

[0173] In FIG. 6, individual method steps relating to this are summarized.

[0174] In step S110, the expected route 4 along the path 5 with the georeference points P.sub.ref located on it is first ascertained.

[0175] In step S120—in particular according to FIG. 5—for all georeference points P.sub.ref on the path 5 it is ascertained whether they lie within a prediction horizon H.sub.PRÄD. For those P.sub.ref within the prediction horizon H.sub.PRÄD, the probability W.sub.REKU for a regeneration operating action and/or, where applicable, W.sub.SSA for a start-stop operating action W.sub.SSA, is ascertained for the third-party vehicles considered in the fleet 30.

[0176] In step S130, the georeference points P.sub.ref are identified for which the ascertained value of the probability W.sub.REKU (or W.sub.SSA) is above a relevance threshold W.sub.rel in order to identify those cases in which an improvement of the prediction—in particular compared to a physically determined estimate of a (dis)charge contribution—is possible at all.

[0177] The expected charge contribution is then determined for all identified georeference points in step S140.

[0178] For all other georeference points, by contrast, in step S141 a characteristic indicator IC is determined, which can be derived, for example, from a road type S, a direction of travel R, and/or in particular a gradient G at the relevant georeference point, and which provides an indication as to how reliably an expected charge contribution can be determined on the basis of physical conditions of the environment of the georeference point. Values for the characteristic indicator I.sub.C can be “deterministic” or “probabilistic”, for example, depending on whether a specific operating action typically occurs for a given georeference point or whether such a clear indication is not possible.

[0179] Following step S141, in step S142 the expected charge quantity tag is determined only for those georeference points with I.sub.C=“deterministic”.

[0180] In step S150, the sum of the charge contributions of the individual georeference points to be taken into account along the path 5 of the expected route 4 is transmitted to the input unit 12 (via communication device 11).

[0181] In step S160, the processing unit 13 decides on possible operating actions B of the on-board network 15 on the basis of the transmitted sum.

[0182] In step S170, operating action B is performed when the processing unit 13 has instructed the output unit 14 to do so and the output unit 14 has issued a corresponding control command. In the exemplary embodiment, the operating action B is, for example, a conditioning of the energy storage units E of the vehicle 1 with regard to an expected (dis)charge quantity.

[0183] This conditioning can involve a targeted discharging of the energy storage unit E if a higher charge quantity, soon to be available, is expected on the basis of a probability W.sub.REKU.

[0184] On the other hand, the conditioning can involve a targeted charging of the energy storage unit E if a higher charge quantity, soon to be required, is expected on the basis of a probability W.sub.SSA.

LIST OF REFERENCE SIGNS

[0185] 1 motor vehicle [0186] 2 road map [0187] 3 mobile communications network [0188] 4 expected route [0189] 5 path [0190] 10 control device [0191] 11 communication device [0192] 12 input unit [0193] 13 processing unit [0194] 14 output unit [0195] 15 on-board electrical network [0196] 16 learning unit [0197] 17 reflex unit [0198] 20 database device [0199] 21 communication device [0200] 22 database memory [0201] 23 computing server [0202] 30 third-party vehicle fleet [0203] B on-board network action [0204] BZ operating state [0205] d type of day [0206] E energy store [0207] G gradient/slope [0208] H.sub.präd prediction horizon [0209] I.sub.C characteristic indicator [0210] K vehicle class and/or weight class [0211] P.sub.ref georeference point [0212] t time of day [0213] UZ environmental condition [0214] R direction of travel [0215] REKU operating action regeneration [0216] i.sub.REKU indicator for regeneration on/off/degree [0217] S road type [0218] SSA operating action Start-Stop-automatic [0219] i.sub.SSA indicator for automatic start/stop with internal combustion engine off/on [0220] v vehicle speed [0221] W.sub.REKU regeneration probability [0222] W.sub.rel relevance threshold [0223] W.sub.SSA start/stop probability