DE102014219216A1 - Method and device for the anticipatory operation of a motor vehicle - Google Patents

Abstract

The invention relates to a method for operating a motor vehicle (1) with a hybrid drive system (2), comprising the following steps: - providing (S1) information about sections of a route most likely to be traveled; - performing (S2) a first optimization, wherein a total energy consumption is minimized based on a first cost function, wherein target vehicle speeds (νsoll) are determined for driving on the sections of the route most likely to be traveled; Performing (S3) a second optimization, wherein the load distribution (LV) between the drive units (3, 4) of the hybrid drive system (2) for one or more of the route sections for the target vehicle speeds (νsoll) determined in the first optimization optimized in terms of total energy consumption; and - operating the motor vehicle based on the target vehicle speed (νsoll) and based on the load distribution (LV) for the currently traveled route section.

Description

Technical area

The invention relates to speed controls for motor vehicles, in particular based on a foresighted consideration of the route to be traveled. Furthermore, the present invention relates to methods for determining power distribution in hybrid propulsion systems.

State of the art

It is known that in order to reduce the fuel consumption or the energy consumption of a motor vehicle driven by motor vehicles, the route ahead is taken into account and optimum driving speeds for a speed control are specified for sections of the route to be traveled. For this purpose, additional information is provided for the individual sections of the route lying ahead, which specify specifications for the speeds permissible in the relevant section of the route and other route parameters influencing the fuel consumption.

In motor vehicles with hybrid drive systems, there is still a need for optimization with regard to the distribution of power between the various drive units (load distribution). An optimization of the target vehicle speed with respect to the optimization target of the energy consumption, taking into account possible load distributions for the performance of the drive units is usually not possible due to the limited computing capacity of a controller available in the motor vehicle in real time.

Disclosure of the invention

According to the invention, a method for determining a desired vehicle speed and a load distribution for the division of services for a plurality of drive units of a hybrid drive system according to claim 1 and the device and the motor vehicle according to the independent claims are provided.

Further embodiments are specified in the dependent claims.

• – Bereitstellen von Informationen über Streckenabschnitte einer am wahrscheinlichsten zu befahrenden Fahrstrecke;
• – Durchführen einer ersten Optimierung, wobei ein gesamter Energieverbrauch basierend auf einer ersten Kostenfunktion unter Vorgabe einer festgelegten oder (unter Berücksichtigung der nachgelagerten Lastverteilung) bekannten Lastverteilung zwischen Antriebseinheiten eines hybriden Antriebssystems minimiert wird, wobei Soll-Fahrzeuggeschwindigkeiten zum Befahren der Streckenabschnitte der am wahrscheinlichsten zu befahrenden Fahrstrecke bestimmt werden;
• – Durchführen einer zweiten Optimierung, wobei für einen oder mehrere der Streckenabschnitte der Fahrstrecke für die in der ersten Optimierung bestimmten Soll-Fahrzeuggeschwindigkeiten die Lastverteilung zwischen den Antriebseinheiten des hybriden Antriebssystems hinsichtlich des gesamten Energieverbrauchs optimiert wird; und
• – Betreiben des Kraftfahrzeugs basierend auf der Soll-Fahrzeuggeschwindigkeit und basierend auf der Lastverteilung für den momentan befahrenen Streckenabschnitt.

According to a first aspect, a method for operating a motor vehicle with a hybrid drive system is provided, comprising the following steps:

• Providing information about sections of a most likely to travel route;
• Performing a first optimization, wherein a total energy consumption is minimized based on a first cost function under specification of a fixed or known (taking into account the downstream load distribution) load distribution between drive units of a hybrid drive system, wherein target vehicle speeds for driving the sections of the most likely to be driven Driving distance to be determined;
• Performing a second optimization, wherein for one or more of the route sections of the route for the target vehicle speeds determined in the first optimization, the load distribution between the drive units of the hybrid drive system is optimized with respect to the total energy consumption; and
• - Operating the motor vehicle based on the target vehicle speed and based on the load distribution for the currently traveled route section.

The above method is to optimize a target vehicle speed for a motor vehicle having a hybrid drive system according to power consumption. In the case of hybrid drive systems with a plurality of drive units, there continues to be a need for determining a load distribution for the division of the services provided by the various drive units or for the power obtained from different energy stores for driving the motor vehicle. However, since both the target vehicle speed and the load distribution have a direct effect on the energy consumption, it is necessary to specify both the target vehicle speed and the load distribution for the road section to be traveled for energy-minimized driving of the motor vehicle.

The above method makes it possible to quickly solve the relatively computational problem resulting from the determination of the minimum energy consumption for a given route, by determining the target vehicle speed and the load distribution separately. This is done by first determining an optimization of the target vehicle speed based on the information about the preceding route and then based on the determined target vehicle speed for at least the current section an optimized load distribution is determined.

By eliminating the determination of the load distribution to minimize the power consumption by the degree of freedom of the determination of the target vehicle speed, the above method can be performed particularly efficiently with a low resource requirement. This allows the above optimization method to be online, i. H. in real time, to calculate in the vehicle.

Furthermore, the route most likely to be traveled can be determined from navigation data input by a driver or from empirical values based on already traveled routes.

According to one embodiment, the information about the route sections resulting from the most probable route may include consumption-relevant route parameters, in particular information on a route gradient or gradient, on a roadway condition or type and / or on one or more speed limits.

It can be provided that the first optimization is carried out based on a predetermined load distribution or based on a load distribution, which was previously determined for the last traveled section.

In particular, the first optimization may include dynamic programming, linear programming, or mixed integer programming.

Furthermore, the second optimization can be carried out using an ECMS method.

The second optimization can be carried out with the aid of a second cost function, wherein a weighting factor K is taken into account as a ratio of the energy costs between the drive powers provided by the first and second drive units and, in particular, as a function of a state of charge of an electrical energy store. The weighting factor may in particular also depend on the nature of the future route.

• – Informationen über Streckenabschnitte einer am wahrscheinlichsten zu befahrenden Fahrstrecke bereitzustellen;
• – eine erste Optimierung durchzuführen, wobei ein gesamter Energieverbrauch basierend auf einer ersten Kostenfunktion minimiert wird, wobei Soll-Fahrzeuggeschwindigkeiten zum Befahren der Streckenabschnitte der am wahrscheinlichsten zu befahrenden Fahrstrecke bestimmt werden,
• – eine anschließende zweite Optimierung durchzuführen, wobei für einen oder mehrere der Streckenabschnitte der Fahrstrecke für die in der ersten Optimierung bestimmten Soll-Fahrzeuggeschwindigkeiten die Lastverteilung zwischen den Antriebseinheiten des hybriden Antriebssystems hinsichtlich des gesamten Energieverbrauchs optimiert wird,
• – das Kraftfahrzeug basierend auf der Soll-Fahrzeuggeschwindigkeit und basierend auf der Lastverteilung für den momentan befahrenen Streckenabschnitt zu betreiben.

According to a further aspect, an apparatus, in particular a vehicle control unit, is provided for operating a motor vehicle having a hybrid drive system, wherein the apparatus is designed to:

• To provide information about sections of a most likely to travel route;
• Perform a first optimization, wherein a total energy consumption is minimized based on a first cost function, wherein target vehicle speeds are determined for driving on the sections of the route most likely to be traveled,
• To perform a subsequent second optimization, wherein for one or more of the route sections of the route for the target vehicle speeds determined in the first optimization, the load distribution between the drive units of the hybrid drive system is optimized with respect to the total energy consumption,
• - To operate the motor vehicle based on the target vehicle speed and based on the load distribution for the currently traveled route section.

According to another aspect, there is provided a motor vehicle having a hybrid drive system and the above apparatus.

Brief description of the drawings

Embodiments are explained below with reference to the accompanying drawings. Show it:

1 a schematic representation of a motor vehicle with a control unit for specifying a target vehicle speed and a division ratio;

2 a possible course of the weighting factor K as a function of a state of charge SOC of an electrical energy store; and

3 a flowchart for illustrating the method for operating the motor vehicle.

Description of embodiments

1 shows a motor vehicle 1 with a hybrid drive system 2 that is a first drive unit 3 , For example, an internal combustion engine, and a second drive unit 4 , For example, an electric drive has. The first drive unit 3 and the second drive unit 4 may collectively or separately provide a drive torque, ie a drive power, to drive wheels via an output shaft (not shown).

The internal combustion engine as the first drive unit 3 is using fuel as a chemical fuel via a fuel tank 6 provided. The electric drive 4 as the second drive unit 4 is using electrical energy from an electrical energy storage 7 provided.

The hybrid drive system 2 further comprises a hybrid control device 5 to the first drive unit 3 and the second drive unit 4 to drive to provide a respective partial drive torque.

It is a vehicle control unit 10 provided that the hybrid control unit 5 indicates information about the drive torque to be provided and information about a load distribution. The load distribution gives a breakdown of the different drive units 3 . 4 to be provided drive services. The drive torque to be provided results as a manipulated variable from a speed control 11 in the control unit 10 or implemented separately.

The speed control 11 serves this purpose by providing a manipulated variable to the hybrid control unit 5 to regulate the speed of the motor vehicle to a target vehicle speed. The speed control 11 can be designed to be dependent on a control deviation of the vehicle speed to the target vehicle speed v _soll as a manipulated variable an indication of the drive torque to be provided to the hybrid control unit 5 to deliver.

The vehicle control unit 10 stands with a route information system 12 that may be included in a navigation system that provides information about the route ahead. The route information system 12 determined based on z. B. provided by the driver navigation data or the like a route that is most likely driven by the vehicle (most likely route). Furthermore, the most probable route can also be determined in a manner known per se from historical driving data on already traveled routes.

The most probable route is determined by one or more connections of the sections. The route information system 12 puts the vehicle control unit 10 In addition to information about the sections also fuel consumption relevant parameters for each of the relevant sections available.

The route information system 12 may be part of a driver assistance system or part of a navigation system. The route information system 12 accesses a map store that can provide information about links.

The vehicle control unit 10 includes an optimization unit 13 that of the route information system 12 the information about the route sections of the route including the fuel consumption relevant parameters for each of the stretch sections receives.

In conjunction with the flowchart of 2 For example, a method for optimizing an operation of a motor vehicle with respect to the energy consumption involved in the optimization unit will be described 13 can be carried out.

In step S1, information is provided about adjacent sections of a most likely to travel route. The most likely to be traveled route results from, for example, entered by a driver navigation data, based on experience based on previously traveled in the past routes or the like.

The information about the route sections resulting from the most probable route includes consumption-relevant. Route parameters, such as information about a route gradient or gradient, to a road condition or type, such. As highway, highway, urban road, as well as speed limits, resulting for example from legal speed specifications, straightening speeds or curve radii. Furthermore, weather information that z. As wind conditions or probability of rain, are specified.

In step S2, a first optimization of a target vehicle speed v _soll for driving the route sections is undertaken with the aid of an objective function, which indicates a first cost function K1 for the energy consumption. The first cost function K1 represents an objective function which determines the energy consumption for speed trajectories over the route sections of the route in question. In other words, the first cost function K1 relates to the sum of the energy consumptions of the individual route sections depending on a respective speed with which each of the route sections is traveled.

The energy consumption determined by the first cost function K1 is minimized by the optimization method.

wobei LV einer Lastverteilung als eine Aufteilung der Teilantriebsleistungen der Antriebseinheiten (Verhältnis der von den Antriebseinheiten jeweils bereitgestellten Antriebsleistungen) entspricht. Die Lastverteilung LV wird vorgegeben bzw. entsprechend einem Verhalten eines nachgelagerten Optimierungsverfahrens antizipiert.For a number k of track sections with two drive units:

wherein LV corresponds to a load distribution as a division of the partial drive powers of the drive units (ratio of drive powers respectively provided by the drive units). The load distribution LV is specified or anticipated in accordance with a behavior of a downstream optimization method.

Furthermore, L corresponds to the drive power required to achieve the desired vehicle speed v, g1, g2 the energy cost functions for the individual drive units based on the required partial drive services, n an index of the relevant section section and K a weighting factor, the energy cost ratio for the energy consumption of both drive units 3 . 4 indicates.

In the first optimization can be assumed by a given load distribution LV, the load distribution z. B. by a behavior of a downstream optimization method, such. As an ECMS method can be determined. Alternatively, an estimated load distribution LV can be assumed, which can correspond to a load distribution LV, as was determined previously for the last traveled section.

Common initial optimization optimization methods known per se may include dynamic programming, linear programming, or mixed integer programming. The provided first cost function K1 (objective function) is based on a total energy consumption, the drive power obtained from the chemical energy of the fuel and that from the electrical energy of the electrical energy store 7 obtained drive power taken into account. In this case, the weighting factor K, which inter alia depends on the efficiency of the conversion of the fuel energy into electrical energy between the chemical and electrical energy and its storage, is taken into account. The total energy consumption corresponds to a demand for energy to be converted into kinetic energy and also takes into account whether the kinetic energy is transferred via the first or second drive unit 3 . 4 provided.

In step S3, in a second optimization, the load distribution LV is determined for at least the current route section or over all route sections of the entire route. This determination is carried out based on the target vehicle speed determined in step S2 for at least the current route section or a trajectory of the determined target vehicle speeds v _soll over the route sections of the entire driving route.

A common optimization method for load balancing corresponds to an ECMS (equivalent consumption minimization strategy) method, which is known per se. The ECMS method minimizes the energy costs according to a second cost function K2 over the considered route sections. The second cost function K2 takes into account the weighted sum of the energy consumptions for each subsection considered for providing the partial drive powers of the various drive units predetermined by the load distribution 3 . 4 ,

The second cost function K2 for the ECMS method takes into account as a parameter in the cost function the weighting factor K. The determination of the weighting factor K as a parameter of the second cost function K2 has a decisive influence on the fuel consumption. If appropriate, the weighting factor K can be adjusted in a forward-looking manner, so that the state of charge SOC of the electrical energy store 6 is utilized and at the same time predetermined charging limits of the electrical energy storage device are maintained. The dependency can provide, for example, that the weighting factor K is high when the charge state of the electrical energy store is low, as a result of which the charge of the energy store increases and thereby a minimum charge of the electrical energy store 6 not fallen below. In 3 For example, is a possible course of the weighting factor K depending on a state of charge SOC of the electrical energy storage 6 shown.

In addition, forward-looking information about the route to be traveled can flow in, so that energy is taken from the electrical energy store, for example, before the start of a journey, so that the full recuperation potential can be utilized while driving and the electrical energy store 6 can be recharged cheaply. Alternatively, the weighting factor of the ECMS method by a simple strategy, ie only as a function of the state of charge of the electrical energy storage 6 be adjusted.

In step S4, the setpoint vehicle speed determined for the current route section can be sent to the cruise control 11 are transmitted and the corresponding load distribution LV to the hybrid control unit 5 to be provided. Subsequently, the method steps are repeated, so that an optimization over the entire route takes place continuously.

In general, it is proposed that the original optimization problem of reducing the energy consumption by specifying a drive torque to be provided and the load distribution LV in two separate optimization tasks, namely an optimization of the target vehicle speed under specification of a fixed load distribution LV and optimization of the load distribution LV below Assumption of the trajectory of the target vehicle speeds previously determined for the route sections. Thus, the entire computational effort to solve the optimization task can be significantly reduced.

For the distribution of power to the various drive units while the already known for hybrid drive systems ECMS method can be used while for the determination of the target vehicle speeds over the entire route conventional optimization methods, such as dynamic programming, can be applied. This makes it possible to optimize the optimization task during operation of the motor vehicle online, d. H. in a control unit located in the motor vehicle, to be released in real time, so that the operating strategy for the motor vehicle can always be adapted to the currently preceding driving route.

Claims (12)

Method for operating a motor vehicle ( 1 ) with a hybrid drive system ( 2 ), comprising the following steps: - providing (S1) information about sections of a route most likely to be traveled; - Performing (S2) a first optimization, wherein a total energy consumption is minimized based on a first cost function, wherein target vehicle speeds (ν _soll ) are determined for driving on the sections of the most likely to be driven route; - performing (S3) a second optimization, wherein for one or more of the route sections of the route for the determined in the first optimization target vehicle speeds (ν _soll ), the load distribution (LV) between the drive units ( 3 . 4 ) of the hybrid propulsion system ( 2 ) is optimized in terms of total energy consumption; and - operating the motor vehicle based on the target vehicle speed (ν _soll) and based on the load distribution (LV) for the currently traveled route section. The method of claim 1, wherein the most likely to be traveled route from determined by a driver navigation data or experience based on already traveled routes is determined. Method according to claim 1 or 2, wherein the information about the route sections resulting from the most probable route includes consumption-relevant route parameters, in particular information on a route gradient or gradient, on a roadway condition or type and / or on one or more speed limits. Method according to one of claims 1 to 3, wherein the first optimization is carried out based on a predetermined load distribution (LV) or based on a load distribution, which was previously determined for the last traveled section. Method according to one of claims 1 to 4, wherein the first optimization comprises a dynamic programming, a linear programming or a mixed integer programming. Method according to one of claims 1 to 5, wherein the second optimization is carried out using an ECMS method. Method according to one of claims 1 to 6, wherein the second optimization is carried out by means of a second cost function (K2), wherein a weighting factor (K) as a ratio of energy costs between that of the first and second drive unit ( 3 . 4 ) provided drive power and in particular in dependence of a state of charge of an electrical energy storage ( 7 ). Device, in particular vehicle control device, for operating a motor vehicle ( 1 ) with a hybrid drive system ( 2 ), the device being designed to: provide information about sections of a most likely to travel route; Perform a first optimization, wherein a total energy consumption is minimized based on a first cost function (K1), wherein target vehicle speeds (ν _soll ) are determined for driving on the sections of the most likely to travel route, - perform a second optimization, wherein for one or more of the route sections of the route for the target vehicle speeds (ν _soll ) determined in the first optimization, the load distribution (LV) between the drive units ( 3 . 4 ) of the hybrid propulsion system ( 2 ) is optimized with respect to the total energy consumption, - to operate the motor vehicle based on the target vehicle speed (ν _soll ) and based on the load distribution (LV) for the currently traveled route section. Motor vehicle ( 1 ) with a hybrid drive system ( 2 ) and a device according to claim 11. Computer program, which is set up to carry out all the steps of a method according to one of Claims 1 to 7. Machine-readable storage medium on which a computer program according to claim 10 is stored. A control unit comprising a machine-readable storage medium according to claim 11.

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