METHOD FOR ADAPTIVELY CONTROLLING A VEHICLE SPEED IN A VEHICLE AND SPEED CONTROL SYSTEM FOR EXECUTING THE METHOD

Description

[0001] The invention relates to a method for adaptively controlling a vehicle speed in a vehicle, in particular a commercial vehicle with a cruise control system, and to a cruise control system for carrying out the method.

[0002] In vehicles, particularly commercial vehicles, speed control systems are known as cruise control (CCS). These systems regulate the current vehicle speed to a reference speed specified by the driver without the need to apply the brake pedal. Such systems can be enhanced with adaptive control, which additionally regulates the vehicle speed in anticipation and thus prescribes a fuel-efficient driving style to achieve the reference speed. Fuel-efficient adaptive control takes into account, for example, route information, particularly the topography of a section of road ahead. One such system is known as a predictive powertrain control (PPC) system.

[0003] DE 10 2014 204 206 A1 proposes route navigation with an optimal speed profile, whereby an optimal vehicle speed is calculated for a predefined route from an initial vehicle position to a destination using dynamic programming. Thus, for example, at the start of the journey, an optimal speed profile is created that specifies the vehicle's target speeds for each point on the predefined route, allowing the route to be traveled with optimized energy consumption. The speed profile is determined outside the vehicle, so that computationally intensive calculations are not performed on the vehicle.

[0004] US 20140277971 A1 also discloses a method for calculating a speed profile between a specified starting position and an end position, wherein a distance to be traveled between the starting position and the end position is determined or specified. An optimal speed profile is created for this distance to be traveled, taking into account route information such as a gradient, speed limits, traffic jams, etc. The calculations are executed and saved in advance, for example, on a computer or in the cloud, so that the pre-determined speed profile can be used to regulate the vehicle's speed for the entire route during the journey.

[0005] US8386091 B1 shows a comparable method for calculating a speed profile, where the calculation takes place outside the vehicle on a cloud-based computer. First, the driver specifies a route to be driven, and a fuel-efficient speed profile is determined for this route based on route information.

[0006] The disadvantage here is that the entire route to be traveled is calculated, requiring a significant amount of computing power and time to determine the speed profile for the predefined route. Furthermore, the calculation is based on current values ​​before the start of the journey, so that if an event occurs during the journey, such as a new or clear traffic jam or an unintentional loading or unloading of the vehicle, the calculated speed profile becomes inaccurate.

[0007] DE 10 2008 039 950 B4 further describes a method for determining a driving profile. A route to be followed is defined, and the current position of the vehicle is determined. A speed profile is determined for the route or a portion of the route in a model, particularly depending on topography and the properties of a drive system, such as acceleration potential, in order to optimize fuel consumption. Furthermore, acceleration at a distance in front of the vehicle can be calculated in order to overcome an incline in a fuel-efficient manner, for example.

[0008] US 20120283928 A relates to a method for controlling overspeed and underspeed of a vehicle with a cruise control system during a downhill or uphill gradient. The vehicle speed and vehicle mass are determined, and the brakes and drive are adjusted in such a way that overspeed or underspeed can be minimized.

[0009] DE 10 2009 022 170 A1 relates to a method for limiting vehicle speed depending on a centripetal force acting on the vehicle. For this purpose, a detection unit detects a curve within the detection range and determines a centripetal force acting on the vehicle for the detection range, particularly depending on the vehicle mass and the vehicle speed. If this force is too high, the vehicle speed is reduced.

[0010] DE 10 2012 214 827A1 describes a method in which the vehicle is controlled depending on a load parameter and route information that is determined in advance for a road section to be traveled.

[0011] US 2014 / 0277835 A1 discloses systems and methods for optimizing the energy consumption of a vehicle using dynamic programming while traveling along a route consisting of road segments. A speed profile generator located at least partially outside the vehicle calculates an optimal speed profile using an energy consumption model of the vehicle together with road condition data of the route. The speed profile specifies target speeds for locations along the route such that the route is traveled with optimal energy consumption. The speed profile generator compares the energy consumption for various possible trajectories in the speed profile between a minimum trajectory and a maximum trajectory.

[0012] The object of the invention is to provide a method for adaptive control of a vehicle speed with which a fuel-efficient driving style can be reliably achieved, particularly with a view to reducing computing time and effort in order to enable fast and cost-effective data processing in the vehicle. Furthermore, the object of the invention is to provide a cruise control system for implementing the method.

[0013] This object is achieved by a method according to claim 1, a cruise control system according to claim 12, and a vehicle according to claim 13. Preferred developments are specified in the dependent claims. According to the invention, the current vehicle speed of a vehicle is adapted to a reference speed specified by the driver, with complex computational operations being outsourced to an external computing unit, preferably a cloud. At least one calculation coefficient is used, which is derived on the external computing unit as a function of vehicle dynamics parameters and current route information.With the at least one calculation coefficient, a target vehicle speed and / or a target vehicle deceleration can be determined, for example, in a control unit of a cruise control system according to the invention. This target vehicle deceleration is used to adjust the current vehicle speed in order to achieve the reference speed, while aiming for a fuel-efficient driving style. The target vehicle deceleration can be positive or negative. This is achieved, for example, by controlling a vehicle's drive with a corresponding drive torque or the vehicle's braking systems with corresponding braking torques, so that the vehicle speed is increased (positive target vehicle deceleration) or reduced (negative target vehicle deceleration).

[0014] This already results in the advantage that no high demands are placed on the performance of the control unit in the vehicle's cruise control system, since complex computing operations, i.e. in particular the determination of the at least one calculation coefficient for determining the vehicle's target speed and / or the vehicle's target deceleration, are outsourced to the external computing unit. The external computing unit can be reached wirelessly via a network, for example via a radio connection, in particular a mobile radio connection, for example to the Internet, and the infrastructure of the external computing unit allows complex computing operations, e.g. simulations, to be carried out in parallel. The external computing unit, which operates, for example, in the manner of cloud computing, can be reached from all vehicles with an adaptive control system according to the invention.Building such a powerful infrastructure outside the vehicle is much easier and more cost-effective, as a cost-intensive computing unit does not have to be installed, maintained, and updated in every vehicle.

[0015] According to the invention, vehicle dynamics parameters are understood to be a current position of the vehicle, a current vehicle mass, a current vehicle speed, a currently maximum available drive torque and a currently maximum available braking torque, by which a currently existing vehicle dynamics situation can be defined; e.g., how quickly can the vehicle be braked or accelerated at the current position starting from the current vehicle speed.

[0016] This already has the advantage that the currently available vehicle parameters are taken into account for the adaptive control of the vehicle speed, enabling reliable adaptive adjustment of the vehicle speed to achieve a fuel-efficient driving style for the current position, even if the vehicle mass changes, for example, after temporary loading or unloading, or if the vehicle speed deviates from the planned speed profile. The vehicle parameters are determined in the vehicle and continuously transmitted to the external processing unit, for example, depending on the vehicle speed, so that at least one calculation coefficient can be determined based on the current vehicle dynamics parameters.

[0017] To calculate the target vehicle speed, the cruise control system according to the invention then weights the currently maximum available braking torque with a first calculation coefficient, the current vehicle mass with a second calculation coefficient, and / or the currently maximum available drive torque with a third calculation coefficient, so that only a simple calculation operation, for example, multiplying the individual factors, takes place in the control unit. In addition, further route information can be taken into account using a fourth calculation factor. Alternatively, only individual calculation coefficients can be used to calculate the target vehicle speed, for example, if a specific vehicle parameter is not available in the vehicle.

[0018] According to the invention, when determining the at least one calculation coefficient, currently available route information for a route section ahead of the vehicle's position is taken into account, which information is stored, for example, in a map system on the external computing unit. Route information includes, for example, topography, i.e., an incline, a decline, or a curve, but also speed limits or traffic information, such as a traffic jam, slow-moving / slow-moving traffic, or traffic approaching intersections, traffic lights, or the like, and / or possibly taking into account the traffic light switching phases.

[0019] Thus, when determining the at least one calculation coefficient in the external processing unit, the topography at the current position and in the section of road ahead of the vehicle, or any traffic jam ahead, can also be taken into account. This route information can advantageously be kept up to date by updating the external processing unit or the map system when changes to the current route information occur. This can further save computing effort and storage capacity on the vehicle, because it is not necessary to update the vehicle's control unit and save current topographies, but only on the external processing unit. Since the external processing unit can be reached by all vehicles with an adaptive control system according to the invention, the current route information only needs to be updated at a central location, thus saving updating effort.This means that the calculation coefficients are constantly kept up to date so that fuel-efficient driving behavior can be maintained even in the event of current events, especially current traffic information such as a new traffic jam.

[0020] Preferably, an algorithm for deriving the at least one calculation coefficient is provided on the external computing unit, wherein the algorithm predetermines the at least one calculation coefficient, in particular for specific positions in the map system. For this purpose, the algorithm can, for example, perform simulations for various target vehicle speeds and / or target vehicle decelerations at the individual positions in the map system, depending on different values ​​for the vehicle's dynamic driving parameters as well as different values ​​for the upcoming route section, and derive the calculation coefficient with the lowest fuel consumption for the corresponding position from the simulations.This calculation coefficient is then saved together with the corresponding values ​​of the vehicle's dynamic driving parameters and the value for the route section in the map system for the corresponding position.

[0021] If a vehicle traveling at a corresponding position transmits vehicle dynamics parameters to the external processing unit, the external processing unit can then send the calculation coefficients for these vehicle dynamics parameters stored for this position or determined with the newly transmitted vehicle dynamics parameters back to the control unit of the cruise control system in this vehicle, which then calculates the vehicle target speed and / or the vehicle target deceleration using simple arithmetic operations and controls an engine and / or brakes and / or a transmission of the vehicle in order to adapt the current vehicle speed to the vehicle target speed accordingly.

[0022] To calculate the target vehicle deceleration, the cruise control system can, for example, also weight the maximum available braking torque and / or the maximum available drive torque and / or the vehicle mass with the correspondingly transmitted calculation coefficients that were determined on the external computing unit, so that only simple calculation operations need to be carried out on the control unit in the vehicle.

[0023] Alternatively, the calculation coefficients can also be derived by the algorithm based on empirical values. For example, if a vehicle with access to the external computing unit travels along a section of road at a fuel-efficient speed, the algorithm can determine the vehicle's dynamic driving parameters along with the calculation coefficients corresponding to the fuel-efficient speed and store them for the corresponding positions in the map system. This allows a vehicle with similar dynamic driving parameters to also access these calculation coefficients.

[0024] This separates simple arithmetic operations, such as simple multiplications or additions, from complex arithmetic operations, such as simulations. Simple arithmetic operations can be performed in the vehicle's control unit, while complex arithmetic operations are outsourced to an external processing unit with a high-performance infrastructure. Alternatively, all arithmetic operations can be outsourced to an external processing unit. To prevent unnecessary computational overhead from being transferred to the external processing unit, simple arithmetic operations that can also be performed in the vehicle are advantageously transferred to the control unit in the respective vehicle.

[0025] In order to further reduce the load on the external computing unit, it is advantageous to have the target vehicle speed and / or the target vehicle deceleration or the calculation coefficients determined by the algorithm only for a specific route section ahead, wherein the route section ahead is determined in particular as a function of a currently existing kinetic energy of the vehicle, which results from the current vehicle mass and the current vehicle speed.

[0026] This advantageously allows for the fact that a vehicle with higher kinetic energy, i.e., with a higher vehicle mass and / or higher vehicle speed, has, for example, a longer braking distance or a longer acceleration distance. Therefore, a longer road section ahead must be considered for the fuel-efficient calculation of the vehicle's target speed and / or deceleration. For a lighter vehicle, however, a shorter road section ahead is relevant, since the vehicle has lower kinetic energy at the same vehicle speed and can therefore be braked or accelerated more quickly.

[0027] Advantageously, this allows the algorithm to make the calculation on the external processing unit more efficient, as the algorithm only uses the route information that is actually required when calculating the target vehicle speed and / or deceleration. This enables reliable adaptive control of the vehicle speed, optimizing computational effort and time. Furthermore, no unnecessary data is transmitted and processed on the external processing unit, as only relevant data is provided, limiting the amount of data to be processed and thus saving resources overall.

[0028] Advantageously, the vehicle's driving dynamics parameters, maximum available drive torque and maximum available braking torque, can also be taken into account when determining the section of road ahead. This makes it possible, for example, to specify a section start point of the road section in front of the vehicle which takes into account how quickly the vehicle can react to a change in vehicle speed, i.e. how quickly braking and acceleration are possible. This also has an impact on the section end point up to which the section of road ahead extends from the section start point. This is because a vehicle with high kinetic energy and a low maximum available braking torque or drive torque has a longer braking distance or acceleration distance than a vehicle with the same kinetic energy but a higher maximum available braking torque or drive torque.Drive torque.

[0029] Thus, based on the vehicle's dynamic driving parameters, a route section can be determined for which reliable, fuel-efficient control of the vehicle's speed can be achieved with minimal computational effort and optimal computing time. By using currently available vehicle parameters, the route section can also be adapted very precisely to the actual vehicle dynamics, thus enabling a reliable response to upcoming route information, such as a newly formed traffic jam or a speed limit.

[0030] The upcoming route section can also be dependent on a route specified by the driver, so that not every conceivable route section is considered, but only sections along the planned route. This can advantageously also be taken into account when providing the calculation coefficients by the external computing unit, by only outputting calculation coefficients for a specific route section along the route.

[0031] When determining the calculation coefficients for the upcoming section of road, a change in vehicle speed can also be indirectly determined, i.e., from when an upcoming event becomes relevant for the vehicle based on the driving dynamics parameters. For example, if there is a speed limit on an uphill section after a downhill section, the vehicle's braking and thus a change in vehicle speed or the calculation coefficients will occur differently than if there is a speed limit on an uphill section after a flat or slightly uphill road. Thus, depending on the route information, it is also possible to regulate how quickly the target vehicle speed should be reached based on the current vehicle speed; this is also taken into account by the algorithm.

[0032] When controlling the brakes and / or the engine and / or the transmission for fuel-saving implementation of the vehicle's target speed and / or the vehicle's target deceleration, an upper and a lower limit speed can also be taken into account, which can be specified by the driver or automatically set, for example. This advantageously makes it possible to set the speed limits within which the vehicle speed should be regulated. As an upper limit speed, for example, the driver can specify a maximum speed of the vehicle or the external processing unit can automatically set a speed limit. The lower limit speed can depend on the upper limit speed or the vehicle configuration as well as on a minimum speed that can be determined, for example, by a travel time or a section of the journey, such asa motorway with a minimum or recommended speed within which the driver wishes to reach his destination.

[0033] In particular, the upper and lower limit speeds can also be taken into account by the algorithm, so that these also play a role in determining the calculation coefficients in order to be able to specify a fuel-saving target vehicle speed and / or target vehicle deceleration depending on them.

[0034] The invention is explained below with reference to the accompanying drawings. They show: Fig. 1 a vehicle with an electronically controlled pneumatic braking system as a block diagram; Fig. 2 an example speed profile; Fig. 3a , b exemplary route sections; and Fig. 4 a flow chart for carrying out the procedure.

[0035] The embodiment according to Fig. 1 relates to a vehicle 100, for example a commercial vehicle, with a control unit 2 according to the invention for adaptively controlling a vehicle speed vFzg, which is part of a cruise control system 200, also known as cruise control. The control unit 2 is connected to a positioning system 3, for example a Global Positioning System (GPS), which transmits a current position P of the vehicle 100 to the control unit 2. Furthermore, a current vehicle mass M of the vehicle 100 is stored in the control unit 2. The vehicle mass M can either be determined in advance and stored or can be continuously determined using a mass determination system 4, for example an axle load sensor or an electronic air suspension system, and transmitted to the control unit 2 in order to be able to determine a current vehicle mass M, for example when the load of the vehicle 100 changes.

[0036] In addition, a currently maximum available drive torque A and a currently maximum available braking torque B of the vehicle 100 are stored in the control unit 2, which can be output by the drive control unit AS or brake control unit BS to the control unit 2 and which indicate the drive torque A or braking torque B with which the vehicle 100 can be maximally accelerated or maximally braked. This can be used to estimate the driving dynamics behavior of the vehicle 100 or to define a driving dynamics situation. In addition, the current vehicle speed vFzg of the vehicle 100 is recorded, for example with wheel speed sensors 5 arranged on wheels 1 of the vehicle 100. Alternatively, the current vehicle speed vFzg can also be determined from the change in the positions P determined by the position determination system 3 or the sensor signals SU of at least one vehicle surroundings sensor 21, such asa radar / LIDAR sensor or a camera, the cruise control system 200, in particular the control unit 2.

[0037] According to the invention, the vehicle speed vFzg is adaptively controlled in the cruise control system 200. For this purpose, the control unit 2 first calculates a desired vehicle speed vSoll and / or a desired vehicle deceleration zSoll. Subsequently, an engine 7 and / or a transmission 8 of the vehicle 100 are controlled via the brake control unit BS Brakes 6 and / or the drive control unit AS in such a way that the vehicle speed vFzg adapts to the desired vehicle speed vSoll, possibly with the predetermined desired vehicle deceleration zSoll. The adaptive control of the vehicle speed vFzg functions in the manner of a cruise control system 200, which attempts to maintain a reference speed vRef by controlling the brakes 6 and / or the engine 7 and / or the transmission 8.

[0038] The reference speed vRef is specified by the driver. In addition, an upper limit speed vo and a lower limit speed vu are specified. The adaptive control of the vehicle speed vVzg in the control unit 2 then specifies a desired vehicle speed vSoll, which lies between the upper limit speed vo and the lower limit speed vu, and / or a desired vehicle deceleration zSoll in order to adapt the vehicle speed vVzg to the reference speed vRef. The calculation of the desired vehicle speed vSoll and / or the desired vehicle deceleration zSoll is carried out adaptively, i.e., according to the invention, the desired vehicle speed vSoll is set within the upper limit speed vo and the lower limit speed vu in such a way that the lowest possible fuel consumption can be achieved for a route section D ahead. This meansThe reference speed vRef is not necessarily set immediately as the target vehicle speed vSoll, but rather a target vehicle speed vSoll within the speed limits vo, vu is selected, which, taking into account the target vehicle deceleration zSoll, approximates the specified reference speed vRef as fuel-efficiently as possible. An example of the speed curves vu, vo, vRef, vSoll is shown in . Fig. 2 as a function of time t.

[0039] The calculation of the desired vehicle speed vSoll and the desired vehicle deceleration zSoll is carried out as follows according to the embodiment shown: The control unit 2 transmits as vehicle parameters in particular the current position P of the vehicle 100, the current vehicle speed vFzg, the current vehicle mass M of the vehicle 100, the maximum available drive torque A and the maximum available braking torque B wirelessly, for example by means of a mobile phone connection, via a cloud signal SCloud to an external computing unit 10. The vehicle parameters vFzg, A, B, M, P can be used in particular to characterize the current driving dynamics situation of the vehicle 100, ie how quickly the vehicle 100 with the vehicle mass M can be braked or accelerated from the current vehicle speed vFzg.

[0040] The external computing unit 10 operates according to the principle of cloud computing, i.e. the control unit 2 sends all driving dynamics vehicle parameters vFzg, A, B, M, P of the vehicle 100, which it can currently determine itself and which are required to calculate the vehicle target speed vSoll and / or the vehicle target deceleration zSoll, wirelessly, for example by means of a mobile radio connection or the like, via a network N, for example the Internet, to the external computing unit 10. The latter can carry out extensive and complex computing operations in its infrastructure and can transmit the result of these computing operations wirelessly back to the control unit 2 via the network N.On the control unit 2, only simple calculation operations are carried out, if at all, in order to obtain the vehicle target speed vSoll and / or the vehicle target deceleration zSoll, or the result is used directly to control the brakes 6 and / or the engine 7 and / or the transmission 8.

[0041] According to this exemplary embodiment, the external computing unit 10 transmits calculation coefficients W, X, Y, Z to the control unit 2 based on the currently available vehicle parameters P, vFzg, M, A, B, whereby the calculation coefficients W, X, Y, Z are decisive for calculating the desired vehicle speed vSoll to be regulated, whereby according to this embodiment, for example, the following applies: vSoll = W ⋅ B + X ⋅ M + Y ⋅ A + Z

[0042] In this case, a first calculation coefficient W weights the maximum available braking torque B, a second calculation coefficient X the current vehicle mass M of the vehicle 100 and a third calculation coefficient Y the maximum available drive torque A. In the case of a speed limit 14, a fourth calculation coefficient Z corresponds to the value of the speed limit 14. If a speed limit 14 is present, the upper limit speed vo can be reduced to the value of the speed limit 14 so that only values ​​lower than the upper limit speed vo are permitted for the desired vehicle speed vsoll. At the same time, a proportional reduction in the lower limit speed vu can also take place so that fuel-saving control within the limit speeds vu, vo is possible.Alternatively, the first, second and / or third calculation coefficients W, X, Y can also be set to zero, so that the vehicle speed vFzg is maintained at the value of the speed limit 14 at least within the speed limit.

[0043] The calculation coefficients W, X, Y, Z are stored for each position P of the vehicle 100 and for the corresponding vehicle parameters vVzg, M, A, B, for example, in the external processing unit 10 in a map system 15. The calculation coefficients W, X, Y, Z for each position P can be provided to the map system 15 using an algorithm 16 executable on the external processing unit 10. The algorithm 16 derives the calculation coefficients W, X, Y, Z from route information I in the route section D in front of the vehicle 100, which is stored in the map system 15. For this purpose, the algorithm 16 simulates fuel consumption for different calculation coefficients W, X, Y, Z and fixed vehicle parameters vVzg, A, B, M, P in the external control unit 10 and then stores the calculation coefficients W, X, Y, Z for the lowest fuel consumption for this position P.Alternatively, the external computing unit 10 can also rely on empirical values, with the algorithm monitoring the fuel consumption of vehicles 100 that have already traveled to this position P and filtering out an optimal fuel consumption from their fuel consumption. The calculation coefficients W, X, Y, Z can then be determined from the target vehicle speed vtarget of this vehicle 100 and stored for this position P.

[0044] If any vehicle 100 transmits vehicle parameters vVzg, A, B, M, P to the external computing unit 10 via the cloud signal SCloud, the external computing unit 10 can then send the calculation coefficients W, X, Y, Z stored for the position P back to the control unit 2 of the cruise control system 200. The control unit 2 can then, based on the calculation coefficients W, X, Y, Z according to the above formula, calculate the desired vehicle speed vSoll without significant computational effort and initiate an engine, brake, and / or transmission request accordingly.

[0045] The route information I taken into account here is a topography 11, i.e., for example, an uphill gradient 12, a downhill gradient 13, curves 18 with a curve radius α or route narrowings 19, but also speed limits 14, traffic information 20, or the like. The speed limits 14 and the traffic information 20 can be kept up to date on the external processing unit 10 via any Internet information service 17, so that when calculating the vehicle's target speed vtarget, for example, immediate action can be taken on the traffic information 20. The topography 11 can be obtained by the external processing unit 10 from the map system 15, in which the route is stored with elevation profiles. From the position P, the topography 11 for the upcoming route section D can then be determined from the map system 15, whereby the topography 11 in the map system 15 can always be kept up to date.An example of such a route is a section D in the . Figuren 3a and 3b shown, where Fig. 3a shows a side view showing a difference in height and Fig. 3b a top view with a curve 18 and a track narrowing 19.

[0046] Furthermore, the external computing unit 10 can also be informed of the upper limit speed vo and the lower limit speed vu so that these can be taken into account when determining the calculation coefficients W, X, Y, Z for a fuel-efficient driving style.

[0047] Using the current position P, the external control unit 10 or the algorithm 16 can, for example, additionally take into account how far the speed limit 14 is still away and thus slowly reduce the calculation coefficients W, X, Y to zero, in particular depending on the topography 11, for example an uphill slope 12 or a downhill slope 13, until the speed limit 14 is reached, so that a change in the vehicle speed vVzg can be set depending on how quickly or from when an event in the course of the route should be taken into account in order to avoid abrupt braking or starting and thus save fuel.

[0048] For example, the weighting of the maximum available drive torque A or the third calculation coefficient Y can be set to zero earlier on a downhill gradient 13 than on an uphill gradient 12, since the maximum available drive torque A is irrelevant on a downhill gradient 13. The maximum available braking torque B or the first calculation coefficient W is not relevant on an uphill gradient 12 but is relevant on a downhill gradient 13. The vehicle mass M, on the other hand, is relevant for fuel-efficient acceleration and braking on both an uphill gradient 12 and a downhill gradient 13, so that the second calculation coefficient X is greater than zero until the speed limit 14 is reached.

[0049] When determining the calculation coefficients W, X, Y, Z, the algorithm 16 also takes into account, for example, that the vehicle 100, starting from its current vehicle speed vVzg with its maximum available drive torque A, overcomes an upcoming uphill slope 12 or a downhill slope 13 with minimal fuel consumption if a desired vehicle speed vSoll is set which lies between the upper limit speed vo and the lower limit speed vu, taking into account how long the upcoming uphill slope 12 or the downhill slope 13 is and whether the upcoming uphill slope 12 is followed by a downhill slope 13 or whether the downhill slope 13 is followed by an uphill slope 12.For example, the vehicle target speed vSoll can be reduced to the lower limit speed vu shortly before a crest of the gradient, taking into account that a downhill slope 13 follows after the crest, through which the vehicle 100 can be accelerated to the reference speed vRef without motor control. This applies analogously to the brake control during a transition from a downhill slope 13 to an uphill slope 12 or a level surface, in which the vehicle 100 can be decelerated by rolling from the upper limit speed vo to the reference speed vRef without any brake control.

[0050] The upper limit speed vo can be set, for example, as a function of a maximum speed vmax of the vehicle 100 or a possibly existing speed limit 14 for the upcoming section of road D. The lower limit speed vu can be set by the driver and take into account how quickly the vehicle 100 should reach its destination. Furthermore, the lower limit speed vu can be set based on the vehicle parameters for the drive or braking torque or the vehicle mass A, B, M or as a function of the upper limit speed vo set by the driver.

[0051] The upcoming route section D considered by algorithm 16 to determine the calculation coefficients W, X, Y, Z is, according to one embodiment, dependent on a currently present kinetic energy Ekin = M vVzg 2< in vehicle 100, i.e. on the current vehicle mass M and the current vehicle speed vVzg. If a vehicle 100 has a high vehicle mass M and a high vehicle speed vVzg, more kinetic energy Ekin is present in vehicle 100, so that, for example, a (braking) distance covered for a braking operation is also greater. Thus, for a vehicle 100 with high kinetic energy Ekin, a larger route section D must also be considered, within which a brake control or engine control must be used to react to the topography 11, traffic information 20 or a speed limit 14.For a vehicle 100 with a lower vehicle mass M and a low vehicle speed vVzg, a faster reaction is possible, so that the route section D can be selected to be smaller.

[0052] The route section D is defined by a route section start point DS and a route section end point DE, both of which are also dependent on the kinetic energy Ekin and the vehicle dynamics parameters vVzg, A, B, M, P. Depending on the topography 11 at the current position P of the vehicle 100, the route section start point DS depends on the reaction capability of the vehicle 100. If the vehicle 100 has a higher maximum available drive torque A or a higher maximum available braking torque B, it can react more quickly to a possible change in the vehicle's target deceleration vSoll on an uphill gradient 12 or a downhill gradient 13. Thus, when calculating the vehicle's target speed vSoll or for the calculation coefficients W, X, Y, Z, route information I that is closer to the vehicle 100 is relevant than for a vehicle 100 that has a lower maximum available drive torque A or a lower maximum available braking torque B.maximum available braking torque B can only bring a correspondingly directed acceleration onto the road at a later point in time.

[0053] The same applies to the route section end point, which is closer to or further away from vehicle 100 depending on the kinetic energy Ekin or the vehicle mass M and the current vehicle speed vVzg. In this case, this also depends in particular on the maximum available drive torque A or the maximum available drive torque B, which determine how much the vehicle 100 can be accelerated or decelerated with its kinetic energy Ekin.

[0054] Algorithm 16 in external computing unit 10, which determines the calculation coefficients W, X, Y, Z, is therefore only provided with route information I on the upcoming route D, as this is sufficient to determine a fuel-efficient target vehicle speed vSoll. This optimizes the computing time and effort, as well as the amount of data, on external computing unit 10, and reduces the signal length of the cloud signal SCloud to be transmitted. Because both the vehicle speed vVzg and the vehicle mass M are constantly transmitted to external computing unit 10 via the cloud signal SCloud, the upcoming route section D can be continuously updated on external computing unit 10 as a function of the kinetic energy Ekin and provided to algorithm 16.

[0055] Similarly, the vehicle target deceleration zSoll is to be determined from the calculation coefficients W, X, Y, Z on the control unit 2, where, for example, the maximum available braking torque B, the maximum available drive torque A, the vehicle mass M and route information I, for example, inclines 12 and declines 13, are weighted accordingly to obtain a target vehicle deceleration zSoll.

[0056] The method for adaptively controlling a vehicle speed vVzg can be carried out, for example, as follows: In an initial step St0, the cruise control system 200 is started, for example, by the driver actuating a corresponding switch. In a first step St1, the vehicle reference speed vRef is set, preferably by the driver. Optionally, an upper speed limit vo and a lower speed limit vu can be set in a second step St2.

[0057] In a third step St3, vehicle dynamics parameters vFzg, M, A, B, P are determined that are currently present in vehicle 100 and that can be provided by corresponding devices 3, 4, 5, AS, BS in vehicle 100. These are transmitted in a fourth step St4 to an external computing unit 10 via a cloud signal SCloud in network N.

[0058] In a fifth step St5, this determines calculation coefficients W, X, Y, Z, which are provided by algorithm 16, wherein algorithm 16 determines calculation coefficients W, X, Y, Z, for example by means of simulations or based on empirical values, and stores them for several positions P in map system 15. If vehicle parameters vVzg, M, A, B, P are transmitted to external computing unit 10 via cloud signal SCloud, the stored calculation coefficients W, X, Y, Z for the corresponding position P of vehicle 100 are retrieved and made available for transmission. In a sixth step St6, the calculation coefficients W, X, Y, Z are transmitted via cloud signal SCloud to control unit 2, for example by means of a mobile radio signal or the like, on which control unit 2 the desired vehicle speed vSoll and / or the desired vehicle deceleration zSoll is calculated in a seventh step St7.Alternatively, the seventh step St7 can also already be carried out on the external computing unit 10, so that the vehicle target speed vSoll and / or the vehicle target deceleration zSoll is already transmitted via the cloud signal SCloud.

[0059] In the last step St8, the brakes 6 and / or the engine 7 and / or the transmission 8 of the vehicle 100 are controlled by the cruise control system 200 in order to set the desired vehicle speed vSoll, if necessary with the corresponding desired vehicle deceleration zSoll, and thus to approximate the current vehicle speed vFzg to the vehicle reference speed vRef specified by the driver in a fuel-saving manner. List of reference symbols (part of the description)

[0060] 1Wheels of vehicle 1 2Control unit 3Positioning system 4Mass determination system 5Wheel speed sensors 6Brakes 7Engine 8Transmission 10External processing unit 11Topography 12Grade 13Grade 14Speed ​​limit 15Map system 16Algorithm 17Internet information service 18Curves 19Road narrowing 20Traffic information 21Environment sensor 100Vehicle 200Cruise control system αCurve radius AMaximum available drive torque ASDrive control unit BMaximum available braking torque BSBrake control unit DAhead section DEStarting point of road section DSEnding point of road section EKin kinetic energy GSTransmission control IStravel information MVehicle mass PPosition SCloudCloud signal SUSignal from the environment sensor tTime vVehicle speed vmax Maximum speed vo Upper limit speed vRef Reference speed vSoll Vehicle target speed vu Lower limit speed First calculation coefficient X Second calculation coefficientYthird calculation coefficient Zfourth calculation coefficient ztarget vehicle target deceleration St0, St1, St2, St3, St4, St5, St6, St7, St8Procedure steps

Claims

1. Method for adaptively controlling a vehicle speed (vFzg) in a vehicle (100), in particular a commercial vehicle, comprising a cruise control system (200), which method comprises at least the following steps: establishing a reference speed (vRef); controlling an engine (7) and / or brakes (6) and / or a transmission (8) of the vehicle (100) by the cruise control system (200) depending on a vehicle target speed (vSoll) and / or on a vehicle target deceleration (zSoll) for fuel-efficient adaptation of the currently existing vehicle speed (vFzg) to the reference speed (vRef), the vehicle target speed (vSoll) and / or the vehicle target deceleration (zSoll) for a current driving-dynamic situation of the vehicle (100), defined by driving-dynamic vehicle parameters (vFzg, M, A, B, P), being determined depending on at least one calculation coefficient (W, X, Y, Z), the at least one calculation coefficient (W, X, Y, Z) being provided by an external computing unit (10) outside the vehicle (100) depending on the currently existing driving-dynamic vehicle parameters (vFzg, M, A, B, P) and depending on currently existing route information (I) for a route portion (D) ahead, the route portion (D) ahead being established based on the currently existing driving-dynamic vehicle parameters (vFzg, M, A, B, P), characterized in that a currently existing position (P) and a currently existing vehicle speed (vFzg) and a current vehicle mass (M) and a maximum currently available drive torque (A) and a maximum currently available braking torque (B) are used as driving-dynamic vehicle parameters, the maximum currently available braking torque (B) being weighted with a first calculation coefficient (W), the current vehicle mass (M) with a second calculation coefficient (X), and the maximum currently available drive torque (A) with a third calculation coefficient (Y) in order to calculate the vehicle target speed (vSoll) and / or the vehicle target deceleration (zSoll), and route information (I) being taken into account via a fourth calculation factor (Z), an algorithm (16) on the external computing unit (10) deriving the at least one calculation coefficient (W, X, Y, Z) depending on the currently existing route information (I) and on a position (P) of the vehicle (100), the algorithm (16) for calculating the at least one calculation coefficient (W, X, Y, Z) only taking into account route information (I) which lies in the route portion (D) ahead, in order to restrict the amount of data to be processed by the algorithm (16).

2. Method according to claim 1, characterized in that the at least one calculation coefficient (W, X, Y, Z) derived by the algorithm (16) is stored for each position (P) in a map system (15) containing the route information (I), each position (P) being assigned route portions (D) and driving-dynamic vehicle parameters (vFzg, M, A, B, P).

3. Method according to claim 2, characterized in that the route information (I) on the map system (15) is kept up to date, in particular via an Internet information service (17).

4. Method according to claim 2 or claim 3, characterized in that the algorithm (16) derives the at least one calculation coefficient (W, X, Y, Z) which has the lowest fuel consumption for the route portion (D) ahead on the basis of simulations.

5. Method according to any of the preceding claims, characterized in that the route portion (D) ahead is determined depending on the current vehicle mass (M) and on the current vehicle speed (vFzg), in particular depending on the kinetic energy (Ekin) of the vehicle (100).

6. Method according to claim 5, characterized in that a route portion start point (DS) and a route portion end point (DE) of the route portion (D) ahead are determined depending on the maximum available drive torque (A) and / or on the maximum available braking torque (B).

7. Method according to any of the preceding claims, characterized in that the vehicle target speed (vSoll) and / or the vehicle target deceleration (zSoll) is calculated and / or set in a control device (2), in particular of the cruise control system (200), in the vehicle (100) on the basis of the at least one calculation coefficient (W, X, Y, Z) ascertained by the external computing unit (10).

8. Method according to any of the preceding claims, characterized in that the vehicle parameters (vFzg, A, B, M, P) are transmitted wirelessly via a cloud signal (SCloud) to the external computing unit (10), and the at least one calculation coefficient (W, X, Y, Z) ascertained therefrom is transmitted wirelessly via the cloud signal (SCloud) from the external computing unit (10) to the control device (2).

9. Method according to any of the preceding claims, characterized in that the external computing unit (10) is a cloud-based computing unit, it being possible to provide the at least one calculation coefficient (W, X, Y, Z) on the external computing unit (10) for a plurality of vehicles (100) simultaneously.

10. Method according to any of the preceding claims, characterized in that a topography (11), in particular inclines (12), gradients (13), curves (18) which have a curve radius (α), route narrowings (19), and / or speed restrictions (14) and / or traffic information (20) can be taken into account as route information (I).

11. Method according to any of the preceding claims, characterized in that the vehicle target speed (vSoll) is set within an upper speed limit (vo) and a lower speed limit (vu).

12. Cruise control system (200) of a vehicle (100), in particular a commercial vehicle, comprising at least: a control device (2) for carrying out the method according to any of claims 1 to 11, a position determination system (3) for ascertaining a current position (P), a mass determination system (4) for ascertaining a current vehicle mass (M), wheel speed sensors (5) for ascertaining a current speed (vFzg), a drive control device (AS) for controlling the motor (7) and for providing the maximum currently available drive torque (A), and a brake control device (BS) for controlling the brakes (6) and for providing the maximum currently available braking torque (B), wherein the control device (2) is designed to read in the driving-dynamic vehicle parameters (vFzg, A, B, M, P) and to transmit them wirelessly via a cloud signal (SCloud) to an external computing unit (10) and to receive via the cloud signal (SCloud) at least one calculation coefficient (W, X, Y, Z) from the external computing unit (10), to determine, from the at least one calculation coefficient (W, X, Y, Z), a vehicle target speed (vSoll) and / or a vehicle target deceleration (zSoll) for controlling the engine (7), and / or the brakes (6) and / or the transmission (8) of the vehicle (100) so that the currently existing vehicle speed (vFzg) adapts to the vehicle reference speed (vRef) specified by the driver in a fuel-efficient manner.

13. Vehicle (100), in particular a commercial vehicle (100), comprising a cruise control system (200) according to claim 12, suited for carrying out a method according to any of claims 1 to 11.