METHOD AND MODULE FOR CONTROLLING A VEHICLE'S SPEED BASED ON RULES AND/OR COSTS

Abstract

A method for determination of at least one reference value for controlling a vehicle's speed is described. The method may entail making a first prediction vpred—Tnew—ret and a second prediction vpred—Tnew—acc of a vehicle speed along a horizon, said first prediction based on an engine torque Tret which retards the vehicle as compared with a conventional cruise control, and said second prediction based on an engine torque Tacc which accelerates the vehicle as compared with a conventional cruise control; comparing said respective first prediction vpred—Tnew—ret and second prediction vpred—Tnew—acc of the vehicle speed with a lower limit value vmin and/or an upper limit value vmax which delineate a range within which the vehicle's speed should be; and determining at least one reference value based on at least one of said respective comparisons and said first prediction vpred—Tnew—ret and second prediction vpred—Tnew—acc of the vehicle speed along the horizon.

Description

FIELD OF THE INVENTION

The present invention relates to a method and a module for determining at least one reference value which indicates how a vehicle's speed is to be influenced and which can be used to control at least one control system of the vehicle, according to the preambles of the independent claims.

BACKGROUND TO THE INVENTION

Cruise control is now usual in motor vehicles, e.g. cars, trucks and buses. An object of cruise control is to achieve a uniform predetermined speed. This is done either by adjusting the engine torque to avoid retardation, or by applying braking action on downhill runs where the vehicle is accelerated by its own weight. A more general object of cruise control is to provide convenient driving and better comfort for the vehicle's driver. A driver of a vehicle equipped with cruise control usually chooses a set speed v_set as the speed he/she wishes the vehicle to maintain on level roads. A cruise control then supplies an engine system of the vehicle with a reference speed v_ref used for control of the engine. The set speed v_set may thus be regarded as an input signal to the cruise control, whereas the reference speed v_ref may be regarded as an output signal from the cruise control and is used for control of the engine.

Today's traditional cruise control (CC) maintains a constant reference speed v_ref usually set by the vehicle's driver in the form of a set speed v_set which is thus here a desired speed chosen for example by him/her, and for today's conventional cruise controls the reference speed is constant and equal to the set speed, i.e. v_ref=v_set. The value of the reference speed v_ref changes only when adjusted by the driver while the vehicle is in motion. The reference speed v_ref is then sent to a control system which controls the vehicle so that its speed corresponds when possible to the reference speed v_ref. If the vehicle is equipped with an automatic gearchange system, the gears may be changed by that system on the basis of the reference speed v_ref to enable the vehicle to maintain the reference speed v_ref, i.e. to enable it to maintain the desired set speed v_set.

In hilly terrain, the cruise control system will try to maintain the set speed vset uphill and downhill. This may result inter alia in the vehicle accelerating over the crest of a hill and into a subsequent downgrade. It will then need to be braked to avoid exceeding the set speed v_set or will reach a speed V_kfb at which the constant speed brake is activated, which is a fuel-expensive way of driving the vehicle. It may also need to be braked downhill to avoid exceeding the set speed v_set or the constant speed brake's activation speed v_kfb in cases where the vehicle does not accelerate over the crest of the hill.

To reduce fuel consumption, especially on hilly roads, economical cruise controls such as Scania's Ecocruise® have been developed. This cruise control tries to estimate the vehicle's current running resistance and also has information about its historical running resistance. The economical cruise control may also be provided with map data comprising topographical information. The vehicle is then located on the map, e.g. by means of GPS, and the running resistance along the road ahead is estimated. The vehicle's reference speed v_ref can thus be optimised for different types of roads in order to save fuel, in which case the reference speed v_ref may differ from the set speed v_set. This specification refers to cruise controls which allow the reference speed v_ref to differ from the set speed v_set chosen by the driver, i.e. reference speed-regulating cruise controls.

An example of a further development of an economical cruise control is a “look ahead” cruise control (LACC), a strategic form of cruise control which uses knowledge of sections of road ahead, i.e. knowledge of the nature of the road ahead, to determine the reference speed v_ref. LACC is thus an example of a reference speed-regulating cruise control whereby the reference speed v_ref is allowed, within a certain range [v_min, v_max], to differ from the set speed v_set chosen by the driver, in order to achieve more fuel saving.

Knowledge of the road section ahead may for example comprise information about prevailing topology, road curvature, traffic situation, roadworks, traffic density and state of road. It may further comprise a speed limit on the section ahead, and a traffic sign beside the road. Such knowledge is for example available from location information, e.g. GPS (global positioning system) information, map information and/or topographical map information, weather reports, information communicated between vehicles and information provided by radio. All this knowledge may be used in a variety of ways. For example, information about a speed limit on the road ahead may be used to achieve fuel efficiency by lowering the vehicle's speed before reaching a lower speed limit. Similarly, knowledge of a road sign which indicates for example a roundabout or intersection ahead may also be used to achieve fuel efficiency by braking before the vehicle reaches the roundabout or intersection.

An LACC cruise control does for example make it possible, before a steep upgrade, for the reference speed v_ref to be raised to a level above the set speed v_set, since the vehicle will be expected to lose speed on such a climb owing to high train weight relative to engine performance. Similarly, before a steep downgrade, the LACC cruise control makes it possible for the reference speed v_ref to be lowered to a level below the set speed v_set, since the vehicle will be expected to accelerate on such a downgrade owing to its high train weight. The concept here is that reducing the speed at which the vehicle begins the downhill run makes it possible to reduce the energy braked away and/or the air resistance losses (as reflected in the amount of fuel injected before the downgrade). The LACC cruise control may thus reduce fuel consumption without substantially affecting journey time.

SUMMARY OF THE INVENTION

An example of a previously known cruise control which uses topographical information is described in the document entitled “Explicit use of road topography for model predictive cruise control in heavy trucks” by Erik Hellstrim, ISRN: LiTH-ISY-EX—05/3660—SE. Cruise control is here effected by real-time optimisation, and a cost function is used to define the optimisation criteria. A large number of different solutions are here calculated and evaluated, and the solution resulting in lowest cost is applied. As a considerable amount of calculations is involved, the processor which is to perform them needs a large capacity.

Other known solutions for cruise control have reduced the number of possible solutions by opting instead to iterate from one solution along the vehicle's intended route. However, the topography of the itinerary and the vehicle's weight and engine performance may lead to various heavy demands in terms of processor load for determining the reference speed v_ref. More calculations are needed when, for example, a heavily laden truck with medium-high power output travels on a hilly road as compared with a lightly laden truck with a higher power output travelling on a relatively level road. The reason is that the truck in the first case is likely to accelerate on each downgrade and decelerate on each upgrade, whereas in the second case the truck will find the road substantially level.

The built-in system's processor will thus be subject to relatively large demands if the previously known solutions are applied, since the processor load may vary greatly in different circumstances. For example, the capacity of the processor needs to be sufficient to deal quickly with cases where a large number of calculations have to be done in a limited time. The processor has therefore to be dimensioned to cater for such cases despite the fact that they arise during only a limited portion of the processor time used.

An object of the present invention is to propose an improved system for controlling a vehicle's speed so that the amount of fuel used can be minimised and, in particular, for controlling the vehicle's speed in such a way that the processor load will be smaller and more uniform over time. A further object of the invention is to propose a simplified cruise control which behaves more predictably than previous known economical and/or reference speed-regulating cruise controls.

According to an aspect of the present invention, at least one of the objects described above is achieved by applying the aforesaid method for controlling a vehicle's speed, which method is characterised by:

• • making a first prediction v_{pred—Tnew—ret} and a second prediction v_{pred—Tnew—acc} of a vehicle speed along a horizon, said first prediction based on an engine torque T_ret which retards the vehicle as compared with a conventional cruise control, and said second prediction based on an engine torque T_acc which accelerates the vehicle as compared with a conventional cruise control;
  • comparing said respective first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max which delineate a range within which the vehicle's speed should be; and
  • determining at least one reference value based on at least one of said respective comparisons and said first prediction V_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed along the horizon.

According to an aspect of the present invention, at least one of the objects described above is achieved by using the aforesaid module to control a vehicle's speed, which module is characterised by:

• • making a first prediction v_{pred—Tnew—ret} and a second prediction v_{pred—Tnew—acc} of a vehicle speed along a horizon, said first prediction based on an engine torque T_ret which retards the vehicle as compared with a conventional cruise control, and said second prediction based on an engine torque T_acc which accelerates the vehicle as compared with a conventional cruise control;
  • comparing said respective first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max which delineate a range within which the vehicle's speed should be; and
  • determining at least one reference value based on at least one of said respective comparisons and said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed along the horizon.

The determination of the at least one reference value and the consequent control of the vehicle's speed by applying the method described above and/or using the module described above result in a substantially constant processor load, since similar numbers of predictions are made during each simulation cycle at a constant rate f. According to the present invention, the processor load is independent of the vehicle's power output and weight and the nature of the road's topography. The processor which is to perform the calculations knows here how much processor power will be needed over time, which makes it very easy to allocate sufficient processor power over time. The processor load will thus here be substantially similar in different situations with different topography and also be independent of the vehicle's engine torque. This means that the processor which is to perform the calculations can be dimensioned without having to cater for peaks associated with worst possible situations. The processor can instead be dimensioned to cater for a uniform processor load. The processor cost can thus be reduced, leading also to lower production costs for the vehicle.

Only vehicle speed variations ahead along the horizon are predicted, rendering the processor load relatively small. The reference value to be used for regulating the vehicle's speed is then chosen on the basis of the result of at least one of said respective comparisons of said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max and said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed along the horizon.

By predicting the vehicle's speed at different torques T, viz. at a torque T_ret which retards the vehicle as compared with a conventional cruise control and a torque T_acc which accelerates the vehicle as compared with a conventional cruise control, the system can evaluate the reference value to be used in regulating the vehicle's speed.

According to an embodiment of the invention, the reference value on which the vehicle speed is to be regulated is based on at least one rule. This rule or rules thus define how to choose the reference value.

According to an embodiment of the present invention, at least one of these rules is that the reference value on which the vehicle speed is to be regulated is a value corresponding to the set speed v_set if said first prediction v_{pred—Tnew—ret} of the vehicle speed is below the lower limit value v_min and at the same time said second prediction v_{pred—Tnew—acc} of the vehicle speed is above the upper limit value v_max.

According to an embodiment of the present invention, at least one of these rules is that the at least one reference value is a value which represents said first predicted vehicle speed v_{pred—Tnew—ret} if a minimum value for said first predicted speed is equal to or above the lower limit value v_min and if also a maximum value for said first predicted speed is equal to or above a further upper limit value v_max2 which is related to a set speed v_set. According to an embodiment, the further upper limit value v_max2 corresponds to the set speed plus a constant c₁, i.e. v_max2=v_set+c₁. According to another embodiment, the further upper limit value v_max2 corresponds to a factor c₁ multiplied by the set speed, i.e. v_max2=v_set*c₁. This factor c₁ may for example have the value 1.02, meaning that the further upper limit value v_max2 is 2% higher than the set speed v_set.

According to an embodiment of the present invention, at least one of these rules is that the at least one reference value is a value which represents said second predicted vehicle speed v_{pred—Tnew—acc} if a maximum value for said second predicted speed is equal to or below the upper limit value v_max and if also a minimum value for said second predicted speed is equal to or below a further lower limit value v_min2 which is related to a set speed. According to an embodiment, the further lower limit value V_min2 corresponds to the set speed v_set minus a constant c₂, i.e. v_min2=v_set−c₂. According to another embodiment, the further lower limit value v_min2 corresponds to a factor c₂ multiplied by the set speed, i.e. v_min2=v_set*c₂. This factor c₂ may for example have the value 0.98, meaning that the further upper limit value v_max2 is 2% lower than the set speed v_set.

According to an embodiment of the invention, the simulations done according to the method for the invention by use of cost functions are evaluated. This involves calculating the cost of at least one of the said first prediction v_{pred—Tnew—ret}, said second prediction v_{pred—Tnew—acc} and a further first prediction v_{pred—Tk+new—acc} and a further second prediction v_{pred—Tk+new—acc} of the vehicle speed by using at least one cost function J_Tnew—ret, J_Tnew—acc, J_TK+new—ret, T_{Tk—new—acc}.

According to an embodiment of the invention, a penalty may be added to at least one of the cost functions J_Tnew—ret, J_Tk+new—ret for said first prediction v_{pred—Tnew—ret} and said second first prediction v_{pred—Tk+new—ret} of the vehicle speed if said first and said further first predictions reach different final speeds.

Similarly, according to an embodiment of the invention, a penalty is added to at least one of the cost functions J_Tnew—acc and T_{Tk—new—acc} for said second prediction v_{pred—Tnew—acc} and said further second prediction v_{pred—Tk+new—acc} of the vehicle speed if said second and said further second predictions reach different final speeds.

Preferred embodiments of the invention are described in the dependent claims and the detailed description.

BRIEF DESCRIPTION OF THE ATTACHED DRAWINGS

The invention is described below with reference to the attached drawings, in which:

FIG. 1 depicts a module according to an embodiment of the invention.

FIG. 2 depicts a flowchart for the method according to an embodiment of the invention.

FIG. 3 illustrates a predicted speed during a simulation cycle according to an embodiment of the invention.

FIG. 4 illustrates a flowchart for the method according to an embodiment of the invention.

FIG. 5 illustrates the vehicle's predicted speeds according to an embodiment of the invention.

FIG. 6 illustrates the vehicle's predicted speeds according to an embodiment of the invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS OF THE INVENTION

FIG. 1 depicts a module for controlling a vehicle's speed according to an aspect of the invention. The module comprises an input unit adapted to receiving a desired speed, i.e. a set speed v_set, for the vehicle. The driver may for example set a speed v_set which he/she wishes the vehicle to maintain. The module comprises also a horizon unit adapted to determining a horizon H for the itinerary by means of map data and location data. The horizon H is made up of route segments with at least one characteristic for each segment. A possible example of characteristics of segments is their gradient α, in radians.

The description of the present invention states that GPS (global positioning system) is used to determine location data for the vehicle, but specialists will appreciate that other kinds of global or regional positioning systems are conceivable to provide these data. Such positioning systems might for example use radio receivers to determine the vehicle's location. The vehicle might also use sensors to scan the surroundings and thereby determine its location.

FIG. 1 illustrates how the module is provided with information about the itinerary from maps (map data) and GPS (location data). The itinerary is sent to the module bit by bit, e.g. via CAN (controller area network) bus. The module may be separate from or be part of the one or more control systems which are to use reference values for regulating. An example of such a control system is the vehicle's engine control system. Alternatively, the unit which handles maps and positioning systems may be part of a system which is to use reference values for regulating. In the module, the bits of the itinerary are then put together in a horizon unit to construct a horizon and are processed by the processor unit to create an internal horizon on which the control system can regulate. The horizon is then continually supplemented by new bits of itinerary from the unit with GPS and map data, to maintain a desired length of horizon. The horizon is thus updated continuously when the vehicle is in motion.

CAN is a serial bus system specially developed for use in vehicles. The CAN data bus makes digital data exchange possible between sensors, regulating components, actuators, control devices etc., and provides assurance that two or more control devices can have access to the signals from a given sensor in order to use them to control components connected to them. Each of the connections between the units illustrated in FIG. 1 may take the form of one or more from among a cable, a data bus, e.g. a CAN (controller area network) bus, an MOST (media orientated systems transport) bus, or some other bus configuration, or a wireless connection.

The module comprises also a calculation unit adapted to making a first prediction v_{pred—Tnew—ret} and a second prediction v_{pred—Tnew—acc} of a vehicle speed along a horizon, said first prediction based on an engine torque T_ret which retards the vehicle as compared with a conventional cruise control, and said second prediction based on an engine torque T_acc which accelerates the vehicle as compared with a conventional cruise control.

The module is further arranged to compare said respective first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max which delineate a range within which the vehicle's speed should be. The module is further arranged to determine at least one reference value based on at least one of said respective comparisons and said first prediction v_{pred—Tnew—ret} and said second prediction v_{pred—Tnew—acc} of the vehicle speed along the horizon.

The module is further arranged to supply, e.g. by sending, to a control system of the vehicle said at least one reference value on which the vehicle is then regulated. How the predictions of the speeds are made will be explained in more detail below.

The module and/or the calculation unit comprise at least a processor and a memory unit which are adapted to making all the calculations, predictions and comparisons of the method according to the invention. Processor means here a processor or microcomputer, e.g. a circuit for digital signal processing (digital signal processor, DSP), or a circuit with a predetermined specific function (application integrated specific circuit. ASIC). The calculation unit is connected to a memory unit which provides it with, for example, the stored programme code and/or stored data which the calculation unit needs to enable it to do calculations. The calculation unit is also adapted to storing partial or final results of calculations in the memory unit.

The method for control of vehicle speed according to the present invention and its various embodiments may also be implemented in a computer programme which, when executed in a computer, e.g. the aforesaid processor, causes the computer to apply the method. The computer programme usually takes the form of a computer programme product stored on a digital storage medium, and is contained in a computer programme product's computer-readable medium which comprises a suitable memory, e.g. ROM (read-only memory), PROM (programmable read-only memory), EPROM (erasable PROM), flash memory, EEPROM (electrically erasable PROM), a hard disc unit, etc.

FIG. 2 is a flowchart for a method which inter alia comprises steps for the method according to the invention. The diagram comprises not only steps for the determination of reference values according to the invention but also steps for controlling the vehicle's speed according to an embodiment of the invention.

The method comprises a first step A) of acquiring v_set as a desired set speed for the vehicle to maintain, and a second step B) of determining a horizon for the itinerary by means of map data and location data comprising route segments with at least one characteristic for each segment.

A number of simulation cycles may be done along the length of the horizon. A simulation cycle s_j may comprise a number N of simulation steps which may be conducted at a predetermined rate f. According to the invention, the following steps are performed during such a simulation cycle s_j;

C1) Making a first prediction v_{pred—Tnew—ret} of a vehicle speed along a horizon on the basis of an engine torque T_ret which retards the vehicle as compared with a conventional cruise control.

C2) Comparing said first prediction v_{pred—Tnew—ret} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max which delineate a range within which the vehicle's speed should be. Said first prediction thus does not have to be compared here both with the lower limit value v_min and with the upper limit value v_max.

C3) Making a second prediction v_{pred—Tnew—acc} of a vehicle speed along a horizon on the basis of an engine torque T_acc which accelerates the vehicle as compared with a conventional cruise control.

C4) Comparing said second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max which delineate a range within which the vehicle's speed should be. Said second prediction thus does not have to be compared here both with the lower limit value v_min and with the upper limit value v_max.

C5) Determining at least one reference value on the basis of at least one of said respective comparisons and said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed along the horizon.

As a further step D) said at least one reference value is then supplied, e.g. by being sent via a CAN bus, to a control system of the vehicle in which it is used to regulate the vehicle's speed according to said at least one reference value.

The method according to the present invention results in a constant and predetermined processor load when determining said at least one reference value.

The set speed v_set is thus the driver's input signal related to a desired cruise control speed, and the at least one reference value is the value on which the vehicle is regulated. The at least one reference value is preferably a reference speed v_ref, a reference torque T_ref or a reference engine speed ω_ref.

The reference speed v_ref, which thus constitutes the at least one reference value, is imparted to the speed regulator of the engine control unit. In traditional cruise control, as mentioned above, the reference speed v_ref is equal to the set speed, i.e. v_ref=v_set. The speed regulator then controls the vehicle's speed on the basis of the reference speed v_ref by demanding necessary torque from the engine's torque regulator. According to the embodiment in which the at least one reference value is a reference torque T_ref, it may be sent directly to the engine's torque regulator. In the embodiment where the at least one reference value is a reference engine speed ω_ref, it may be sent directly to the engine's speed regulator.

There follows a description of how the various predicted speeds are determined.

The total force F_env acting upon the vehicle from the environment is made up of rolling resistance F_roll, gravitation F and air resistance F_air. Gravitation is calculated as

F=m·g·α  (eq. 1)

where m is the weight of the vehicle and α the gradient of the road in radians. Since mostly only small angles are concerned, sin(α) is approximated to α.

Air resistance is calculated as a factor k multiplied by the square of vehicle speed, as follows:

$\begin{array}{cc}{F}_{\mathrm{env}}=F_{\mathrm{roll},\mathrm{present}}+m·9.82·\alpha +k·v_{i-1}^2& \left(\mathrm{eq}.2\right)\\ F_{\mathrm{roll},\mathrm{present}}=F_{\mathrm{roll},\mathrm{est}},m=m_{\mathrm{est}},k=\frac{1}{2}\rho ·C_d·A& \left(\mathrm{eq}.3\right)\end{array}$

where A is the vehicle's estimated frontal area, C_d the resistance coefficient which depends on the streamline shape of the object, ρ the density of the air and m the weight of the vehicle estimated by its weight estimation system as mest. Current rolling resistance F_roll,present is also estimated in the vehicle continuously as F_roll,est. For calculation of m_est and F_roll,est please refer to the dissertation entitled “Fuel Optimal Powertrain Control for Heavy Trucks Utilizing Look Ahead” by Maria Ivarsson, Linköping 2009, ISBN 978-91-7393-637-8. v_i−1 is the vehicle's predicted speed at preceding simulation step.

The force F_drive which propels the vehicle forwards depends on which prediction is made. It is taken according to an embodiment as either a torque which accelerates the vehicle or a torque which retards the vehicle as compared with conventional cruise control.

The force F_drive which propels the vehicle forwards may be taken as between a maximum possible force (maximum torque) and at least possible force (minimum torque, e.g. drag torque). It is possible, however, as described above, to use substantially any desired force within the range

F _min ≦F _drive ≦F _max  (eq. 4)

and the first prediction v_{pred—Tnew—ret} and the second prediction v_{pred—Tnew—acc} of the vehicle's speed may therefore be made at torques other than maximum or minimum torque. F_max is calculated as a maximum available engine torque, which is described as a function of engine speed, multiplied by the total transmission ratio i_tot and divided by the effective tyre radius r_wheel. The minimum force F_min is calculated in a similar way to the maximum force F_max but with minimum torque instead:

$\begin{array}{cc}{F}_{\max }=\frac{T_{\max }\left(\omega \right)·i_{\mathrm{tot}}}{r_{\mathrm{wheel}}}& \left(\mathrm{eq}.5\right)\\ F_{\min }=\frac{T_{\min }\left(\omega \right)·i_{\mathrm{tot}}}{r_{\mathrm{wheel}}}& \left(\mathrm{eq}.6\right)\end{array}$

where n is the vehicle's engine speed and i_tot the vehicle's total transmission ratio.

The vehicle's acceleration Acc is given by

Acc=(F_drive−F_env)/m  (eq. 7)

According to an embodiment, simulation steps C1-C5 during a simulation cycle s_j of N steps have a constant step length which depends on the vehicle's speed. The length dP of each simulation step is given by

dP=K·ν _init  (eq. 8)

where K is a time constant, e.g. 0.9 s, and v_init is prevailing vehicle speed at the beginning of the simulation.

The time dt for a simulation step is given by

dt=dP/v _i−1  (eq. 9)

where v_i−1 is predicted speed at preceding simulation step i-1.

The speed difference dv is

dv=Acc·dt  (eq. 10)

Energy consumed dW for a simulation step is given by

dW=dP·(F_drive−F_min)  (eq. 11)

The speed v_i at current simulation step becomes

v _i =v _i−1 +dv  (eq. 12)

Total time t_i for current simulation step is

t _i =t _i−1 +dt  (eq. 13)

Total energy consumed W_i for current simulation step is

W _i =W _i−1 +dW  (eq. 14)

FIG. 3 illustrates how a vehicle speed is predicted during a simulation cycle s_j of N simulation steps with a horizon which is L metres long. The prediction is discontinued after N simulation steps, i.e. after a simulation cycle s_j. A fresh simulation cycle s_j+1 then begins in the next time sample. Each simulation cycle s_j has a predetermined frequency f. At a frequency of 100 Hz, for example, 100 simulation steps are conducted per second. As the length of each simulation step depends on the vehicle's speed v_init at the beginning of the prediction, the length of the predicted section of the horizon varies with the vehicle's speed.

For example, at 80 km/h (22.22 m/s) the horizon becomes 2 km long if f=100 Hz and K=0.9 s, since each simulation step dP then becomes 20 m long and over 100 steps the horizon then becomes 2 km. FIG. 3 shows a fresh speed v_i predicted at each simulation step i. The processor load here becomes constant and the number of simulation steps i decides how long a simulation cycle s_j will taken. The number of simulation steps is determined by the rate f, which according to an embodiment is a predetermined value. The maximum processor load can therefore always be determined in advance, which is advantageous in that the processor can be dimensioned accordingly. The processor load is therefore independent of road topography, vehicle weight and engine type. According to an embodiment, the first prediction v_{pred—Tnew—ret} and the second prediction v_{pred—Tnew—acc} of the vehicle speed may be vectors with N values each, or alternatively only maximum and minimum values for the first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} may be saved in each simulation cycle s_j.

The one or more reference values which the vehicle's control system is to aim at are determined continuously when the vehicle is in motion. They are preferably determined as from a certain predetermined distance ahead of the vehicle and are then synchronised in the control unit so that the calculated reference value for a given situation is set at the right time. An example of such a distance is 50 metres, which the control unit therefore caters for in regulating the vehicle.

An embodiment according the invention will now be explained with reference to the flowchart in FIG. 4.

The flowchart in FIG. 4 illustrates how at the least one reference value is determined according to an embodiment of the invention. It shows the method starting at step S1. This is followed at steps 21 and 31 respectively by a first prediction v_{pred—Tnew—ret} and a second prediction v_{pred—Tnew—acc} of vehicle speed along the horizon, said first prediction based on an engine torque T_ret which retards the vehicle as compared with a conventional cruise control, and said second prediction based on an engine torque T_acc which accelerates the vehicle as compared with a conventional cruise control.

According to an embodiment of the invention, said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of a vehicle speed along the horizon are made in parallel, i.e. at substantially the same time in different branches of the flowchart for the method as illustrated in FIG. 4. According to another embodiment of the invention, said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of a vehicle speed along the horizon are made sequentially, i.e. one after another.

This is followed by the respective steps S22 and S32 of comparing said respective first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower value v_min and/or an upper limit value v_max which delineate a range within which the vehicle's speed should be.

According to an embodiment, the respective comparisons of said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max take place substantially in parallel at the respective steps S22 and S32, as depicted in FIG. 4. According to another embodiment, the comparisons of said first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed with a lower limit value v_min and/or an upper limit value v_max take place sequentially.

According to an embodiment of the invention, rules are applied for determining which at least one reference value the vehicle is to be regulated on. A set of rules is therefore used here to determine the value of the at least one reference value.

According to an embodiment, such a rule is that the at least one reference value, which here is the reference speed v_ref, is determined to a value which represents the set speed v_set if at the same time said first prediction v_{pred—Tnew—ret} of the vehicle speed is below the lower limit value v_min and said second prediction v_{pred—Tnew—acc} of the vehicle speed is above the upper limit value v_max. This is illustrated at step S3 in FIG. 4, which the method moves on to if the result of both the S22 and the S32 comparisons is “YES”.

If on the contrary said first prediction v_{pred—Tnew—ret} of the vehicle speed is not below the lower limit value v_min, the method moves on to step S33, in which the retardation (the lowering of the speed) is evaluated.

At step S33, according to an embodiment, the reference speed v_ref is determined to a value which represents said first predicted vehicle speed v_{pred—Tnew—ret} if a minimum value for said first predicted speed is equal to or above the lower limit value v_min and if also a maximum value for said first predicted speed is equal to or above a further upper limit value v_max2 which is related to a set speed v_set. According to an embodiment, the further upper limit value v_max2 corresponds to the set speed plus a constant c₁, i.e. v_max2=v_set+c₁. According to another embodiment, the further upper limit value v_max2 corresponds to a factor c₁ multiplied by the set speed v_set, i.e. v_max2=v_set*c₁. This factor c₁ may for example have the value 1.02, meaning that the further upper limit value v_max2 is 2% higher than the set speed v_set.

At step S33, according to an embodiment, the reference speed v_ref is determined to a value which corresponds to the set speed v_set if said first predicted vehicle speed v_{pred—Tnew—ret} is below the lower limit value v_min and/or below the further upper limit value v_max2.

At step S33, according to an embodiment, the reference speed v_ref is determined to a value which corresponds to the lower limit value v_min if a smallest value for said first predicted vehicle speed v_{pred—Tnew—ret} is above or equal to the lower limit value v_min and if a largest value for said first predicted speed is above or equal to the further upper limit value v_max2. This is illustrated schematically in FIG. 6.

If on the contrary said second prediction v_{pred—Tnew—acc} of the vehicle speed is not below the lower limit value v_min, the method moves on to step S23, in which the acceleration (the raising of the speed) is evaluated.

At step S23, according to an embodiment, the reference speed v_ref is determined to a value which represents said second predicted vehicle speed v_{pred—Tnew—acc} if a maximum value for said second predicted speed is equal to or below the upper limit value v_max and if also a minimum value for said second predicted speed is equal to or below a further lower limit value v_min2 which is related to a set speed. According to an embodiment, the further lower limit value v_min2 corresponds to the set speed v_set minus a constant c₂, i.e. v_min2=v_set−c₂. According to another embodiment, the further lower limit value v_min2 corresponds to a factor c₂ multiplied by the set speed v_set, i.e. v_min2=v_set*c₂. This factor c₂ may for example have the value 0.98, meaning that the further upper limit value v_max2 is 2% lower than the set speed v_set.

At step S23, according to an embodiment, the reference speed v_ref is determined to a value which corresponds to the set speed v_set if said second predicted vehicle speed v_{pred—Tnew—acc} is above the upper limit value v_max and/or above the further lower limit value v_min2.

At step S23, according to an embodiment, the reference speed v_ref is determined to a value which corresponds to the upper limit value v_max if a largest value for the second predicted vehicle speed v_{pred—Tnew—acc} is below or equal to the upper limit value v_max and if a smallest value for second predicted speed is smaller than or equal to the further lower limit value v_min2. According to an embodiment of the invention, the reference speed v_ref may here also be ramped up towards a value which corresponds to the further upper limit value V_max2.

For the vehicle to be retarded or accelerated (e.g. reach minimum torque or maximum torque), it is possible, according to an embodiment of the invention, for the at least one reference value, e.g. the reference speed v_ref, to be imparted with an offset. Minimum torque may than for example be imparted by giving the reference speed v_ref a low value below the lower limit value v_min. For example, the reference speed v_ref may be given the value v_min−k₁, in which k₁ is within the range 1-10 km/h. The engine's control unit will then demand drag torque from the engine. In a similar way, maximum torque may be reached by giving the reference speed v_ref a high value above the second upper limit value v_max. For example, the reference speed v_ref may be given the value v_max+k₂, in which k₂ is within the range 1-10 km/h.

According to an embodiment of the invention, account is taken of the efficiency of the power train (i.e. the efficiency of the engine, gearbox and final gear) and comfort/drivability when making the first prediction v_{pred—Tnew—ret} and second prediction v_{pred—Tnew—acc} of the vehicle speed, i.e. in choosing the control strategies to be predicted when the first and second predictions are determined. Comfortable and economical cruise control are achievable by determining in terms of magnitude and/or time the torque T, depending on the engine's efficiency or based on comfort requirements, resulting in different magnitudes for the respective first and second predictions. This embodiment may be implemented on the basis of rules such as that the engine has to have a certain torque at a certain engine speed or that torque resulting in more acceleration than a certain limit value is never allowed.

How various rules may be applied to decide which at least one reference value on which the vehicle is to be regulated was described above. According to embodiments described below, cost functions are instead used for deciding which at least one reference value the vehicle is to be regulated on. FIG. 4 illustrates the calculations based on these cost functions at steps S23 and S33. How the cost functions are used in determining the at least one reference value will therefore be described in detail below in relation to further embodiments of the present invention.

According to an embodiment of the present invention, at least one further first prediction v_{pred—Tk+new—ret} and second prediction v_{pred—Tk+new—acc} of the vehicle's speed along the horizon are made in each simulation cycle s_j. Here a conventional predication of the vehicle's speed v_pred—cc along the horizon is first made according to a conventional cruise control. This is followed by at least one further first prediction v_{pred—Tk+new—ret} of the vehicle's speed along the horizon, each of the at least one further first prediction based on a torque which is required to lower the vehicle's speed below the conventionally predicted vehicle speed v_pred—cc. In addition, at least one further second prediction of the vehicle's speed along the horizon is made, each of the at least one further second prediction being based on a torque which is required to increase the vehicle's speed above the conventionally predicted vehicle speed v_pred—cc, and the torque on which the at least one further first prediction v_{pred—Tk+new—ret} and second prediction v_{pred—Tk+new—acc} are based depends on said conventionally predicted vehicle speed v_pred—cc in the immediately preceding simulation cycle s_j−1.

According to this embodiment of the invention, a total of five different predictions of the vehicle's speed are here made, viz. v_pred—cc, v_{pred—Tnew—ret}, v_{pred—Tnew—acc}, v_{pred—Tk+new—ret} and v_{pred—Tk+new—acc}. Each of these predictions of the vehicle's speed other than the conventional prediction v_pred—cc is based on a torque which is required to increase the vehicle's speed above the first predicted vehicle speed v_pred—cc or on a torque which is required to lower the vehicle's speed below the first predicted vehicle speed v_pred—cc, and the torque on which the at least one further first prediction v_{pred—Tk+new—ret} and second prediction v_{pred—Tk+new—acc} are based depends on said conventionally predicted vehicle speed v_pred—cc, in the immediately preceding simulation cycle s_j−1.

According to an embodiment, other criteria are used for determining another torque T which results in an alternative mode of driving, in order to decide when and with what torque T the at least one further first prediction v_{pred—Tk+new—ret} and second prediction v_{pred—Tk+new—acc} of the vehicle's speed along the horizon are to be made, e.g. where particular comfort requirements are desired. Making the at least one further first prediction v_{pred—Tk+new—ret} and second prediction v_{pred—Tk+new—acc} preferably comprises initially one or more simulation steps by using functions of a conventional cruise control, followed by conducting the remaining simulation steps with a different torque T from that for the conventional cruise control, e.g. maximum or minimum torque in a similar way to as described above.

A total of five different predictions of the vehicle's speed, viz. v_pred—cc, v_{pred—Tnew—ret}, v_{pred—Tnew—acc}, v_{pred—Tk+new—ret} and v_{pred—Tk+new—acc}, with different control strategies are thus made according to this embodiment, for a limited distance of length L ahead of the vehicle, also called the horizon. Each such prediction preferably involves, according to an embodiment of the invention, calculating the vehicle's speed profile v, total energy consumption E_N and journey time t_N.

The total energy consumption E_N for a predicted speed during a simulation cycle is calculated by using equation 14. The total time t_N for a predicted speed during the simulation cycle is similarly calculated by equation 13. The prediction of the conventional vehicle speed v_pred—cc gives the total energy consumption designated E_pred—cc and the total journey time designated t_pred—cc and decides which of the other control strategies/modes of driving are to be predicted, in a similar way to as described above.

According to an embodiment, the at least one reference value, which here is the reference speed v_ref, is determined to a value which represents the set speed v_set if not only is said first prediction v_{pred—Tnew—ret} of the vehicle speed below the limit value set directly or indirectly by the driver, e.g. the lower limit value v_min, but also said second prediction v_{pred—Tnew—acc} of the vehicle speed is above the upper limit value v_max. This is illustrated at step S3, in FIG. 4, which the method moves on to if both of the comparisons at steps S22 and S32 produce the answer “YES”.

The total time t_{LA—Tnew—acc} and the total energy consumption E_{LA—Tnew—acc} are calculated during each simulation cycle for the second predicted speed v_{pred—Tnew—acc} based on an acceleration. The further second predicted vehicle speed v_{pred—Tk+new—acc} is also predicted as described above, and the total time t_{LA—Tk+new—acc} and the total energy consumption E_{LA—Tk+new—acc} for the further second predicted vehicle speed v_{pred—Tk+new—acc} are calculated during a single simulation cycle. The acceleration torque may here be any appropriate high engine torque which results in acceleration of the vehicle, e.g. a working point which has better efficiency and/or results in more comfortable acceleration than the maximum torque would.

The total time t_{LA—Tnew—ret} and the total energy consumption E_{LA—Tnew—ret} are calculated during each simulation cycle for the first predicted speed v_{pred—Tnew—ret} and then represent the total time and the energy consumption for the first predicted speed v_{pred—Tnew—re} based on a retardation. In addition, the further first predicted vehicle speed v_{pred—Tk+new—ret} is predicted as above, and the total time t_{LA—Tk+new—ret} and the total energy consumption E_{LA—Tk+new—ret} for the further first predicted vehicle speed v_{pred—Tk+new—ret} are also predicted and then represent the total time and the energy consumption for the further first predicted vehicle speed v_{pred—Tk+new—ret} based on a retardation, e.g. a minimum torque. The retardation torque may for example be a drag torque but might also be some other low engine torque which results in retardation if for example the working point has better efficiency and/or results in more comfortable retardation than the minimum torque would.

According to an embodiment of the invention, the speed predictions are evaluated by calculating the cost with respect to at least these predicted vehicle speeds. Determining said at least one reference value is therefore based here on at least one evaluation of a cost for at least one from among said first prediction v_{pred—Tnew—ret}, said second prediction v_{pred—Tnew—acc} and a further first prediction v_{pred—Tk+new—ret} and a further second prediction v_{pred—Tk+new—acc} of the vehicle speed by using at least one cost function J_Tnew—ret, J_Tnew—acc, J_Tk+new—ret, J_Tk+new—acc. On the basis of these costs it is possible to identify one of the predictions of vehicle speeds/control strategies as the best one for the particular case, making it possible to choose an appropriate predicted vehicle speed/control strategy.

The calculation unit described above is preferably adapted to performing these calculations. According to an embodiment, the cost functions J_Tnew—ret, J_Tnew—acc, J_Tk+new—ret and J_Tk+new—acc for said first prediction v_{pred—Tnew—ret}, said second prediction v_{pred—Tnew—acc}, said further first prediction v_{pred—Tk+new—ret} and said further second prediction v_{pred—Tk+new—acc} of the vehicle speed are determined by weighting their respective energy reductions and journey time reductions relative to a conventional prediction of the vehicle's speed v_pred—cc with a weighting parameter β according to the cost functions

$\begin{array}{cc}{J}_{\mathrm{Tnew\_ret}}=\frac{E_{\mathrm{LA},\mathrm{Tnew\_ret}}}{E_{\mathrm{pred\_cc}}}+\beta \frac{t_{\mathrm{LA},\mathrm{Tnew\_ret}}}{t_{\mathrm{pred\_cc}}}& \left(\mathrm{eq}.15\right)\\ J_{\mathrm{Tk}+\mathrm{new\_ret}}=\frac{E_{\mathrm{LA},\mathrm{Tk}+\mathrm{new\_ret}}}{E_{\mathrm{pred\_cc}}}+\beta \frac{t_{L,A,\mathrm{Tk}+\mathrm{new\_ret}}}{t_{\mathrm{pred\_cc}}}& \left(\mathrm{eq}.16\right)\\ J_{\mathrm{Tnew\_acc}}=\frac{E_{\mathrm{LA},\mathrm{Tnew\_acc}}}{E_{\mathrm{pred\_cc}}}+\beta \frac{t_{\mathrm{LA},\mathrm{Tnew\_acc}}}{t_{\mathrm{pred\_cc}}}& \left(\mathrm{eq}.17\right)\\ J_{\mathrm{Tk}+\mathrm{new\_acc}}=\frac{E_{\mathrm{LA},\mathrm{Tk}+\mathrm{new\_acc}}}{E_{\mathrm{pred\_cc}}}+\beta \frac{t_{\mathrm{LA},\mathrm{Tk}+\mathrm{new\_ac}}}{t_{\mathrm{pred\_cc}}}& \left(\mathrm{eq}.18\right)\end{array}$

The cost functions J_Tnew—ret, J_Tnew—acc, J_Tk+new—ret and J_Tk+new—acc are thus standardised with respect to the vehicle's predicted mode of driving according to the conventional cruise control (E_pred—cc and t_pred—cc). The cost estimations are therefore independent of, for example, the vehicle's weight. They are based solely on energy consumption and journey time, and the calculations take no account of the vehicle's fuel consumption. This means that there is no need for any model of the engine's efficiency, thereby simplifying the calculations when evaluating which control strategy is the most advantageous.

The weighting parameter β also depends very little on vehicle weight, distance traveled and engine type. The introduction of modes or setting facilities for controlling the vehicle speed is thus simplified. According to an embodiment, the driver or the system may for example choose whether to give priority to reducing fuel consumption or reducing journey time by altering the weighting parameter β. This function may be presented to the driver in a user interface, e.g. in the vehicle's instrument panel, in the form of the weighting parameter β or a parameter which depends on the weighting parameter β.

According to an embodiment of the invention, the cost functions J_Tnew—ret, J_Tnew—acc, J_Tk+new—ret and J_Tk+new—acc for said first prediction v_{pred—Tnew—ret}, said second prediction v_{pred—Tnew—acc}, said further first prediction v_{pred—Tk+new—ret} and said further second prediction v_{pred—Tk+new—acc} of the vehicle speed v_{pred—Tnew—ret}, of the vehicle speed are subjected to a cost function comparison followed by determining said at least one reference value on the basis of said comparison to arrive at lowest cost. In other words, the reference value is set to whichever from among said first prediction, said second prediction, said further first prediction and said further second prediction of the vehicle speed results in least cost. This is done in this embodiment at step S23 for acceleration and at step S33 for retardation (FIG. 4).

According to an embodiment, a penalty is added to at least one of the cost functions J_Tnew—ret, J_Tk+new—ret, for said first prediction v_{pred—Tnew—ret}, and said further first prediction v_{pred—Tk+new—ret} of the vehicle speed if said first prediction and said further first prediction reach different final speeds.

Similarly, a penalty is added to at least one from among the cost functions J_Tnew—acc, J_Tk+new—acc, for said second prediction v_{pred—Tnew—acc}, and said further second prediction v_{pred—Tk+new—acc} of the vehicle speed if said second prediction and said further second prediction reach different final speeds.

According to an embodiment, the different control strategies, e.g. said first prediction v_{pred—Tnew—ret} and said further first prediction v_{pred—Tk+new—ret} of the vehicle speed often do not have the same final speed at the end of the horizon, which according to an embodiment is catered for in the evaluation of the costs of the control strategies. This is illustrated in the diagram, in which said second prediction and said further second prediction are based on an acceleration.

The second predicted vehicle speed v_{pred—Tnew—acc} results in a higher final speed V_{end,Tnew—acc} than the final speed v_{end,Tk+new—acc} for the further second predicted vehicle speed v_{pred—Tk+new—acc}.

According to the aforesaid embodiments of the invention, a penalty is added to at least one out of the cost functions J_Tnew—acc and J_TK+new—acc if the second predicted vehicle speed v_{pred—Tnew—acc} in FIG. 5 results in a higher final speed v_{end,Tnew—acc} than the final speed v_{end,Tk+new—acc} for the further second predicted vehicle speed v_{pred—Tk+new—acc}. Similarly, a penalty would be added to at least one of the cost functions J_Tnew—acc and J_TK+new—acc if they resulted in different final speeds.

The size of the penalty may be calculated on the basis of the energy consumption E_γ and journey time t_γ which would be required along the horizon to bring the final speed v_{end,Tk+new—acc} of the further second prediction to the final speed v_{end,Tnew—acc} for the second prediction v_{pred—Tnew—acc} and at the same time cause both predictions to travel equally long distances. We describe below how this is done for the second prediction and the further second prediction. The same also applies to the first prediction v_{pred—Tnew—ret} and the further first prediction v_{pred—Tk+new—ret} of the vehicle speed but with changes of indices in the equations and the reasoning set out below.

The cost functions will then take the form

$\begin{array}{cc}{J}_{\mathrm{Tnew\_acc}}=\frac{E_{\mathrm{LA},\mathrm{Tnew\_acc}}+E_{\gamma ,\mathrm{Tnew\_acc}}}{E_{\mathrm{pred\_cc}}}+\beta \frac{t_{\mathrm{LA},\mathrm{Tnew\_acc}}+t_{\gamma ,\mathrm{Tnew\_acc}}}{t_{\mathrm{pred\_cc}}}& \left(\mathrm{eq}.19\right)\\ J_{\mathrm{Tk}+\mathrm{new\_acc}}=\frac{E_{\mathrm{LA},\mathrm{Tk}+\mathrm{new\_acc}}+E_{\gamma ,\mathrm{Tk}+\mathrm{new\_acc}}}{E_{\mathrm{pred\_cc}}}+\beta \frac{t_{\mathrm{LA},\mathrm{Tk}+\mathrm{new\_acc}}+t_{\gamma ,\mathrm{Tk}+\mathrm{new\_acc}}}{t_{\mathrm{pred\_cc}}}& \left(\mathrm{eq}.20\right)\end{array}$

Arriving at the energy consumption E_γ and journey time t_γ, involves a number of calculations based on Newton's second law, supposing a constant running resistance in the case where F_env is constant, i.e. it is here assumed that the road is level and that the air resistance and rolling resistance do not depend on the vehicle speed:

m{dot over (v)}=(F_drive−F_env)  (eq. 21)

On these assumptions, the vehicle speed becomes a linear function of time.

The journey time for the second further prediction v_{pred—Tk+new—acc} to change from V_{end,Tk+new—acc} to V_{end,Tnew—acc} becomes

$\begin{array}{cc}{t}_{\gamma ,\mathrm{Tk}+\mathrm{new\_acc}}=\left(v_{\mathrm{end},\mathrm{Tnew\_acc}}-v_{\mathrm{end},\mathrm{Tk}+\mathrm{new\_acc}}\right)\frac{m}{F_{\mathrm{drive}-F_{\mathrm{env}}}}.& \left(\mathrm{eq}.22\right)\end{array}$

The distance traveled by the vehicle is

$\begin{array}{cc}{s}_{\gamma }=\frac{F_{\mathrm{drive}}-F_{\mathrm{env}}}{2m}t_{\gamma ,\mathrm{Tnew\_acc}}^2+v_{\mathrm{end},\mathrm{Tk}+\mathrm{new\_acc}}·t_{\gamma ,\mathrm{Tk}+\mathrm{new\_acc}}.& \left(\mathrm{eq}.23\right)\end{array}$

The energy requirement is

E _{γ,Tk+new — acc} =F _driv ·S _γ.  (eq. 24)

The journey time for the second prediction to cover the same distance s_γ with no change in the speed v_{end,Tnew—acc} is

$\begin{array}{cc}{t}_{\gamma ,\mathrm{Tnew\_acc}}=\frac{s_{\gamma }}{v_{\mathrm{end},\mathrm{Tk}+\mathrm{new\_acc}}}.& \left(\mathrm{eq}.25\right)\end{array}$

The energy requirement is

E _{γ,Tnew — acc} =F _env ·s _γ.  (eq. 26)

If V_{end,Tk+new—acc}<V_{end,Tnew—acc} a maximum torque (F_drive=F_max) is used, and if V_{end,Tk+new—acc}>V_{end,Tnew—acc} a drag torque (F_drive=0) is used.

According to an embodiment, the standardising values E_pred—cc and t_pred—cc are not updated to obtain values for exactly the same distance traveled as the other predictions. For example, the values may be updated for each simulation cycle. The distance s_γ is so short relative to the total distance predicted that the standardisation works well even without taking into account energy and time consumed by conventional cruise controls over the distance s_γ.

According to an aspect of the invention a computer programme product is proposed which comprises programme instructions for enabling a computer system in a vehicle to perform steps according to the method described when those instructions are run on said computer system. The invention comprises also a computer programme product in which the programme instructions are stored on a medium which can be read by a computer system.

The present invention is not restricted to the embodiments described above. Various alternatives, modifications and equivalents may be used. The aforesaid embodiments therefore do not limit the invention's scope which is defined by the attached claims.

Claims

1. A method for determination of at least one reference value for a speed regulator that controls a speed of a vehicle such that said reference value may differ from a value corresponding to the speed indicated by a driver of the vehicle, the method comprising: making, automatically by a control unit including an automated processor, a first prediction and a second prediction of a speed of the vehicle along a horizon, said first prediction based on an engine torque which retards the vehicle as compared with the speed regulator in which the reference value equals the speed indicated by the driver, and said second prediction based on an engine torque which accelerates the vehicle as compared with the speed regulator in which the reference value equals the speed indicated by the driver;comparing each of the first prediction and the second prediction with a lower limit value and/or an upper limit value which delineate, respectively, a lower limit and an upper limit of a range within which the speed of the vehicle is maintained;determining the at least one reference value based on at least one of the comparisons and the first prediction and the second prediction; andcontrolling the speed of the vehicle based on the at least one reference value determined.

2. A method according to claim 1, wherein the first prediction and the second prediction are made in parallel.

3. A method according to claim 1, wherein the comparing of the first prediction and the second prediction with the lower limit value and/or the upper limit value are done in parallel.

4. A method according to claim 1, wherein the at least one reference value is any of the following: reference speed vref a reference torque Tref a reference speed ωref.

5. A method according to claim 1, wherein a hysteresis is applied to the at least one reference value.

6. A method according to claim 1, further comprising applying a rule to determine the at least one reference value.

7. A method according to claim 6, wherein the rule is that the at least one reference value is the speed indicated by the driver when the first prediction is below the lower limit value and the second prediction is above the upper limit value.

8. A method according to claim 6, wherein the rule is that the at least one reference value is the first predicted vehicle speed when both following conditions are true: (a) a minimum value for the first predicted speed is equal to or above the lower limit value, and(b) a maximum value for said first predicted speed is equal to or above a further upper limit value,wherein the further upper limit value equals the speed indicated by the driver plus a constant c1.

9. A method according to claim 6, wherein the rule is that the at least one reference value is the second predicted vehicle speed when both following conditions are true: (a) a maximum value for said second predicted speed is equal to or below the upper limit value, and(b) a minimum value for said second predicted speed is equal to or below a further lower limit value,wherein the further lower limit value equals the speed indicated by the driver minus a constant c2.

10. A method according to claim 1, further comprising: determining the at least one reference value in each cycle of a plurality of simulation cycles,wherein a simulation cycle Sj comprises: predicting a speed vpred—cc of the vehicle along the horizon according to the speed indicated by the driver; andmaking a first prediction of a speed vpred—Tk+new—ret of the vehicle along the horizon, the first prediction being based on a torque required to lower the vehicle's speed below vpred—cc,making a second prediction of a speed vpred—Tk+new—acc of the vehicle along the horizon, the second prediction being based on a torque required to increase the vehicle's speed above the vpred—cc, such that the torque on which the first prediction vpred—Tk+new—ret and the second prediction vpred—Tk+new—acc are based depends on vpred—cc in an immediately preceding simulation cycle sj−1.

11. A method according to claim 1, further comprising calculating a speed profile v, an energy consumption EN and a journey time tN of the vehicle at each prediction of the vehicle speed.

12. A method according to claim 11, wherein the determination of the at least one reference value is based on at least one evaluation of a cost for at least one of the first prediction, the second prediction and a further first prediction vpred—Tk+new—ret and a further second prediction vpred—Tk+new—acc of the vehicle speed by using at least one cost function JTnew—ret, JTnew—acc, JTk+new—ret, JTk+new—acc.

13. A method according to claim 12, wherein respective cost functions JTnew—ret, JTnew—acc, JTk+new—ret and JTk+new—acc for said first prediction, said second prediction, said further first prediction vpred—Tk+new—ret and said further second prediction vpred—Tk+new—acc of the vehicle speed are determined by weighting with a weighting parameter P their respective energy reductions and journey time reductions relative to a conventional prediction of the vehicle's speed vpred—cc.

14. A method according to claim 13, wherein the method further comprises: subjecting the cost functions JTnew—ret, JTnew—acc, JTk+new—ret and JTk+new—acc for said first prediction, said second prediction, said further first prediction vpred—Tk+new—ret and said further second prediction vpred—Tk+new—acc of the vehicle speed vpred—Tnew—ret, of the vehicle speed to a cost function comparison,wherein the determining said at least one reference value is made based on the comparison to arrive at lowest cost.

15. A method according to claim 1, further comprising adding a penalty to at least one of the cost functions JTnew—ret, JTk+new—ret, for said first prediction, and said further first prediction vpred—Tk+new—ret of the vehicle speed, when the first prediction and said further first prediction reach different final speeds.

16. A method according to claim 11, further comprising adding a penalty to at least one from among the cost functions JTnew—acc, JTk+new—acc, for said second prediction, and said further second prediction vpred—Tk+new—acc of the vehicle speed, when the second prediction and said further second prediction reach different final speeds.

17. A module arranged for determination of at least one reference value for a speed regulator that controls a speed of a vehicle such that said reference value may differ from a value corresponding to the speed indicated by a driver of the vehicle, the module comprising: a calculation unit configured to make a first prediction and a second prediction of the vehicle speed along a horizon, said first prediction based on an engine torque which retards the vehicle as compared with the speed regulator in which the reference value equals the speed indicated by the driver, and said second prediction based on an engine torque which accelerates the vehicle as compared with the speed regulator in which the reference value equals the speed indicated by the driver;said module further configured: to compare the first prediction and the second prediction with a lower limit value and/or an upper limit value which delineate, respectively, a lower threshold and an upper threshold of a range within which the speed of the vehicle is maintained;to determine at least one reference value based on at least one of the comparisons and said first prediction and second prediction; andto output the at least one reference value determined for controlling the speed of the vehicle.

18. A module according to claim 17, said module being arranged to make said first prediction and second prediction of a vehicle speed along the horizon in parallel.

19. A module according to claim 17, said module being arranged to do said comparisons of said first prediction and a second prediction with a lower limit value vmin and/or an upper limit value vmax in parallel.

20. A module according to claim 17, in which said at least one reference value is any of the following: reference speed vref a reference torque Tref a reference speed ωref.

21. A module according to claim 17, wherein said module applies a hysteresis to said at least one reference value.

22. A module according to claim 17, wherein said module applies rules to determine which at least one reference value the vehicle is to regulated on.

23. A module according to claim 22, wherein a rule is that the at least one reference value is determined as the set speed vset, when said first prediction of the vehicle speed is below the second limit value and said second prediction of the vehicle speed is above the upper limit value.

24. A module according to claim 23, wherein said module determines, as the at least one reference value, said first predicted vehicle speed, when a minimum value for said first predicted speed is equal to or above the lower limit value and if also a maximum value for said first predicted speed is equal to or above a further upper limit value, wherein the further upper limit value is the set speed plus a constant c1.

25. A module according to claim 23, wherein said module determines, as the at least one reference value, said second predicted vehicle speed, when both following conditions are true: (a) a maximum value for said second predicted speed is equal to or below the upper limit value, and(b) a minimum value for said second predicted speed is equal to or below a further lower limit value,wherein the further lower limit value is a speed indicated by the driver minus a constant c2.

26. A module according to claim 17, wherein said module is configured to determine the at least one reference value in each cycle of a plurality of simulation cycles, wherein in a simulation cycle sj the module performs: a conventional prediction of the speed vpred—cc of the vehicle along the horizon according to a conventional cruise control; andat least one further first prediction vpred—Tk+new—ret of the vehicle's speed along the horizon, each such further first prediction being based on a torque required to lower the speed of the vehicle below the conventionally predicted vehicle speed vpred—cc,at least one further second prediction of the speed of the vehicle along the horizon is made, each such further second prediction being based on a torque required to increase the vehicle's speed above the conventionally predicted vehicle speed vpred—cc,where the torque on which the at least one further first prediction vpred—Tk+new—ret and second prediction vpred—Tk+new—acc are based depends on said conventionally predicted vehicle speed vpred—cc in an immediately preceding simulation cycle sj−1.

27. A module according to claim 17, wherein said module is configured to calculate the speed profile v of the vehicle, energy consumption EN and journey time tN during each prediction of the speed of the vehicle.

28. A module according to claim 27, wherein said module is configured to determine said at least one reference value on the basis of at least one evaluation of a cost for at least one from among said first prediction, said second prediction and a further first prediction vpred—Tk+new—ret and a further second prediction vpred—Tk+new—acc of the vehicle speed by using at least one cost function JTnew—ret, JTnew—acc, JTk+new—ret, JTk+new—acc.

29. A module according to claim 28, wherein said module is configured to determine the respective the cost functions JTnew—ret, JTnew—acc, JTk+new—ret and JTk+new—acc for said first prediction, said second prediction, said further first prediction vpred—Tk+new—ret and said further second prediction vpred—Tk+new—acc of the vehicle speed by weighting with a weighting parameter β their respective energy reductions and journey time reductions relative to a conventional prediction of the vehicle's speed vpred—cc.

30. A module according to claim 29, wherein said module is configured to subject the cost functions JTnew—ret, JTnew—acc, JTk+new—ret and JTk+new—acc for said first prediction, said second prediction, said further first prediction vpred—Tk+new—ret and said further second prediction vpred—Tk+new—acc of the vehicle speed vpred—Tnew—ret, of the vehicle speed to a cost function comparison, wherein the determining of said at least one reference value is based on the comparison to arrive at lowest cost.

31. A module according to claim 27, wherein said module is configured to add a penalty to at least one of the cost functions JTnew—ret, JTk+new—ret, for said first prediction vpred—Tnew—ret, and said further first prediction vpred—Tk+new—ret of the vehicle speed, when said first prediction and said further first prediction reach different final speeds.

32. A module according to claim 27, wherein said module is configured to add a penalty to at least one from among the cost functions JTnew—acc, JTk+new—acc, for said second prediction vpred—Tnew—acc, and said further second prediction vpred—Tk+new—acc of the vehicle speed, when said second prediction and said further second prediction reach different final speeds.

33. A non-transitory computer readable medium product incorporating instructions configured to enable a computer of a vehicle to perform the method of claim 1, when the instructions are run on said computer.

34. (canceled)

35. A vehicle comprising the module of claim 17.