Method for forecasting the evolution of the magnitude of a data for a vehicle journey
The magnitude (Y) of a data associated to a journey of an automotive vehicle is expressed by a function (f) of at least one input parameter (x). This method includes at least the steps of: a) defining a first model (f t=0 ) of the function; b) running the vehicle on a reference trip, the input parameter (x, m, p) and the magnitude (Y) being measured (Y M , x M ) during or at the end of the reference trip; c) computing a value (Y C ) of the magnitude by using the first model (f t=0 ) of the function (f) and the value of the parameter (x M ) measured at step b); d) comparing the values (Y M , Y C ) of the magnitude at said time; and e) adjusting the function (f t=1 ) in a way corresponding to the reduction of the difference between the measured value (Y M ) and the computed value (Y C ).
1. A method for forecasting the evolution of the magnitude of a data associated to a journey of an automotive vehicle via a mathematical model and for selecting the best miming conditions for a vehicle, in an onboard computer computation system, where the magnitude is expressed by a function of at least one input parameter, comprising:
defining a first model of the function used for computing the magnitude on the basis of the input parameter;
running the vehicle on a reference trip, for a given time or a given distance, the input parameter and the magnitude being measured (Y M , x M ) to provide a measured value of the magnitude at least at one time during or at the end of the reference trip;
computing a computed value of the magnitude by using the first model of the function and the value of the parameter measured at the running step;
comparing the values of the magnitude at the at least one time measured at the running step and computed at the computation step;
if the comparison of the measured value and the computed value reveals a difference greater than a predetermined difference value between the measured value and the computed value, adjusting the function in a way corresponding to a reduction of the difference between the measured value and the computed value; and
selecting by onboard computation means, based on the forecasting of the magnitude of the data associated to a given journey, a road to be followed.
2. Method according to claim 1 , comprising performing the running step, the computation step the comparison step, and the adjustment step successively, a plurality of times, the function adjusted in the adjustment step of a preceding performance of the running step, the computation step, the comparison step, and the adjustment step being used to compute the value of the magnitude on a next performance of the running step, the computation step, the comparison step, and the adjustment step.
3. Method according to claim 1 , wherein the reference trip is a part of the journey to be followed by the vehicle.
4. Method according to claim 3 , wherein the reference trip is an initial part of the journey.
5. Method according to claim 1 , wherein the computation step, the comparison step and the adjustment step occur in real time.
6. Method according to claim 1 , wherein in the defining step, the first model is based on an initial data set for the function.
7. Method according to claim 1 , wherein in the defining step, the first model is based on the last data set used for the function in a previous journey of the vehicle.
8. Method according to claim 1 , wherein the magnitude (Y) of the data is expressed as a polynomial function of one parameter in the form
Y
=
∑
i
=
0
N
a
i
x
i
where x is the input parameter, N is an integer larger than 1 and a i is a real number for i integer between 0 and N, and wherein the first model includes a set of N+1 real numbers ([a 0 , . . . a N ] t=0 ) corresponding, to values of a i for i integer between 0 and N.
9. Method according to claim 8 , wherein in the comparison step, adjustment of the function occurs by adjusting the respective values ([a 0 , . . . a N ] t=0 ) of real numbers a i for i integer between 0 and N.
10. Method according to claim 1 , wherein the magnitude (Y) of the data is expressed as a polynomial function of several parameters in the form,
Y
=
Ax
+
B
ⅆ
x
ⅆ
t
+
Cm
+
Dp
+
E
where x is a distance travelled during a reference trip, a journey or a part of a journey, m is the mass of the vehicle, p is the tire pressure, and A, B, C, D and E are real numbers and wherein the first model includes a set of real numbers (A 0 , B 0 , C 0 , D 0 and E 0 ) corresponding to A, B, C, D and E.
11. Method according to claim 10 , wherein in the comparison step, adjustment of the function occurs by adjusting the respective values (A 1 , B 1 , C 1 , D 1 and E 1 ) of numbers A, B, C, D and E.
12. Method according to claim 1 , wherein the magnitude of the data is expressed as a function of a parameter
(
ⅆ
x
ⅆ
t
)
which depends on the driver's behaviour and wherein the first model includes a set of numbers.
13. Method according to claim 12 , wherein in the comparison step, adjustment of the function occurs by selecting a set of numbers which depends on the driver's behaviour determined on the reference trip.
14. Method according to claim 1 , wherein the data comprises fuel consumption.