Digital twin and a method for modelling connectivity of a heavy-duty vehicle

1 . A method performed by a digital twin for modelling connectivity of a heavy-duty vehicle,

wherein the digital twin comprises a digital model of the heavy-duty vehicle,

wherein the digital twin is configured to access another digital model of one or more communication networks in which the heavy-duty vehicle is expected to operate;

the method comprising:

modelling an expected degree of connectivity of the heavy-duty vehicle to at least one of the one or more communication networks,

wherein the modelling is in dependence of a vehicle state and vehicle connectivity system(s) onboard the heavy-duty vehicle;

determining that the expected degree of connectivity is below an acceptance criterion;

determining that one or more applications comprised in the heavy-duty vehicle are at least partly out-of-service due to the connectivity being below the acceptance criterion; and

triggering a warning message that one or more applications comprised in the heavy-duty vehicle are at least partly out-of-service due to the connectivity being below the acceptance threshold.

2 . The method according to claim 1 , wherein the vehicle state comprises a vehicle geographical position.

3 . The method according to claim 1 , comprising:

predicting which application(s) out of a configured set of applications comprised in the heavy-duty vehicle that are enabled given the expected degree of connectivity.

4 . The method according to claim 1 , comprising:

estimating a vehicle position based on performed dead reckoning or transportation mission route data;

determining that the expected degree of connectivity at the estimated vehicle position is below an acceptance criterion; and

determining, based on the estimated vehicle position, when the degree of connectivity of the heavy-duty vehicle is expected to be at or above the acceptance criterion.

5 . The method according to claim 1 , wherein the heavy-duty vehicle comprises two or more vehicle connectivity systems, and wherein the expected degree of connectivity of the heavy-duty vehicle is modelled using the two or more connectivity systems in combination.

6 . The method according to claim 1 , comprising:

evaluating if the expected degree of connectivity would be changed if the heavy-duty vehicle is configured with one or more alternative vehicle connectivity systems from a catalogue of alternative vehicle connectivity systems instead of or in addition to the vehicle connectivity system currently comprised in the heavy-duty vehicle.

7 . The method according to claim 1 , comprising:

evaluating if the expected degree of connectivity would be changed if the heavy-duty vehicle is configured with one or more alternative vehicle antenna systems from a catalogue of alternative vehicle antenna systems instead of or in addition to a current vehicle antenna system currently comprised in the heavy-duty vehicle.

8 . The method according to claim 1 , comprising:

obtaining configuration data from another digital twin.

9 . The method according to claim 1 , wherein the expected degree of connectivity is a current expected degree of connectivity, wherein the vehicle state is a current vehicle state and the vehicle connectivity system(s) are current vehicle connectivity system(s), and

wherein the method comprises:

modelling, given the current vehicle state and current vehicle connectivity system(s), an amount of data that can be successfully transferred to or from at least one of the one or more communication networks in an amount of time and with the current expected degree of connectivity.

10 . The method according to claim 1 , wherein the expected degree of connectivity is a future expected degree of connectivity, wherein the vehicle state is a future vehicle state and the vehicle connectivity system(s) are future vehicle connectivity system(s), and

wherein the method comprises:

estimating a future point in time when an amount of data can be successfully transferred to or from at least one of the one or more communication networks in a given amount of time, and the future vehicle state and the future vehicle connectivity system(s) and with the future expected degree of connectivity.

11 . The method according to claim 1 , wherein the connectivity of the heavy-duty vehicle is associated with at least one of: bandwidth, latency and spectral efficiency.

12 . A digital twin for modelling connectivity of a heavy-duty vehicle, wherein the digital twin is arranged to perform the method according to claim 1 .

13 . A heavy-duty vehicle comprising the digital twin according to claim 12 .

14 . A computer readable medium carrying a non-transitory computer program comprising program code for performing the method of claim 1 when said program code is run on a computer.