Method for classifying energy consumers in a vehicle
The method comprises providing preview information comprising at least one of a predicted road condition and a predicted road event; processing the preview information with an estimation model adapted to relate a risk level associated with a power unavailability for each one of the energy consumers to the at least one predicted road condition and/or predicted road event; classifying the energy consumers having a risk level higher than a predetermined risk level threshold value as critical energy consumers, and classifying the energy consumers with a risk level lower than the predetermined risk level threshold value as non-critical energy consumers; estimating a required amount of energy and/or power for powering all the energy consumers in the predetermined group of energy consumers for the predicted road condition and/or the predicted road event; estimating the available energy and/or power of the EST system; in response to determining that the required amount of energy for powering all the energy consumers in the predetermined group of energy consumers is higher than the available energy, powering the energy consumers classified as critical, and deactivating at least one of the energy consumers classified as non-critical.
1. A method for classifying a predetermined group of energy consumers in a vehicle into critical and non-critical energy consumers being powered by an energy storage or transformation (EST) system, the method comprises:
providing preview information of vehicle operation, the preview information comprising at least one of a predicted road condition and a predicted road event;
processing the preview information with an estimation model adapted to relate a risk level associated with a power unavailability for each one of the energy consumers to the at least one predicted road condition and/or predicted road event;
classifying the energy consumers having a risk level higher than a predetermined risk level threshold value as critical energy consumers, and classifying the energy consumers with a risk level lower than the predetermined risk level threshold value as non-critical energy consumers;
estimating a required amount of energy and/or power for powering all the energy consumers in the predetermined group of energy consumers for the predicted road condition and/or the predicted road event;
estimating an available energy and/or power of the EST system;
in response to determining that the required amount of energy and/or power for powering all the energy consumers in the predetermined group of energy consumers is higher than the available energy and/or power of the EST system for the predicted road condition and/or the predicted road event, powering the energy consumers classified as critical, and deactivating at least one of the energy consumers classified as non-critical.
2. The method according to claim 1 , wherein the classification of the energy consumers is performed dynamically.
3. The method according to claim 1 , wherein at least one of the energy consumers in the predetermined group of energy consumers is a traction electric machine, and wherein classifying the energy consumers comprises classifying the traction electric machine as a critical energy consumer.
4. The method according to claim 1 , comprising:
identifying, for each one of the energy consumers, a vehicle situation which, in case of power unavailability of the energy consumer for the predicted road condition and/or the predicted road event, belong to a predetermined group of vehicle situations defined as hazardous, and wherein the risk level of the estimation model is determined in response to such hazardous vehicle situations.
5. The method according to claim 4 , wherein the vehicle situations belonging to the predetermined group of vehicle situations defined as hazardous has risk level higher than the predetermined risk level threshold value.
6. The method according to claim 1 , wherein the step of estimating the available energy and/or power of the EST system is carried out for the predicted road condition and/or the predicted road event.
7. The method according to claim 1 , wherein the preview information comprises road topography and/or current traffic conditions.
8. The method according to claim 1 , wherein the estimation model is a statistical model, or a machine learning model formed from data of power unavailability for the energy consumers related to the predicted road condition and/or the predicted road event from the vehicle or from a plurality of vehicles.
9. The method according to claim 1 , further comprising:
in response to determining that the required amount of energy and/or power for powering all the energy consumers in the predetermined group of energy consumers is higher than the available energy and/or power of the EST system for the predicted road condition and/or the predicted road event, warning a driver that prioritization of powering the critical energy consumers, and/or that deactivation of at least one of the non-critical energy consumers, are expected.
10. A computer program comprising program code for performing the method of claim 1 when said program code is run on a computer.
11. A non-transitory computer readable medium carrying a computer program comprising program code for performing the method of claim 1 when said computer code is run on a computer.
12. A controlling apparatus for classifying energy consumers in a vehicle into critical and non-critical energy consumers, the controlling apparatus being configured to perform the method according to claim 1 .
13. A system for classifying a predetermined group of energy consumers in a vehicle into critical and non-critical energy consumers, the energy consumers being powered by an energy storage or transformation, EST, system, characterised by:
a data acquisition unit configured to acquire preview information of the vehicle operation, the preview information comprising at least one of a predicted road condition and a predicted road event; and
a control unit configured to:
process the preview information with an estimation model adapted to relate a risk level associated with a power unavailability for each one of the energy consumers to the at least one predicted road condition and/or predicted road event;
classify the energy consumers having risk level higher than a predetermined risk level threshold value as critical energy consumers, and classify the energy consumers with a risk level lower than the predetermined risk level threshold value as non-critical energy consumers;
estimate a required amount of energy and/or power for powering all the energy consumers in the predetermined group of energy consumers for the predicted road condition and/or the predicted road event;
estimate the available energy and/or power of the EST system;
in response to determining that the required amount of energy and/or power for powering all the energy consumers in the predetermined group of energy consumers is higher than the available energy and/or power of the EST system for the predicted road condition and/or the predicted road event, powering the energy consumers classified as critical, and deactivating at least one of the energy consumers classified as non-critical.
14. A vehicle comprising a system according to claim 13 .