METHOD AND SYSTEM FOR AVOIDING OVERHEATING OF A VEHICLE SUBSYSTEM

Abstract

The present disclosure relates to a method for avoiding overheating of a vehicle subsystem, which comprises a compressor with a pressure chamber. The method comprises the steps of executing an Extended Kalman Filter on a control module that calculates an error between a predicted state model of the vehicle subsystem and a corresponding measured state model of the vehicle subsystem, and processes the calculated error to adjust the predicted state model, including adjusting the estimated ambient pressure, based on weighted uncertainties of the measured and estimated parameters. The method further comprises the steps of comparing the estimated ambient pressure to a predetermined ambient pressure default value; and reducing a cut-off pressure target value of the vehicle subsystem by a reduction amount for a period of time, when the estimated ambient pressure is less than or equal to the predetermined ambient pressure default value.

Claims

1. A method for avoiding overheating of a vehicle subsystem, the vehicle subsystem comprising a compressor with a pressure chamber, wherein the method comprises the steps of: executing an Extended Kalman Filter on a control module that calculates an error between a predicted state model of the vehicle subsystem and a corresponding measured state model of the vehicle subsystem, the predicted state model comprising as parameters an estimated pressure inside the pressure chamber, an estimated ambient pressure, an estimated rotational speed of the compressor and an estimated fluid volume stream of the compressor, and the measured state model comprising as parameters a measured pressure inside the pressure chamber, a measured rotational speed of the compressor and a measured fluid volume stream of the compressor, and processes the calculated error to adjust the predicted state model, including adjusting the estimated ambient pressure, based on weighted uncertainties of the measured and estimated parameters; comparing the estimated ambient pressure to a predetermined ambient pressure default value; and reducing a cut-off pressure target value of the vehicle subsystem by a reduction amount for a period of time, when the estimated ambient pressure is less than or equal to the predetermined ambient pressure default value.

2. The method according to claim 1, wherein the weighted uncertainties of the measured parameters are incorporated in the adjusting in form of a measurement covariance matrix including a variance of pressure chamber pressure sensor data, a variance of compressor rotational velocity sensor data, and variance of volume flow sensor data.

3. The method according to claim 1, wherein the weighted uncertainties of the estimated parameters are incorporated in the adjusting in form of a process covariance matrix including at least one variable that represents an uncertainty about the pressure in the pressure chamber.

4. The method according to claim 3, wherein the vehicle subsystem is switchable between an open state in which the subsystem is open towards a connected further subsystem and a closed state in which the subsystem is closed towards the connected further subsystem.

5. The method according to claim 4, wherein the process covariance matrix of the Extended Kalman Filter is temporarily dynamically changed, when the vehicle subsystem switches from the closed state to the open state.

6. The method according to claim 1, further comprising the step of generating a warning signal for warning a driver of the vehicle, when the estimated ambient pressure is less than or equal to the predetermined ambient pressure default value.

7. The method according to claim 1, further comprising the steps of: comparing the measured pressure inside the pressure chamber with the cut-off pressure target value; and switching-off the compressor for a period of time, when the measured pressure inside the pressure chamber reaches or rises above the cut-off pressure target value.

8. The method according to claim 1, wherein the vehicle is an electric vehicle.

9. The method according to claim 4, wherein the further subsystem is an air suspension system which is connected to the vehicle subsystem by a controllable valve.

10. A control module configured to perform the method according to claim 1 for controlling the vehicle subsystem, the vehicle subsystem comprising the compressor with the pressure chamber.

11. A system for a vehicle for an electric vehicle, comprising: a vehicle subsystem having a compressor with a pressure chamber; and a control module with an Extended Kalman Filter implemented thereon, which is configured to calculate an error between a predicted state model of the vehicle subsystem and a corresponding measured state model of the vehicle subsystem, the predicted state model comprising as parameters an estimated pressure inside the pressure chamber, an estimated ambient pressure, an estimated rotational speed of the compressor and an estimated fluid volume stream of the compressor, and the measured state model comprising as parameters a measured pressure inside the pressure chamber, a measured rotational speed of the compressor and a measured fluid volume stream of the compressor, and which is configured to process the calculated error to adjust the predicted state model, including adjusting the estimated ambient pressure, based on weighted uncertainties of the measured and estimated parameters, wherein the control module comprises a comparing unit configured to compare the estimated ambient pressure to a predetermined ambient pressure default value, and wherein the control module comprises a cut-off pressure setting unit configured to reduce a cut-off pressure target value of the vehicle subsystem by a reduction amount for a period of time, when the estimated ambient pressure is less than or equal to the predetermined ambient pressure default value.

12. The system according to claim 11, comprising a further subsystem connected to the vehicle subsystem by a controllable valve, wherein the system is configured to supply pressure from the pressure chamber of the compressor to the further subsystem upon opening of the controllable valve.

13. The system according to claim 11, wherein the system further comprises: a pressure chamber pressure sensor configured to measure the pressure inside the pressure chamber, a compressor rotational velocity sensor configured to measure the rotational speed of the compressor, and a volume flow sensor configured to measure the fluid volume stream of the compressor.

14. The method according to claim 5, wherein the value of the at least one variable is multiplied when the vehicle subsystem switches from the closed state to the open state.

15. The system according to claim 12, wherein the further subsystem comprises an air suspension system.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0052] For a better understanding of embodiments of the invention and to show how the same may be carried into effect, reference will now be made, purely by way of example, to the accompanying drawings in which like numerals designate corresponding elements or sections throughout.

[0053] In the accompanying drawings:

[0054] FIG. 1 shows a schematic perspective view of a vehicle comprising a system according to the invention;

[0055] FIG. 2 shows a schematic detailed view of the control module of FIG. 1;

[0056] FIG. 3 shows a schematic diagram of an ambient pressure estimation by a method according to the invention.

DETAILED DESCRIPTION OF THE DRAWINGS

[0057] Various examples of embodiments of the present invention will be explained in more detail by virtue of the following embodiments illustrated in the figures and/or described below.

[0058] FIG. 1 shows a system 10 according to the invention that is implemented in a vehicle 12 in or-der to avoid overheating of a subsystem 14.

[0059] The system 10 comprises the vehicle subsystem 14 having a compressor 16 with a pressure chamber 16A and having a control module 18 operationally connected therewith. An Extended Kalman Filter (EKF) is implemented on the control module 18. The EKF is configured to calculate an error between a predicted state model of the vehicle subsystem 14 and a corresponding measured state model of the vehicle subsystem 14.

[0060] The predicted state model comprises as parameters an estimated pressure inside the pressure chamber 16A, an estimated ambient pressure, an estimated rotational speed of the compressor 16 and an estimated fluid volume stream of the compressor 16. The measured state model comprises as parameters a measured pressure inside the pressure chamber 16A, a measured rotational speed of the compressor 16 and a measured fluid volume stream of the compressor 16.

[0061] The EKF is further configured to process the calculated error to adjust the predicted state model, including adjusting the estimated ambient pressure, based on weighted uncertainties of the measured and estimated parameters.

[0062] More precisely, in this example, when the vehicle is turned on without knowledge of the ambient pressure the method will initially estimate the ambient pressure to be 1.05 bar. This leads to an error after the prediction by the EKF that expects the ambient pressure as an input value. This error is then processed with the state vector depending on the specified uncertainties. Since the standard deviation of the measured signals is relatively low, the error is compensated by reducing the estimated ambient pressure 40 continuously. Thus the estimated ambient pressure 40 is corrected over time. This approximation of the actual ambient pressure 50 by the estimated ambient pressure 40 over time is shown in the diagram of FIG. 2.

[0063] As shown in FIG. 1, the compressor 16 is provided with various sensors for measuring the parameters of the measured state model. Namely, the compressor 16 is provided with a pressure chamber pressure sensor 28 configured to measure the pressure inside the pressure chamber 16A, a compressor rotational velocity sensor 30 configured to measure the rotational speed of the compressor 16, and a volume flow sensor 32 configured to measure the fluid volume stream of the compressor 16.

[0064] As shown in FIG. 3, the control module 18 comprises a comparing unit 20 and a cut-off pressure setting unit 22. The comparing unit 20 is configured to compare the estimated ambient pressure 40 to a predetermined ambient pressure default value, which can for example be 1 bar. The cut-off pressure setting unit 22 is configured to reduce a cut-off pressure target value of the vehicle subsystem 14 by a reduction amount for a period of time, when the estimated ambient pressure is less than or equal to the predetermined ambient pressure default value. In this example, the cut-off pressure target value can be 17 bar. The cut-off pressure target value can be reduced by a reduction amount of 3 bar to a reduced amount of 14 bar.

[0065] Subsequently, the compressor 16 is switched-off for a period of time, when the measured pressure inside the pressure chamber 16A reaches or rises above the cut-off pressure target value, i.e. above 14 bar in the reduced state. The compressor 16 is switched-off until the measured pressure falls below the cut-off pressure target value again.

[0066] This principle can reduce an error in the estimated ambient pressure state when the vehicle 12 drives into areas of higher altitude for a longer period of time. Since this change of state happens relatively slowly, the EKF has enough time to adjust the predictions and provide exact estimations on the ambient pressure. When the estimated ambient pressure reaches a certain predefined minimum, the compressor's cut-off pressure is temporarily reduced to avoid overheating.

[0067] As can be seen in FIG. 1, the system 10 comprises a further subsystem 24 in form of an air suspension system. The further subsystem 24 is connected to the vehicle subsystem 14 by a controllable valve 26. The system 10 is configured to supply pressure from the pressure chamber 16A of the compressor 16 to the further subsystem 24 upon opening of the controllable valve 26.

[0068] Thus, by means of the present invention, even when there is no knowledge of the ambient pressure available, the ambient pressures estimation accuracy increases over time.