NONLINEAR SYSTEM IDENTIFICATION FOR OPTIMIZATION OF WIRELESS POWER TRANSFER

• US 20140172338A1
• Filed: 12/16/2013
• Published: 06/19/2014
• Est. Priority Date: 12/18/2012
• Status: Active Grant

• Current Assignee: Indigo Technologies, Inc.
• Original Assignee: Nucleus Scientific, Incorporated
• Inventors: Lafontaine, Serge R., Hunter, Ian W.
• Granted Patent: US 9,746,506 B2
• Time in Patent Office: Days
• US Class Current: 702/65
• CPC Class Codes: G01R 19/2509 Details concerning sampling, digitizing or waveform capturing
• CPC Class Codes: G01R 23/02 Arrangements for measuring frequency, e.g. pulse repetition rate; Arrangements for measuring period of current or voltage
• CPC Class Codes: G01R 25/00 Arrangements for measuring phase angle between a voltage and a current or between voltages or currents
• CPC Class Codes: G01R 31/001 Measuring interference from external sources to, or emission from, the device under test, e.g. EMC, EMI, EMP or ESD testing measuring electromagnetic fields G01R29/08; circuits for generating HV pulses in dielectric strength testing G01R31/14
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: H02J 50/10 using inductive coupling
• CPC Class Codes: H02J 50/12 of the resonant type
• CPC Class Codes: H02J 50/60 responsive to the presence of foreign objects, e.g. detection of living beings
• CPC Class Codes: H02J 50/80 involving the exchange of data, concerning supply or distribution of electric power, between transmitting devices and receiving devices
• CPC Class Codes: H02J 50/90 involving detection or optimisation of position, e.g. alignment
• CPC Class Codes: H02J 7/007 Regulation of charging or discharging current or voltage
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 90/12 Electric charging stations
• CPC Class Codes: Y02T 90/14 Plug-in electric vehicles

Abstract

A method of detecting whether a receiver coil is near a transmit coil in a wireless power transfer system (WPTS), the method involving: applying a pseudo-random signal to the transmit coil; while the pseudo-random signal is being applied to the transmit coil, recording one or more signals produced within the WPTS in response to the applied pseudo-random signal; by using the one or more recorded signals, generating a dynamic system model for some aspect of the WPTS; and using the generated dynamic system model in combination with stored training data to determine whether an object having characteristics distinguishing the object as a receiver coil is near the transmit coil.

Claims

1. A method of detecting whether a receiver coil is near a transmit coil in a wireless power transfer system (WPTS), said method comprising:

applying a pseudo-random signal to the transmit coil;

while the pseudo-random signal is being applied to the transmit coil, recording one or more signals produced within the WPTS in response to the applied pseudo-random signal;

by using the one or more recorded signals, generating a dynamic system model for some aspect of the WPTS; and

using the generated dynamic system model in combination with stored training data to determine whether an object having characteristics distinguishing the object as a receiver coil is near the transmit coil.

2. The method of claim 1, further comprising, if the receiver coil is determined to be near the transmit coil, initiating a wireless power transfer through the transmit coil to the receiver coil.

3. The method of claim 1, wherein the pseudo-random signal is a pseudo-random voltage signal.

4. The method of claim 1, wherein the pseudo-random signal is sufficiently strong to stimulate nonlinearities in a receiver system connected to the receiver coil.

5. The method of claim 3, wherein the one or more signals includes a current signal of the transmit coil.

6. The method of claim 3, wherein the one or more signals includes a current signal and a voltage signal of the transmit coil.

7. The method of claim 1, wherein using the generated dynamic system model comprises comparing information contained in the generated dynamic system model to empirically-derived, stored information that is indicative of a nearby presence of a receiver coil.

8. The method of claim 1, wherein generating the dynamic system model comprises using system identification to fit a selected model to data derived from the one or more recorded signals.

9. The method of claim 1, wherein generating the dynamic system model comprises using nonlinear system identification to fit a selected model to the data derived from the one or more recorded signals.

10. The method of claim 9, wherein the selected model is a Wiener system.

11. The method of claim 9, wherein the selected model is a Hammerstein system.

12. The method of claim 9, wherein the selected model is a parallel cascade of structures blocks.

13. The method of claim 9, wherein the selected model is a Volterra series.

14. The method of claim 9, wherein the selected model is a parametric linear model.

15. The method of claim 9, wherein the selected model has a dynamic linear part and a static nonlinear part.

16. The method of claim 5, wherein the dynamic system model is an impedance function for the transmit coil.

17. The method of claim 6, wherein the dynamic system model is a transmitted power function for transmit coil.

18. The method of claim 1, wherein using the generated dynamic system model comprises decomposing the dynamic system model into basis functions to generate a set of basis function parameters.

19. The method of claim 18, wherein using the generated dynamic system model further comprises using the set of basis function parameters to determine whether a receiver coil is near the transmit coil.

20. The method of claim 1, wherein the pseudo-random signal is a selected one of a Gaussian White Noise signal and a Pseudo-Random Binary Sequence (PRBS).

21. The method of claim 9, wherein the generated dynamic system model comprises a time domain representation.

22. The method of claim 9, wherein the generated dynamic system model comprises a frequency domain representation.

23. The method of claim 1, wherein the stored training data is represented by a stored filter function and wherein using the generated dynamic system model in combination with stored training data comprises processing the generated dynamic system model to generate an output signal, wherein the output signal indicates whether an object having characteristics recognizable from the stored training data as a receiver coil is near the transmit coil and wherein processing the dynamic system model comprises applying the stored filter function.

24. The method of claim 23, wherein the one or more recorded signals includes a current signal of the transmit coil.

25. The method of claim 23, wherein the generated dynamic system model is the measured current signal.

26. The method of claim 23, wherein the filter function is a nonlinear filter function.

27. The method of claim 26, wherein the nonlinear filter function was derived from measurements made on a test system including a test transmit coil and a test receiver coil located at different distances of separation from each other.

28. The method of claim 23, further comprising, if a receiver coil is detected near the transmit coil, initiating a wireless power transfer through the transmit coil to the detected receiver coil.

29. A wireless power transfer system comprising:

a transmit coil;

a power transmitter circuit connected to the transmit coil;

a sensor circuit connected to the transmit coil; and

a controller for controlling the power transmitter circuit and the sensor circuit, wherein said controller includes a memory for storing training data and a processor system programmed to;

cause the power transmitter circuit to apply a pseudo-random signal to the transmit coil;

while the pseudo-random signal is being applied to the transmit coil, cause the sensor circuit to record one or more signals produced within the WPTS in response to the applied pseudo-random signal;

by using the one or more recorded signals, generate a dynamic system model for some aspect of the WPTS; and

use the generated dynamic system model in combination with the stored training data to determine whether an object having characteristics distinguishing the object as a receiver coil is near the transmit coil.

30. The wireless power transfer system of claim 29, wherein the one or more signals includes a current signal and a voltage signal of the transmit coil.

31. The wireless power transfer system of claim 29, wherein the stored training data is represented by a stored filter function and wherein the processor system is programmed to use the generated dynamic system model in combination with stored training data by processing the generated dynamic system model with the filter function to generate an output signal, wherein the output signal indicates whether an object having characteristics recognizable from the stored training data as a receiver coil is near the transmit coil.

32. The wireless power transfer system of claim 31, wherein the one or more recorded signals includes a current signal of the transmit coil.

33. The wireless power transfer system of claim 31, wherein the generated dynamic system model is the measured current signal.

34-56. -56. (canceled)