Method of characterizing a vehicle crash event based on shear waves in the vehicle frame

• US 20080259729A1
• Filed: 04/17/2007
• Published: 10/23/2008
• Est. Priority Date: 04/17/2007
• Status: Active Grant

• Current Assignee: Aptiv Technologies AG
• Original Assignee: Delphi Technologies, Inc. (BorgWarner Incorporated)
• Inventors: Griffin, Dennis P., Fultz, William W.
• Granted Patent: US 7,675,820 B2
• Time in Patent Office: Days
• US Class Current: 367/117
• CPC Class Codes: B60R 2021/0119 Plausibility check
• CPC Class Codes: B60R 21/0136 responsive to actual contact with an obstacle , e.g. to vehicle deformation, bumper displacement or bumper velocity relative to the vehicle monitoring crash strength in combination with passenger seat detection B60R21/01558

Abstract

A vehicle crash event is detected and characterized based on the transmission of acoustical shear waves through the vehicle frame. At least three, and preferably four or more, acoustical emission sensors longitudinally and laterally distributed on the vehicle frame produce acoustical signals that are processed to extract the shear wave energy due to impacts. Since shear waves are non-dispersive and travel through the vehicle frame at a known velocity, they can be detected in any part of the frame. The extracted shear wave signals are used not only to judge the severity of the impact, but also to characterize the type of crash and determine the direction of the impact based on when the shear wave is detected by each of the acoustical emission sensors.

Claims

1. A method of characterizing an impact to a vehicle, comprising the steps of:

sensing acoustic emission wave energy in a frame of the vehicle;

isolating shear wave components of the sensed acoustic emission wave energy; and

characterizing a transmission of the isolated shear wave components through the frame to determine a direction of the impact.

2. The method of claim 1, including the steps of:

determining a severity of the impact based on a magnitude of the isolated shear wave components.

3. The method of claim 1, including the step of:

sensing the acoustic emission wave energy at first, second and third distributed locations on the frame;

isolating the shear wave components of the sensed acoustic emission wave energy at each of the first, second and third locations;

characterizing the transmission of the isolated shear wave components through the frame by identifying at time-of-arrival of the shear wave components at the first, second and third locations; and

determining the direction of the impact based on the identified times-of-arrival.

4. The method of claim 3, including the step of:

evaluating the identified times-of-arrival for plausibility; and

issuing a diagnostic error report if the evaluation reveals that identified times-of-arrival are implausible.

5. The method of claim 3, including the steps of:

storing a table of shear wave times-of-arrival vs. impact direction; and

determining the impact direction by indexing the stored table based on the identified times-of-arrival.

6. The method of claim 3, where the first, second and third locations define a sensing plane that is substantially parallel to a road surface on which the vehicle is supported.

7. The method of claim 6, including the step of:

sensing the acoustic emission wave energy at a fourth location on the frame that is vertically displaced from the sensing plane defined by the first, second and third locations;

isolating the shear wave components of the sensed acoustic emission wave energy at the fourth location;

characterizing the transmission of the isolated shear wave components through the frame by identifying at time-of-arrival of the shear wave components at the first, second, third and fourth locations; and

determining the direction of the impact based on the identified times-of-arrival.

8. The method of claim 1, including the steps of:

performing a time-domain correlation of the isolated shear wave components with a library of stored shear wave signatures for different test crashes; and

if the correlation reveals a sufficiently close match between the isolated shear wave components and the stored shear wave signatures for a given test crash, classifying the impact based on a classification of the given test crash.

9. The method of claim 8, including the steps of:

identifying a set of test crashes characterized by impact directions similar to the determined direction of impact; and

performing the time-domain correlation of the isolated shear wave components with the stored shear wave signatures for the identified set of test crashes.

10. The method of claim 1, including the steps of:

sensing the acoustic emission wave energy with a plurality of piezoelectric acoustic emission sensors mounted on the frame; and

applying an electrical pulse to a selected piezoelectric acoustic emission sensor to create a test acoustic emission, and monitoring signals produced by the other piezoelectric acoustic emission sensors to diagnostically test such other sensors.

11. The method of claim 10, including the step of:

diagnostically evaluating said other piezoelectric acoustic emission sensors based on sensed times-of-arrival of the test acoustic emission.

12. The method of claim 11, including the step of:

auto-calibrating to compensate for sensor drift and changes in the frame based on deviations in the sensed times-of-arrival from calibrated norms.