Method for detecting damage to an outer shell of a vehicle

Patent metadata

Field	Value
Publication number	US-12515599-B2
Application number	US-202218681854-A
Country	US
Kind code	B2
Filing date	Aug 5, 2022
Priority date	Aug 24, 2021
Publication date	Jan 6, 2026
Grant date	Jan 6, 2026

Abstract

A method for detecting damage to an outer shell of a vehicle. The vehicle is of a specific type with specific vehicle data. Damage can be classified into at least two groups. Damage of a first group has a greater severity of the damage than damage of a second group. An acceleration of the vehicle is ascertained and/or a rotation rate of the vehicle is ascertained. Damage of the first group is ascertained if the acceleration of the vehicle exceeds a threshold value of the acceleration and/or if the rotation rate of the vehicle exceeds a threshold value of the rotation rate. The acceleration and/or the rotation rate are compared to acceleration values and/or rotation rate values learned for the specific vehicle type. Damage of the second group is ascertained if damage is detected as a function of the comparison to the learned values.

First claim

The invention claimed is:

1 . A method for detecting damage to an outer shell of a vehicle, wherein the vehicle is of a specific type with specific vehicle data, the method comprising the following steps:
classifying damage to the outer shell of the vehicle into at least two groups, wherein damage of a first group of the groups has a greater severity of damage than damage of a second group of the groups; ascertaining: (i) an acceleration of the vehicle using an acceleration sensor and/or (ii) a rotation rate of the vehicle using a rotation rate sensor; wherein damage of the first group is ascertained when the acceleration of the vehicle exceeds a threshold value of the acceleration and/or when the rotation rate of the vehicle exceeds a threshold value of the rotation rate, and comparing the acceleration and/or the rotation rate to acceleration values learned for a specific vehicle type of the vehicle and/or rotation rate values learned for the specific vehicle type, wherein damage of the second group is ascertained when damage is detected as a function of the comparison to the learned values, wherein the outer shell of the vehicle is divided into at least nine different zones, and wherein a position of the damage to the vehicle in one or more of the nine areas is detected as a function of the comparison to the acceleration values learned for a specific vehicle type of the vehicle and/or the rotation rate values learned for the specific vehicle type.

2 . The method according to claim 1 , wherein the acceleration values learned for the specific vehicle type and/or the rotation rate values learned for the specific vehicle type are learned using machine learning of already detected damages of the specific vehicle type.

3 . The method according to claim 1 , wherein damage of a first group requires repair of the damage.

4 . The method according to claim 1 , wherein the first threshold value of the acceleration is a value of 2 g to 3 g.

5 . The method according to claim 1 , wherein the specific vehicle data are data of a vehicle geometry and/or an axle spacing and/or a model and/or a body type and/or a weight of the vehicle.

6 . The method according to claim 1 , wherein the acceleration and/or the rotation rate are compared to the acceleration values learned for the specific vehicle type and/or the rotation rate values learned for the specific vehicle type, (i) when the acceleration of the vehicle exceeds a second threshold value of the acceleration and falls below a first threshold value of the acceleration and/or (ii) when the rotation rate of the vehicle exceeds a second threshold value of the rotation rate and falls below a first threshold value of the rotation rate.

7 . The method according to claim 1 , wherein a position of the damage to the vehicle is detected as a function of the comparison to the acceleration values learned for a specific vehicle type of the vehicle and/or the rotation rate values learned for the specific vehicle type.

8 . The method according to claim 1 , wherein a report is output when damage to the outer shell of the vehicle is detected.

9 . A device configured to detect damage to an outer shell of a vehicle, wherein the vehicle is of a specific type with specific vehicle data, the device being configured to:
classify damage to the outer shell of the vehicle into at least two groups, wherein damage of a first group of the groups has a greater severity of damage than damage of a second group of the groups; ascertain: (i) an acceleration of the vehicle using an acceleration sensor and/or (ii) a rotation rate of the vehicle using a rotation rate sensor; wherein damage of the first group is ascertained when the acceleration of the vehicle exceeds a threshold value of the acceleration and/or when the rotation rate of the vehicle exceeds a threshold value of the rotation rate, and compare the acceleration and/or the rotation rate to acceleration values learned for a specific vehicle type of the vehicle and/or rotation rate values learned for the specific vehicle type, wherein damage of the second group is ascertained when damage is detected as a function of the comparison to the learned values, wherein the outer shell of the vehicle is divided into at least nine different zones, and wherein a position of the damage to the vehicle in one or more of the nine areas is detected as a function of the comparison to the acceleration values learned for a specific vehicle type of the vehicle and/or the rotation rate values learned for the specific vehicle type.

10 . The device according to claim 9 , wherein the device includes: (i) the acceleration sensor configured to ascertain the acceleration of the vehicle, and/or (ii) the rotation rate sensor configured to ascertain the rotation rate of the vehicle.

Assignees

• Bosch Gmbh Robert

Inventors

• Klein Martin
• Koenig Simon
• Fischer Yannick
• Heyer Klaus

Classifications

• B60Y2400/304

  Acceleration sensors · CPC title

• G06N20/00

  Machine learning · CPC title

• G07C5/0808

  Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005) · CPC title

• G07C5/085

  using electronic data carriers · CPC title

• B60R16/0234 Primary

  related to maintenance or repairing of vehicles · CPC title