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US 12,654,659 B2Granted
Rough road detection for vehicles
AssigneeGM Global Technology Operations LLC
InventorsIan Betz, Emilio Olay
Life of this patent
Estimating the term…
Abstract
Methods and systems are provided that include wheel speed sensors of a vehicle that are configured to obtain wheel speed sensor data as to a speed of wheels of the vehicle; and a processor that is coupled to the wheel speed sensors and that is configured to at least facilitate determining a variability of the wheel speed sensor data; and determining a measure of roughness of a path on which the vehicle is operating, based on the variability.
Claims13
A method comprising:
- obtaining, via one or more wheel speed sensors of a vehicle, wheel speed sensor data as to a speed of wheels of the vehicle;
- determining, via a processor of the vehicle, a variability of the wheel speed sensor data;
- and
- determining, via the processor, a measure of roughness of a path on which the vehicle is operating, based on the variability;
- wherein:
- the measure of roughness is determined by the processor based on a rolling average of the variability of the wheel speed sensor data and also based on a rolling variance of the wheel speed sensor data;
- the rolling average is calculated by the processor in accordance with the following equation:
- Xn=Xn-1+(Xn−Xn-1)/n, in “Xn” represents wheel speed at a current time, Xn represents a current rolling average at the current time, Xn-1 represents a previous rolling average, and “n” represents a number of samples in an average window;
- and
- the rolling variance is calculated by the processor in accordance with the following equation:
- σ2n=σ2n-1+[(Xn−Xn-1)−σ2n-1]/n, in which σ2n represents a current variance, σ2n-1 represents a previous variance, and Xn represents a current wheel noise sample.
8 more elements
A system comprising:
- one or more wheel speed sensors of a vehicle that are configured to obtain wheel speed sensor data as to a speed of wheels of the vehicle;
- and
- a processor that is coupled to the one or more wheel speed sensors, the processor configured to at least facilitate:
- determining a variability of the wheel speed sensor data;
- and
- determining a measure of roughness of a path on which the vehicle is operating, based on the variability;
- wherein the processor is further configured to at least facilitate:
- determining the measure of roughness based on a rolling average of the variability of the wheel speed sensor data and also based on a rolling variance of the wheel speed sensor data;
- calculating the rolling average in accordance with the following equation:
- Xn=Xn-1+(Xn−Xn-1)/n, in “Xn” represents wheel speed at a current time, Xn represents current rolling average at the current time, Xn-1 represents a previous rolling average, and “n” represents a number of samples in an average window;
- and
- calculating the rolling variance of an average of the wheel speed sensor data in accordance with the following equation:
- σ2n=σ2n-1+[(Xn−Xn-1)−σ2n-1]/n, in which on represents a current variance, σ2n-1 represents a previous variance, and Xn represents a current wheel noise sample.
10 more elements
A vehicle comprising:
- a body;
- a drive system configured to move the body;
- a braking system;
- one or more wheel speed sensors that are configured to obtain wheel speed sensor data as to a speed of wheels of the vehicle;
- and
- a processor that is coupled to the one or more wheel speed sensors and to the braking system, the processor configured to at least facilitate:
- determining a variability of the wheel speed sensor data;
- determining a measure of roughness of a path on which the vehicle is operating, based on the variability, including by based on a rolling average of the variability of the wheel speed sensor data;
- a rolling variance of the wheel speed sensor data;
- and corner detection and rejection of the wheel speed sensor data;
- and
- controlling braking of the vehicle based on the measure of roughness, in accordance with instructions provided by the processor that are implemented by the braking system;
- wherein the processor is further configured to at least facilitate:
- calculating the rolling average in accordance with the following equation:
- Xn=Xn-1+(Xn−Xn-1)/n, in “Xn” represents wheel speed at a current time, Xn represents a current rolling average at the current time, Xn-1 represents a previous rolling average, and “n” represents a number of samples in an average window;
- calculating the rolling variance of an average of the wheel speed sensor data in accordance with the following equation:
- σ2n=σ2n-1+[(Xn−Xn-1)−σ2n-1]/n, in which σ2n represents a current variance, σ2n-1 represents a previous variance, and Xn represents a current wheel noise sample;
- binning the measure of roughness for the vehicle into one of the following categories:
- (i) smooth, if the variability is less than a first predetermined threshold;
- (ii) low, if the variability is greater than the first predetermined threshold and less than a second predetermined threshold;
- (iii) mid, if the variability is greater than the second predetermined threshold and less than a third predetermined threshold;
- (iv) high, if the variability is greater than the third predetermined threshold and less than a fourth predetermined threshold;
- and
- (v) extreme, if the variability is greater than the fourth predetermined threshold;
- and
- adjusting a braking threshold for the braking system of the vehicle, in accordance with instructions providing by the processor to the braking system, based on the binning.
23 more elements
Dependencies are inferred from the claim text.