# US 11,027,776 B2 · System and method for adapting parameters used in target slip estimation

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- Number: US 11,027,776 B2
- Document ID: US11027776B2
- Status: Granted
- Kind: B2
- Application number: 16/508,754
- Filed: 2019-07-11
- Published: 2021-01-14
- Granted: 2021-06-08
- Earliest claimed: 2019-07-11
- Assignees: GM Global Technology Operations LLC
- Applicants: GM Global Technology Operations LLC
- Inventors: Joonho Lee; Qingrong Zhao; Bakhtiar B. Litkouhi
- Web page: https://patentgrep.com/patent/US11027776B2

## CPC

- B62D 6/006: {using a measured or estimated road friction coefficient}
- B60W 30/18172: {Preventing, or responsive to skidding of wheels}
- B60W 40/064: Degree of grip
- B60W 40/068: Road friction coefficient
- G06F 16/903: Querying (for retrieval from the web G06F16/953)
- B62D: MOTOR VEHICLES; TRAILERS (steering, or guiding on a desired track, of agricultural machines or implements A01B69/00; wheels, castors, axles, increasing wheel adhesion B60B; vehicle tyres, tyre inflation or tyre changing B60C; connections between vehicles of a train or the like B60D; vehicles for use on rail and road, amphibious or convertible vehicles B60F; suspension arrangements B60G; heating, cooling, ventilating or other air treating devices B60H; windows, windscreens, non-fixed roofs, doors or similar devices, protective coverings for vehicles not in use B60J; propulsion plant arrangements, auxiliary drives, transmissions, controls, instrumentation or dashboards B60K; electric equipment or propulsion of electrically-propelled vehicles B60L; power supply for electrically-propelled vehicles B60M; passenger accommodation not otherwise provided for B60N; adaptations for load transportation or to carry special loads or objects B60P; arrangement of signalling or lighting devices, the mounting or supporting thereof or circuits therefor, for vehicles in general B60Q; vehicles, vehicle fittings or vehicle parts not otherwise provided for B60R; servicing, cleaning, repairing, supporting, lifting, or manoeuvring, not otherwise provided for, B60S; brake arrangements, brake control systems or parts thereof B60T; air-cushion vehicles B60V; motor-cycles, accessories therefor B62J, B62K; testing of vehicles G01M)
- B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

Systems and methods are provided for generating adapted tuning parameters for target slip estimation, the parameters being adapted to real-time road surface conditions. The method includes, receiving, from a road surface detection module, a road surface condition, Sn, from among N road surface conditions S, range of friction, mu, and a confidence level, Ci. The method receives sensor system data from a sensor system, and determines, as a function of Sn, range of mu, and Ci, initial estimator values including an estimated initial frictional force {circumflex over (Θ)}(0), an initial gain, P0, and an initial projected range of signal bounds, (Pu) and (Pl). The method tunes (i.e., adapts) the initial estimator values to generate therefrom adapted tuning parameters based on received inputs. The method outputs adapted tuning parameters.

## Claims

### Claim 1

A system for generating adapted tuning parameters for use by a target slip estimator module in a vehicle, the system comprising:
a road surface detection module providing a road surface condition, Sn, a range of friction, mu, for the Sn, and a confidence level, Ci, of the Sn, Ci having a value between 0 and 1;
a sensor system providing sensor system data; and
a controller module in operative communication with the road surface detection module and the sensor system, and programmed to:
receive the sensor system data;
determine an initial gain P0 as a function of signal and noise in the sensor system data;
receive the Sn, the range of mu, and the Ci;
generate an adapted gain, by tuning P0 as a function of the Ci;
determine, as a function of Sn, range of mu, and Ci, initial estimator values including an estimated initial frictional force, {circumflex over (Θ)}(0), and an initial projected range of signal bounds, (Pu and Pl);
generate an adapted projection range of signal bounds, by constraining Pu and Pl by the Sn and range of mu;
generate an adapted range of the estimated initial frictional force, {circumflex over (Θ)}(0), by widening the range of the estimated initial frictional force, {circumflex over (Θ)}(0), when the confidence level in the road surface condition is lower than a preprogrammed confidence threshold Ct; and
output the adapted gain, adapted projection range of signal bounds, and adapted range of frictional force, when the confidence level in the road surface condition is lower than the preprogrammed confidence threshold Ct.

### Claim 2 (depends on 1)

The system of claim 1, wherein the controller module is further programmed to:
compare Ci to the preprogrammed confidence threshold Ct;
determine that Ci is high when it is >=Ct;
determine that Ci is low when it is <Ct; and
output the adapted gain, estimated initial projection range of signal bounds, and estimated initial frictional force, when the confidence level in the road surface condition is higher than the preprogrammed confidence threshold Ct.

### Claim 3 (depends on 2)

The system of claim 2, wherein the controller module is further programmed to determine, as a function of Sn, range of mu, and Ci, an initial forgetting factor, β0, for a recursive least squares estimation method.

### Claim 4 (depends on 3)

The system of claim 3, wherein the controller module is further programmed to generate an adapted parameter β by adapting β0 as a function of Ci.

### Claim 5 (depends on 4)

The system of claim 4, wherein Sn is one of N road conditions, S, further comprising:
a database for storing data comprising, for each combination of Sn and Ci: respective initial estimator values; and
wherein the controller module determines the {circumflex over (Θ)}(0), β0, and Pu, and Pl by referencing the data using Sn and Ci.

### Claim 6 (depends on 5)

The system of claim 5, wherein the controller module generates adaptive parameter β by widening β0, as a function of Ci when Ci is low.

### Claim 7 (depends on 6)

The system of claim 6, wherein the controller module is further programmed to widen the estimated initial frictional force, {circumflex over (Θ)}(0), as a function of Ci when Ci is low.

### Claim 8 (depends on 7)

The system of claim 7, wherein the controller module is further programmed to:
widening the range of the estimated initial frictional force, {circumflex over (Θ)}(0), includes
generating, as a function of time, a lower widened estimated frictional force value {circumflex over (Θ)}l(t) and an upper widened estimated frictional force value {circumflex over (Θ)}u(t);
adding {circumflex over (Θ)}l(t) to Pl to widen the initial projected range of signal bounds; and
adding {circumflex over (Θ)}u(t) to Pu to widen the initial projected range of signal bounds.

### Claim 9

A method for generating adapted tuning parameters for a target slip estimator module for a vehicle, comprising:
at a controller module,
receiving, from a road surface detection module, a road surface condition, Sn, range of friction, mu, for the road surface Sn, and a confidence level, Ci for the Sn, the Ci being between 0 and 1;
receiving sensor system data from a sensor system;
determining an initial gain P0 as a function of signal and noise in the sensor system data;
generating an adapted gain, by tuning P0 as a function of the Ci;
determining, as a function of Sn, range of mu, and Ci, initial estimator values including an estimated initial frictional force, {circumflex over (Θ)}(0), and an initial projected range of signal bounds, (Pu and Pl);
generating an adapted projection range of signal bounds, by constraining Pu and Pl by the Sn and range of mu;
generating an adapted range of the estimated initial frictional force, {circumflex over (Θ)}(0), by widening the range of the estimated initial frictional force, {circumflex over (Θ)}(0), when the confidence level in the road surface condition is lower than a preprogrammed confidence threshold Ct; and
outputting the adapted gain, adapted projection range of signal bounds, and adapted range of frictional force, when the confidence level in the road surface condition is lower than the preprogrammed confidence threshold Ct.

### Claim 10 (depends on 9)

The method of claim 9, wherein Sn is one of N road conditions, S, and further comprising:
storing, in a database, previously developed data comprising, for each combination of Sn and Ci: respective initial estimator values; and
wherein determining the {circumflex over (Θ)}(0), and Pu and Pl comprises referencing the previously developed data using Sn and Ci.

### Claim 11 (depends on 10)

The method of claim 10, further comprising:
comparing Ci to the preprogrammed confidence threshold Ct;
determining that Ci is high when it is >=Ct;
determining that Ci is low when it is <Ct; and
outputting the adapted gain, estimated initial projection range of signal bounds, and estimated initial frictional force, when the confidence level in the road surface condition is higher than the preprogrammed confidence threshold Ct.

### Claim 12 (depends on 11)

The method of claim 11, further comprising: when the Ci is low,
determining, as a function of time, a widened estimated frictional force value {circumflex over (Θ)}l(t) and a widened estimated frictional force value {circumflex over (Θ)}u(t);
adding {circumflex over (Θ)}l(t) to Pl to widen the initial projected range of signal bounds; and
adding {circumflex over (Θ)}u(t) to Pu to widen the initial projected range of signal bounds.

### Claim 13 (depends on 11)

The method of claim 11, wherein the least squares estimation method employed by the target slip estimator module is recursive least squares, and further comprising:
determining an initial forgetting factor, β0; and
generating an adapted tuning parameter, β, by widening β0, as a function of Ci.

### Claim 14 (depends on 10)

The method of claim 10, further comprising determining the β0 by referencing the data using Sn and Ci.

### Claim 15

A vehicle, comprising:
a road surface detection module configured to provide a road surface condition, Sn, a range of friction, mu, for the Sn, and a confidence level, Ci, of the Sn, Ci having a value between 0 and 1;
a sensor system configured to provide sensor system data; and
a controller module in operative communication with the road surface detection module and the sensor system, and programmed to:
receive the sensor system data;
determine an initial gain P0 as a function of signal and noise in the sensor system data;
receive the Sn, the range of mu, and the Ci;
generate an adapted gain, by tuning P0 as a function of the Ci;
determine, as a function of Sn, range of mu, and Ci, initial estimator values including an estimated initial frictional force, {circumflex over (Θ)}(0), and an initial projected range of signal bounds, (Pu and Pl);
generate an adapted projection range of signal bounds, by constraining Pu and Pl by the Sn and range of mu;
generate an adapted range of the estimated initial frictional force, {circumflex over (Θ)}(0) la widening the range of the estimated initial frictional force, {circumflex over (Θ)}(0), when the confidence level in the road surface condition is lower than a preprogrammed confidence threshold Ct; and
output the adapted gain, adapted projection range of signal bounds, and adapted range of frictional force when the confidence level in the road surface condition is lower than the preprogrammed confidence threshold Ct.

### Claim 16 (depends on 15)

The vehicle of claim 15, wherein the controller module is further programmed to:
compare Ci to the preprogrammed confidence threshold Ct;
determine that Ci is high when it is >=Ct;
determine that Ci is low when it is <Ct; and
output the adapted gain, estimated initial projection range of signal bounds, and estimated initial frictional force, when the confidence level in the road surface condition is higher than the preprogrammed confidence threshold Ct.

### Claim 17 (depends on 16)

The vehicle of claim 16, wherein Sn is one of N road conditions, S, and further comprising:
a database for storing previously developed data comprising, for each combination of Sn, and Ci: respective initial estimator values; and
wherein the controller module is further programmed to determine the {circumflex over (Θ)}(0), and Pu and Pl by referencing the previously developed data using Sn and Ci.

### Claim 18 (depends on 17)

The vehicle of claim 17, wherein the controller module is further programmed to:
determine, as a function of Sn, range of mu, and Ci, an initial forgetting factor, β0; and
generate an adapted tuning parameter, β, by widening β0, when Ci is low.

### Claim 19 (depends on 18)

The vehicle of claim 18, wherein the controller module is further programmed to determine the β0 by referencing the data in the database using Sn and Ci.