Dynamic slip target traction control
Systems and methods to automatically detect and respond to driving on a deformable surface are provided. A system can determine, for a first time interval, a difference between an expected acceleration of a vehicle and an actual acceleration of the vehicle measured via one or more sensors of the vehicle. The system can detect, for the first time interval, a condition for the vehicle to increase a first slip target set for the vehicle. The system can increase the first slip target set for the vehicle to a second slip target responsive to the difference greater than or equal to a threshold and the detection of the condition.
1. A system, comprising:
one or more processors coupled with memory to:
determine, for a first time interval, a difference between an expected acceleration of a vehicle and an actual acceleration of the vehicle measured via one or more sensors of the vehicle;
detect, for the first time interval, a condition for the vehicle to increase a first slip target set for the vehicle;
increase the first slip target set for the vehicle to a second slip target responsive to the difference greater than or equal to a threshold and the detection of the condition; and
generate a control signal to cause a motor to increase a torque applied during a second time interval subsequent to the first time interval, responsive to the increase from the first slip target to the second slip target.
2. The system of claim 1 , comprising:
the one or more processors to determine, via a model, the expected acceleration for the vehicle responsive to an amount of force applied via the motor of the vehicle.
3. The system of claim 1 , comprising the one or more processors to:
detect, during a third time interval, that the condition for the vehicle is not present and a speed of the vehicle is greater than a second threshold;
update a model via an adaptive learning technique responsive to the detection that the condition for the vehicle is not present and the speed of the vehicle is greater than the second threshold; and
determine the expected acceleration for the vehicle via the model updated via the adaptive learning technique.
4. The system of claim 1 , comprising the one or more processors to:
receive data via the one or more sensors of the vehicle, the data based on at least one of the actual acceleration of the vehicle, an angular acceleration of a wheel of the vehicle, the torque applied by the motor of the vehicle, a speed of the vehicle, a steering angle of the vehicle, or a yaw rate of the vehicle; and
detect the condition based on one or more comparisons of the data with one or more thresholds.
5. The system of claim 1 , comprising:
the one or more processors to detect the condition for the vehicle based on a traction control system of the vehicle being active.
6. The system of claim 1 , comprising:
the one or more processors to detect the condition for the vehicle based on a cross-axle torque being less than a second threshold.
7. The system of claim 1 , comprising:
the one or more processors to detect the condition for the vehicle based on:
a traction control system of the vehicle actively engaged to increase traction for the vehicle; and
a cross-axle torque being less than a second threshold,
wherein the condition corresponds to traversal by the vehicle on a deformable surface.
8. The system of claim 1 , comprising:
the one or more processors to detect the condition for the vehicle based on:
a traction control system of the vehicle actively engaged to increase traction for the vehicle;
the torque of the motor of the vehicle exceeding a second threshold; and
a wheel slip error below a third threshold.
9. The system of claim 1 , comprising:
the one or more processors to detect the condition for the vehicle based on:
the actual acceleration of the vehicle greater than a second threshold;
a wheel slip error within a range;
a traction control system of the vehicle actively engaged to increase traction for the vehicle;
the torque of the motor of the vehicle exceeding a third threshold; and
a cross-axle torque being less than a fourth threshold.
10. The system of claim 1 , comprising the one or more processors to:
detect, for a third time interval subsequent to the first time interval and the increase of the first slip target to the second slip target, the condition is present;
determine, for the third time interval, a second difference between a second expected acceleration of the vehicle and a second actual acceleration of the vehicle measured; and
determine not to increase the second slip target based on the second difference less than the threshold.
11. The system of claim 1 , comprising the one or more processors to:
detect, for a third time interval subsequent to the first time interval and the increase of the first slip target to the second slip target, the condition is present;
determine, for the third time interval, a second difference between a second expected acceleration of the vehicle and a second actual acceleration of the vehicle measured; and
determine to increase the second slip target to a third slip target based on the second difference greater than or equal to the threshold.
12. The system of claim 1 , wherein:
a difference between the second slip target and the first slip target is set based on a default slip increment.
13. A method, comprising:
determining, by one or more processors coupled with memory of a vehicle, for a first time interval, a difference between an expected acceleration of the vehicle and an actual acceleration of the vehicle measured via one or more sensors of the vehicle;
detecting, by the one or more processors for the first time interval, a condition for the vehicle to increase a first slip target set for the vehicle;
increasing, by the one or more processors, the first slip target set for the vehicle to a second slip target responsive to the difference greater than or equal to a threshold and the detection of the condition; and
generating a control signal to cause a motor to increase a torque applied during a second time interval subsequent to the first time interval, responsive to the increase from the first slip target to the second slip target.
14. The method of claim 13 , comprising:
determining, by the one or more processors via a model, the expected acceleration for the vehicle responsive to an amount of force applied via the motor of the vehicle.
15. The method of claim 13 , comprising:
detecting, by the one or more processors during a third time interval, that the condition for the vehicle is not present and a speed of the vehicle is greater than a second threshold;
updating, by the one or more processors, a model via an adaptive learning technique responsive to the detection that the condition for the vehicle is not present and the speed of the vehicle is greater than the second threshold; and
determining, by the one or more processors, the expected acceleration for the vehicle via the model updated via the adaptive learning technique.
16. The method of claim 13 , comprising:
receiving, by the one or more processors, data via the one or more sensors of the vehicle, the data based on at least one of the actual acceleration of the vehicle, an angular acceleration of a wheel of the vehicle, the torque applied by the motor of the vehicle, a speed of the vehicle, a steering angle of the vehicle, or a yaw rate of the vehicle; and
detecting, by the one or more processors, the condition based on one or more comparisons of the data with one or more thresholds.
17. The method of claim 13 , comprising:
detecting, by the one or more processors, the condition for the vehicle based on a traction control system of the vehicle being active.
18. The method of claim 13 , comprising:
detecting, by the one or more processors, the condition for the vehicle based on:
the actual acceleration of the vehicle greater than a second threshold;
a wheel slip error within a range;
a traction control system of the vehicle actively engaged to increase traction for the vehicle;
the torque of the motor of the vehicle exceeding a third threshold; and
a cross-axle torque being less than a fourth threshold.
19. A vehicle, comprising:
a plurality of wheels;
one or more motors configured to rotate the plurality of wheels; and
one or more processors coupled with memory to:
determine, for a first time interval, a difference between an expected acceleration of the vehicle and an actual acceleration of the vehicle measured via one or more sensors of the vehicle;
detect, for the first time interval, a condition for the vehicle to increase a first slip target set for the vehicle;
increase the first slip target set for the vehicle to a second slip target responsive to the difference greater than or equal to a threshold and the detection of the condition; and
generate a control signal to cause a motor to increase a torque applied during a second time interval subsequent to the first time interval, responsive to the increase from the first slip target to the second slip target.
20. The vehicle of claim 19 , comprising:
the one or more processors to determine, via a model, the expected acceleration for the vehicle responsive to an amount of force applied via the motor of the vehicle.