IP Library › Granted Patent US 12,358,379
Granted Patent B2
US 12,358,379 · App. 18/282,480 · Granted Jul 15, 2025

Vehicle mass and road grade based regenerative braking and anti-rollback

Inventors: Jaime Antonio Lugo-Castillo (Unionville, IN); Jack Schneider (Columbus, IN); Sashwat Mahapatra (Columbus, IN)
Assignee: Cummins Inc.
B60L15/2018G01G19/03B60L2240/12B60L2240/16B60L2240/642
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Quick Facts
Patent No.
US 12,358,379
App. No.
18/282,480
Granted
Jul 15, 2025
Kind
B2
Abstract

A method of controlling torque of an electric vehicle, including sensing a surface grade; determining an acceleration of the vehicle; determining an initial torque of the vehicle; estimating a weight of the vehicle based the surface grade, the acceleration, and the initial torque; converting the weight of the vehicle to a weight factor; and determining an output torque by applying the weight factor to the initial torque.

Claims (27)

1. A method of controlling torque of an electric vehicle, the method comprising:

sensing a surface grade;

determining an acceleration rate of the vehicle;

determining an initial torque of the vehicle;

estimating a weight of the vehicle based on the surface grade, the determined acceleration rate, and the initial torque;

converting the weight of the vehicle to a weight factor;

determining an output torque by applying the weight factor to the initial torque; and

determining whether the vehicle is in a regenerative braking state or an anti-rollback state,

wherein the weight factor is a regenerative weight factor in the regenerative braking state and an anti-rollback weight factor in the anti-rollback state.

2. The method of claim 1 , wherein the regenerative weight factor and the anti-rollback weight factor are different.

3. The method of claim 1 , further comprising receiving a mass-estimation logic disable signal, and responsive to the mass-estimation logic disable signal, setting the output torque to the initial torque.

4. The method of claim 1 , further comprising receiving a mass-estimation logic disable signal, and responsive to the mass-estimation logic disable signal, setting the weight factor to 1.0.

5. The method of claim 1 , further comprising filtering the acceleration and the initial torque before estimating the weight.

6. The method of claim 5 , wherein filtering comprises applying Kalman filters to the acceleration and the initial torque.

7. The method of claim 1 , further comprising sensing a speed of a vehicle, wherein determining the acceleration includes converting the speed to an acceleration value.

8. The method of claim 1 , further comprising sensing a speed of a vehicle, wherein determining the acceleration includes converting the speed to an acceleration value.

9. The method of claim 8 , wherein generating a vehicle weight estimation is further based on a physics-based model of the vehicle, the physics-based model comprising at least aerodynamics, inertia, rolling resistance, and input torque values related to the vehicle.

10. The method of claim 1 , wherein the gain factor is a positive, real number.

11. The method of claim 1 , wherein determining the output torque comprises multiplying the weight factor to the initial torque.

12. A driveline controller for an electric vehicle, comprising:

weight estimation logic structured to implement a torque control method as in claim 1 .

13. An electric vehicle comprising:

a road grade sensor;

a speed sensor;

a motor-generator; and

the driveline controller as in claim 12 , the driveline controller operable to cause the motor-generator to generate the output torque.

14. The electric vehicle of claim 13 , wherein the driveline controller further comprises a vehicle dynamics model, the vehicle dynamics model containing values associated with vehicle torque, direction, aerodynamics, inertia, rolling resistance, and frictional losses.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 27, 2023
From: LUGO-CASTILLO, JAIME ANTONIO; SCHNEIDER, JACK; MAHAPATRA, SASHWAT
To: CUMMINS INC.
Reel/Frame 065054/0313 →
Continuity (1)
Related Publication 20240042870A1 · Feb 8, 2024
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