APPARATUS, METHOD AND PROGRAM FOR VEHICLE MASS ESTIMATION

• US 20110218764A1
• Filed: 10/26/2010
• Published: 09/08/2011
• Est. Priority Date: 03/03/2010
• Status: Active Grant

• Current Assignee: Sumitomo Rubber Industries Limited
• Original Assignee: Sumitomo Rubber Industries Limited
• Inventors: FUJITA, Hajime, Wada, Mitsuhiro
• Granted Patent: US 8,554,511 B2
• Time in Patent Office: Days
• US Class Current: 702/175
• CPC Class Codes: G01G 19/086 wherein the vehicle mass is dynamically estimated

Abstract

A vehicle mass estimation apparatus for estimating the mass of a vehicle based on rotation information of tires attached to the vehicle. The apparatus includes a rotation speed information detection means for periodically detecting tire rotation speed information of the respective wheels of the vehicle; a rotation acceleration information calculation means for calculating tire rotation acceleration information based on the rotation speed information obtained by the rotation speed information detection means; a driving force calculation means for calculating a driving force of the vehicle based on axle shaft torque information of the vehicle; and a vehicle mass estimation means for estimating the mass of the vehicle as a regression coefficient when the rotation acceleration information and the driving force information are subjected to linear regression. The vehicle mass estimation means calculates, with regard to an error between driving force information calculated based on the estimated mass and the rotation acceleration information and the driving force information calculated by the driving force calculation means, a ratio between the dispersion of the error obtained one time before and an error at the current moment; and calculates an update adjustment parameter by adding a stabilization parameter to thus obtained ratio, and uses the calculated update adjustment parameter to calculate a Kalman gain so that the mass is sequentially estimated so as to reduce an update width of the regression coefficient when the error ratio is higher.

Claims

1. A vehicle mass estimation apparatus for estimating the mass of a vehicle based on rotation information of tires attached to the vehicle, comprising:

a rotation speed information detection means for periodically detecting tire rotation speed information of the respective wheels of the vehicle;

a rotation acceleration information calculation means for calculating tire rotation acceleration information based on the rotation speed information obtained by the rotation speed information detection means;

a driving force calculation means for calculating a driving force of the vehicle based on axle shaft torque information of the vehicle; and

a vehicle mass estimation means for estimating the mass of the vehicle as a regression coefficient when the rotation acceleration information and the driving force information are subjected to linear regression,

wherein the vehicle mass estimation means calculates, with regard to an error between driving force information calculated based on the estimated mass and the rotation acceleration information and the driving force information calculated by the driving force calculation means, a ratio between the dispersion of the error obtained one time before and an error at the current moment; and

wherein the vehicle mass estimation means calculates an update adjustment parameter by adding a stabilization parameter to thus obtained ratio, and uses the calculated update adjustment parameter to calculate a Kalman gain so that the mass is sequentially estimated so as to reduce an update width of the regression coefficient when the error ratio is higher.

2. A vehicle mass estimation method for estimating the mass of a vehicle based on rotation information of tires attached to the vehicle, comprising:

a rotation speed information detection step for periodically detecting tire rotation speed information of the respective wheels of the vehicle;

a rotation acceleration information calculation step for calculating tire rotation acceleration information based on the rotation speed information obtained in the rotation speed information detection step;

a driving force calculation step for calculating a driving force of the vehicle based on axle shaft torque information of the vehicle; and

a vehicle mass estimation step for estimating the mass of the vehicle as a regression coefficient when the rotation acceleration information and the driving force information are subjected to linear regression,

wherein the vehicle mass estimation step calculates, with regard to an error between driving force information calculated based on the estimated mass and the rotation acceleration information and the driving force information calculated in the driving force calculation step, a ratio between the dispersion of the error obtained one time before and an error at the current moment; and

wherein the vehicle mass estimation step calculates an update adjustment parameter by adding a stabilization parameter to thus obtained ratio, and uses the calculated update adjustment parameter to calculate a Kalman gain so that the mass is sequentially estimated so as to reduce an update width of the regression coefficient when the error ratio is higher.

3. A vehicle mass estimation program which causes, in order to estimate the mass of a vehicle based on rotation information of tires attached to the vehicle, a computer to function as:

a rotation acceleration information calculation means for calculating tire rotation acceleration information based on the rotation speed information obtained by a rotation speed information detection means for periodically detecting tire rotation speed information of the respective wheels of the vehicle;

a driving force calculation means for calculating a driving force of the vehicle based on axle shaft torque information of the vehicle; and

a vehicle mass estimation means for estimating the mass of the vehicle as a regression coefficient when the rotation acceleration information and the driving force information are subjected to linear regression,

wherein the vehicle mass estimation means calculates, with regard to an error between driving force information calculated based on the estimated mass and the rotation acceleration information and the driving force information calculated by the driving force calculation means, a ratio between the dispersion of the error obtained one time before and an error at the current moment; and

wherein the vehicle mass estimation means calculates an update adjustment parameter by adding a stabilization parameter to thus obtained ratio, and uses the calculated update adjustment parameter to calculate a Kalman gain so that the mass is sequentially estimated so as to reduce an update width of the regression coefficient when the error ratio is higher.