Method to estimate the time to end of a laundry-drying cycle and laundry drying machine to carry out said method

Patent metadata

Field	Value
Publication number	US-2025066987-A1
Application number	US-202118721583-A
Country	US
Kind code	A1
Filing date	Dec 23, 2021
Priority date	Dec 23, 2021
Publication date	Feb 27, 2025
Grant date	—

Abstract

A method to estimate the time to end ({circumflex over (t)}f,n) of a laundry-drying cycle (DC(n)) performed by a laundry drying machine. The method comprises the following steps: defining a time to end learning function (); during a drying cycle (DC(n)), collecting cycle parameters/signals (K(n), Sraw(n)); determining informative features (I(n)) based on the collected cycle parameters/signals (K(n), Sraw(n)); during the execution of the drying cycle (DC(n)), implementing the time to end learning function () based on the determined informative features (I(n)) to estimate the time to end ({circumflex over (t)}f,n) of the current drying cycle (DC(n)); at the end of the current drying cycle (DC(n)), receiving a cycle feedback indicative of the actual duration (tf,n) of the executed drying cycle (DC(n)); adapting the time to end learning function () based on the cycle feedback indicative of the actual duration (tf,n) in order to determine an adapted time to end learning function (); during the next drying cycle (DC(n+1)), implementing the adapted time to end learning function (); to cause the data processing module to estimate the time to end ({circumflex over (t)}f,n) of the next drying cycle (DC(n+1)).

First claim

1 .- 20 . (canceled)

21 . A method to estimate the time to end ({circumflex over (t)} f,n ) of a laundry-drying cycle (DC(n)) performed by a laundry drying machine, wherein the laundry drying machine comprises:
an outer casing; a rotatable drum arranged inside the outer casing and configured to receive a laundry-load to be dried; an electric motor that rotates the laundry drum based on a laundry-drying cycle (DC(n)); drying means for drying the laundry-load in the drum based on the drying cycle (DC(n)); and an electronic control system comprising a data processing module and a sensor system configured to provide cycle parameters (K(n)) and signals (S raw (n)) indicative of at least the moisture of the laundry-load, wherein the method comprises the steps of:
a) defining a time to end learning function ( );
b) during a drying cycle (DC(n)), collecting cycle parameters (K(n)) and signals (S raw (n));
c) determining informative features (I(n)) based on the collected cycle parameters and signals (K(n), S raw (n));
d) during the execution of the in cycle (DC(n)), implementing the time to end learning function ( ) by the data processing module based on the determined informative features (I(n)) to cause the data processing module to estimate the time to end ({circumflex over (t)} f,n ) of the current drying cycle (DC(n));
e) at the end of the drying cycle (DC(n)), receiving a cycle feedback indicative of the actual duration (t f,n ) of the executed drying cycle (DC(n));
f) adapting the time to end learning function ( ) by the data processing module based on the cycle feedback indicative of the actual duration (t f,n ) in order to determine an adapted time to end learning function ( ); and
g) during the next drying cycle (DC(n+1)), implementing the adapted time to end learning function ( ) by the data processing module to cause the data processing module ( 16 b )( 56 b ) to estimate the time to end ({circumflex over (t)} f,n ) of the next drying cycle (DC(n+1)).

22 . The method of claim 21 , wherein:
the sensor system is configured to provide load moisture signals (s t ) indicative of the moisture of the laundry load, and/or drum motor torque signals (m t ) indicative of the torque provided by the electric motor, the informative features (I(n)) comprise:
the mean (μ s,n ) of the load moisture signals in a predefined interval of the drying cycle (DC(n)), the variance (σ s,n ) of the moisture sensor signals in a predefined interval of the drying cycle (DC(n)); and
the mean of the electrical torque signals (μ m,n ) in a predefined interval of the drying cycle (DC(n)).

23 . The method of claim 22 , wherein:
the time to end learning function ( (n)) used to estimate the time to end ({circumflex over (t)} f,n ) of the current drying cycle (DC(n)) is based on the linear mathematical system

t
ˆ

f
,
n

=

M

TTE

,
n

(

μ

s
,
n

,

σ

s
,
n

,

μ

m
,
n

)

=

α

0
,
n

+

α

1
,
n

⁢

μ

s
,
n

+

α

2
,
n

⁢

σ

s
,
n

+

α

3
,
n

⁢

μ

m
,
n

wherein {circumflex over (t)} f,n is the estimated time to end of the current drying cycle, α i,n are coefficients of the linear mathematical model/function, μ s,n is the mean of the load moisture sensor signal, σ s,n is the variance of the moisture sensor signals and μ m,n is the mean of the motor torque signals.

24 . The method of claim 23 , wherein A n =[α 0,n α 1,n α 2,n α 3,n ] T is a vector of parameters minimizing the sum of the squares of the residuals of the mathematical matrix

[

1

μ

s
,
1

σ

s
,
1

μ

m
,
1

1

μ

Assignees

• Electrolux Appliances AB

Inventors

• Pattarello Giorgio

Classifications

• D06F2105/56

  Remaining operation time; Remaining operational cycles · CPC title

• D06F34/18

  Condition of the laundry, e.g. nature or weight · CPC title

• D06F34/05

  for wireless communication between components, e.g. for remote monitoring or control · CPC title

• D06F2103/08

  Humidity · CPC title

• G06N3/09

  Supervised learning · CPC title