Method to determine an end of cycle condition of a laundry-drying cycle and laundry drying machine to carry out said method

A method to determine an end of cycle condition of a laundry-drying cycle (DC(n)) performed by a laundry drying machine comprising (1) a rotatable drum arranged inside an outer casing and configured to receive a laundry load to be dried, (2) an electric motor that rotates the rotatable drum based on DC(n), (3) a drying device for drying the laundry load in the rotatable drum based on DC(n), and (4) an electronic control system comprising a processing module and a sensor system configured to provide cycle parameters (K(n)) and signals (Sraw(n)) indicative of at least the moisture of the laundry load, the method comprising:

• a) defining an end of cycle learning function (EOC,n);
• b) collecting K(n) and Sraw(n) during DC(n);
• c) during DC(n), implementing EOC(n) based on the collected K(n) and Sraw(n) to cause the processing module to estimate a remaining moisture content of the laundry-load (t,n);
• d) determining an end of cycle condition based on t,n;
• e) at the end of DC(n), receiving a user feedback indicative of the satisfaction of the user about dryness of the laundry-load (fRMC,n);
• f) using the processing module, adapting EOC(n) based on fRMC,n in order to determine an adapted end of cycle learning function (EOC,n+1);
• g) during a next drying cycle (DC(n+1)), implementing EOC,n+1, based on collected cycle parameters (K(n+1) and signals (Sraw(n+1)) to cause the processing module to estimate a remaining moisture content (t,n+1) of the laundry load of the next drying cycle (DC(n+1)).

A method to determine an end of cycle condition of a laundry-drying cycle (DC(n)) performed by a laundry drying machine comprising (1) a rotatable drum arranged inside an outer casing and configured to receive a laundry load to be dried, (2) an electric motor that rotates the rotatable drum based on DC(n), (3) a drying device for drying the laundry load in the rotatable drum based on DC(n), and (4) an electronic control system comprising a processing module and a sensor system configured to provide cycle parameters (K(n)) and signals (Sraw(n)) indicative of at least the moisture of the laundry load, the method comprising:

• a) defining an end of cycle learning function (EOC,n);
• b) collecting K(n) and Sraw(n) during DC(n);
• c) during DC(n), implementing EOC(n) based on the collected K(n) and Sraw(n) to cause the processing module to estimate a remaining moisture content of the laundry-load (t,n);
• d) determining an end of cycle condition based on t,n and communicating the end of cycle condition to a user communication device;
• e) at the end of DC(n), receiving a user feedback indicative of the satisfaction of the user about dryness of the laundry-load (fRMC,n);
• f) using the processing module and in response to a user command, adapting EOC(n) based on fRMC,n in order to determine an adapted end of cycle learning function (EOC,n+1);
• g) during a next drying cycle (DC(n+1)), implementing EOC,n+1, based on collected cycle parameters (K(n+1) and signals (Sraw(n+1)) to cause the processing module to estimate a remaining moisture content (t,n+1) of the laundry load of the next drying cycle (DC(n+1)).

A laundry drying machine comprising:

• an outer casing;
• a rotatable drum arranged inside the outer casing configured to receive a laundry load to be dried;
• an electric motor that rotates the drum based on a drying cycle (DC(n));
• a drying device for drying the laundry load based on DC(n);
• an electronic control system comprising a data processing module and a sensor system, wherein the sensor system is configured to provide cycle parameters (K(n)) and signals (Sraw(n)) indicative of DC(n) and/or the laundry load to be dried, wherein the data processing module is configured to:
• define an end of cycle learning function (EOC,n);
• using the sensor system, collect K(n) and Sraw(n) during DC(n);
• during DC(n), implement EOC(n) based on collected K(n) and Sraw(n) to estimate a remaining moisture content (t,n) of the laundry load;
• determine an end of cycle condition based on t,n;
• at the end of DC(n), receive a user feedback indicative of the satisfaction of the user about dryness of the laundry load (fRMC,n);
• adapting EOC(n)) based on at least fRMC,n in order to determine an adapted end of cycle learning function (EOC,n+1);
• during a next drying cycle (DC(n+1)), implementing EOC,n+1 based on collected cycle parameters (K(n+1) and signals (Sraw(n+1)) to estimate a remaining moisture content (t,n+1) of the laundry load of DC(n+1).