IP Library › Granted Patent US 12,726,038
Granted Patent B2
US 12,726,038 · App. 18/095,817 · Granted Sep 1, 2026

Systems, apparatuses and methods for appliances with integrated energy storage

Inventors: Samuel Redmond D'Amico (San Francisco, CA); Samuel William Lenius (Palo Alto, CA); Bradley James Tallon (Los Angeles, CA); Deanna James Chang (New York, NY); Brian H. Sharp (San Francisco, CA)
Assignee: Impulse Labs, Inc.
H02J7/92G06F1/263H02J7/04H02J7/40H02J7/50H02J7/855H02J7/933H02J3/32H02J2207/20
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Quick Facts
Patent No.
US 12,726,038
App. No.
18/095,817
Granted
Sep 1, 2026
Kind
B2
Abstract

An intelligent energy system includes an energy-consuming appliance, a battery module coupled to the appliance, and a bidirectional converter coupled to the appliance and the battery module by a power bus. The battery module is configured to provide power to the appliance. The bidirectional converter converts between alternating current (AC) and direct current (DC) and interfaces with a power infrastructure external to the appliance. The system further includes a control unit communicatively coupled to the battery module, the bidirectional converter, and the appliance. The control unit is configured to determine a charge and discharge schedule for the battery module. The battery module coupled with the bidirectional converter provides uninterrupted power to the appliance, abstracts the power demands of the appliance from local power infrastructure, and allows for greater appliance peak power draw than would otherwise be practical or possible.

Claims (44)

1 . A system for intelligent power management, comprising:

an appliance having a battery module and a heat transfer element, the battery module being configured to provide power to the heat transfer element;

a sensor coupled to the heat transfer element and not coupled to the battery module to monitor a temperature value of the heat transfer element at a specific time point; and

a control unit communicatively coupled to the sensor to collect information obtained from the sensor, the control unit being configured to determine whether to adjust the power provided to the heat transfer element from the battery module based on the temperature value of the heat transfer element.

2 . The system of claim 1 , wherein the appliance is a stove and the sensor is a temperature sensor.

3 . The system of claim 2 , wherein the temperature sensor is configured to monitor a cooking process.

4 . The system of claim 3 , wherein:

the heat transfer element includes a stovetop burner, and

the control unit is configured to determine whether to adjust the power provided to the stovetop burner of the stove from the battery module according to the cooking process and a predefined cooking protocol.

5 . The system of claim 1 , wherein the appliance is a refrigerator and the sensor is a temperature sensor.

6 . The system of claim 5 , wherein the temperature sensor is configured to detect a temperature sensitivity of food items stored in the refrigerator.

7 . The system of claim 6 , wherein the control unit is configured to determine whether to adjust the power provided to the heat transfer element of the refrigerator from the battery module according to the temperature sensitivity of the food items stored in the refrigerator.

8 . The system of claim 1 , wherein the control unit is further configured to determine a charge and discharge schedule for the battery module based on a power usage pattern of the heat transfer element.

9 . The system of claim 8 , further comprising one or more sensors or third party services coupled to the control unit and configured to collect contextual information related to one or more of the battery module or the appliance.

10 . The system of claim 9 , wherein the control unit further comprises a machine learning model trained to predict a usage of the appliance based on the collected contextual information.

11 . The system of claim 10 , wherein the control unit is further configured to adjust the determined charge and discharge schedule based on the predicted usage of the appliance by the trained machine learning model.

12 . The system of claim 8 , further comprising a physical user interface configured to receive a user input for manually editing the charge and discharge schedule for the battery module at a time point.

13 . A method of intelligent power management, comprising:

monitoring a temperature value of a heat transfer element of an appliance at a specific time point, the temperature value being monitored by a sensor coupled to the heat transfer element of the appliance and not coupled to a battery module included in the appliance;

collecting power usage data of the appliance at the specific time point, wherein the power usage data indicates power provided to the heat transfer element of the appliance by the battery module included in the appliance; and

determining whether to adjust the power provided to the heat transfer element of the appliance from the battery module based on the temperature value of the heat transfer element of the appliance and the power usage data of the appliance.

14 . The method of claim 13 , wherein the appliance is a stove and the sensor is a temperature sensor.

15 . The method of claim 14 , wherein the temperature sensor is configured to monitor a cooking process.

16 . The method of claim 15 , wherein:

the heat transfer element of the stove includes a stovetop burner, and

determining whether to adjust the power provided to the heat transfer element of the appliance includes determining whether to adjust the power provided to the stovetop burner of the stove from the battery module according to the cooking process and a predefined cooking protocol.

17 . The method of claim 13 , wherein the appliance is a refrigerator and the sensor is a temperature sensor.

18 . The method of claim 17 , wherein the temperature sensor is configured to detect measure a temperature sensitivity of food items stored in the refrigerator.

19 . The method of claim 18 , wherein determining whether to adjust the power provided to the heat transfer element of the appliance includes determining whether to adjust the power provided to the heat transfer element of the refrigerator from the battery module according to the temperature sensitivity of the food items stored in the refrigerator.

20 . The method of claim 13 , further comprising:

determining a charge and discharge schedule for the battery module based on a power usage pattern of the heat transfer element of the appliance.

21 . The system of claim 1 , wherein the appliance is any one of an air conditioner, a water heater, a space heater, an electric range, a microwave, an oven, a dishwasher, or a clothing dryer.

22 . The system of claim 11 , wherein:

the appliance is an air conditioner, and

the contextual information includes weather data.

23 . The system of claim 11 , wherein:

the appliance is an electric water heater, and

the contextual information includes at least one of (1) a first set of times indicating usage of a shower, (2) a second set of times indicating usage of the shower by a specific user, (3) a set of time periods defining durations of usage of the shower, or (4) water temperature data associated with usage of the shower.

24 . The system of claim 1 , further comprising:

an audio sensor configured to detect a voice of a user of the appliance to produce audio data,

the control unit being configured to use a machine learning model to identify text from the audio data, the machine learning model being trained for voice recognition, the control unit configured to modify an operation of the appliance based on the text.

25 . The system of claim 1 , further comprising:

an audio sensor configured to identify text from audio data, the audio data being representative of a voice of a user of the appliance,

the control unit configured to modify an operation of the appliance, based on the text.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 11, 2023
From: D'AMICO, SAMUEL REDMOND; LENIUS, SAMUEL WILLIAM; TALLON, BRADLEY JAMES; CHANG, DEANNA JAMES; SHARP, BRIAN H.
To: IMPULSE LABS, INC.
Reel/Frame 064216/0618 →
Continuity (2)
Provisional Application 63301861 · Jan 21, 2022
Related Publication 20230238819A1 · Jul 27, 2023
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