Induction Heating Temperature Estimation via Electrical Model Tuning

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Solution Overview

Problem

Induction heating systems face challenges in accurately estimating the temperature of cooking utensils and food due to their active involvement in the heating process, and existing methods lack quantitative temperature evaluation and noise compensation.

Innovation Solution

A method using the switching frequency of the induction heating system and additional electrical measurements, combined with a mathematical model and online tuning algorithms like the Extended Kalman Filter, to estimate pot, food, and coil temperatures, while compensating for noise factors and uncertainties.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If existing temperature evaluation methods are used, then the temperature derivative can be evaluated, but quantitative temperature estimation is not achieved

Engineering Contradiction:
Improvetemperature estimation precisionVSAvoidquantitative temperature information
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent introduces an intermediary mathematical model that relates electrical measurements to temperature. The model uses electrical parameters (current, voltage, impedance) as intermediaries to infer temperature, since direct temperature measurement is not available. This mediator approach transforms electrical domain measurements into thermal domain information through the thermal-electrical coupling model.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces direct thermal measurement mechanisms with electrical measurement mechanisms. Instead of using thermocouples or other contact-based temperature sensors, the system uses electrical impedance and power measurements to infer temperature, substituting a mechanical/thermal measurement system with an electrical sensing system.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If multiple electrical measurements are taken, then estimation reliability improves, but system complexity and measurement requirements increase

Engineering Contradiction:
Improvetemperature estimation reliabilityVSAvoidmeasurement system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent makes the existing electrical measurement system multi-functional. The same electrical measurements used for basic power control are also utilized for temperature estimation. The induction coil's electrical characteristics serve dual purposes: heating control and temperature sensing, eliminating the need for separate measurement hardware.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system uses its own electrical characteristics to measure temperature. The induction heating system's electrical impedance and power consumption serve as self-indicators of the cooking vessel's temperature state. The system monitors itself through its electrical behavior without requiring external sensing infrastructure.

Inventive Principle:
Principle #25Self-service

3Measurement precision

If temperature monitoring is enhanced, then cooking phase control improves, but noise from voltage fluctuations and component drift affects accuracy

Engineering Contradiction:
Improvetemperature measurement precisionVSAvoidnoise factors
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent implements feedback through iterative model tuning. The mathematical model is continuously adjusted based on the difference between measured electrical parameters and model-predicted values. This feedback mechanism compensates for noise factors by adapting the model to current operating conditions, reducing the impact of voltage fluctuations and component drift.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The patent performs preliminary characterization of the cooking vessel and system parameters before actual temperature estimation. The model is pre-tuned with electrical measurements taken at different switching frequencies to establish baseline characteristics. This preliminary action creates a reference model that accounts for system variations before operational temperature monitoring begins.

Inventive Principle:
Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach improves temperature estimation reliability, enabling effective monitoring and control of cooking phases, preventing overheating, and detecting pot quality and dynamic mismatches, even under varying conditions such as voltage fluctuations.

Implementation Method 1

an induction heating system of a cooktop provided with an induction coil

Methodology Applied
Scientific EffectElectromagnetic induction: Electromagnetic Induction

Implementation Method 2

The control method according to the present invention is used for estimating the temperature of a pot, pan or a griddle

Methodology Applied
Scientific EffectInduction heating: Induction Heating

Data Source

PatentEP2194755B1Method for controlling an induction heating system of a cooking appliance
Publication Date: 2016.08.03 WHIRLPOOL CORP
  • EP2194755B1 patent drawingFigure 1~2
  • EP2194755B1 patent drawingFigure 3~4
  • EP2194755B1 patent drawingFigure 5~6

AI summary

A method for controlling an induction heating system of a cooking appliance provided with an induction coil, particularly for controlling it in connection with a predetermined working condition, comprises measuring the value of one electrical parameter of the induction heating system, feeding a computing model with actual switching frequency signals in order to estimate a temperature indicative of the thermal status of the heating system and to provide an estimated value of said electrical parameter, and comparing the measured electrical parameter with the estimated one and tuning the computing model on the basis of such comparison.