Vehicle Cabin Climate Control for Fogging and Breath Temperature

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Solution Overview

Problem

Existing HVAC systems in vehicles face challenges in accurately estimating and efficiently managing fogging and breath temperature conditions, requiring complex data-driven models or additional sensors to ensure optimal thermal comfort and clear cabin views.

Innovation Solution

Implementing physics-based models that utilize readily available vehicle sensors to determine fogging and breath temperature metrics, allowing for dynamic control of climate control devices such as blowers, heaters, and duct doors to manage these conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If data-driven models or additional sensors are used to estimate fogging and breath temperature conditions, then measurement precision is improved, but device complexity and cost increase

Engineering Contradiction:

Improvefogging and breath temperature estimation accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system uses existing vehicle sensors (temperature, humidity, solar flux, air flow rate) to self-determine fogging and breath temperature metrics without requiring additional dedicated sensors. The control circuitry processes readily available data through physics-based models to achieve accurate estimation while avoiding system complexity increases

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Existing vehicle sensors serve multiple functions: temperature sensors monitor both cabin temperature and contribute to breath temperature estimation, humidity sensors provide data for both comfort control and fogging prediction. This multi-functional use of existing components improves measurement precision without adding device complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Device complexity

If physics-based models are used with readily available sensors, then device complexity is reduced, but measurement precision may worsen

Engineering Contradiction:

Improvesystem complexityVSAvoidfogging and breath temperature estimation accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system transforms readily available sensor parameters (temperature, humidity, solar flux, air flow rate) into meaningful metrics (fogging probability, breath temperature estimation) through physics-based calculations. By changing the parameters from raw sensor data to derived metrics, the system maintains measurement precision while using simple, existing hardware

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces complex mechanical sensor systems with computational models that use existing sensor data. Instead of adding dedicated fogging sensors or breath temperature sensors, the system uses mathematical relationships and physics-based models to calculate these metrics from standard vehicle environmental sensors

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If dynamic control of climate control devices is implemented, then adaptability is improved, but device complexity increases

Engineering Contradiction:

Improveresponse to fogging and breath temperature conditionsVSAvoidcontrol system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The control circuitry continuously monitors sensor data, calculates fogging and breath temperature metrics, and adjusts climate control device operation accordingly. This closed-loop feedback system dynamically adapts to changing conditions while using straightforward control logic that manages complexity

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically adjusts climate control device operation based on real-time calculation of fogging and breath temperature metrics. The control parameters (air flow rate, temperature, duct positions) are continuously modified in response to changing environmental conditions, providing adaptability through dynamic control rather than static settings

Inventive Principle:

Principle #15Dynamics

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

Improves the accuracy and efficiency of cabin climate control by reducing reliance on additional sensors while maintaining thermal comfort and ensuring clear cabin views, balancing cost and performance.

Implementation Method 1

determining the fogging metric is based on a dewpoint temperature corresponding to a windshield, a temperature corresponding to the windshield, and a temperature gradient corresponding to the windshield

Methodology Applied

Scientific EffectDew point temperature:

Implementation Method 2

determining the breath temperature metric includes determining a radiant temperature, determining an air temperature for the vehicle interior, or determining a convection metric for the vehicle interior

Methodology Applied

Scientific EffectRadiant temperature: Thermal Radiation

Implementation Method 3

Methodology Applied

Scientific EffectConvection: Convection

Data Source

PatentUS12594813B2Systems and methods for dynamic climate control

Publication Date: 2026.04.07 RIVIAN HOLDINGS LLC

AI summary

Methods and systems are provided for managing cabin conditions. A fogging metric and a breath temperature metric are determined. A control signal response is generated based on the fogging metric and the breath temperature metric. The system facilitates modification to the operation control of the at least one climate control device based on the control signal response.