Vehicle Cabin HVAC Control Using Passenger Thermal Load Data

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Solution Overview

Problem

The high energy consumption of HVAC systems in electric vehicles reduces the mileage range and increases the need for larger batteries, leading to higher operating costs and less frequent charging, necessitating an optimized control method.

Innovation Solution

A system and method utilizing a counting system, camera, and processor to collect and analyze passenger data, including headcount, thermal loads, and environmental conditions to optimize HVAC settings, reducing manual interaction and enhancing thermal comfort.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Temperature

If HVAC system is used to maintain thermal comfort in electric vehicles, then passenger comfort is improved, but energy consumption increases and mileage range decreases

Engineering Contradiction:
Improvethermal comfortVSAvoidenergy consumption
Core Design Contradiction:
TemperatureVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts HVAC operating parameters (temperature, humidity, air flow rate, ventilation mode) based on real-time thermal load calculations that consider passenger headcount, location, and environmental conditions. This optimized parameter control reduces energy consumption while maintaining thermal comfort

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The system continuously monitors thermal load conditions through multiple sensors (temperature, humidity, solar radiation, passenger presence) and adjusts HVAC operations in real-time based on feedback from these measurements, enabling energy-efficient climate control that adapts to changing conditions

Inventive Principle:
Principle #23Feedback

2Measurement precision

If multiple sensors are installed around the cabin to accurately measure thermal conditions, then measurement precision is improved, but device complexity increases

Engineering Contradiction:
Improvethermal condition measurementVSAvoidsensor system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system divides the cabin into multiple thermal zones and uses strategically positioned sensors to measure conditions in each zone. By segmenting the measurement task across multiple locations and using data fusion algorithms, the system achieves comprehensive thermal monitoring without requiring excessive sensors throughout the entire cabin

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The sensor system is designed to perform multiple functions simultaneously: measuring temperature, humidity, solar radiation, and detecting passenger presence. This multi-functional approach reduces the total number of separate devices needed while maintaining comprehensive environmental monitoring capability

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

Data Source

PatentEP4385772B1System and method for controlling HVAC system of vehicle
Publication Date: 2025.11.05 ROBERT BOSCH GMBH
  • EP4385772B1 patent drawingFigure 1~2
  • EP4385772B1 patent drawingFigure 3A~3D
  • EP4385772B1 patent drawingFigure 4A~4D

AI summary

A method (800) for controlling a HVAC system (110) in a cabin (20) of a vehicle (10) comprising: a step (810) of collecting headcount data of passengers (30) in the cabin (20) by a counting system (120); a step (820) of capturing a plurality of images of an inside of the cabin (20) at different times by a camera (130); a step (822) of obtaining data of headcount of passengers (30) in the cabin (20) based on the captured images by a processor (150); a step (830) of validating the collected headcount data with the obtained data of headcount by the processor (150); a step (840) of obtaining thermal loads based on the collected headcount data, obtained data of location and density of the passengers (30), calculated humidity and heat generation, obtained solar thermal distribution along the cabin (20), collected HVAC information and collected location and time based weather forecast data by the processor (150).