HVAC Fuel Feed Control Using Hourly Heating Load Calculation

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Solution Overview

Problem

Current HVAC heating systems rely on manual fuel feed adjustments and estimate heating loads based on annual minimum outside air temperatures, leading to inefficiencies and increased greenhouse gas emissions, as they do not account for hourly temperature variations or automate fuel input optimization.

Innovation Solution

Implementing hourly outside air temperature monitoring and automatic calculation of heating loads using dry bulb thermometers and dedicated computers to adjust fuel feed rates in HVAC systems, incorporating heat transfer coefficients and infiltration rates, ensuring optimal fuel usage based on real-time data and system efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual fuel feed adjustments are used at higher levels than optimum, then heating load coverage is ensured, but fuel consumption increases and efficiency decreases

Engineering Contradiction:

Improveheating load coverageVSAvoidfuel consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system dynamically adjusts fuel feed rates based on real-time hourly outside air temperature measurements and calculated heating loads, transitioning from static manual settings to dynamic automated control. This allows the fuel feed to match actual heating demands while ensuring reliability through continuous monitoring and adjustment.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements feedback control by continuously measuring outside air temperature, calculating the heating load, and adjusting the fuel feed rate accordingly. This closed-loop control ensures that fuel consumption is optimized while maintaining adequate heating coverage, as the system responds to actual environmental conditions rather than fixed manual settings.

Inventive Principle:

Principle #23Feedback

2Device complexity

If manual fuel feed control is used, then system simplicity is maintained, but automation and optimization are limited

Engineering Contradiction:

Improvecontrol system simplicityVSAvoidfuel feed automation

Core Design Contradiction:

Device complexityVSExtent of automation

Solution Approach 1:

The system enables self-service automation where the control system automatically measures temperature, calculates heating loads, and adjusts fuel feed without manual intervention. This maintains operational simplicity from the user perspective while implementing sophisticated automation internally, resolving the contradiction between simplicity and automation.

Inventive Principle:

Principle #25Self-service

3Device complexity

If annual minimum temperature estimates are used for Design Heating Load, then calculation simplicity is maintained, but hourly temperature variations are not accounted for

Engineering Contradiction:

Improvecalculation method simplicityVSAvoidtemperature variation accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system transitions from using a single annual minimum temperature estimate to periodic hourly temperature measurements. By measuring and calculating heating loads hourly based on actual temperature conditions, the system achieves precise tracking of temperature variations while maintaining calculation simplicity through automated routine operations.

Inventive Principle:

Principle #19Periodic 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 results in significant fuel savings, up to 50% reduction in heating costs, and a substantial decrease in greenhouse gas emissions by optimizing fuel feed to match actual hourly heating demands, while maintaining indoor temperatures.

Implementation Method 1

hourly outside air temperature monitoring and automatic calculation of heating loads using dry bulb thermometers

Methodology Applied

Scientific EffectThermal conduction: Conduction (thermal)

Implementation Method 2

Q=(Σi=1nU(i)*A(i))*ΔT+I*H*ΔT where U=Heating Load Factor for various exterior surfaces

Methodology Applied

Scientific EffectHeat transfer: Conduction (thermal)

Implementation Method 3

I=Outside Air infiltration into the building, at the rate of one air change per hour

Methodology Applied

Scientific EffectConvection: Convection

Data Source

PatentUS11698204B1Automation and optimization of fuel feed to heating elements of heating, ventilation, and air conditioning (HVAC) systems

Publication Date: 2023.07.11 ESMAILI HOUSHANG

AI summary

This Patent application is based on a new method for calculating the hourly heating load for the heating elements of HVAC systems, with a potential for saving over 50% of the current fuel use by these systems. The method is based on using hourly outside air temperature from one or more thermometer installed along the vertical center of each of the building's orientations, and at the roof center. The temperature data, the building surface areas with different heat transmission characteristics in each orientation, plus hourly air infiltration rate into the building, adjusted for overall system efficiency, and Codes and regulatory requirements would yield the total hourly heating load. The fuel feed would then be automatically adjusted to release the hourly required fuel volume, or wattage, to the heating elements. The installed thermometer system could also be used to calculate the hourly cooling load for the building's air conditioning system, during the summer season.