Fuel Cell Gas Temperature Correction via Iterative Thermal Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In fuel cell systems, accurately measuring the temperature of gases flowing through conduits is challenging due to turbulent flow and varying speeds, which can lead to inaccurate measurements by physical sensors, especially when these sensors are exposed to environmental conditions in confined spaces.
Innovation Solution
A controller system that uses a temperature sensor within the conduit and a wall temperature sensor to iteratively apply a thermal model, accounting for conductive, convective, and radiative heating effects, to calculate a predicted temperature value, adjusting input values based on differences between measured temperatures until a predetermined criterion is met, thereby correcting the temperature measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If physical sensors are placed directly in the gas flow within confined conduits to measure temperature, then measurement accessibility is improved, but measurement accuracy deteriorates due to conductive and radiative heating from conduit walls
Solution Approach 1:
The patent introduces an intermediary computational model that acts as a mediator between the physical sensor reading and the actual gas temperature. The model uses the sensor measurement along with conduit wall temperature and flow conditions to calculate the true gas temperature, effectively decoupling the sensor from direct thermal interference while preserving measurement capability
Solution Approach 2:
The patent replaces the direct physical measurement approach with a computational/algorithmic system. Instead of relying solely on physical sensor accuracy, the system uses mathematical modeling incorporating heat transfer equations to compute the actual temperature, substituting physical measurement limitations with computational correction
2Reliability
If sensors are sheltered to protect from environmental conditions and turbulent gas flow, then sensor durability is improved, but measurement accuracy deteriorates due to additional thermal interference
Solution Approach 1:
The computational model serves as an intermediary that compensates for the thermal interference introduced by protective sheltering. By incorporating the shelter geometry and material properties into the heat transfer model, the system calculates the true gas temperature despite the sensor being thermally isolated by the protective structure
Solution Approach 2:
The patent changes the approach from directly measuring physical temperature to measuring multiple parameters (sensor temperature, wall temperature, flow velocity, shelter properties) and computationally deriving the gas temperature. This parameter transformation allows the system to account for shelter-induced thermal effects
3Measurement precision
If iterative thermal modeling is applied to correct temperature measurements, then measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the iterative thermal model continuously compares predicted sensor temperatures with actual measurements and adjusts the gas temperature calculation accordingly. This feedback loop refines the temperature estimate until convergence, improving accuracy through systematic error correction
Solution Approach 2:
The patent applies partial action by performing iterative corrections only when necessary (when initial measurements indicate significant thermal interference) rather than continuously. The iteration stops when a predetermined accuracy threshold is met or a maximum number of iterations is reached, balancing computational effort with measurement accuracy
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 enhances the accuracy of temperature measurement and control within fuel cell systems, improving efficiency and extending sensor lifespan by accounting for complex heating effects, and is applicable to other enclosed spaces beyond fuel cell systems.
Implementation Method 1
conductive, convective and radiative heating effects on the sensor
Implementation Method 2
conductive, convective and radiative heating effects on the sensor
Implementation Method 3
conductive, convective and radiative heating effects on the sensor
Data Source
AI summary
A fuel cell system comprising a controller, a temperature sensor that has a physical presence in a conduit within the system to measure the temperature of the fluid at a point within the conduit (Tg) and a wall temperature sensor for sensing a temperature of a wall of the conduit (Tw). The controller takes Tg and Tw as inputs and applies an equation with known constants to calculate measurement error of Tg based on the local flow temperature and geometry and arrives at a calculated temperature. The equation may be applied iteratively until the difference between the calculated temperature and Tg is below an acceptable value when the calculated temperature can then be assumed to be an accurate representation of the actual gas temperature at the Tg measurement point. The direction of calculation is controlled by the relative difference between Tg and Tw.