Hydrogen Tank Refill MC Method Algorithm
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Solution Overview
Problem
Current hydrogen tank refueling methods are conservative due to unknown parameters, leading to inefficiencies and increased safety margins, resulting in longer fill times, lower final pressures, and excessive energy usage, with no method to adjust for deviations from standard operating conditions.
Innovation Solution
The MC Method employs a new tank filling model based on the total heat capacity of the hydrogen fueling system and an advanced algorithm that uses additional thermodynamic information to improve fill performance, allowing operation outside standard tables and optimizing fill speed and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conservative refueling procedures are used to ensure safety, then safety margins are improved, but fill time increases and final fill pressure decreases
Solution Approach 1:
The system dynamically adjusts refueling parameters (pressure ramp rate, target pressure, pre-cooling temperature) based on real-time monitoring of actual tank conditions (initial temperature, initial pressure, tank volume) rather than using fixed conservative lookup tables. This allows optimization of fill time and final pressure while maintaining safety through continuous parameter adaptation.
Solution Approach 2:
The system implements feedback control by continuously monitoring actual tank temperature and pressure during refueling and comparing them against predicted values. When deviations are detected, the system adjusts the refueling rate and pre-cooling operations in real-time to maintain safe operating conditions while maximizing fill efficiency.
2Reliability
If conservative refueling procedures are used to ensure safety, then safety margins are improved, but energy consumption increases
Solution Approach 1:
The system optimizes pre-cooling temperature and duration based on actual tank conditions and ambient temperature rather than applying fixed conservative pre-cooling. This dynamic parameter adjustment reduces unnecessary energy consumption while maintaining safety margins through real-time condition-based control.
Solution Approach 2:
The system applies pre-cooling and active cooling only to the extent necessary to maintain safe operating temperatures, rather than applying excessive conservative cooling throughout. This partial action approach reduces energy consumption by matching cooling intensity to actual thermal conditions and refueling rate.
3Reliability
If lookup tables with conservative assumptions are used, then safety is improved, but fill speed decreases
Solution Approach 1:
The system replaces static lookup tables with dynamic parameter adjustment based on real-time tank conditions. By continuously adapting pressure ramp rate, target pressure, and pre-cooling temperature to actual measured parameters (initial tank temperature, initial pressure, tank volume), the system achieves faster fill speeds while maintaining safety through ongoing parameter optimization rather than fixed conservative values.
Solution Approach 2:
The system transitions from static lookup table procedures to dynamic real-time control where refueling parameters are continuously adjusted based on monitoring actual tank temperature, pressure, and other conditions. This dynamic adaptation enables faster fill speeds by removing unnecessary conservative margins while maintaining safety through active feedback control.
4Reliability
If pre-cooling temperature is maintained at design set point, then safety is improved, but station cost increases
Solution Approach 1:
The system allows pre-cooling temperature to deviate from the strict design set point by dynamically adjusting it based on actual ambient conditions, tank initial temperature, and refueling rate. This flexible temperature management reduces the need for expensive over-designed cooling infrastructure while maintaining safety through real-time monitoring and adaptive control of refueling parameters.
Solution Approach 2:
The system replaces rigid pre-cooling temperature maintenance with dynamic temperature management that adapts to actual operating conditions. By allowing pre-cooling temperature to vary within safe ranges and compensating through real-time adjustment of refueling rate and active cooling, the system reduces infrastructure costs while maintaining safety through flexible dynamic control rather than expensive fixed-capacity cooling systems.
5Use of energy by moving object
If pre-cooling temperature is increased to reduce energy use, then energy efficiency is improved, but customer satisfaction decreases
Solution Approach 1:
The system optimizes pre-cooling temperature based on actual ambient conditions and tank parameters rather than using fixed high pre-cooling settings. By dynamically adjusting pre-cooling temperature and duration to match actual thermal conditions, the system reduces energy consumption while avoiding excessive pre-cooling that would delay refueling and reduce customer satisfaction.
Solution Approach 2:
The system applies pre-cooling only to the extent necessary to enable safe and efficient refueling under current conditions, rather than applying excessive pre-cooling that would waste energy and delay service. This partial action approach optimizes the balance between energy efficiency and customer satisfaction by matching pre-cooling intensity to actual refueling requirements.
6Reliability
If conservative assumptions are made for non-communication fueling, then safety is improved, but information accuracy decreases
Solution Approach 1:
The system implements feedback control by continuously monitoring actual tank temperature, pressure, and other parameters during refueling and comparing them against predicted values based on communicated tank information. When deviations are detected, the system adjusts refueling parameters in real-time to maintain safety, compensating for any inaccuracies in the initial tank parameter information.
Solution Approach 2:
The system performs preliminary safety assessments and establishes conservative initial refueling parameters based on communicated tank information before beginning refueling. Once refueling starts, the system continuously monitors actual conditions and adjusts parameters in real-time, allowing it to start with conservative assumptions and then optimize based on actual measured data throughout the refueling process.
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 hydrogen filling station performance by accurately predicting end-of-fill temperatures and pressures, reducing energy consumption, and enabling lower-cost stations to meet performance needs while maintaining safety margins.
Implementation Method 1
a cooling system to remove heat from the hydrogen fueling system at a rate sufficient to maintain the temperature of the hydrogen fueling system within a safe operating range
Implementation Method 2
a heating system to add heat to the hydrogen fueling system to prevent the temperature of the hydrogen fueling system from falling below a safe operating minimum
Data Source
AI summary
Disclosed is a simple, analytical method that can be utilized by hydrogen filling stations for directly and accurately calculating the end-of-fill temperature in a hydrogen tank that, in turn, allows for improvements in the fill quantity while tending to reduce refueling time. The calculations involve calculation of a composite heat capacity value, MC, from a set of thermodynamic parameters drawn from both the tank system receiving the gas and the station supplying the gas. These thermodynamic parameters are utilized in a series of simple analytical equations to define a multi-step process by which target fill times, final temperatures and final pressures can be determined. The parameters can be communicated to the station directly from the vehicle or retrieved from a database accessible by the station. Because the method is based on direct measurements of actual thermodynamic conditions and quantified thermodynamic behavior, significantly improved tank filling results can be achieved.