Gasoline Blending Control for Excess Octane and Volatility Limits
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Solution Overview
Problem
Current gasoline blending processes face challenges in minimizing excess fuel octane, leading to significant profit losses, as they struggle to accurately and efficiently blend gasoline, ethanol, and butane to meet government-mandated octane specifications without exceeding volatility limits.
Innovation Solution
A system comprising premium and regular octane pipes, butane and ethanol pipes, analyzer cells, and a programmable logic controller that continuously measures and calculates the blend ratios based on real-time octane and volatility data, using estimated values for ethanol and butane to optimize the blend and prevent excess octane, ensuring the produced gasoline meets specifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If real-time octane measurements and rapid blending are implemented, then manufacturing precision of octane specifications is improved, but device complexity increases due to multiple analyzer cells and control systems
Solution Approach 1:
The system divides the blending process into separate streams for premium octane gasoline, regular octane gasoline, and butane, each with dedicated analyzer cells and control mechanisms. This segmentation allows independent measurement and control of each component's octane contribution, improving overall precision while managing complexity through modular architecture
Solution Approach 2:
The system continuously measures octane numbers of input streams and uses this real-time data to dynamically adjust blend ratios via programmable logic controllers. This closed-loop feedback ensures precise compliance with octane specifications by constantly comparing actual measurements against target values and making corrective adjustments
2Measurement precision
If multiple analyzer cells and sensors are deployed for continuous monitoring, then measurement precision is improved, but loss of time for data processing and blending operations increases
Solution Approach 1:
The system performs preliminary measurements of octane numbers and volatility characteristics on all input streams before blending begins. This advance characterization allows the control system to pre-calculate optimal blend ratios, eliminating the need for iterative adjustments during actual blending operations and reducing overall processing time
Solution Approach 2:
Multiple analyzer cells operate continuously and simultaneously on different input streams, providing uninterrupted real-time data flow to the control system. This continuous parallel measurement eliminates sequential processing delays and maintains constant monitoring without interrupting the blending operation
3Loss of energy
If blend ratios are dynamically adjusted based on real-time measurements, then excess octane is minimized improving profit, but ease of operation decreases due to complex control requirements
Solution Approach 1:
The programmable logic controller automatically calculates optimal blend ratios and executes adjustments based on real-time octane measurements from the analyzer cells. The system serves itself by autonomously optimizing the blend composition to minimize excess octane without requiring manual intervention, thereby reducing profit loss while maintaining operational simplicity through automation
Solution Approach 2:
The system dynamically changes the blend ratio parameters of premium gasoline, regular gasoline, and butane based on real-time octane measurements and target specifications. By continuously adjusting these compositional parameters, the system minimizes excess octane content while meeting minimum specifications, directly improving profit margins through optimized blending
Data Source
AI summary
Systems operable to blend at least one finished gasoline from a refined petroleum product comprising at least one neat gasoline with ethanol and optionally butane utilizing a blend model that calculates a volumetric blend ratio comprising at least one neat gasoline, ethanol and optionally, butane. The blend model incorporates estimated values for the octane number and the volatility of the ethanol and butane when calculating the volumetric blend ratio.