Ammonia Cracking Control for Predictive Multi-Fuel Engine Load
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Solution Overview
Problem
Existing multi-fuel engines face inefficiencies in fuel usage, maintenance, and greenhouse gas emissions due to unpredictable load demands and suboptimal fuel substitution strategies.
Innovation Solution
A system for multi-fuel engines that includes a cracker to convert ammonia into hydrogen and nitrogen gases, a controller to predict future load demands, and adjust ammonia flow rates based on predefined routes, and an energy storage device to optimize energy use, thereby enhancing fuel efficiency and reducing emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If ammonia flow rate is increased to meet future load demand, then fuel efficiency is improved, but cracker wear and operational cycles increase
Solution Approach 1:
The controller predicts future load demands based on predefined routes and adjusts ammonia flow rates in advance. By anticipating future power needs, the system optimizes fuel substitution proactively rather than reactively, improving overall fuel efficiency while avoiding excessive cracker operation during low-demand periods
Solution Approach 2:
The system dynamically adjusts the ammonia flow rate to the cracker based on predicted future load demands. This dynamic control allows the cracker to operate at optimal levels matching actual power needs, preventing both under-utilization (wasting fuel efficiency opportunities) and over-utilization (excessive wear)
2Productivity
If ammonia flow rate is adjusted based on predicted load demand, then fuel efficiency is improved, but system complexity increases
Solution Approach 1:
The controller implements a feedback mechanism that continuously monitors actual power demand against predicted demand, and adjusts ammonia flow rates accordingly. This closed-loop control optimizes fuel efficiency by matching cracker output to actual engine needs, while the automated nature of the feedback reduces manual intervention complexity
Solution Approach 2:
The system uses the vehicle's existing route information and power demand data to automatically predict and adjust ammonia flow rates without external intervention. The controller self-regulates the fuel substitution strategy based on predefined routes and actual operating conditions, reducing operational complexity
3Reliability
If cracker operational cycles are minimized to reduce wear, then reliability is improved, but fuel efficiency deteriorates
Solution Approach 1:
By predicting future load demands before they occur, the system can pre-optimze ammonia flow rates to match upcoming power needs. This prevents last-minute cracker activation that would cause excessive wear, while ensuring the cracker operates efficiently when power demand actually increases
Solution Approach 2:
The system changes the ammonia flow rate parameter dynamically based on predicted load conditions. By adjusting this key parameter in advance, the system optimizes the balance between cracker utilization (for fuel efficiency) and operational frequency (for wear reduction), achieving both reliability and productivity goals
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
The system improves fuel efficiency by optimizing fuel substitution and reducing emissions by predicting load demands and adjusting ammonia flow rates, thereby minimizing operational cycles and wear on the cracker.
Implementation Method 1
crack the ammonia to form cracked gas including hydrogen gas and a nitrogen gas
Implementation Method 2
The energy storage device can provide the energy to the cracker
Implementation Method 3
combusting, by the engine, a cracked gas mixture including the cracked gas
Data Source
AI summary
A vehicle includes an engine to receive a cracked gas mixture. A cracker of the vehicle can receive ammonia and energy, crack the ammonia to form the hydrogen gas and a nitrogen gas, and convey the hydrogen gas to the engine. A controller for the vehicle can receive a predefined route for the vehicle. The controller can predict a future load demand of the vehicle based on the predefined route. The controller can adjust a flow rate of ammonia delivered to the cracker based on the future load demand.