Flight Algorithm Emulation Using Pre-Certified LRUs and Real-World Data
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Solution Overview
Problem
Aviation systems require lengthy development and certification cycles due to laboratory-based development and simulated flight conditions, leading to urgent fixes and limited customer options before certification.
Innovation Solution
An emulated environment system that uses pre-certified systems, remote activation of customer options, and optimization of flight algorithms with real-world operational conditions and data, allowing for parallel testing with certified systems and remote activation of experimental features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aviation systems are developed in laboratories with simulated flight conditions, then system reliability is ensured through controlled testing, but development and certification cycles become excessively lengthy
Solution Approach 1:
The patent applies preliminary action by conducting development and testing of pre-certified systems in parallel with the certification process. Multiple systems are developed simultaneously in the lab, and real-world testing is initiated before formal certification is complete, allowing the system to mature faster while maintaining reliability through controlled parallel validation.
Solution Approach 2:
The patent uses copying by creating virtual replicas of flight environments and systems through emulation technology. Virtual flight conditions and system models are copied to allow extensive testing in silico, reducing the need for prolonged physical laboratory testing while maintaining reliability through virtual validation.
2Reliability
If flight conditions are simulated in the laboratory, then testing can be conducted before real-world deployment, but the window for identifying anomalies prior to certification is shortened
Solution Approach 1:
The patent applies continuity of useful action by transitioning seamlessly from laboratory-based simulated testing to real-world operational testing. The testing process continues uninterrupted as systems move from virtual to physical environments, extending the anomaly identification window by maintaining continuous validation across both controlled and uncontrolled conditions.
Solution Approach 2:
The patent uses an intermediary approach by implementing a gradual transition phase where pre-certified systems operate in controlled real-world conditions before full certification. This intermediary testing environment bridges the gap between simulation and full operational deployment, allowing extended anomaly detection while managing risk.
3Adaptability or versatility
If customers select options before the unit is built, then product configuration is确定的, but customers are limited in which products and services they can sample
Solution Approach 1:
The patent applies dynamics by enabling dynamic reconfiguration of system options and features after deployment. Customers can sample and evaluate different product configurations in the field, and the system can be remotely reconfigured based on customer feedback and performance data, providing both determination and flexibility.
Solution Approach 2:
The patent uses parameter changes by allowing remote modification of system parameters and customer-selected options after the unit is built and deployed. This enables customers to sample different configurations by changing software parameters remotely, without requiring physical reconfiguration or new hardware deployment.
Data Source
AI summary
Systems, methods, and apparatus for hosting pre-certified systems, remote activation of customer options, and optimization of flight algorithms in an emulated environment with real world operational conditions and data are disclosed. A method for operating in an emulated environment comprises generating and outputting, by a plurality of production line replaceable units (LRUs) operating in an operational environment, physical environmental data and production LRU output data. The method further comprises emulating, by a plurality of emulators in an emulation server, the production LRUs. Also, the method comprises generating and outputting, by the emulators using the physical environmental data, a model of the operational environment. Further, the method comprises generating and outputting, by a plurality of pre-certified LRUs using the model of the operational environment, pre-certified LRU output data. In one or more embodiments, the pre-certified LRUs correspond to the production LRUs.