Optimizing Fuel Management for Halifax Class Frigates: Leveraging Sensor Data for Enhanced Efficiency
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Résumé
This article explores how operational data from sensors integrated with Royal Canadian Navy (RCN) Halifax Class Frigates onboard Integrated Platform Management System (IPMS) can be leveraged to minimize fuel consumption. The idea is to use IPMS data logged by the L3HARRIS Equipment Health Monitoring (EHM) software tool. This, along with data collected from temporary fuel flowmeters installed on several Halifax Class Frigates, aids in the development of fuel consumption models for onboard power generating and propulsion equipment. The study aims to identify the most fuel-efficient driving mode among the options available for specific operational conditions, leveraging the CODOG propulsion system and twin shaft arrangement of the Halifax Class Frigates. Building upon this, the developed fuel consumption models are employed to implement various fuel optimization methods on a specific ship platform. This entails the adaptation and integration of these methods into dashboards for enhanced accessibility, with the fuel consumption models providing essential input data. The process of fuel optimization methods development consists of several steps. First, the targeted power generating and propulsion equipment operational data and fuel flowmeters data were selected. Secondly, data from these sources was consolidated and preprocessed and data analysis was conducted. Then, equipment fuel consumption baselines were generated and validated using available historical data. After that, fuel consumption prediction models for each type of equipment were built. Finally, a Fuel Management Application prototype was developed to facilitate user access to current operational data, fuel consumption-related information as well as fuel consumption optimization tools. In the course of the study, several fuel optimization techniques were examined, revealing valuable information about their applicability in specific cases, taking into account factors such as data availability and reliability. The development process of equipment fuel consumption models showcased how sensors designed for operational support could enhance fuel consumption optimization efforts. Enhanced value could be realized with the installation of high-quality fuel flowmeters during ship construction or the prolonged use of temporary fuel flowmeters to capture data across the ship's speed and load ranges. L3HARRIS IPMS emerged as a valuable information source supporting fuel optimization initiatives. Validation of the Fuel Management Application's performance in the field and its value to end-users is pending; however, the progress achieved thus far shows promising potential.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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