Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data
Clemens Deutsch, Ariel Chiche, Sriharsha Bhat, Carina Lagergren, Göran Lindbergh, Jakob Kuttenkeuler
Abstract
This study combines high-fidelity simulation models with experimental power consumption data to evaluate the performance of Energy Management Strategies (EMS) for fuel cell/battery hybrid Autonomous Underwater Vehicles (AUV). The performance criteria are energy efficiency, power reliability and system degradation. The lack of standardized drive cycles is met by the cost-efficient solution of synthesizing power profiles from sampled AUV field trial data. Three power profiles are used to evaluate finite-state machine, fuzzy logic and two optimization-based EMS. The results reveal that there is a trade-off between the objectives. The rigidity of the EMS determines its load-following behavior and consequently the performance regarding the objectives. Rule-based methods are particularly suitable to design energy-efficient operations, whereas optimization-based methods can easily be tuned to provide power reliability through load-following behavior. Both classes of EMS can be best-choice methods for different types of missions.