Maribot LoLo is an autonomous underwater vehicle (AUV) developed at the KTH Centre for Naval Architecture as part of the Swedish Maritime Robotics Centre (SMaRC). The center's cross-disciplinary activities require an AUV research platform that can be used for data collection and to test and demonstrate novel technologies. The challenge herein is to create a well-performing and yet versatile vehicle. This paper introduces Maribot LoLo and presents the underlying design philosophy which focuses on versatility and endurance. A free-flooded hull offers modularity and modifiability while reliability and robustness are achieved through hardware redundancy and a hierarchical captain-scientist relationship in the embedded system. The vehicle is designed to be operated at moderate water depths and on long-range missions. This leads to challenges in the design of the variable buoyancy system (VBS) which also is presented. The achievable range of the AUV is evaluated with a simple hydrodynamics model based on frictional drag.

This paper analyses the transit performance of state-of-the-art underwater vehicles and presents an intermediate-fidelity steady-state flight mechanics model for qualitative performance assessment of underwater vehicles. Focusing on the comparison of underwater gliders and propeller-driven AUVs, a simple glide metric is presented and the transit performance of the legacy underwater gliders Slocum, Spray and Seaglider as well as propeller-modified versions thereof is evaluated. The evaluation is based on various data sets from wind tunnel tests and Computational Fluid Dynamics (CFD) studies, and shows that for the respective hull shapes gliding locomotion proves more efficient in ideal conditions. However, biofouling conditions inflict a double penalty on glider performance, rendering gliders inferior to propeller-driven vehicles. The Slocum data set is used to validate a steady-state flight mechanics model for qualitative performance prediction. It is shown that even simplistic models based on semi-empirical and analytical expressions can be successfully used for design optimization through parametrization. Being computationally efficient, the model can be a useful tool for design engineers in early design phases. The model is used to evaluate the effects of wing span on gliding efficiency, indicating that the current design of the Slocum glider is near-optimal.

This paper presents a comparison of different energy management strategies (EMS) for autonomous underwater vehicles (AUV) with fuel cell-battery hybrid power systems. Sophisticated EMS can decrease energy consumption, limit fuel cell degradation or increase reliability. EMS for hybrid vehicles have been studied extensively in the automotive industry where standardised drive cycles are applied. As for AUVs, there are no standard drive cycles and power profiles can vary significantly depending on the type of mission. In this study, rule-based and optimization-based EMS are compared. The rule-based strategies rely on deterministic rules and fuzzy logic, the optimization-based strategies minimize a constrained cost function to efficiently split the power demand. The EMS are evaluated against a previously sampled power profile of a Hugin 3000 AUV. The evaluation against real power profiles adds significant value to this study. 

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.

This study focuses on the feasibility and benefits of implementing of a fuel cell/battery hybrid power system in the autonomous underwater vehicle LoLo. We highlight the practical implications and challenges related to such a power system conversion and compare the benefits of using a fuel cell system rather than a pure battery system. Storage of hydrogen and oxygen as pressurized gases is considered most suitable for a conversion of this kind. In order to outperform Li-ion battery packs, high-pressure gas storage is required, preferably at pressures of 500 MPa or higher. Through a market analysis, we analyze the performance of commercial gas cylinders in terms of volumetric and gravimetric densities. This information can subsequently be used to compare energy density and effective energy density for the respective power systems. The study exemplifies how fuel cell/battery hybrid systems can provide up to 75% higher effective energy density compared to conventional battery packs. Ongoing developments in the fuel cell and auxiliary system markets are likely to allow for further optimization of the fuel cell system.