Autonomous control for adaptive ships: with hybrid propulsion and power generation

Shipping plays a crucial role in modern society, but has to reduce its impact on the environment. The commercial availability of power electronic converters and lithium-ion batteries provides an opportunity to improve performance of ships energy systems while reducing their environmental impact. However, the degrees of freedom in control for hybrid propulsion and power generation require advanced control strategies to autonomously achieve the best trade-off between fuel consumption, emissions, radiated noise, propulsion availability, manoeuvrability and maintainability. This PhD thesis proposes dynamic simulation models, benchmark manoeuvres and measures of performance (MOP) to quantify energy system performance. These simulation models and MOPs are used to quantify the improvements with three novel control strategies: adaptive pitch control, parallel adaptive pitch control and energy management for hybrid propulsion and power generation. Finally, a layered control strategy is proposed that can autonomously adapt to changing ship functions, using the proposed control strategies. The proposed energy systems and control strategies can thus significantly reduce the impact of shipping on the environment, while more autonomously achieving its increasingly diverse missions at seaShip Design, Production and Operation

Naval engineering and ship control special edition editorial

Editorial Special Issue: Naval Engineering and Ship Control IIGreen Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Ship Design, Production and Operation

Motor current and vibration monitoring dataset for various faults in an E-motor-driven centrifugal pump

Induction motor driven pumps are a staple in many sectors of industry, and crucial equipment in naval ships. Such machines can suffer from a wide variety of issues, which may cause it to not perform its function. This can either be due to degradation of components over time, or due to incorrect installation or usage. Unexpected failure of the machine causes downtime and lowers the availability. In some cases, it can even lead to collateral damage. To prevent collateral damage and optimise the availability, many asset owners apply condition monitoring, measuring the dynamic response of the system while in operation. Two high-frequency measurement methods are widely accepted for the detection of faults in rotating machinery at an early stage: vibration measurements, and motor current and voltage measurements. These methods can also distinguish between different failure mechanisms and severities. The dataset described in this article presents experimental data of two centrifugal pumps, driven by induction motors through a variable frequency drive. Besides measurements of behaviour that is considered healthy (new bearings, well aligned), the machines have also been subjected to a variety of (simulated) faults. These faults include bearing defects, loose foot, impeller damage, stator winding short, broken rotor bar, soft foot, misalignment, unbalance, coupling degradation, cavitation and bent shaft. Most faults were implemented at multiple levels of severity for multiple motor speeds. Both vibration measurements, and current and voltage measurements were recorded for all cases. The dataset holds value for a wide range of engineers and researchers working on the development and validation of methods for damage detection, identification and diagnostics. Due to the extensive documentation of the presented data, labelling of the data is close to perfect, which makes the data particularly suitable for developing and training machine learning and other AI algorithms

Adaptive pitch control for ships with diesel mechanical and hybrid propulsion

Shipping urgently needs to reduce its impact on the environment, both due to CO2, NOx and particulate matter (PM) emissions and due to underwater noise. On the other hand, multifunction ships such as offshore support vessels, anchor handling and towing vessels, naval vessels and wind farm construction and support vessels require fast and accurate manoeuvring and need highly reliable systems to support reduced or no crew. Diesel mechanical propulsion with controllable pitch propellers provides high efficiency and low CO2 emissions, but has traditionally been poor in manoeuvrability, can suffer from thermal overloading due to manoeuvring and requires significant measures to meet NOx and PM emission regulations. The control strategy of diesel mechanical propulsion with fixed combinator curves is one of the causes of the poor manoeuvrability, thermal overloading and cavitation noise during manoeuvring, such as slam start and intermediate acceleration manoeuvres. This paper proposes an adaptive pitch control strategy with slow integrating speed control that reduces fuel consumption, CO2, NOx and PM emissions and underwater noise, improves acceleration performance, limits engine loading and prevents engine under- and overspeed. A simulation study with a validated model of a case study Holland class Patrol Vessel demonstrates 5–15% reduction in fuel consumption and CO2 emissions, compared to the baseline transit control mode in the ship speed range from 6 to 15 kts, during constant speed sailing. Moreover, the adaptive pitch control strategy reduces acceleration time from 0 to 15 kts with the slam start procedure by 32% compared to the baseline manoeuvre control mode and by 84% for an intermediate acceleration from 10 to 15 kts, while preventing thermal overloading of the engine, during straight line manoeuvres. Combining this control strategy with hybrid propulsion, running an electric drive in parallel with the propulsion diesel engine, can potentially further reduce fuel consumption at low speeds while also improving acceleration performance even more. Therefore, hybrid propulsion plants with controllable pitch propellers and adaptive pitch control can provide a significant contribution to the urgent reduction of environmental impact of shipping and to the need for more autonomous and reliable ship systems.Ship Design, Production and OperationsTransport Engineering and Logistic

Operational data-driven energy performance assessment of ships: the case study of a naval vessel with hybrid propulsion

Ship designers hardly ever receive feedback from the actual operation of their designs apart from sea acceptance trials. Similarly, crews operating the vessels do not receive a clear picture of the energy performance and environmental footprint of different options. This paper proposes a methodology based on operational data from continuous monitoring, and applies it to an ocean patrol vessel of the Royal Netherlands Navy in order to identify the impact of diverse operational conditions on energy performance over the whole operating range, but also to examine the decision to equip the vessel with hybrid propulsion. Specifically, it introduces mean energy effectiveness indicator and mean total energy efficiency over discretised vessel speed, as the main tool in quantifying the energy gains and losses to assist in making better-advised design and operational decisions. Moreover, it demonstrates a dataset enrichment procedure, using manufacturers' information, in case not all needed sensors are available. Results suggest that electrical propulsion was 15–25% less efficient than the best mechanical propulsion mode, and on the overall energy performance of the vessel, increasing speed by 1 knot caused a 7% and 14% increase over the minimum (Formula presented.) /mile emissions between 8 and 14, and above 14 knots respectively.Ship Design, Production and Operation

Energy transition for the replacement Air Defense and Command Frigate

Progressing targets on Greenhouse Gas (GHG) emission reduction urge the Netherlands Ministry of Defense (NL MoD) to reduce GHG emissions, without sacrificing striking power. The Royal Netherlands Navy (RNLN) is investigating the replacement of the Air Defense and Command Frigate (LCF) between 2030 and 2040 by a Large Surface Combatant. As it will be impossible to achieve substantial reduction of GHG emissions through energy-saving technologies, sustainable fuels need to be implemented in the design. In this paper, a literature review is presented to establish possible directions for the strategy to migrate future naval combatants from current fossil fuels to future sustainable fuels. We examined the effect of short- and long-carbon chain sustainable fuels, sustainable methanol and sustainable diesel, respectively, on the replacement Large Surface Combatant; specifically their advantages, disadvantages, production routes, future production cost estimates and availability to give an understanding which pathways can help the NL MoD to achieve their stated GHG emissions reduction goals. Moreover, we present three different design concepts with respect to fuel composition and propulsion configuration on which the impact of the established fuels is qualitatively examined. Firstly, operating on methanol has a significant impact on the design of a large surface combatant: the endurance of the ship is more than halved or the tank capacity has to be increased by 700 to 900 m3 ; the ship might need a longer machinery space to allow for more propulsion engines to compensate for the increased power requirement and unavailability of gas turbines on methanol; and required auxiliary and safety systems add further volume area to the engine room. Secondly, sustainable diesel is a drop-in fuel, which makes blending of sustainable diesel with fossil diesel possible in the existing infrastructure allowing a gradual transfer from fossil diesel to sustainable diesel. However, the production is less efficient in a well-to-wake approach and the cost of Bio-diesel and E-diesel is 5% to 30% more expensive with a mean estimated additional cost of 6 C/GJ compared to methanol. Finally, navies could consider a two-fuel strategy: sail on methanol during operations with limited autonomy, typically in peace time, and operate on diesel during operations with high autonomy, during war time operations. In this case the design needs to include both diesel and methanol fuel systems and additional space for methanol safety measures. In order to more exactly quantify the impact of methanol on the design, a concept design iteration is required, which is identified as research for future work.Ship Design, Production and Operation

A digital twin approach for maritime carbon intensity evaluation accounting for operational and environmental uncertainty

Maritime industry has set ambitious goals to drastically reduce its greenhouse gas emissions through stipulating and enforcing a number of energy assessment measures. Unfortunately, measures like the EEDI, EEXI, SEEMP and CII do not account for the operational and environmental uncertainty of operations at sea, even though they do provide a first means of evaluating the carbon footprint of ships. The increasing availability of high-frequency operational data offers the opportunity to quantify and account for this uncertainty in energy performance predictions. Current methods to evaluate and predict energy performance at a whole energy system level do not sufficiently account for operational and environmental uncertainty. In this work, we propose a digital twin that accurately predicts the fuel consumption and carbon footprint of the hybrid propulsion system of an Ocean-going Patrol Vessel (OPV) of the Royal Netherlands Navy under the aggregate effect of operational and environmental uncertainty. It combines first-principle steady-state models with machine learning algorithms to reach an accuracy of less than 5% MAPE on both mechanical and electrical propulsion, while bringing a 40% to 50% improvement over a model that does not utilise machine learning algorithms. Results over actual voyage intervals indicate a prediction accuracy of consumed fuel and carbon intensity within 2.5% accounting for a confidence interval of 95%. Finally, the direct comparison between mechanical and electrical propulsion showed no clear energy-saving benefits and a strong dependency of the results on each voyage's specific operational and environmental conditions.Ship Design, Production and Operation

Transient performance of alternatively fueled internal combustion engines for naval applications

Navies worldwide are exploring the use of alternative fuels for their vessels, aiming to cut down greenhouse gas emissions and lessen their reliance on fossil fuels. This effort also seeks to reduce their environmental impact and emissions signatures. However, combustion engines running on low reactivity fuels, including most alternative fuels like natural gas or alcohols, are limited by their lower load acceptance compared to diesel engines. As a result, they may not meet the stringent naval requirements for dynamic load capacity in power generation. A high dynamic loading capacity is a precondition for high maneuverability of the vessel on the one hand and handling of pulsed power loads and step loads caused by rail-guns and directed energy weapons on the other hand. Previous research into the dynamic response of natural gas engines required detailed in-cylinder combustion models to predict knock. These 0D/1D simulation models rely on extensive data to calibrate the combustion model, which is generally unavailable to the naval engineer designing a propulsion or energy system. Additionally, these simulation models require a significant amount of computational power and do rarely run in real-time. This study predicts the dynamic response using a Mean Value First Principle (MVFP) engine model based on the filling and emptying approach and turbocharger performance maps derived from limited data and measurements. Initially, the model is calibrated using engine data provided by the manufacturer and experimental measurements in steady state on a spark-ignited Caterpillar 3508A gas engine driving a generator at a constant speed of 1500 rpm. Additional calibrations are performed using experimental measurements of the dynamic response to step loads. Analysis of the simulation results reveals the model’s capability to predict the dynamic response of the air intake and exhaust system while being able to run in real-time. The results further show that steady-state simulations do not consider the effect of turbocharger inertia and lagging fresh air supply on the thermal loading and knock probability of the engine sufficiently. This paper underlines the significance of implementing the air and exhaust path dynamics, including turbocharger performance models, in mean-value models when investigating combustion engines operating on low reactivity fuels. Furthermore, the paper provides guidance on the minimum required number of measurements and load steps to calibrate a mean value model for the prediction of the engine operating parameters under dynamic loads. The resulting model can be used to establish limitations for the loads on the electric grid and evaluate control strategies to improve the combustion engine generator and electrical systems’ performance.Ship Design, Production and Operation

Hybrid Modelling Approach of a Four-stroke Medium Speed Diesel Engine

Diesel engines will remain a fundamental component of propulsion systems due to their maturity, reliability, and power density. Building Digital Twins of the propulsion system is one feasible solution to pursue the optimal propulsions system operation, estimating system states and efficiency. This work will investigate a modelling approach that combines high accuracy while satisfying real-time prediction capabilities by coupling a physics-based model with a data-driven modelling approach. We will demonstrate that the proposed hybridisation framework can provide state-of-the-art prediction capabilities in real-time, utilising operational data from a turbocharged, four-stroke medium-speed diesel engine

Artificial Intelligence-based short-term forecasting of vessel performance parameters

Deterministic models based on the laws of physics, as well as data-driven models, are often used to assess the current state of vessels and their systems, as well as predict their future behaviour. Predictive maintenance methodologies (i.e., Condition Based Maintenance), and advanced control strategies (i.e., Model Predictive Control), are built upon the use of such numerical tools to identify ensuing performance shifts. In fact, near-future performance prediction can substantially contribute to enhancing operational efficiency and enabling advanced system control. Data from modern sensor technology, which has been becoming more readily available, combined with automatic control systems able to prescribe optimal control strategies can enhance vessel operation and reduce energy consumption. A data-driven model that relies on recent advances in Artificial Intelligence, Machine Learning, and Data Mining, leveraging historical observations is employed to forecast a vessel's onboard power generation trends as a function of the past, present, and future behaviour of a ship and its systems. In order to prove the framework, the proposed methodology is tested on real data collected from the Integrated Platform Management System of an Oceangoing Patrol Vessel of the Royal Netherlands Navy. The developed data-driven model is observed to achieve high forecasting accuracy in the near-term. The authors foresee that the proposed methodology could be used as part of an electric energy control strategy, within a more integrated and intelligent mission planning framework