EP4039579A1

EP4039579A1 - Propulsive power estimator

Info

Publication number: EP4039579A1
Application number: EP21155512.3A
Authority: EP
Inventors: Miltiadis Kalikatzarakis
Original assignee: Damen 40 BV
Current assignee: Damen 40 BV
Priority date: 2021-02-05
Filing date: 2021-02-05
Publication date: 2022-08-10

Abstract

Methods and systems are disclosed for determining a power distribution of a propulsion system of a vessel with a propeller and a hull, the propulsion system comprising a plurality of power sources, preferably hybrid power sources, for powering one or more engines for driving the propeller. The method may comprise receiving a shaft speed set-point (302) defining a target rotational speed or target effective rotational speed of the propeller. The method may further comprise determining an advance ratio (306) of the propeller based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull, determining a propeller torque parameter (310), preferably a propeller torque or a propeller torque coefficient based on the shaft speed set-point and the advance ratio, and determining a predicted load (312) based on the determined propeller torque parameter, the predicted load defining an estimated load of the propeller when rotating at the shaft speed set point. The method may further comprise determining a power distribution based on the predicted load. Determining a power distribution may comprise selecting a power source, the power distribution defining an amount of power to be delivered by each of the plurality of power sources.

Description

Field of the invention

The disclosure relates to vehicle energy management, and in particular, though not exclusively, to methods and systems for estimating a propulsive power and a computer program product enabling a computer system to perform such methods.

Background

Hybrid power systems are system comprising different power sources, typically an energy storage device such as a battery and a combustion engine. Hybrid power systems have been successfully implemented in vehicles, e.g. cars, vessels, and trains, to reduce fuel consumption and local emissions (e.g. in heavily populated areas).
Typically, a hybrid power system comprises a controller that selects one or more power sources based on at least the current power demand. Conventionally, these controllers were rules-based. More advanced systems may use an optimisation algorithm, e.g. an Equivalent Consumption Minimisation Strategy, which may result in a higher fuel efficiency than a rules-based controller.
However, energy management systems in ships usually assume steady state conditions. Consequently, they do not work, or at least do not work very well, during acceleration (including deceleration) periods. Instead, when a command setting a shaft speed is received, existing systems typically only reoptimize the power distribution when the speed has been attained. However, on large vessels, an acceleration period may have a duration of several minutes. During this period, the distribution of the power supply over the plurality of power sources may not be optimized. It is therefore desirable to provide a method to enable fuel minimisation during acceleration periods.
Diju Gao et al., "An energy optimization strategy for hybrid power ships under load uncertainty based on load power prediction and improved NSGA-II algorithm," Energies 2018, 11, 1699 describes load forecasting based on historical load data by applying a load power prediction model based on a multi-resolution analysis of a wavelet neural network (MRA-WNN). The modelled load cycle comprises acceleration, constant speed, and deceleration phases. Subsequently, multi-objective optimisation is performed using an improved non-dominated sorting genetic algorithm II (NSGA-II).
However, this kind of modelling is essentially only suitable for ships with a mostly repetitive load cycle, such as ferries or water buses, where the power distribution may be optimised over a typical load cycle. The method is not very suitable for ships with a more variable load, that is not as predictable based on historical data.
Therefore, there is a need in the art to provide a method for determining an energy strategy of a hybrid power system that further reduces fuel consumption.

Summary

It is an aim of the embodiments in this disclosure to eliminate, or at least reduce one or more of the drawbacks known in the art. It is furthermore an aim of the embodiments in this disclosure to provide a method to reduce fuel consumption of a hybrid power system.
In an aspect, the invention may relate to a method for determining a power distribution of a propulsion system of a vessel with a propeller and a hull, the propulsion system comprising a power system comprising a plurality of power sources for powering one or more engines for driving the propeller. Preferably, the power system is a hybrid power system. The method may comprise receiving a shaft speed set-point defining a target rotational speed or target effective rotational speed of the propeller. The method may further comprise determining a predicted load defining an estimated load of the propeller when rotating at the shaft speed set point, based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull. The method may further comprise determining a power distribution based on the predicted load, the power distribution defining an amount of power to be delivered by each of the plurality of power sources. Determining a power distribution may comprise selecting one or more of the plurality of power sources.
A hybrid power system may be understood as a system comprising different power sources, typically electrical power sources, such as a battery pack, and fuel-based power sources, such as combustion engines.
Thus, a load may be predicted based on the shaft speed set-point and a priori known parameters, such as intrinsic properties of the propeller, typically a screw propeller, the ship hull, and optionally the engines. These properties, or parameters derived from these properties, are typically determined during design of the vessel. The predicted load may be used to determine a power distribution, e.g. selecting one or more power sources of the propulsion system. Determining a power distribution may comprise using the predicted load during optimization of the power distribution by e.g. an energy management system, preferably using the predicted load as a constraint or boundary condition. This way, the optimization may take future power requirements into account. This allows to exclude unwanted solutions, e.g. solutions that might be more efficient on the short term but are less efficient on the long term, thus improving the long-term results of the optimization. Thus, the method may lead to a reduced fuel consumption.
By implementing the predicted load, the system may, at least up to a point, distinguish between e.g. a change in (current) load due to changed environmental circumstances such as the weather of currents, and a change due to a change in shaft speed set-point. By contrast, a system that only optimises fuel consumption based on the momentaneous load, cannot take the longer term into account. As an example, in case of an acceleration, a system without a predicted load might decide to deplete the batteries to deal with the increased power demand and only increase the power of the main engine when the batteries are empty; while a system with load prediction might immediate increase the power of the main engine to that required after the acceleration, and only use battery assistance during the acceleration phase.
In an embodiment, determining a predicted load may comprise determining an advance ratio of the propeller based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; and determining the predicted load based on the determined advance ratio.
The advance ratio of a propeller may be understood as the ratio of the freestream fluid speed to the propeller tip speed.
In an embodiment, determining an advance ratio may comprise determining an advance ratio for which a thrust coefficient of the propeller is equal to a thrust coefficient of the vessel, the thrust coefficients preferably being expressed as functions of the advance ratio and the propeller pitch divided by the propeller diameter.
In an embodiment, determining a predicted load may further comprise determining a propeller torque parameter based on the shaft speed set-point and the advance ratio, the propeller torque parameter preferably defining a propeller torque or a propeller torque coefficient; and determining the predicted load based on the determined propeller torque parameter.
In an embodiment, each of the one or more engines may be associated with an engine operating envelope, and determining a predicted load may comprise comparing the predicted load to a combination of the respective engine operating envelopes of the one or more engines at the current shaft speed, and if the predicted load exceeds a predetermined threshold based on the combination of the respective engine operating envelopes, limiting the predicted load such that it does not exceed the predetermined threshold.
This way, unfeasible solutions may be filtered out, improving the optimisation result. The predetermined threshold may be equal to the maximum provided power by the one or more engines.
In an embodiment, the propeller may be an adaptive pitch propeller, and the method may further comprise determining a pitch set-point based on the shaft speed set-point, and, optionally, an effective shaft speed set-point based on the shaft speed set-point and the pitch set-point. Determining an advance ratio may comprise determining an advance ratio based on the pitch set-point and, optionally, the effective shaft speed set-point.
This way, the effect of pitch adjustment on shaft speed and (predicted) required power may be taken into account.
In an embodiment, the method may further comprise controlling at least one of the plurality of power sources to deliver power based on the determined power distribution.
In an embodiment, determining a power distribution may further comprise minimizing a fuel consumption and/or an equivalent fuel consumption by the one or more power sources based on the predicted load, and determining a power distribution based on a minimum fuel consumption and/or a minimum equivalent fuel consumption.
In an embodiment, the minimum fuel consumption and/or minimum equivalent fuel consumption may be determined using a non-convex optimisation algorithm, preferably a Mesh Adaptive Direct Search algorithm. Although in general any type of non-convex solver may be used, this type of algorithm has been found to be efficient for solving the optimisation problem.
In a further aspect, embodiments of this disclosure may relate to a controller for a power system comprising a plurality of power sources, preferably a hybrid power system comprising hybrid power sources, e.g. one or more main engines, one or more electric-power generators, and one or more energy storage devices such as battery packs. The power system may be configured to power a propulsion plant of a vessel, preferably a marine vessel. The vessel may comprise a hull. The propulsion plant may be configured to drive a propeller, preferably a screw propeller. The controller may comprise a computer readable storage medium having computer readable program code embodied therewith, and a processor, preferably a microprocessor, coupled to the computer readable storage medium. Responsive to executing the computer readable program code, the processor may be configured to perform executable operations comprising: receiving a shaft speed set-point defining a target rotational speed or target effective rotational speed of the propeller; determining an advance ratio of the propeller based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; determining a propeller torque parameter, preferably a propeller torque or a propeller torque coefficient, based on the shaft speed set-point and the advance ratio, and determining a predicted load based on the determined propeller torque parameter. The executable operations may further comprise determining a power distribution, e.g. selecting one or more power sources, based on the predicted load.
In further embodiments, the executable operations may comprise any of the process steps described above.
In an aspect, embodiments of this disclosure may relate to a power system, preferably a hybrid power system comprising hybrid power sources, e.g. one or more main engines, preferably combustion engines, one or more induction motors, one or more electric-power generators, and one or more energy storage devices such as battery packs. The power system may be configured to power a propulsion plant of a vessel, preferably a marine vessel. The vessel may comprise a hull. The propulsion plant may be configured to drive a propeller, preferably a screw propeller. The controller may comprise a computer readable storage medium having computer readable program code embodied therewith, and a processor, preferably a microprocessor, coupled to the computer readable storage medium. Responsive to executing the computer readable program code, the processor may be configured to perform executable operations comprising: receiving a shaft speed set-point defining a target rotational speed or target effective rotational speed of the propeller; determining an advance ratio of the propeller based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; determining a propeller torque parameter, preferably a propeller torque or a propeller torque coefficient, based on the shaft speed set-point and the advance ratio, and determining a predicted load based on the determined propeller torque parameter. The executable operations may further comprise determining a power distribution, e.g. selecting one or more power sources, based on the predicted load.
In a further aspect, embodiments of this disclosure may relate to a vessel, preferably a marine vessel, comprising a hybrid propulsion system as described above.
In a further aspect, the invention may also relate to a computer program product comprising software code portions configured for, when run in the memory of a computer, executing the method steps according to any of the process steps described above.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," "module" or "system". Functions described in this disclosure may be implemented as an algorithm executed by a microprocessor of a computer. Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied, e.g., stored, thereon.
Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non- exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fibre, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can comprise, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fibre, cable, RF, etc., or any suitable combination of the foregoing. Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including a functional or an object oriented programming language such as Java(TM), Scala, C++, Python or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer, server or virtualized server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor, in particular a microprocessor or central processing unit (CPU), or graphics processing unit (GPU), of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer, other programmable data processing apparatus, or other devices create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The invention will be further illustrated with reference to the attached drawings, which schematically will show embodiments according to the invention. It will be understood that the invention is not in any way restricted to these specific embodiments.

Brief description of the drawings

Fig. 1 depicts a schematic overview of a hybrid propulsion system according to an embodiment of the invention;
Fig. 2 schematically depicts a control system for a hybrid power supply according to an embodiment of the invention;
Fig. 3 schematically depicts a method for predicting a load for a propulsion system;
Fig. 4 depicts an example of an energy optimisation routine according to an embodiment of the invention;
Fig. 5A-C depict the effect of a propulsive power estimator on the power distribution and fuel consumption; and
Fig. 6 is a block diagram illustrating an exemplary data processing system that may be used for executing methods and software products described in this disclosure.

Detailed description

In this disclosure embodiments are described for predicting a load of a hybrid power system, typically in response to receiving a new shaft speed set-point. Based on the predicted load an efficient power distribution may be determined.
Fig. 1 depicts a schematic overview of a hybrid propulsion system according to an embodiment of the invention. The hybrid propulsion system 100 comprises a main engine 102, for example an internal combustion engine such as a Diesel engine or gas turbine, connected to a propeller 104 via a shaft 103. The main engine is arranged to power the propeller and may comprise or be connected to a gearbox (not shown). The propeller is preferably a screw propeller and may be a fixed pitch propeller or a variable pitch propeller.
An asynchronous motor or induction motor 106 is also coupled to the propeller and typically acts on the shaft 103. The induction motor may be electrically connected to a switchboard 110 via one or more transformers and/or AC/DC converters 108_1-2 . The switchboard may further electrically connect an energy storage device 112, e.g. a battery pack, one or more electric-power generators 116_1-2 , e.g. Diesel generators, and other electric loads, e.g. so-called hotel loads 118. Hotel loads may refer to any electrical loads not used for propulsion, e.g. for lighting, climate control, or communication. The energy storage device may be connected to the switchboard via an AC/DC converter 114.
Depending on the configuration, the one or more power generators may be arranged to provide hotel electric power, to charge the energy storage device, and/or to power the induction motor. In some embodiments, there may be no electric-power generators. In such and other embodiments, electric power for charging the energy storage device may (additionally) be provided by e.g. the main engine and absorbed by the induction engine coupled to the same shaft, and/or by absorbing breaking energy. In some embodiments, there may be no main engine, and the propeller may only be powered by the induction motor.
The hybrid propulsion system may comprise further mechanical and/or electrical components for further controlling the propulsion. In some embodiments, the hybrid propulsion system may also comprise one or more additional main engines and/or one or more additional propellers. In some embodiments, each propeller may be powered by a plurality of main engines.
A controller 120 is communicatively connected to one or more elements of the hybrid propulsion system to control one or more aspects of the propulsion system, such as a state, e.g. the rotational speed, of the main engine, the charging or discharging of the energy storage device, a state of the one or more electric-power generators, et cetera.
The controller may comprise a computer readable storage medium having computer readable program code embodied therewith, and a processor, preferably a microprocessor, coupled to the computer readable storage medium. Responsive to executing the computer readable program code, the processor may be configured to perform executable operations for predicting a load and/or determining a power distribution. The power distribution may define how much power one or more components of the power system (e.g. main engine, induction motor, energy storage device and electric-power generators) may provide and/or absorb.
Fig. 2 schematically depicts a control system for a hybrid power supply according to an embodiment of the invention. The control system 200 may receive first input data 202 comprising information associated with a desired state of the hybrid power system, for example, a shaft speed set-point indicating a desired shaft speed that is set by an operator. The control system may also receive second input data 204 comprising information about the current state of the hybrid power system, for example the current shaft speed, the state of charge of an energy storage device, the hotel load and the power supply by one or more electric-power generators. The second input data may be provided continuously or periodically, and/or may be retrieved on request.
In some embodiments, the control system may comprise an adaptive pitch control subsystem 206, for example if the system is employed on a vessel comprising an adaptive pitch propeller. The adaptive pitch control subsystem may receive one or more parameters from the first and/or second input data, such as the shaft speed set-point and the current engine speed, as input. The adaptive pitch control subsystem may interpret the received shaft speed set-point as a virtual or effective shaft speed set-point. The adaptive pitch control subsystem may provide a pitch ratio and, optionally, an actual shaft speed set-point as output.
Virtual shaft speed (n _virt) for an adaptive pitch propeller is a compound variable that contains both actual shaft speed, and actual pitch. Virtual shaft speed may be defined as: $n_{virt} = \frac{P_{pd} - P_{pd, 0}}{P_{pd, nom} - P_{pd, 0}} n_{ME, set}$
where P _pd,0 and P _pd,nom stand for the zero-thrust and nominal pitch angle, respectively, P _pd is the current pitch angle, and n _ME,set is the engine speed set point. In static conditions, the virtual shaft speed is almost linearly related to ship speed, which allows for an intuitive use by operators, such as watch keepers.
Thus, in an embodiment, the operator-received shaft speed set-point may be a virtual shaft speed set-point. The adaptive pitch control subsystem 206 may extract an actual engine speed set point from the current pitch and the virtual shaft speed set-point, based on the zero-thrust and nominal pitch angles. The adaptive pitch control may be implemented as described in R. Geertsma et al., 'Adaptive pitch control for ships with Diesel mechanical and hybrid propulsion', Applied Energy (2018) pages 2490-2509, which is hereby incorporated by reference.
Based on this implementation, the adaptive pitch control may ensure optimal utilization of a controllable pitch propeller so as to reduce fuel consumption by keeping the operating point of the propeller at the maximum open water efficiency; increase accelerations and provide a more consistent acceleration time without thermally overloading the engine; reduce cavitation risk for propellers designed for low cavitation; and eliminate a need for the operator to switch between fuel efficient or maneuverable mode.
Other embodiment may not implement an adaptive pitch control subsystem. In these embodiment, a pitch set-point may be determined e.g. by using fixed combinator curves, or a constant pitch may be used, in particular for a vessel with fixed pitch propellers.
Based on one or more of the received parameters, a propulsive power estimator 208 may determine an estimate of the power required to achieve the desired state. The propulsive power estimator will be discussed in more detail below with reference to Fig. 3 . In general, the propulsive power estimator may receive the (actual or virtual) shaft speed set-point and, when applicable, the pitch ratio as input, and may provide an estimated power requirement as output. The propulsive power estimator may further use stored data 212, such as design data, for its computations.
The output of the propulsive power estimator may be used by an optimiser 210 to determine a power distribution 214 defining the distribution of the required power over the power sources of the hybrid power supply. The power distribution may comprise quantities such as an energy storage device discharge current, rotational speeds for main engine and/or electric-power generators, and an induction motor torque. The optimiser will be discussed in more detail below with reference to Fig. 4 .
Fig. 3 schematically depicts a method for predicting a load for a propulsion system. The propulsion system may comprise a plurality of power sources, preferably hybrid power sources, for powering one or more engines for driving a propeller or other propulsion mechanism. In an embodiment, the propeller is a variable pitch propeller. For example, the propulsion system may be a hybrid power, hybrid propulsion system as discussed with reference to Fig. 1. The propulsion system may be configured to propel a vessel, preferably a marine vessel. The vessel may comprise a hull.
In a first step 302, a new shaft speed set-point n _set may be received. The new shaft speed set-point may define a target rotational speed or target effective rotational speed of the propeller. Thus, depending on the propulsion system, new shaft speed set-point n _set may be an actual shaft speed set-point or a virtual shaft speed set-point, e.g. in the case of a variable pitch propulsion system.
In an optional step 304, a new propeller pitch p _set, based on the new shaft speed set-point may be determined or received. Based on the new shaft speed set-point n _set and, optionally, the new propeller pitch p _set, a new advance ratio J _set may be determined 306 for the propeller. The new advance ratio J _set may furthermore be determined based on one or more design parameters of the propeller and/or of the hull.
In an embodiment, determining the new advance ratio J _set may comprise determining 308 the advance ratio J for which the thrust coefficient of the propeller K _t,prop(J) is equal to the thrust coefficient of the vessel K _t,ship(J), or equivalently, where: $K_{t, prop} (J) - K_{t, ship} (J) = 0.$
The thrust coefficients are preferably expressed as functions of the advance ratio and the propeller pitch divided by the propeller diameter. This determination may be based on the respective open-water diagrams, which are typically determined during the design phase of a vessel or propeller, and which may be stored in a memory coupled to the load predicting system. The determination of J may assume steady-state conditions.
In a next step 310, a new propeller torque or new propeller torque coefficient K _Q,set may be determined based on the determined new advance ratio J _set and the new shaft speed set-point n _set. Subsequently, a load may be predicted 312 based on the new propeller torque or new propeller torque coefficient K _Q,set and the new shaft speed set-point n _set. The predicted load may further depend on one or more additional parameters, preferably design parameters such as the diameter of the propeller D, the gearbox reduction rate i, the transmission efficiency η _TRM, the relative rotative efficiency η _R, and the resistance curve (typically expressed as R/v _s ², R being the hull resistance and v _s the vessel speed) or known (or estimated) parameters such as the density of (sea) water ρ. These parameters may be stored in a memory coupled to the load predicting system.
In an embodiment, the propeller power P _prop may be determined by computing: $P_{prop} = \frac{2 πρ D^{5}}{η_{R}} {(\frac{n_{set}}{i})}^{3} K_{Q, set}$
and the corresponding predicted power P _pred may be determined by computing: $P_{pred} = P_{sh} = \frac{P_{prop}}{k_{e} η_{TRM}}$
where k _e is the number of main engines connected to each propeller shaft, and the other symbols have the meaning defined above.
In an embodiment, each of the one or more engines and/or motors is associated with an engine operating envelope. In an optional extra step, the predicted load may be adjusted, typically limited, by comparing 314 the predicted load to a combination of the respective engine operating envelopes of the one or more engines at the current shaft speed. The combination of the respective operating envelopes may represent a maximum load that may be provided by the power supply. If the predicted load exceeds a predetermined threshold based on the combination of the respective engine operating envelopes, the predicted load may be adjusted 316, preferably limiting the predicted load such that it does not exceed the predetermined threshold. This way, unfeasible solutions may be filtered out, improving the result of the prediction.
Based on the predicted load, a power distribution may be determined, e.g. selecting one or more power sources for powering the propeller. Selecting one or more power sources may comprise solving an optimisation problem, e.g. a fuel consumption minimalization problem.
Fig. 4 depicts an example of an energy optimisation routine according to an embodiment of the invention. An energy optimisation routine typically receives operator input data 402, such as parameters are set by a controller, e.g. a desired shaft speed n _set. The energy optimisation routine may further receive system input data 404, such as dynamically determined parameters representing a state of the power system, e.g. a state of charge of the energy storage device and an amount of electric power required by the hotel. These parameters may affect the desired output of the hybrid power system.
The energy optimisation routine may further have access to a data storage 406 comprising parameters and/or functions describing the hybrid power system, such as the number and types of engines, the power-specific fuel consumptions of the one or more main engines sfc ⁱ _ME(P, n) and the electric-power generators sfs ^j _DG(P), and the efficiency of the induction motor as a function of power and/or rotational speed. The data storage may further information defining an equivalent power-specific fuel consumption of the energy storage device which may be determined by any suitable method, for example as described in European patent application EP21 155 425 .
In some embodiments, the operator input data and/or the system input data may be pre-processed 408 by a pre-processor, which may provide derived input data 410 as output. For example, in a vessel with an adaptive pitch propeller, the pre-processor may determine a new propeller pitch which may affect the relation between required power and shaft speed, and thus the efficiency of the main engine. The pre-processor may also determine a predicted power demand P _pred.
Based on the predicted power demand P _pred, and, typically, operator input data, system input data and other derived input data, as well as, usually, on parameters or functions from the data storage, the optimiser may determine 412 one or more boundary conditions or constraints, limiting the solution space to ensure viable solutions and, preferably, decrease the computational burden. For example, the solutions may be limited such that the power provided by the main engine(s) and electric-power generator(s) does not exceed their respective maximum provided power. Thus, constraints may be used to prevent overloading, to ensure sufficient electric power for the hotel at a predetermined voltage and frequency, et cetera. The solution space may be constrained based on the predicted load, thus guiding the optimiser to long-term optimal solutions, which may be different from short-term optimal solutions. For example, the induction motor power may be constrained based on the predicted load: $P_{IM, set} (t) \leq P_{pred} (t) \leq P_{ME, \max} (n_{ME, set}) + P_{IM, set} (t)$
Based on the operator input data and/or the system input data and, optionally, the derived input data, as well as, optionally, on parameters or functions from the data storage, the optimiser may determine 414 a target function may be determined. Typically, the object of the optimiser is to minimise the (equivalent) fuel consumption of the hybrid power system while providing the desired power to satisfy the hotel needs and set shaft speed. In an embodiment, the object function may be formulated as: $\min ({\dot{m}}_{f} (t)) = \min (\sum_{i = 1}^{N_{ME}} {\dot{m}}_{f, {ME}_{i}} (t) + \sum_{j = 1}^{N_{DG}} {\dot{m}}_{f, {DG}_{j}} (t) + {\dot{m}}_{f, BAT} (t))$
where ṁ_f (t) is the total (equivalent) fuel consumption rate of the hybrid power system, which in a typical system is equal to the sum of fuel consumption rates of the main engines and the electric-power generators and the equivalent fuel consumption rate of the energy storage device. Here, ṁ_f,MEi (t) is the fuel consumption rate of the i ^th of the N_ME main engines, ṁ_f,DGj (t) is the fuel consumption rate of the j ^th of the N_DG electric-power generators, and ṁ _f,BAT(t) is the equivalent fuel consumption rate of the energy storage device, based on the equivalent power-specific fuel consumption defined above. In general, the fuel consumption rate is proportional to the delivered power multiplied with the power-specific fuel consumption. In the example depicted in Fig. 1 , N_ME = 1 and N_DG = 2. In other embodiments, there may be a plurality of energy storage devices, in which case the last term in equation (6) would be a summation over all such devices.
An optimisation algorithm may then optimise 416, for example minimise, the target function subject to the determined boundary conditions. In general, the optimiser may use any non-convex optimiser, for example an optimiser based on the Mesh Adaptive Direct Search algorithm. The Mesh Adaptive Direct Search algorithm is described in more detail in C. Audet & J. Dennis, 'Mesh adaptive direct search algorithms for constrained optimization', SIAM Journal on Optimization (2006) 188-217.
Based on the output of the optimiser, one or more power distributions 418 may be determined, for instance a propulsive power distribution defining a power split between the main engine(s) and the induction engine(s), and/or an electric power distribution defining a power split between the energy storage device and the electric-power generator(s). One or more power sources may then be selected based on at least one of the power distributions.
As was explained above, the (long-term) optimal power distribution can only be determined with hindsight, as it depends on future events. A common way in the art to determine the quality of an optimisation routine is to determine one or more sample trajectories and determine the optimal (typically, minimal) fuel consumption taking the entire trajectory into account. This may be achieved using a method named Dynamic Programming. Actual optimisation routines may have knowledge of current conditions and of past conditions, but lack knowledge of future power demands. The quality of a routine may then be determined by comparing the fuel consumption according to the routine to the optimal fuel consumption according to dynamic programming. Similarly, other quantities such as state of charge of the energy storage device may be plotted.
Fig. 5A-C depict the effect of a propulsive power estimator on the power distribution and fuel consumption. In particular, Fig. 5A-B depict the power distribution of a vessel comprising two variable pitch propellers, each propeller being connected to a main engine with a maximum power output of 10 MW. Each propeller is furthermore connected to an induction motor, and the induction motors are connected to a switchboard. The switchboard is connected to a battery pack with a capacity of 2000 kWh and a maximum power supply of 6 MW, and to four Diesel generators, each having a maximum power supply of 2,5 MW. Initially, the shaft speed set-point = 0.7 times the maximum shaft speed. After 120 s (indicated with a vertical line), the shaft speed set-point is increased to 1.0 times the maximum shaft speed.
Fig. 5A depicts the power distribution resulting from a state-of-the-art rules-based system. Fig. 5B depicts the power distribution using the propulsive power estimator as described above with reference to Fig. 3 to select the one or more power sources. Fig. 5C depicts the resulting relative fuel consumption, where the dashed line denotes the state-of-the-art rules based system and the continuous line denotes the propulsive-power-estimator-based system. It can be clearly seen that using the propulsive power estimator leads to a reduced fuel consumption.
Fig. 6 is a block diagram illustrating an exemplary data processing system that may be used in as described in this disclosure. Data processing system 600 may include at least one processor 602 coupled to memory elements 604 through a system bus 606. As such, the data processing system may store program code within memory elements 604. Further, processor 602 may execute the program code accessed from memory elements 604 via system bus 606. In one aspect, data processing system may be implemented as a computer that is suitable for storing and/or executing program code. It should be appreciated, however, that data processing system 600 may be implemented in the form of any system including a processor and memory that is capable of performing the functions described within this specification.
Memory elements 604 may include one or more physical memory devices such as, for example, local memory 608 and one or more bulk storage devices 610. Local memory may refer to random access memory or other non-persistent memory device(s) generally used during actual execution of the program code. A bulk storage device may be implemented as a hard drive or other persistent data storage device. The processing system 600 may also include one or more cache memories (not shown) that provide temporary storage of at least some program code in order to reduce the number of times program code must be retrieved from bulk storage device 610 during execution.
Input/output (I/O) devices depicted as input device 612 and output device 614 optionally can be coupled to the data processing system. Examples of input device may include, but are not limited to, for example, a keyboard, a pointing device such as a mouse, or the like. Examples of output device may include, but are not limited to, for example, a monitor or display, speakers, or the like. Input device and/or output device may be coupled to data processing system either directly or through intervening I/O controllers. A network adapter 616 may also be coupled to data processing system to enable it to become coupled to other systems, computer systems, remote network devices, and/or remote storage devices through intervening private or public networks. The network adapter may comprise a data receiver for receiving data that is transmitted by said systems, devices and/or networks to said data and a data transmitter for transmitting data to said systems, devices and/or networks. Modems, cable modems, and Ethernet cards are examples of different types of network adapter that may be used with data processing system 600.
As pictured in Fig. 6 , memory elements 604 may store an application 618. It should be appreciated that data processing system 600 may further execute an operating system (not shown) that can facilitate execution of the application. Application, being implemented in the form of executable program code, can be executed by data processing system 600, e.g., by processor 602. Responsive to executing application, data processing system may be configured to perform one or more operations to be described herein in further detail.
In one aspect, for example, data processing system 600 may represent a client data processing system. In that case, application 618 may represent a client application that, when executed, configures data processing system 600 to perform the various functions described herein with reference to a "client". Examples of a client can include, but are not limited to, a personal computer, a portable computer, a mobile phone, or the like.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

A method for determining a power distribution of a propulsion system of a vessel with a propeller and a hull, the propulsion system comprising a power system comprising plurality of power sources for powering one or more engines for driving the propeller, the power system preferably being a hybrid power system, the method comprising:
receiving a shaft speed set-point defining a target rotational speed or target effective rotational speed of the propeller;

determining a predicted load defining an estimated load of the propeller when rotating at the shaft speed set point, based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; and

determining a power distribution based on the predicted load, the power distribution defining an amount of power to be delivered by each of the plurality of power sources.
The method as claimed in claim 1, wherein determining a predicted load comprises:
determining an advance ratio of the propeller based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; and

determining the predicted load based on the determined advance ratio.
The method as claimed in claim 2, wherein determining an advance ratio comprises:
determining an advance ratio for which a thrust coefficient of the propeller is equal to a thrust coefficient of the vessel, the thrust coefficients preferably being expressed as functions of the advance ratio and the propeller pitch divided by the propeller diameter.
The method as claimed in claim 2 or 3, wherein determining a predicted load further comprises:
determining a propeller torque parameter based on the shaft speed set-point and the advance ratio, the propeller torque parameter preferably defining a propeller torque or a propeller torque coefficient; and

determining the predicted load based on the determined propeller torque parameter.
The method as claimed in any one of claims 2-4, wherein the propeller is an adaptive pitch propeller, the method further comprising:
determining a pitch set-point based on the shaft speed set-point, and, optionally, an effective shaft speed set-point based on the shaft speed set-point and the pitch set-point; and

wherein determining an advance ratio comprises determining an advance ratio based on the pitch set-point and, optionally, the effective shaft speed set-point.
The method as claimed in any one of the preceding claims, wherein each of the one or more engines is associated with an engine operating envelope, and wherein determining a predicted load comprises:
comparing the predicted load to a combination of the respective engine operating envelopes of the one or more engines based on the current shaft speed; and

if the predicted load exceeds a predetermined threshold based on the combination of the respective engine operating envelopes, limiting the predicted load such that it does not exceed the predetermined threshold.
The method as claimed in any one of the preceding claims, further comprising controlling at least one of the plurality of power sources to deliver power based on the determined power distribution.
The method as claimed in any one of the preceding claims, wherein determining a power distribution comprises:
minimizing a fuel consumption and/or an equivalent fuel consumption by the one or more power sources based on the predicted load; and,

determining a power distribution based on a minimum fuel consumption and/or minimum equivalent fuel consumption.
The method as claimed in claim 8, wherein the minimum equivalent fuel consumption is determined using a non-convex optimisation algorithm, preferably a Mesh Adaptive Direct Search algorithm.
A controller for a propulsion system of a vessel with a propeller and a hull, the propulsion system comprising a power system comprising a plurality of power sources for powering one or more engines for driving the propeller, the power system preferably being a hybrid power system;
the controller comprising a computer readable storage medium having computer readable program code embodied therewith, and a processor, preferably a microprocessor, coupled to the computer readable storage medium, wherein, responsive to executing the computer readable program code, the processor may be configured to perform executable operations comprising:
receiving a shaft speed set-point defining a target rotational speed or target effective rotational speed of the propeller;

determining a predicted load based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; and,

determining a power distribution based on the predicted load, the power distribution defining an amount of power to be delivered by each of the plurality of power sources.
A propulsion system for a vessel with a propeller and a hull, the propulsion system comprising a power system comprising a plurality of power sources for powering one or more engines for driving the propeller and a controller, the power system preferably being a hybrid power system;
the controller comprising a computer readable storage medium having computer readable program code embodied therewith, and a processor, preferably a microprocessor, coupled to the computer readable storage medium, wherein, responsive to executing the computer readable program code, the processor may be configured to perform executable operations comprising:
receiving a shaft speed set-point defining a target rotational speed or target effective rotational speed of the propeller;

determining a predicted load based on the received shaft speed set-point and one or more design parameters of the propeller and/or of the hull; and,

determining a power distribution based on the predicted load, the power distribution defining an amount of power to be delivered by each of the plurality of power sources.
A vessel, preferably a marine vessel, comprising a hybrid propulsion system as claimed in claim 11.
Computer program product comprising software code portions configured for, when run in the memory of a computer, executing the method steps according to any of the claims 1-9.