A Ship Energy Management Method, Device, Equipment and Storage Medium

Abstract

The present invention discloses a ship energy management method, device, equipment and storage medium. The ship is a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor. The method includes: determining a set of energy collection points during the entire voyage of the ship, obtaining the actual energy information of the ship at each energy collection point in the set of energy collection points, determining the optimal equivalent factor of the minimum equivalent fuel consumption strategy based on the actual energy information of each energy collection point, and adopting the minimum equivalent fuel consumption strategy generated based on the optimal equivalent factor to perform real-time fuel consumption control on the diesel engine and the electric motor of the ship, so as to keep the sum of the fuel consumption of the diesel engine and the equivalent fuel consumption of the electric motor at a minimum in real time. It has strong real-time performance, improves the working efficiency of the diesel engine and the electric motor, reduces the fuel consumption, and improves the utilization rate of the battery power.

Description

Technical Field

[0001] The present invention belongs to the technical field of ship power control, and particularly relates to a ship energy management method, device, equipment and storage medium. Background Art

[0002] At present, in the field of hybrid ships, in recent years, the diesel-electric hybrid technology has received increasing attention from more and more research scholars. Due to its advantages such as good speed regulation performance, strong overload capacity, high efficiency of the motor, and high thermal efficiency, large low-speed torque, high safety performance of the diesel engine, the power is coupled through a gearbox to output torque and jointly drive the propeller, reflecting the concept of "dual-machine complementarity" of hybrid power.

[0003] At the present stage, for the energy management of hybrid power, the commonly used methods are divided into three categories: rule-based, optimal control, and intelligent control algorithms. In the field of hybrid ships, the three commonly used types of energy management methods all have one or more of the following problems: poor real-time performance, low working efficiency of the diesel engine and the motor, high fuel consumption, poor fuel economy, and low battery power utilization rate. Summary of the Invention

[0004] The present invention provides a ship energy management method, device, equipment and storage medium to solve the problems of poor real-time performance, low working efficiency of the diesel engine and the motor, poor fuel economy, and low battery power utilization rate in the current ship energy management.

[0005] According to the first aspect of the present invention, a ship energy management method is provided. The ship is a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor. The method includes:

[0006] Determine the set of energy collection points of the ship during the entire voyage;

[0007] Obtain the actual energy information of the ship at each energy collection point in the set of energy collection points;

[0008] Based on the actual energy information of each energy collection point, determine the optimal equivalent factor of the minimum equivalent fuel consumption strategy;

[0009] Adopt the minimum equivalent fuel consumption strategy generated based on the optimal equivalent factor to perform real-time fuel consumption control on the diesel engine and the electric motor of the ship.

[0010] According to the second aspect of the present invention, a ship energy management device is provided. The ship is a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor. The device includes:

[0011] An energy collection point set determination module, configured to determine an energy collection point set of the ship during the entire voyage;

[0012] An acquisition module, configured to acquire actual energy information of the ship at each energy collection point in the energy collection point set;

[0013] An optimal equivalent factor determination module, configured to determine an optimal equivalent factor for the minimum equivalent fuel consumption strategy based on the actual energy information of each energy collection point;

[0014] A control module, configured to perform real-time fuel consumption control on the diesel engine and the electric motor of the ship by adopting a minimum equivalent fuel consumption strategy generated based on the optimal equivalent factor.

[0015] According to a third aspect of the present invention, there is provided an electronic device, including:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute a ship energy management method according to any embodiment of the present invention.

[0019] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement a ship energy management method according to any embodiment of the present invention when executed.

[0020] In the technical solution of the embodiment of the present invention, for a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor, energy management is performed. First, an energy collection point set of the ship during the entire voyage is determined, and actual energy information of the ship is acquired at each energy collection point in the energy collection point set. Based on the actual energy information of each energy collection point, an optimal equivalent factor for the minimum equivalent fuel consumption strategy is determined, and a minimum equivalent fuel consumption strategy generated based on the optimal equivalent factor is adopted. By making the diesel engine always work in the high-efficiency working area, the fuel consumption is reduced, so that the sum of the fuel consumption of the diesel engine and the equivalent fuel consumption of the electric motor is always kept minimum, and real-time fuel consumption control is performed on the diesel engine and the electric motor of the ship, improving the working efficiency of the diesel engine and the electric motor. Moreover, the real-time performance of this energy management method is strong, the fuel consumption is reduced, and the battery power utilization rate is improved.

[0021] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become readily understood from the following description. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0023] Figure 1 is a flowchart of a ship energy management method provided in Embodiment 1 of the present invention;

[0024] Figure 2 is a schematic diagram of a battery SOC reference trajectory provided in Embodiment 1 of the present invention;

[0025] Figure 3 is a schematic diagram of the actual SOC decrease provided in Embodiment 1 of the present invention;

[0026] Figure 4 is a flowchart of a method for implementing an equivalent fuel consumption minimization strategy provided in Embodiment 2 of the present invention;

[0027] Figure 5 is a flowchart of an adaptive particle swarm optimization provided in Embodiment 3 of the present invention;

[0028] Figure 6 is a flowchart of outputting an optimal equivalent factor provided in Embodiment 3 of the present invention;

[0029] Figure 7 is a schematic diagram of the structure of a ship energy management device provided in Embodiment 4 of the present invention;

[0030] Figure 8 is a schematic diagram of the structure of an electronic device for implementing a ship energy management method according to an embodiment of the present invention. Detailed Embodiments

[0031] In order to enable those skilled in the art to better understand the solution of the present invention, the following clearly and completely describes the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0032] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0033] Embodiment 1

[0034] Figure 1 A flowchart of a ship energy management method is provided for Embodiment 1 of the present invention.

[0035] This method can be executed by a ship energy management device, and the ship energy management device can be implemented in the form of hardware and / or software.

[0036] For hybrid ships, energy management is the core content of the hybrid ship integrated control system and the key to achieving the performance of the whole ship. Since the diesel-electric hybrid system has multiple working modes, the complexity of the energy management strategy is increased. This requires comprehensive consideration of the navigation mileage and the available battery power to effectively distribute the power of the motor and the diesel engine, so as to achieve the dual goals of improving the fuel economy of the diesel engine and the battery power utilization rate.

[0037] At present, the energy management methods of hybrid ships are divided into three categories: ship energy management strategies based on rules, optimal control, and intelligent control algorithms. At present, the rule-based (Charge Depleting / Charge Sustaining, CD-CS) energy management has good real-time performance and is simple and easy to implement. However, it is more widely used in the field of hybrid vehicles and relatively less used in the field of hybrid ships. Therefore, it has relatively high requirements for the experience of engineering and technical personnel.

[0038] In addition, there is currently an Equivalent Consumption Minimum Strategy (ECMS) that can optimize the energy of diesel-electric hybrid ships. However, in the current energy management methods of hybrid ships, the problems of poor real-time performance of the ECMS strategy and low battery power utilization rate cannot be considered simultaneously.

[0039] The current Equivalent Consumption Minimum Strategy (ECMS) is mainly implemented through the following process:

[0040] In a parallel diesel-electric hybrid ship, the energy mainly comes from the fuel consumption of the diesel engine and the electrical energy of the battery. To make the consumption of these two types of energy comparable, the equivalent fuel consumption is derived from the electrical energy consumption of the battery. The concept of the ECMS strategy is to minimize the total fuel consumption of the diesel engine and the equivalent fuel consumption within each time interval. To minimize fuel consumption to the greatest extent, it is necessary to allocate the motor power. Otherwise, it is very difficult to solve the optimization problem.

[0041] Given the battery SOC (State of Charge), which needs to be maintained at an appropriate value, the battery electrical energy needs to consume an equal amount of fuel consumption for replenishment. In the motor propulsion mode, using the battery to provide power demand can reduce fuel consumption, but additional fuel will be consumed in the future to charge the battery. Similarly, using the diesel engine to charge the battery will increase the instantaneous fuel consumption, but this will reduce the future fuel consumption because it can save fuel for future motor propulsion modes. Therefore, the equivalent fuel consumption is regarded as the sum of the instantaneous fuel consumptions of the diesel engine and the battery.

[0042] The ECMS control strategy meets the power demand of the entire ship and determines the power distribution between the diesel engine and the motor to minimize the instantaneous fuel consumption to the greatest extent.

[0043] According to the principle of the ECMS control strategy, the entire instantaneous equivalent fuel consumption can be expressed as:

[0044] Equation 1: Equation 2:

[0045] Where: is the total equivalent fuel consumption; is the fuel consumption of the diesel engine; is the battery equivalent fuel consumption; P e is the power output by the diesel engine; η e is the diesel engine efficiency; Q LHV is the lower calorific value of diesel.

[0046] The output torques of the diesel engine and the motor meet the navigation requirements:

[0047] Equation 3: T req = T m + T e

[0048] Where: T req is the ship demand torque; T m is the motor output torque; T e is the diesel engine output torque.

[0049] The system satisfies the following constraints:

[0050] Equation 4:

[0051] In the formula: P s is the battery power consumption; ω m is the motor speed; ω e is the diesel engine speed.

[0052] When the torque of the diesel engine is selected as the control variable, the optimal solutions of the diesel engine and the motor can be expressed as:

[0053] Equation 5:

[0054] ECMS is based on the concept that the battery can be regarded as an auxiliary and reversible fuel tank. By allocating the power consumption of the electric energy and converting it into the corresponding fuel consumption, this coefficient is called the equivalent factor, which is the key control parameter of ECMS and largely determines the performance of ECMS. The equivalent factor represents the conversion efficiency between fuel and electric energy.

[0055] It changes with the operating conditions of each component of the power transmission system. In the original formula of ECMS, the equivalent factor is a set of constants, which can be interpreted as the average overall efficiency of the path under each operation mode (charging or discharging) of a given task. The equivalent factor is very important in the ECMS strategy.

[0056] The size of the equivalent factor determines the equivalent fuel consumption. When the value of the equivalent factor is too large, it means that the equivalent fuel quantity increases. At this time, the cost of using electric energy is high, and the control strategy will tend to use the diesel engine to provide power. It is best to stop the battery from supplying power to the motor, resulting in an increase in fuel consumption; when the value of the equivalent factor is too small, the control strategy will tend not to use the diesel engine to provide power, and the diesel engine stops working. At this time, the cost of using electric energy is low, and it is best to use more electric energy and have the motor provide power, which may lead to a sharp decrease in the battery power and cause the battery SCO to be at the lowest level.

[0057] To avoid a large deviation between the battery reference SOC and the actual SOC, a penalty factor for the battery SOC deviation is used to correct the equivalent factor. When the battery SOC is low, the equivalent factor is increased as much as possible to make the control strategy use less electric energy and more fuel; when the battery SOC is high, the equivalent factor is decreased as much as possible to make the control strategy use more electric energy and less fuel. When the equivalent factor of the diesel engine control module is too large, the diesel engine control module tends to charge the battery to the maximum value of SOC. Then it is in the pure fuel mode for most of the journey. In this case, the power required by the ship is provided by the engine because using the diesel engine is considered more reasonable. If the ECMS strategy forces the use of the pure electric mode, the cost of using electric energy is high at this time, and the battery discharge will significantly increase the fuel cost.

[0058] Within a certain range, the equivalent factor s in the ECMS function is characterized in that a larger equivalent factor tends to operate only in the diesel engine operating mode, while a smaller equivalent factor tends to operate only in the motor operating mode. The equivalent factor can be used to adjust the power consumption and fuel consumption. For example, if the SOC is relatively high, more electrical energy is consumed by reducing the equivalent factor, otherwise more fuel energy is consumed by increasing the equivalent factor. In the ECMS control strategy, the equivalent fuel consumption of the battery is divided into two cases: charging and discharging. When the battery is in the charging state, the equivalent fuel consumption of the battery is negative at this time, and the output power is negative. At this time, the system wants to maintain the battery SOC state, and the battery will discharge under a certain working condition at a future moment; when the battery is in the discharging state, the equivalent fuel consumption is positive at this time, and the system will charge the battery at a certain moment, compensating for the consumed electrical energy. Therefore, the equivalent fuel consumption of the battery is expressed by Equation 6:

[0059] Equation 6:

[0060] In the formula: m Batt is the equivalent fuel consumption of the battery; V Batt is the battery voltage; I Batt is the battery current; η dis is the battery discharge efficiency.

[0061] Charging the battery at a future moment, the length of time is closely related to the average efficiency of the diesel engine. The equivalent factor is expressed by Equation 7:

[0062] Equation 7:

[0063] In the formula: η chg is the diesel engine charging efficiency; η MC is the motor discharge efficiency; s(t) dis is the equivalent factor during discharging; s(t) chg is the equivalent factor for charging; η GC is the generator power generation efficiency.

[0064] It is important to accurately adjust the equivalent factor. As long as the driving mode can be predicted in advance and the equivalent factor can be adjusted in real time, without the need to adjust the entire driving cycle.

[0065] In summary, the key to the ECMS strategy is to find a suitable equivalent factor s. However, the value of the equivalent factor is very sensitive to the ECMS strategy. Generally, if the equivalent factor changes by 0.01, it will also cause a large fluctuation in the power. Arbitrarily adjusting the equivalent factor will seriously affect the control effect of the ECMS strategy. However, due to the influence of the external environment, in actual control, the equivalent factor must be optimized. In the ship energy management method of this embodiment, the equivalent factor can be optimized to obtain the optimal equivalent factor, so as to realize the reasonable distribution of power between the diesel engine and the motor.

[0066] In this embodiment, the ship is a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor, as Figure 1 shown. The method includes the following steps:

[0067] S110. Determine the set of energy collection points of the ship during the entire voyage.

[0068] The voyage of the ship can be determined in advance. After obtaining the entire voyage of the ship, based on different power requirements during the voyage, the entire voyage can be divided to determine multiple energy collection points, so as to obtain the set of energy collection points.

[0069] After dividing the voyage using the energy collection points, in the adjacent voyage segments divided by the same energy collection point, the power distribution between the electric motor and the oil engine can be different.

[0070] In one embodiment, step S110 includes the following sub-steps:

[0071] S110-1. Obtain multiple voyage segments during the entire voyage.

[0072] For the entire voyage of the ship, it can be pre-divided into multiple voyage segments. When making the pre-division, the entire voyage can be evenly divided, or it can be divided according to a certain strategy.

[0073] S110-2. Obtain the first output power of the diesel engine and the second output power of the generator, and determine the power required for the ship's navigation according to the first output power and the second output power.

[0074] When obtaining the first output power of the diesel engine and the second output power of the generator, the total ship demand torque can be composed of the ship resistance torque and the demand torque obtained by the ship speed PI controller (proportional integral controller, a linear controller). The SOC correction function can be determined by the battery SOC state, and then the control variable diesel engine speed range can be determined. By performing grid processing on the speeds and torques of the diesel engine and the motor, the target torque of the diesel engine at the current speed can be obtained through look-up tables, and then the first output power of the diesel engine can be obtained. By looking up the target torque of the motor at the current speed, the second output power of the generator can be determined.

[0075] After determining the first output power and the second output power, the first output power and the second output power can be summed, and the result is used as the power required for the ship's navigation, which can be expressed by the following formula: Equation 8: P req =P e +P m ;

[0076] Among them, P req is the power required for navigation, P e is the first output power of the diesel engine, and P m is the second output power of the generator.

[0077] S110-3. Determine the equivalent fuel consumption power of the ship according to the first output power and the second output power.

[0078] In this embodiment, the equivalent fuel consumption power of the ship can be represented by p eqv,hev , and the formula for determining p eqv,hev is as follows: Equation 9: p eqv,hev =a e P e +b e +s(a m P m +b m );

[0079] Substituting Equation 8 into Equation 9, we can get:

[0080] Equation 10:

[0081] In the formula, a e and b e are linear fitting coefficients, the fitting coefficients are functions of speed, b m is the fitting coefficient of the motor output power when the motor is in the power generation state, and s is the equivalent factor.

[0082] S110-4. Using a piecewise linear function related to multiple voyage segments, divide the power required for navigation into several demand power intervals, and determine the equivalent fuel consumption power for each demand power interval.

[0083] For the output power of the diesel engine and the electric motor respectively, there is a correlation between their output power and consumption power. Among them, the first output power of the diesel engine and the diesel fuel consumption power P ef The relationship is as follows:

[0084] Equation 11:

[0085] In the formula: P e Is the first output power of the diesel engine; P e1 Is the first turning point; P e_opt Is the highest power point; P e_max Is the maximum output power: a el , a e2 , a e3 , b el , b e2 , b e3 Are the linear fitting coefficients for each segment, and the fitting coefficients are functions of speed.

[0086] During the electric and power generation processes of the electric motor, the current is opposite. The output power P of the electric motor s And the second output power P of the generator m The relationship is as follows:

[0087] Equation 12:

[0088] In the formula: P s Is the output power of the electric motor; P m Is the second output power of the generator; a m+ , b m+ , Are the fitting coefficients of the input power and output power of the motor during motor drive; a m- , b m- Are the fitting coefficients of the input power and output power of the motor during motor power generation.

[0089] Since both the diesel engine model and the motor model are piecewise linear functions, the equivalent fuel consumption power can be further written in the form of a piecewise function. According to the range of power demand, it can be divided into four cases:

[0090] (1) 0 ≤ P req < P el

[0091]

[0092] (2) Pe1 ≤P req <P e-opt

[0093]

[0094] (3)P e-opt ≤P req ≤P e-max

[0095]

[0096] (4)P req >P e-max

[0097]

[0098] S110 - 5 aims to achieve the optimal output power of the diesel engine at the equivalent fuel consumption power in each interval, solve the minimum value of the piecewise linear function, and use it as the energy collection point for the corresponding voyage segment.

[0099] After determining the piecewise linear functions corresponding to the equivalent fuel consumption power in various situations, the minimum value of the equivalent fuel consumption power can be solved based on each piecewise linear function, and the point corresponding to the minimum value is used as the energy collection point for the corresponding voyage segment.

[0100] In one embodiment, S110 - 5 includes:

[0101] Determine the constraint conditions for the optimal output power as the power constraint conditions;

[0102] Convert the power constraint conditions into torque constraint conditions;

[0103] Determine the optimal torque distribution according to the torque constraint conditions, and the optimal torque distribution includes multiple optimal torque points;

[0104] Use the optimal torque points as the energy collection points.

[0105] In this embodiment, when determining the equivalent factor, rotational speed, and power demand, the piecewise linear function of the diesel engine power is the equivalent fuel consumption power. According to relevant mathematical knowledge, the minimum value of the piecewise linear function can be found at the end of each segment. Therefore, the optimal output power of the diesel engine should satisfy the following formula:

[0106] Equation 13:

[0107] Meanwhile, satisfy the following constraint conditions, that is, the power constraint conditions:

[0108] Equation 14:

[0109] The results obtained above have achieved the purpose of discretization. Equation 14 is the control variable obtained under the minimum equivalent fuel consumption constraint point after discretization. Therefore, the minimum value of the piecewise linear function can be solved as the energy collection point of the voyage segment, and the minimum equivalent fuel consumption can be obtained at each energy collection point.

[0110] When the maximum power output of the diesel engine exceeds the ship's demand power, only the equivalent fuel consumption of 5 energy collection points needs to be calculated; when the maximum power output of the diesel engine cannot meet the required power, at most only the equivalent fuel consumption of 4 energy collection points needs to be calculated. For the hybrid drive mode of the diesel engine and the motor, the equivalent fuel consumption of 5 energy collection points can be used to obtain the optimal torque distribution.

[0111] When the maximum output power of the diesel engine is less than the required power, at most only 4 equivalent fuel consumption points need to be calculated. Since the control method of the motor and the diesel engine is the torque control method, the above discrete power points can be converted into torque points, and the power constraint conditions can be converted into torque constraint conditions.

[0112] The power of the diesel engine is related to torque and speed, as shown in the following equation: Equation 15: P = Tω;

[0113] It can be seen from Equation 15 that when the speed is constant, the power and torque have a one-to-one relationship.

[0114] Therefore, based on Equation 13 and Equation 14, the following torque form can be obtained:

[0115] Equation 16:

[0116] Where: T el is the first turning point; is the maximum torque value; T e-max , is the maximum output torque. The optimal diesel engine torque must satisfy the following constraint conditions, that is, the torque constraint conditions:

[0117] Equation 17:

[0118] Where: T e-minact is the actual minimum torque limit of the diesel engine; T e-maxact is the actual maximum torque limit of the diesel engine.

[0119] According to the torque constraint conditions, the optimal torque distribution can be determined. The optimal torque distribution includes multiple optimal torque points, and the optimal torque points are used as energy collection points.

[0120] In the calculation, the discrete points 0 and T in Equation 16 m-maxIt should be replaced with the actual maximum or minimum torque in Equation 17. Derive the analytical formula for the equivalent fuel consumption, design the constraint conditions for the optimal solution, and achieve the purpose of discretization within the search domain of the control variables, thereby greatly improving the calculation speed of the algorithm. If the analytical formula is accurate, the solution after discretization should be the same as the solution of the original problem. In the diesel-electric hybrid drive mode, according to the above derivation results, only the equivalent fuel consumption of up to 5 equivalent fuel consumption points needs to be calculated to obtain the optimal torque distribution.

[0121] S120. Obtain the actual energy information of the ship at each energy collection point in the set of energy collection points.

[0122] In this embodiment, after determining each energy collection point, the actual energy information of the ship can be obtained at the energy collection points respectively, and the actual energy information of multiple ships can be obtained.

[0123] S130. Based on the actual energy information of each energy collection point, determine the best equivalent factor for the strategy of minimizing the equivalent fuel consumption.

[0124] When collecting the actual energy information, regardless of the initial SOC value, the optimal SOC trajectory decreases linearly with the sailing mileage. (SOC, State of Charge, the charging state of the battery, also known as the remaining power, represents the ratio of the remaining dischargeable power to the fully charged power of the battery after being used for a period of time or maintained for a long time, usually expressed as a percentage).

[0125] In order to improve the utilization rate of the battery power, a strategy in which the reference trajectory decreases linearly with the mileage is proposed under the condition of known sailing mileage. Refer to Figure 2 a schematic diagram of a battery SOC reference trajectory. Among them,

[0126] After obtaining the actual energy information, it can be combined with Figure 2 the SOC characteristics shown to determine the best equivalent factor for the strategy of minimizing the equivalent fuel consumption.

[0127] In one embodiment, step S130 includes the following sub-steps:

[0128] S130-1. According to the actual energy information, determine the equivalent factor for the known voyage;

[0129] S130-2. Perform adaptive adjustment on the equivalent factor for the known voyage to obtain the best equivalent factor.

[0130] After obtaining the actual energy information, the equivalent factor of the voyage can be calculated according to Equation 7. In order to obtain a better equivalent factor, the equivalent factor under a known voyage can be adaptively adjusted. In one embodiment, the historical data of the voyage can be used to adaptively adjust the equivalent factor. Specifically, the power demand in the historical data of the voyage can be used to adaptively adjust the equivalent factor.

[0131] In another embodiment, an adaptive particle swarm algorithm can be used to complete the adaptive adjustment of the equivalent factor and obtain the optimal equivalent factor.

[0132] In one embodiment, step S130-1 includes:

[0133] Calculate the power deviation between the remaining battery power at each energy collection point and the preset reference remaining power respectively, and determine the maximum power deviation from the power deviations corresponding to all energy collection points;

[0134] Calculate the deviation coefficient according to the remaining battery power, the preset reference remaining power, and the maximum power deviation;

[0135] Calculate the product of the deviation coefficient and the preset reference equivalent factor to obtain the equivalent factor corresponding to the energy collection point.

[0136] In this embodiment, the energy information may include the remaining battery power.

[0137] When it is necessary to make the remaining battery power change according to the reference remaining power trajectory, the equivalent factor will be corrected according to the deviation between the remaining battery power and the reference remaining power.

[0138] Among them, the calculation formula of the deviation coefficient p(ξ) is as follows:

[0139] Equation 18: p(ξ) = (1 + (ξ ref - ξ(t) / Δξ) 3

[0140] The calculation formula of the equivalent factor s is as follows: Equation 19: s = s0·p(ξ);

[0141] In the formula: s0 is the reference equivalent factor; ξ(t) is the remaining battery power; ξ ref is the preset reference remaining power; Δξ is the maximum power deviation.

[0142] In one embodiment, when using the adaptive particle swarm algorithm to complete the adaptive adjustment of the equivalent factor and obtain the optimal equivalent factor, step S130-2 includes the following steps:

[0143] Use the equivalent factor obtained in real time as particles to construct a particle swarm, and use the pre-established particle swarm algorithm to determine the adaptive equivalent factor;

[0144] Adopt the strategy of minimizing the equivalent fuel consumption based on the adaptive equivalent factor to control the fuel consumption of the diesel engine and the electric motor of the ship, and obtain the power deviation;

[0145] If the power deviation is less than the set deviation threshold, then take this adaptive equivalent factor as the optimal equivalent factor.

[0146] In this embodiment, the adaptive particle swarm optimization algorithm can be adopted. Take the equivalent factor obtained in real time as the particle to construct a particle swarm, and dynamically adjust the weight ω of each particle in the particle swarm according to the fitness value of the particle. The calculation process of the adaptive weight is as follows:

[0147] Equation 20:

[0148] In the formula, ω max is the maximum value of the weight, ω min is the minimum value of the weight. Usually, take ω max = 0.9, ω min = 0.4; f i is the fitness value of the i-th particle, f avg is the average fitness value of the whole particle, f g is the best fitness value of the whole particle.

[0149] Then the velocity and position corresponding to the i-th particle can be updated as follows

[0150] Equation 21:

[0151] Equation 22:

[0152] In the formula, ω i is the adaptive weight corresponding to the particle; c1 and c2 are constant learning factors. r1 and r2 are random numbers in the interval [0,1]; k is the evolutionary generation; m is the population size; d is the space dimension of the problem to be solved, 1 ≤ i ≤ m, 1 ≤ j ≤ d. is the single optimal value of the i-th particle in the k-th iteration. is the global optimal value of the k-th iteration.

[0153] In the particle swarm, adaptive mutation can occur. The specific calculation of the fitness variance is as follows

[0154] Equation 23:

[0155] In the formula, N is the overall size; f i is the fitness value of the i-th particle, i = 1, 2,..., N; f avgis the average fitness value of the entire population; D is the fitness variance of the entire population; f is a normalization factor used to control the range of the fitness variance. Dynamically adjust a specific value according to the fitness value of the current particle. Among them, the calculation formula of the normalization factor f is as follows: Equation 24: f = max{1, max{|f i - f avg |}};

[0156] If the algorithm falls into a local optimal solution, then the population extreme value g of the current particle best mutates with a certain probability p m , and the specific calculation of p m is expressed as

[0157] Equation 25:

[0158] where q is a random number in the interval [0, 0.4], and is the maximum value much smaller than the fitness variance D. According to the particle swarm extreme value g best , perform the following mutation operation.

[0159] The first step: Randomly generate a random number r that follows a normal distribution n(0, 1);

[0160] The second step: Compare the random number r with p m . If r is greater than p m , then the particle mutates. The specific calculation formula of the mutation operation is as follows: Equation 26:

[0161] The third step: If r is less than p m , then no mutation occurs.

[0162] After the equivalent factor completes the adaptive adjustment, based on the equivalent fuel consumption minimum strategy of the adaptive equivalent factor, the fuel consumption of the ship's diesel engine and electric motor can be controlled, the power of the diesel engine and electric motor can be reasonably allocated, and the power deviation can also be obtained. The power deviation can be compared with the set deviation threshold. If the absolute value of the obtained power deviation is less than the set deviation threshold, then the adaptive equivalent factor is used as the optimal equivalent factor. Specifically, the deviation threshold can be 1%.

[0163] In one embodiment, the method further includes the following steps:

[0164] Obtain the real-time power deviation;

[0165] If the power deviation is greater than the set deviation threshold, then perform adaptive adjustment on the optimal equivalent factor.

[0166] Specifically, if the absolute value of the power deviation is greater than or equal to the set deviation threshold, the adaptive adjustment of the optimal equivalent factor can start from the step of dynamically adjusting the weight ω of each particle in the above particle swarm, recalculate the equivalent factor until the optimal equivalent factor that meets the conditions is solved.

[0167] In one embodiment, for the optimal SOC decline trajectories under different sailing distances and different initial SOCs, after giving the corresponding battery SOC reference trajectory, the equivalent factor is adaptively adjusted to optimize the equivalent factor in real time. Although the current technology can obtain the corresponding voyage information, during the ship's voyage, some information cannot be predicted in advance. For example, affected by objective factors such as sea conditions and weather, the voyage also has uncertainties.

[0168] Therefore, it is more practically significant to analyze the unknown voyage. When the voyage is known, the ideal SOC decline trajectory is linear throughout the voyage. For the unknown sailing mileage, the interval average value based on the maximum distribution probability of historical sailing mileage can be used as the reference mileage for SOC planning. In practical engineering applications, the battery SOC decline trajectory will be between the reference trajectory and the CD-CS strategy (Charge Depletion - Charge Sustain strategy), as Figure 3 shown in a schematic diagram of an actual SOC decline.

[0169] S140, adopt the equivalent fuel consumption minimum strategy generated based on the optimal equivalent factor to perform real-time fuel consumption control on the ship's diesel engine and electric motor.

[0170] The ship is driven by a diesel-electric hybrid ship model. After determining the optimal equivalent factor, the corresponding optimal output power of the diesel engine and the optimal output power of the generator can be determined through a preset correlation. Specifically, the corresponding optimal output power can be obtained by looking up a table.

[0171] After determining the optimal equivalent factor and the corresponding optimal output powers of the diesel engine and the electric motor, the obtained data can be substituted into the model parameters, thereby affecting the model and realizing real-time fuel consumption control of the ship's diesel engine and electric motor.

[0172] The diesel-electric hybrid ship model includes the following models:

[0173] (1) Diesel engine model

[0174] Considering the complexity of the engine, a quasi-static model is established. The fuel rate m f can be expressed as: where ω e and T e are the engine speed and torque respectively, is the vector form of m f respectively.

[0175] In addition, P e = H LHV , P e is the available power of the engine, and H LHV is the lower calorific value of the fuel.

[0176] (2) Motor model

[0177] The motor is a three-phase asynchronous motor, which can be used as a traction motor to provide torque or as a generator to charge the battery. Therefore, the motor power pm can be expressed as

[0178]

[0179] where: ω m is the motor speed; η em is the efficiency of the motor driving the motor; η ge is the efficiency of the motor as a generator.

[0180] (3) Battery model

[0181] Ignoring the influence of temperature on the battery, the battery is modeled, and the expressions for the battery SOC and output power are as follows

[0182]

[0183] P bat = -SOC·U oc ·Q b

[0184] where SOC is the battery SOC change rate, in vector form; U is the battery open-circuit voltage; R is the battery internal resistance; Q is the battery maximum capacity; P is the battery output power.

[0185] (4) Transmission system model

[0186] The double reduction ratio is adopted to transmit power, namely the main reduction ratio and the PTI reduction ratio:

[0187]

[0188] where T2 and n2 are the output torque and speed; T1 and n1 are the input torque and speed. i is the transmission ratio of the transmission system. At this time, only the superposition of torques is considered. The modeling is as follows: T out = T in1 + T in2 ;

[0189] where T in1 and T in2 are the input torques; T outIs the output torque

[0190] (5) Engine-propeller mathematical model

[0191] The motion equations of the ship and the propeller are as follows:

[0192]

[0193]

[0194] Wherein, v s Is the speed of the ship, m / s; R t Is the resistance of the ship, N; M p Is the torque output by the diesel engine, N·m; M f Is the resistance torque, N·m; i is the reduction ratio of the gearbox.

[0195] R t = f(v s ); Wherein, Where λ is the ship resistance coefficient and θ is a constant.

[0196] In an embodiment of the present invention, a method for energy management of a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor is provided. First, a set of energy collection points for the ship throughout the voyage is determined. At each energy collection point in the set of energy collection points, the actual energy information of the ship is obtained. Based on the actual energy information of each energy collection point, the optimal equivalent factor of the minimum equivalent fuel consumption strategy is determined. The minimum equivalent fuel consumption strategy generated based on the optimal equivalent factor is adopted. By making the diesel engine always operate in the high-efficiency working area, the fuel consumption is reduced, so that the sum of the fuel consumption of the diesel engine and the equivalent fuel consumption of the electric motor is always kept minimum. Real-time fuel consumption control is performed on the diesel engine and the electric motor of the ship, improving the working efficiency of the diesel engine and the electric motor. Moreover, the real-time performance of this energy management method is strong, reducing the fuel consumption and improving the battery power utilization rate.

[0197] Embodiment Two

[0198] Figure 4 The flowchart of a method for implementing the minimum equivalent fuel consumption strategy provided by an embodiment of the present invention. This embodiment is based on the foregoing embodiment and further elaborates in detail the determination process and application process of the minimum equivalent fuel consumption strategy. The steps for implementing the minimum equivalent fuel consumption strategy are as follows:

[0199] S410, The total ship demand torque is jointly constituted by the ship resistance torque and the demand torque obtained by the speed PI controller;

[0200] S420, The SOC correction function is determined by the battery SOC state;

[0201] S430. Determine the speed range of the control variable diesel engine;

[0202] S440. Perform grid processing on the speeds and torques of the diesel engine and the motor;

[0203] S450. Look up the target torque of the diesel engine at the current speed in a table and then obtain the output power of the diesel engine;

[0204] S460. Look up the target torque of the motor at the current speed in a table and then obtain the output power of the motor;

[0205] S470. Input the obtained diesel output power into the diesel engine model and input the motor output power into the battery model;

[0206] S480. Form the objective function;

[0207] S490. Obtain the minimum value of the objective function;

[0208] S4010. Determine the operating point of the diesel engine and the operating point of the motor.

[0209] In this embodiment, during the process of determining the minimum equivalent fuel consumption strategy, the total ship demand torque can be first constituted by the ship resistance torque and the demand torque obtained from the PI controller of the ship speed.

[0210] The SOC correction function can be determined by the battery SOC state. Currently, there are various correction methods for SOC. Exemplarily, when the BMS is in the static mode (no load), query the OCV table, obtain the SOC value corresponding to the current voltage and temperature according to the OCV curve, and then wait for the next load moment to start correcting the SOC, and smooth-correct it to the target value at a certain rate to speed up or slow down the ampere-hour integration; or when the SOC is equal to 99.4% in the charging mode, first stop the ampere-hour integration to keep the SOC unchanged until the full charge condition is reached (the highest voltage of a single cell reaches the full charge voltage at the current temperature and the charging current is the minimum allowable charging current), and the SOC jumps to 100%; or through the extreme correction method, that is, when the lowest voltage of a single cell lasts for a certain time below the threshold boundary point SOC_Bms in the discharge mode, it directly jumps to 0, and SOC_Disp quickly smooth-tracks to 0% at a faster speed; in the charging mode, when the highest voltage of a single cell lasts for a certain time above the threshold and above the full charge voltage point but below the safety protection point SOC_Bms, SOC_Disp is directly corrected to 100%; or establish a battery model, that is, the equivalent circuit of the battery, so as to perform dynamic correction. In this embodiment, no specific limitation is imposed on the specific SOC correction method.

[0211] Then, the speed range of the control variable diesel engine can be determined, and the speed range of the diesel engine can be determined based on the equipment attributes of the diesel engine itself.

[0212] When performing grid processing on the rotational speed and torque of a diesel engine and an electric motor, it can be achieved through a two-dimensional Lagrange interpolation polynomial, or through the polynomial least squares fitting method, or through the weighted average method. The uneven distribution of rotational speed and torque can be solved through grid processing.

[0213] Since there is a correlation between the power, rotational speed, and torque of a diesel engine, a table corresponding to the rotational speed and torque can be established in advance. Then, the target torque of the diesel engine at the current rotational speed can be obtained by looking up the table, and further the output power of the diesel engine, that is, the first output power, can be obtained. The target torque of the electric motor at the current rotational speed is obtained by looking up the table, and further the output power of the generator, that is, the second output power, can be determined.

[0214] The output power of the diesel engine and the output power of the electric motor can be respectively input into the diesel engine model and the battery model to determine the objective function, and the minimum value can be obtained for the objective function, thereby determining the operating point of the diesel engine and the operating point of the electric motor.

[0215] This embodiment elaborates on the determination process and application process of the minimum equivalent fuel consumption strategy. On the premise of meeting the required power of the entire ship, the diesel engine can be adjusted to always operate in the high-efficiency working area, reducing fuel consumption, and achieving the purpose of always keeping the sum of the fuel consumption of the diesel engine and the equivalent fuel consumption of the electric motor at the minimum.

[0216] Embodiment Three

[0217] Figure 5 This is a flowchart of an adaptive particle swarm optimization provided by an embodiment of the present invention. This embodiment is based on the foregoing embodiment and further elaborates in detail the process of constructing a particle swarm and obtaining the best equivalent factor by using the adaptive optimization process of the particle swarm. The steps are as follows:

[0218] S510, Initialize the particle position and velocity;

[0219] S520, Calculate the fitness value of the particle;

[0220] S530, Update the individual extreme value and the global extreme value of the particle;

[0221] S540, Update the fitness variance of the population;

[0222] S550, Update the adaptive weight of the particle;

[0223] S560, Generate a random number r;

[0224] S570, Determine whether the random number meets the condition. If it meets, execute S580. If it does not meet, execute S590;

[0225] S580, Perform a mutation operation on the global extreme value of the population;

[0226] S590, Calculate the current fitness value of the particle;

[0227] S5010, Update the position and velocity of the particle;

[0228] S5011, Determine whether the final condition is met. If so, execute S5012; if not, execute S520;

[0229] S5012, Output the optimization result.

[0230] In this embodiment, the proposed construction of the particle swarm and the adaptive optimization process using the particle swarm. The core idea is to dynamically adjust the weight of each particle in the particle swarm according to the fitness value of the particle.

[0231] Among them, the generated random number r follows the normal distribution n(0,1);

[0232] p m The specific calculation is expressed as:

[0233]

[0234] q is a random number in the interval [0, 0.4], is the maximum value much smaller than the fitness variance D.

[0235] If r is greater than p m , then the particle mutates, that is, execute S580. The specific calculation formula of the mutation operation is as follows:

[0236] If r is less than p m , then no mutation occurs, that is, execute S590.

[0237] Starting from S540 belongs to the steps of the optimization equivalent factor, and the purpose of optimization is to find the optimal equivalent factor.

[0238] Specifically, the specific processes of step S5011 and step S5012 can refer to Figure 6 A flowchart for outputting the optimal equivalent factor, the steps are as follows:

[0239] S610, Given the initial values of the working condition and SOC;

[0240] S620, Select the initial values of the equivalent factors s0 and s1;

[0241] S630, Call the D-ECMS strategy;

[0242] S640, Calculate the SOC deviation;

[0243] S650, determine whether │SOC deviation│ < 1%. If so, call S670; otherwise, call S660.

[0244] S660, call A-PSO to calculate the new equivalent factor s n+1 ;

[0245] S670, output the optimal equivalent factor.

[0246] In this embodiment, the initial values of the equivalent factors s0 and s1 can be determined first based on the basic information of the ship. Then, by calling the equivalent fuel consumption minimum strategy, i.e., the D-ECMS strategy in 6, the power deviation can be obtained, which is Figure 6 the SOC deviation in. The power deviation can be compared with the set deviation threshold of 1%. If the absolute value of the obtained power deviation is less than the set 1%, then the adaptive equivalent factor is output as the optimal equivalent factor.

[0247] If the absolute value of the obtained power deviation is greater than the set 1%, then call the A-PSO strategy, that is, continue to execute Figure 5 the process until an optimized result that meets the conditions, i.e., the optimal equivalent factor, is determined.

[0248] In the construction of the particle swarm and the adaptive optimization process using the particle swarm proposed in this embodiment, improvements are made on the basis of the conventional particle swarm algorithm, overcoming the disadvantage of poor particle adaptability and achieving the optimal equivalent factor.

[0249] Embodiment 4

[0250] Figure 7 The following is a schematic structural diagram of a ship energy management device provided in Embodiment 4 of the present invention. The ship is a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor, as Figure 7 shown. The device includes:

[0251] An energy collection point set determination module 710, which is used to determine the energy collection point set of the ship during the entire voyage;

[0252] An acquisition module 720, which is used to acquire the actual energy information of the ship at each energy collection point in the energy collection point set;

[0253] An optimal equivalent factor determination module 730, which is used to determine the optimal equivalent factor of the equivalent fuel consumption minimum strategy based on the actual energy information of each energy collection point;

[0254] A control module 740, which is used to perform real-time fuel consumption control on the diesel engine and the electric motor of the ship by adopting the equivalent fuel consumption minimum strategy generated based on the optimal equivalent factor.

[0255] In one embodiment, the energy harvesting point set determination module 610 includes the following sub-modules:

[0256] A voyage segment acquisition sub-module, configured to acquire a plurality of voyage segments in the entire voyage;

[0257] An output power acquisition sub-module, configured to acquire a first output power of the diesel engine and a second output power of the generator;

[0258] A required power for navigation determination sub-module, configured to determine the required power for the ship's navigation according to the first output power and the second output power;

[0259] A first equivalent fuel consumption power determination sub-module, configured to determine the equivalent fuel consumption power of the ship according to the first output power and the second output power;

[0260] A second equivalent fuel consumption power determination sub-module, configured to divide the required power for navigation into several required power intervals by using a piecewise linear function related to the plurality of voyage segments, and determine the interval equivalent fuel consumption power corresponding to each required power interval;

[0261] An energy harvesting point determination sub-module, configured to take the minimum value of the piecewise linear function with the goal of achieving the optimal output power of the diesel engine at each of the interval equivalent fuel consumption powers as the energy harvesting point of the corresponding voyage segment, wherein the minimum equivalent fuel consumption can be obtained at each energy harvesting point.

[0262] In one embodiment, the energy harvesting point determination sub-module includes the following units:

[0263] A power constraint condition determination unit, configured to determine the constraint condition of the optimal output power as the power constraint condition;

[0264] A torque constraint condition determination unit, configured to convert the power constraint condition into a torque constraint condition;

[0265] An optimal torque distribution unit, configured to determine an optimal torque distribution according to the torque constraint condition, where the optimal torque distribution includes a plurality of optimal torque points;

[0266] An energy harvesting point determination unit, configured to use the optimal torque point as the energy harvesting point.

[0267] In one embodiment, the best equivalent factor determination module 730 includes the following sub-modules:

[0268] An equivalent factor determination sub-module, configured to determine the equivalent factor of a known voyage according to the actual energy information;

[0269] The optimal equivalent factor determination sub-module is used to adaptively adjust the equivalent factor of the known voyage to obtain the optimal equivalent factor.

[0270] In one embodiment, the actual energy information includes the remaining battery power; the equivalent factor determination sub-module is specifically used for:

[0271] Calculate the power deviation between the remaining battery power of each energy collection point and the preset reference remaining power respectively, and determine the maximum power deviation from the power deviations corresponding to all energy collection points;

[0272] Calculate the deviation coefficient according to the remaining battery power, the preset reference remaining power and the maximum power deviation;

[0273] Calculate the product of the deviation coefficient and the preset reference equivalent factor to obtain the equivalent factor of the corresponding energy collection point.

[0274] In one embodiment, the optimal equivalent factor determination sub-module is specifically used for:

[0275] Construct a particle swarm with the equivalent factors obtained in real time as particles, and use the pre-established particle swarm algorithm to determine the adaptive equivalent factor;

[0276] Adopt the equivalent fuel consumption minimum strategy based on the adaptive equivalent factor to control the fuel consumption of the diesel engine and the electric motor of the ship, and obtain the power deviation;

[0277] If the power deviation is less than the set deviation threshold, use this adaptive equivalent factor as the optimal equivalent factor.

[0278] In one embodiment, the device is further used for:

[0279] Obtain the real-time power deviation;

[0280] If the power deviation is greater than the set deviation threshold, adaptively adjust the optimal equivalent factor.

[0281] A ship energy management device provided by an embodiment of the present invention can implement a ship energy management method provided by Embodiment 1, Embodiment 2 and Embodiment 3 of the present invention, and has corresponding function modules and beneficial effects for executing the method.

[0282] Embodiment Five

[0283] Figure 8FIG. 0 shows a schematic structural diagram of an electronic device 10 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0284] As Figure 8 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0285] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0286] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a ship energy management method.

[0287] In some embodiments, a ship energy management method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the ship energy management method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute a ship energy management method by any other suitable means (e.g., by means of firmware).

[0288] The various embodiments of the systems and techniques described above in this document may be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0289] The computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0290] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, 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 fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0291] For providing interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used for providing interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0292] The systems and techniques described herein can be implemented in a computing system that includes backend components (such as, for example, a data server), or a computing system that includes middleware components (such as, for example, an application server), or a computing system that includes frontend components (such as, for example, a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by any form or medium of digital data communication (such as, for example, a communication network). Examples of the communication network include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0293] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is created by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0294] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0295] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A ship energy management method, characterized in that, The ship is a diesel-electric hybrid ship powered by a diesel engine and an electric motor, and the method includes: Determine the set of energy collection points of the ship during the entire voyage; Obtain the actual energy information of the ship at each energy collection point in the set of energy collection points; Based on the actual energy information of each energy collection point, determine the optimal equivalent factor of the minimum equivalent fuel consumption strategy; Adopt the minimum equivalent fuel consumption strategy generated based on the optimal equivalent factor to perform real-time fuel consumption control on the diesel engine and the electric motor of the ship; The determination of the set of energy collection points of the ship during the entire voyage includes: Obtain multiple voyage segments during the entire voyage; Obtain the first output power of the diesel engine and the second output power of the electric motor, and determine the power required for the ship's navigation according to the first output power and the second output power; According to the first output power and the second output power, determine the equivalent fuel consumption power of the ship; Use a piecewise linear function related to the multiple voyage segments to divide the power required for navigation into several demand power intervals, and determine the interval equivalent fuel consumption power corresponding to each demand power interval; Taking the minimum value of the piecewise linear function with the goal of achieving the optimal output power of the diesel engine under each interval equivalent fuel consumption power as the energy collection point of the corresponding voyage segment, where the minimum equivalent fuel consumption can be obtained at each energy collection point; The calculation formula for the equivalent fuel consumption power of the ship is: p eqv,hev = a e P e + b e + s(a m P m + b m ) = a e P e + b e + s(a m (P req - P e ) + b m ) P req = P e + P m where p eqv,hev is the equivalent fuel consumption power, P req is the power required for navigation, P e is the first output power of the diesel engine, P m is the second output power of the motor, a e and b e are linear fitting coefficients, and the fitting coefficients are functions of speed. a m , b m are the fitting coefficients of the input power and output power of the motor when the motor is in the power generation state, and s is the equivalent factor.

2. The method according to claim 1, characterized in that The determination of taking the minimum value of the piecewise linear function with the goal of achieving the optimal output power of the diesel engine under each interval equivalent fuel consumption power as the energy collection point of the corresponding voyage segment includes: Determine the constraint conditions of the optimal output power as the power constraint conditions; Convert the power constraint conditions into torque constraint conditions; Determine the optimal torque distribution according to the torque constraint conditions, and the optimal torque distribution includes multiple optimal torque points; Take the optimal torque points as the energy collection points.

3. The method according to claim 1, characterized in that, The determination of the optimal equivalent factor of the minimum equivalent fuel consumption strategy based on the actual energy information of each energy collection point includes: According to the actual energy information, determine the equivalent factor of the known voyage; Perform adaptive adjustment on the equivalent factor of the known voyage to obtain the optimal equivalent factor.

4. The method according to claim 3, wherein The actual energy information includes the remaining battery power; the determination of the equivalent factor of the known voyage according to the actual energy information includes: Calculate the power deviation between the remaining battery power at each energy collection point and the preset reference remaining power respectively, and determine the maximum power deviation from all the power deviations corresponding to the energy collection points; Calculate the deviation coefficient according to the remaining battery power, the preset reference remaining power, and the maximum power deviation; Calculate the product of the deviation coefficient and the preset reference equivalent factor to obtain the equivalent factor corresponding to the energy collection point.

5. The method according to claim 4, characterized in that, The adaptive adjustment of the equivalent factor of the known voyage to obtain the optimal equivalent factor includes: Construct a particle swarm with the equivalent factors obtained in real time as particles, and use the pre-established particle swarm algorithm to determine the adaptive equivalent factor; Adopt the strategy of minimizing the equivalent fuel consumption based on the adaptive equivalent factor to control the fuel consumption of the diesel engine and the motor of the ship, and obtain the power deviation; If the power deviation is less than the set deviation threshold, use this adaptive equivalent factor as the optimal equivalent factor.

6. The method according to claim 5, wherein After adopting the strategy of minimizing the equivalent fuel consumption generated based on the optimal equivalent factor to control the fuel consumption of the diesel engine and the motor of the ship, the method further includes: Obtain the real-time power deviation; If the power deviation is greater than the set deviation threshold, adaptively adjust the optimal equivalent factor.

7. A ship energy management device, characterized in that, The ship is a diesel-electric hybrid ship jointly powered by a diesel engine and an electric motor, and the device includes: An energy collection point set determination module for determining the set of energy collection points of the ship during the entire voyage; An acquisition module for acquiring the actual energy information of the ship at each energy collection point in the set of energy collection points; An optimal equivalent factor determination module for determining the optimal equivalent factor of the strategy of minimizing the equivalent fuel consumption based on the actual energy information of each energy collection point; A control module for using the strategy of minimizing the equivalent fuel consumption generated based on the optimal equivalent factor to perform real-time fuel consumption control on the diesel engine and the motor of the ship; The energy collection point set determination module includes the following sub-modules: A voyage segment acquisition sub-module for acquiring multiple voyage segments in the entire voyage; An output power acquisition sub-module for acquiring the first output power of the diesel engine and the second output power of the motor; A navigation required power determination sub-module for determining the navigation required power of the ship according to the first output power and the second output power; A first equivalent fuel consumption power determination sub-module for determining the equivalent fuel consumption power of the ship according to the first output power and the second output power; A second equivalent fuel consumption power determination sub-module for using a piecewise linear function related to the multiple voyage segments to divide the navigation required power into several required power intervals, and determining the interval equivalent fuel consumption power corresponding to each required power interval; An energy collection point determination sub-module for taking the minimum value of the piecewise linear function with the goal of achieving the optimal output power of the diesel engine at each interval equivalent fuel consumption power as the energy collection point of the corresponding voyage segment, where the minimum equivalent fuel consumption can be obtained at each energy collection point; The calculation formula for the equivalent fuel consumption power of the ship is: p eqv,hev = a e P e + b e + s(a m P m + b m ) = a e P e + b e + s(a m (P req - P e ) + b m ) P req = P e + P m where p eqv,hev is the equivalent fuel consumption power, P req is the power required for navigation, P e is the first output power of the diesel engine, P m is the second output power of the motor, a e and b e are the linear fitting coefficients, and the fitting coefficients are functions of speed. a m , b m are the fitting coefficients of the input power and output power of the motor during the power generation state of the motor, and s is the equivalent factor.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a ship energy management method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for implementing, when executed by a processor, a ship energy management method according to any one of claims 1-6.

Images