A fuel optimization calculation method and system for ship energy management

Abstract

This invention discloses a fuel optimization calculation method and system for ship energy management, belonging to the field of hybrid power system energy management technology. The method includes: real-time acquisition of generator set fuel consumption rate, battery charging and discharging current, and ambient temperature; calculation of the battery instantaneous charge and discharge rate factor, obtaining the basic attenuation coefficient by combining a temperature lookup mapping table, and generating the actual loss rate by associating it with a cycle life model; when the actual loss rate exceeds a preset threshold, marking the battery as a high-loss state, and determining the accelerated aging life attenuation increment using the battery aging characteristic curve, and generating a one-sided loss compensation value by combining it with replacement costs; converting the one-sided loss compensation value into an equivalent fuel loss amount and adding it to the fuel consumption rate; and generating a power distribution optimization command based on the superimposed fuel consumption rate. This invention accurately quantifies the implicit costs of the battery under high-loss conditions and incorporates them into the optimization objective, significantly improving the overall economic efficiency of ship hybrid power system operation.

Description

Technical Field

[0001] This invention relates to the field of energy management technology for hybrid power systems, and in particular to a fuel optimization calculation method and system for ship energy management. Background Technology

[0002] In marine hybrid power systems, traditional energy management strategies mainly focus on optimizing the instantaneous fuel consumption of generator sets. These strategies typically treat the charging and discharging behavior of batteries as a fixed or negligible energy source. However, when batteries are in a high-loss state (e.g., high-current charging and discharging, high-temperature environment), their aging rate will be significantly accelerated, far exceeding the loss level under normal operating conditions. This accelerated aging and the resulting battery life degradation constitute a significant hidden cost in long-term operation.

[0003] Existing technologies fail to effectively identify this high-loss state of batteries, and are unable to accurately quantify the additional lifespan loss cost caused by the portion exceeding the normal loss threshold, and incorporate it into the scope of real-time energy optimization. Therefore, traditional optimization strategies based on minimizing instantaneous fuel consumption often overuse batteries in high-loss states (because they appear to be "fuel-efficient"), leading to an unexpected shortening of battery life and ultimately increasing the overall operating cost of the system, failing to achieve true global economic optimization. Summary of the Invention

[0004] This invention provides a fuel optimization calculation method and system for ship energy management. Its main purpose is to solve the problem that the overall economic efficiency of the system is not optimal in hybrid ship energy management because the hidden costs caused by the accelerated aging of batteries under high-loss conditions are ignored.

[0005] To achieve the above objectives, the present invention provides a fuel optimization calculation method for ship energy management, comprising:

[0006] Real-time data collection of generator set fuel consumption rate, battery pack charging and discharging current, and ambient temperature;

[0007] The instantaneous charge / discharge rate factor of the battery pack is determined based on the charge / discharge current. Based on the instantaneous charge / discharge rate factor and the ambient temperature, the temperature-rate decay mapping table of the battery pack is queried to output the basic decay coefficient. The basic decay coefficient is associated with the cycle life model of the battery pack to generate the actual loss rate.

[0008] When the actual loss rate exceeds the preset loss rate threshold, the current battery pack is marked as being in a high loss state.

[0009] For battery packs in a high-loss state, the positive difference between the actual loss rate and the preset loss rate threshold is calculated in real time.

[0010] Based on the three-dimensional relationship between current, temperature and lifespan decay in the battery aging characteristic curve, the positive difference is mapped to the accelerated aging lifespan decay increment, and multiplied by the battery pack replacement cost coefficient to generate a one-sided loss compensation value.

[0011] The unilateral loss compensation value is converted into an equivalent fuel loss amount and superimposed on the fuel consumption rate. Based on the superimposed fuel consumption rate, a ship power distribution optimization command is generated.

[0012] To address the above problems, the present invention also provides a fuel optimization calculation system for ship energy management, the system comprising:

[0013] The data acquisition module is used to collect data on the generator set's fuel consumption rate, battery pack charging and discharging current, and ambient temperature in real time.

[0014] The battery loss quantification module is used to determine the instantaneous charge-discharge rate factor of the battery pack based on the charge-discharge current, query the temperature-rate decay mapping table of the battery pack based on the instantaneous charge-discharge rate factor and the ambient temperature to output the basic decay coefficient, and associate the basic decay coefficient with the cycle life model of the battery pack to generate the actual loss rate.

[0015] The high loss state determination module is used to mark the current battery pack as being in a high loss state when the actual loss rate exceeds a preset loss rate threshold.

[0016] The loss difference calculation module is used to calculate the positive difference between the actual loss rate and the preset loss rate threshold in real time for a battery pack in a high loss state.

[0017] The unilateral loss compensation module is used to map the positive difference into an accelerated aging life decay increment based on the three-dimensional relationship of current-temperature-life decay in the battery aging characteristic curve, and multiply it by the replacement cost coefficient of the battery pack to generate a unilateral loss compensation value.

[0018] The power distribution optimization module is used to convert the unilateral loss compensation value into an equivalent fuel loss amount and add it to the fuel consumption rate, and generate a ship power distribution optimization command based on the superimposed fuel consumption rate.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. By collecting key parameters such as generator set fuel consumption rate, battery charging and discharging current, and ambient temperature in real time, and accurately calculating the actual battery loss rate based on the battery cycle life model, it can effectively identify whether the battery is in a high loss state. On this basis, it can specifically calculate the positive difference exceeding the preset loss rate threshold, and use the pre-established battery aging characteristic curve (reflecting the three-dimensional relationship of current-temperature-life decay) to accurately map the positive difference into the accelerated aging life decay increment. Then, combined with the battery replacement cost coefficient, it can calculate the one-sided loss compensation value only for the part exceeding the normal loss, which solves the technical problem that traditional methods cannot accurately quantify the additional loss cost of batteries under abnormal operating conditions.

[0021] 2. By converting the unilateral loss compensation value into an equivalent fuel loss and adding it to the original fuel consumption rate of the generator set, a new optimization objective that comprehensively considers both instantaneous fuel consumption and the implicit aging cost of the battery is constructed. Based on this added fuel consumption rate, power allocation optimization is performed in combination with system constraints (such as using a quadratic programming algorithm), generating a power allocation command with better global economy. This effectively overcomes the limitation of traditional strategies that only focus on instantaneous fuel consumption and ignore the long-term aging cost of the battery, realizing the coordinated optimization of power allocation between the generator set and the battery pack. This significantly improves the overall economy of energy management in hybrid ships and reduces the system's total life cycle operating cost. Attached Figure Description

[0022] Figure 1 A flowchart illustrating a fuel optimization calculation method for ship energy management according to an embodiment of the present invention;

[0023] Figure 2 A temperature-rate degradation mapping table stored in a battery management system is provided in one embodiment of the present invention;

[0024] Figure 3 A functional block diagram of a fuel optimization calculation system for ship energy management provided in an embodiment of the present invention;

[0025] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0026] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0027] This application provides a fuel optimization calculation method for ship energy management. The execution entity of the fuel optimization calculation method for ship energy management includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the fuel optimization calculation method for ship energy management can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0028] Reference Figure 1 The diagram shown is a flowchart illustrating a fuel optimization calculation method for ship energy management according to an embodiment of the present invention. In this embodiment, the fuel optimization calculation method for ship energy management includes:

[0029] S1. Real-time acquisition of generator set fuel consumption rate, battery pack charging and discharging current and ambient temperature.

[0030] In some embodiments, the real-time acquisition of the generator set's fuel consumption rate, the battery pack's charging and discharging current, and the ambient temperature includes:

[0031] Real-time fuel flow signals from the diesel generator set are obtained through the ship's bus interface to generate fuel consumption rates.

[0032] The charging and discharging current of the lithium-ion battery pack is collected through the battery management system.

[0033] Temperature readings at various points within the battery compartment are obtained using a temperature sensor array, with the highest reading taken as the ambient temperature.

[0034] In this embodiment, fuel consumption rate refers to the mass of fuel consumed by the generator set per unit time; charging and discharging current refers to the current passing through the battery pack during charging or discharging; and ambient temperature refers to the highest reading among multiple temperature distribution points within the battery compartment.

[0035] In this embodiment of the application, the real-time acquisition of the generator set's fuel consumption rate, the battery pack's charging and discharging current, and the ambient temperature includes:

[0036] Firstly, regarding the fuel consumption rate of the generator set, the ship's bus interface is the communication interface connecting various ship equipment. When the diesel generator set is running, it generates a real-time fuel flow signal, which is transmitted through the ship's bus interface. After receiving this signal, the system calculates and processes it according to unit time to generate the fuel consumption rate. For example, if the real-time fuel flow signal from the ship's bus interface shows a fuel consumption of 0.6 kg per minute, then the calculated fuel consumption rate is 36 kg per hour.

[0037] Secondly, regarding the charging and discharging current of the battery pack, the battery management system (BMS) is a system specifically designed to manage the battery pack. It includes a current acquisition module that can monitor the current changes of the lithium-ion battery pack in real time during the charging and discharging process, thereby acquiring the charging and discharging current. For example, when the battery pack is in a discharging state, the current acquired by the BMS may be -100A, with the negative sign indicating discharging; when it is in a charging state, it may acquire a current of 80A.

[0038] Finally, regarding the ambient temperature, the temperature sensor array consists of multiple temperature sensors distributed at different locations within the battery compartment. These sensors acquire temperature readings at each location, and the system processes these readings, selecting the highest reading as the ambient temperature. Assuming the temperature readings acquired by the temperature sensor array at different locations within the battery compartment are 30℃, 32℃, 35℃, and 33℃, then the ambient temperature is determined to be 35℃.

[0039] In this embodiment of the application, the collected fuel consumption rate, charge and discharge current and ambient temperature will be used as input data for calculating parameters such as instantaneous charge and discharge rate factor and basic attenuation coefficient in step S2, and will be the starting data source for the entire fuel optimization calculation process.

[0040] S2. Determine the instantaneous charge / discharge rate factor of the battery pack based on the charge / discharge current, query the temperature-rate decay mapping table of the battery pack based on the instantaneous charge / discharge rate factor and the ambient temperature to output the basic decay coefficient, and associate the basic decay coefficient with the cycle life model of the battery pack to generate the actual loss rate.

[0041] In this embodiment of the application, the instantaneous charge / discharge rate factor refers to the ratio of the absolute value of the charge / discharge current to the rated capacity of the battery pack, and the unit is the reciprocal of the hour; the temperature-rate decay mapping table is a two-dimensional lookup table stored in the battery management system, with the rate factor on the horizontal axis and the ambient temperature on the vertical axis, and the values ​​in the table are the basic decay coefficients between 0 and 1.

[0042] In this embodiment of the application, the basic attenuation coefficient is a value obtained by looking up the temperature-rate attenuation mapping table and is used to reflect the degree of battery attenuation under the current operating conditions. Its value is between 0 and 1.

[0043] In the embodiments of this application, the cycle life model is a model used to describe the life decay law of the battery pack under different operating conditions. In this application, an exponential life decay function based on the Arrhenius equation is used. The actual loss rate is a parameter that characterizes the rate of battery life consumption after associating the basic decay coefficient with the cycle life model.

[0044] In some embodiments, determining the instantaneous charge / discharge rate factor of the battery pack based on the charge / discharge current includes:

[0045] Obtain the rated capacity value of the battery pack, divide the absolute value of the charging and discharging current by the rated capacity value, and output the instantaneous charge and discharge rate factor of the battery pack.

[0046] In this embodiment of the application, determining the instantaneous charge / discharge rate factor of the battery pack based on the charge / discharge current includes:

[0047] First, you need to obtain the rated capacity value of the battery pack. This rated capacity value is an inherent parameter of the battery pack and can be obtained from the battery pack's datasheet. For example, the rated capacity value of a certain lithium-ion battery pack is 200 amp-hours.

[0048] Then, the charging and discharging current collected in step S1 is obtained. Since the charging and discharging current is positive and negative, it is positive when charging and negative when discharging. The rate factor only focuses on the magnitude of the current, so the absolute value of the charging and discharging current needs to be taken.

[0049] Finally, the absolute value of the charging / discharging current is divided by the rated capacity value, and the result is the instantaneous charge / discharge rate factor. For example, if the charging / discharging current collected in S1 is -100 amperes (indicating discharge), and its absolute value is 100 amperes, then the instantaneous charge / discharge rate factor is 100 amperes divided by 200 amperes, which is the reciprocal of 0.5 hours.

[0050] In some embodiments, such as Figure 2 As shown, the step of querying the temperature-rate degradation mapping table of the battery pack based on the instantaneous charge / discharge rate factor and the ambient temperature to output the basic degradation coefficient includes:

[0051] The two-dimensional lookup table stored in the battery management system is invoked, wherein the horizontal axis of the two-dimensional lookup table is the rate factor and the vertical axis is the ambient temperature;

[0052] Using the instantaneous charge / discharge rate factor and ambient temperature under the current operating conditions as joint index coordinates, the basic attenuation coefficient between 0 and 1 is output.

[0053] In this embodiment, the basic attenuation coefficient is output by querying a temperature-rate attenuation mapping table based on the instantaneous charge / discharge rate factor and ambient temperature. This includes: the temperature-rate attenuation mapping table is pre-stored in the battery management system. This table is obtained through extensive laboratory testing of the same type of battery pack and covers the basic attenuation coefficients corresponding to different combinations of rate factors and ambient temperatures. When a query is needed, the system calls this two-dimensional lookup table, using the currently calculated instantaneous charge / discharge rate factor as the horizontal axis and the ambient temperature obtained in step S1 as the vertical axis. The corresponding value is found in the lookup table using the combined index formed by these two coordinates; this value is the basic attenuation coefficient.

[0054] For example, if the current instantaneous charge / discharge rate factor is the reciprocal of 0.5 hours and the ambient temperature is 35 degrees Celsius, the corresponding base attenuation coefficient in the lookup table is 0.6.

[0055] In some embodiments, the step of associating the basic attenuation coefficient with the cycle life model of the battery pack to generate the actual loss rate includes:

[0056] Input the basic decay coefficient into the exponential lifetime decay function constructed based on the Arrhenius equation;

[0057] The exponential life decay function is cumulatively corrected based on the number of cycles the battery pack has undergone, and the actual loss rate, which characterizes the rate at which the battery life is consumed, is output.

[0058] In this embodiment of the application, the actual loss rate is generated by associating the basic attenuation coefficient with the cycle life model of the battery pack, including:

[0059] First, an exponential lifetime decay function is constructed based on the Arrhenius equation. This function can be expressed as an exponential relationship between the lifetime decay and parameters such as the basic decay coefficient and temperature, which can reflect the influence of temperature on battery aging.

[0060] Then, the previously obtained basic degradation coefficient is input into the exponential lifetime degradation function. Simultaneously, the number of battery cycles completed needs to be obtained, which can be recorded and stored by the battery management system; for example, a battery pack may have completed 500 cycles.

[0061] Next, the exponential life decay function is cumulatively corrected based on the number of cycles already completed. This is because battery aging is a cumulative process; the more cycles completed, the greater the cumulative impact on aging. This process is implemented accordingly.

[0062] Ultimately, the output represents the actual degradation rate that characterizes the current rate at which the battery's lifespan is being consumed. For example, by inputting a base degradation coefficient of 0.6 into the function and correcting it for 500 cycles, the actual degradation rate is 0.002 per cycle.

[0063] In this embodiment of the application, this step enables a quantitative assessment of battery wear, solving the problem that traditional methods cannot accurately measure the degree of battery aging under different operating conditions, and providing a basis for subsequent judgment on whether the battery is in a high-wear state.

[0064] S3. When the actual loss rate exceeds the preset loss rate threshold, mark the current battery pack as being in a high loss state.

[0065] In this embodiment of the application, the preset loss rate threshold refers to the upper limit of the battery pack's loss rate under normal operating conditions, which is determined based on the statistics of the ship's historical operating data and in conjunction with the verification of the battery specifications; the high loss state refers to the state when the actual loss rate of the battery pack continuously exceeds the preset loss rate threshold for a preset duration.

[0066] In some embodiments, marking the current battery pack as being in a high-loss state when the actual loss rate exceeds a preset loss rate threshold includes:

[0067] The upper limit of the battery pack's loss rate under normal operating conditions is determined based on statistics from the ship's historical operation database.

[0068] By combining the accelerated aging critical conditions in the battery specifications, the rationality of the upper limit of the loss rate is verified, and the verified upper limit of the loss rate is solidified as a preset loss rate threshold.

[0069] The actual loss rate is continuously compared with the preset loss rate threshold. When the actual loss rate is continuously greater than the preset loss rate threshold for a preset duration, the current battery pack is marked as being in a high loss state.

[0070] In this embodiment, the upper limit of battery pack wear rate under normal operating conditions is determined based on statistics from a ship's historical operation database. This includes: the ship's historical operation database stores a large amount of wear rate data for battery packs during the past operation of this type of ship. This data covers various normal operating conditions such as different routes, different loads, and different ambient temperatures. The system calls this database and uses statistical analysis methods, such as calculating the 95th percentile of the data, to use this percentile as the preliminary upper limit of the wear rate under normal operating conditions.

[0071] For example, statistical analysis was performed on 1,000 sets of normal operating condition loss rate data from the database over the past year. The loss rate corresponding to the 95th percentile value was 0.0015 per cycle. This value was used as the initial upper limit of the loss rate.

[0072] In this embodiment, the rationality of the upper limit of the loss rate is verified and solidified as a preset loss rate threshold in conjunction with the accelerated aging critical conditions in the battery specifications. This includes: the battery specifications clearly record the accelerated aging critical conditions for this type of battery pack under different operating conditions, including the aging rate at a specific loss rate. The statistically obtained upper limit of the loss rate is compared with the accelerated aging critical conditions. If the upper limit is lower than the loss rate corresponding to the critical conditions, it indicates that the upper limit is within a safe range and is reasonable; if it is higher, it needs to be lowered to below the critical conditions. After verification, the above-mentioned upper limit of the loss rate of 0.0015 per cycle is lower than the 0.002 per cycle corresponding to the accelerated aging critical conditions in the specifications, therefore it is solidified as a preset loss rate threshold.

[0073] In this embodiment, continuously comparing the actual loss rate with a preset loss rate threshold and marking a high loss state includes: acquiring the actual loss rate calculated in step S2 in real time and continuously comparing it with the preset loss rate threshold. The preset duration is set according to battery characteristics and ship operation requirements, for example, 5 minutes. When the actual loss rate continues to exceed the preset loss rate threshold for 5 minutes, the system automatically marks the current battery pack as being in a high loss state.

[0074] For example, if the actual loss rate is 0.002 per cycle, the preset loss rate threshold is 0.0015 per cycle, and this state lasts for 5 minutes, then the battery pack is marked as a high loss state.

[0075] In this embodiment of the application, this step can identify the abnormal aging state of the battery pack in a timely manner, which solves the problem that traditional methods cannot accurately determine whether the battery is in an accelerated aging state, and provides a premise for subsequent loss compensation calculation.

[0076] S4. For a battery pack in a high-loss state, calculate the positive difference between the actual loss rate and the preset loss rate threshold in real time.

[0077] In this embodiment of the application, the positive difference refers to the positive value obtained by subtracting the preset loss rate threshold from the actual loss rate of the battery pack in a high loss state.

[0078] In this embodiment of the application, the positive difference between the actual loss rate and the preset loss rate threshold is calculated in real time for a battery pack in a high-loss state, including:

[0079] First, the system confirms that the battery pack has been marked as being in a high-loss state, which is a prerequisite for performing the calculation. This state information comes from the output of step S3.

[0080] Then, the actual loss rate continuously updated in step S2 is obtained in real time, and the preset loss rate threshold that has been fixed in step S3 is retrieved. The actual loss rate is subtracted from the preset loss rate threshold by subtraction. Since the battery pack is in a high loss state at this time, the actual loss rate is greater than the preset loss rate threshold, so the result is positive. This positive value is the positive difference.

[0081] For example, if the current actual loss rate is 0.002 per cycle and the preset loss rate threshold is 0.0015 per cycle, then by subtracting 0.0015 from 0.002, the positive difference is 0.0005 per cycle. The system will repeat the above data acquisition and calculation process at certain time intervals (e.g., once per second) to achieve real-time updates of the positive difference.

[0082] In this embodiment of the application, this step quantifies the portion of the battery pack that exceeds normal wear and tear, solving the problem that traditional methods cannot clearly define the degree of excessive battery wear and tear, and providing a specific quantitative basis for converting wear and tear into economic costs.

[0083] S5. Based on the three-dimensional relationship of current-temperature-life decay in the battery aging characteristic curve, the positive difference is mapped to the accelerated aging life decay increment, and multiplied by the replacement cost coefficient of the battery pack to generate a one-sided loss compensation value.

[0084] In this embodiment, the battery aging characteristic curve is a curve describing the life decay law of the battery pack under different charging and discharging currents and ambient temperatures; the current-temperature-life decay three-dimensional relationship refers to the correlation between charging and discharging current, ambient temperature and battery life decay amount; the accelerated aging life decay increment refers to the additional life decay amount generated by the battery pack due to exceeding normal wear and tear, which is obtained by mapping the positive difference.

[0085] In the embodiments of this application, the replacement cost coefficient refers to the replacement cost per unit capacity of the battery pack; the one-sided loss compensation value refers to the compensation value obtained by converting the accelerated aging life decay increment into economic cost, which is only for the part exceeding the normal loss.

[0086] In some embodiments, the method of mapping the positive difference based on the three-dimensional relationship of current-temperature-lifetime degradation in the battery aging characteristic curve to an accelerated aging lifetime degradation increment, and multiplying it by the battery pack replacement cost coefficient to generate a one-sided loss compensation value, includes:

[0087] Multi-condition cyclic aging tests were conducted on the same type of battery pack in a laboratory environment, and life decay data under different combinations of charge and discharge current and ambient temperature were recorded.

[0088] Based on the lifetime decay data, and combined with the least squares method, a nonlinear decay surface with current-temperature dual dimensions is generated, wherein the nonlinear decay surface uses the charge and discharge current under the current operating condition as the X-axis coordinate and the ambient temperature as the Y-axis coordinate.

[0089] Extract the accelerated aging lifetime decay increment corresponding to the positive difference from the nonlinear decay surface;

[0090] The accelerated aging life decay increment is converted into a capacity decay percentage and multiplied by the total capacity of the battery pack to obtain the equivalent loss capacity.

[0091] Multiply the equivalent loss capacity by the unit capacity replacement cost of the battery pack to output an economic compensation value as a one-sided loss compensation value.

[0092] In this embodiment, multi-condition cyclic aging tests are conducted on the same type of battery pack in a laboratory environment, and lifespan degradation data under different combinations of charge / discharge current and ambient temperature are recorded. This includes: selecting the same type of battery pack used on ships as the test sample; building a test platform in the laboratory simulating the working environment of ship batteries; and precisely controlling the charge / discharge current and ambient temperature. Multiple combinations of different charge / discharge currents (e.g., 50A, 100A, 150A) and ambient temperatures (e.g., 25℃, 30℃, 35℃) are set up to conduct cyclic charge / discharge aging tests on the battery pack. During the test, the lifespan degradation data of the battery pack under each condition is continuously recorded. For example, under a charge / discharge current of 100A and an ambient temperature of 35℃, how much the battery lifespan has decreased after a certain number of cycles. This data will serve as the basis for subsequently constructing a nonlinear degradation surface.

[0093] In this embodiment, a nonlinear decay surface with current-temperature dual dimensions is generated based on lifetime decay data and combined with the least squares method. This includes: collecting all lifetime decay data obtained from laboratory tests, establishing a data point set with charge / discharge current as the X-axis coordinate, ambient temperature as the Y-axis coordinate, and lifetime decay amount as the Z-axis coordinate; and then fitting these data points using the least squares method to construct a nonlinear decay surface that reflects the lifetime decay law under the current-temperature dual dimensions. This surface can output the corresponding lifetime decay amount for any given charge / discharge current and ambient temperature.

[0094] For example, when the charging / discharging current is 100A and the ambient temperature is 35℃, the corresponding lifetime degradation can be found through this surface.

[0095] In this embodiment, extracting the accelerated aging lifetime decay increment corresponding to the positive difference from the nonlinear decay surface includes: obtaining the positive difference calculated in step S4, and searching for it in the constructed nonlinear decay surface in conjunction with the charge / discharge current and ambient temperature under the current operating conditions. Using the positive difference, charge / discharge current, and ambient temperature as search criteria, the lifetime decay increment corresponding to it is found in the surface, and this increment is the accelerated aging lifetime decay increment.

[0096] For example, when the positive difference is 0.0005 per cycle, the charge / discharge current is 100A, and the ambient temperature is 35℃, the accelerated aging life decay increment extracted from the surface is 5%.

[0097] In this embodiment, converting the accelerated aging life decay increment into a capacity decay percentage and multiplying it by the total capacity of the battery pack to obtain the equivalent loss capacity includes: Based on the characteristics of the battery, there is a corresponding relationship between the accelerated aging life decay increment and the capacity decay percentage; for example, a 5% accelerated aging life decay increment corresponds to a 2% capacity decay percentage. The obtained accelerated aging life decay increment is converted into a capacity decay percentage according to this relationship. Then, the total capacity of the battery pack (e.g., 200Ah) is obtained, and the capacity decay percentage is multiplied by the total capacity to obtain the equivalent loss capacity. For example, if the capacity decay percentage is 2% and the total capacity is 200Ah, then the equivalent loss capacity is 200Ah × 2% = 4Ah.

[0098] In this embodiment of the application, the equivalent loss capacity is multiplied by the unit capacity replacement cost of the battery pack to output an economic compensation value as a one-sided loss compensation value. This includes: obtaining the unit capacity replacement cost of the battery pack (e.g., 10 yuan / Ah), multiplying the equivalent loss capacity by the unit capacity replacement cost, and the result is the economic compensation value, which is also the one-sided loss compensation value.

[0099] For example, if the equivalent loss capacity is 4Ah and the unit capacity replacement cost is 10 yuan / Ah, then the one-sided loss compensation value is 4Ah × 10 yuan / Ah = 40 yuan.

[0100] In this embodiment of the application, this step quantifies the excessive battery wear into a specific economic cost, which solves the problem that traditional methods cannot incorporate the hidden aging cost of batteries into energy management considerations, and provides an economic basis for optimizing ship power distribution.

[0101] S6. Convert the unilateral loss compensation value into an equivalent fuel loss amount and add it to the fuel consumption rate. Generate a ship power distribution optimization command based on the superimposed fuel consumption rate.

[0102] In this embodiment, the equivalent fuel loss refers to the fuel mass that is economically equivalent to the compensation value, obtained by converting the unilateral loss compensation value according to the current market price of marine fuel oil and the measured lower heating value of the generator set; the superimposed fuel consumption rate refers to the rate obtained by superimposing the equivalent fuel loss onto the original fuel consumption rate; the ship power distribution optimization command refers to the command generated based on the superimposed fuel consumption rate to guide the generator set and battery pack in power distribution.

[0103] In some embodiments, converting the unilateral loss compensation value into an equivalent fuel loss includes:

[0104] Obtain the current market price of marine fuel oil;

[0105] Based on the measured lower heating value of the generator set and the market price, calculate the mass of edible fuel corresponding to one unit of currency.

[0106] Divide the unilateral loss compensation value by the consuming fuel mass corresponding to the unit currency to generate the equivalent fuel loss amount for cost optimization.

[0107] In this embodiment of the application, the market price of marine fuel oil refers to the unit mass price of this type of fuel oil in the current market; the measured lower heating value of the generator set refers to the heat released when the fuel oil used by the generator set is completely burned, as obtained through actual measurement; the consuming fuel mass corresponding to a unit of currency refers to the fuel mass that can be purchased with each unit of currency.

[0108] In some embodiments, generating ship power distribution optimization instructions based on the superimposed fuel consumption rates includes:

[0109] Establish an optimization model with the superimposed fuel consumption rate as the objective function;

[0110] Add the power limit of the generator set and the safety range of the battery pack as constraints;

[0111] The optimal power allocation instruction set between the generator set and the battery pack is solved using a quadratic programming algorithm.

[0112] In this embodiment of the application, the optimization model is a mathematical model with the superimposed fuel consumption rate as the objective function and the generator set power limit and the battery pack safety range as constraints; the generator set power limit refers to the maximum power range that the generator set can achieve under the premise of safe and stable operation.

[0113] In this embodiment, the safe range of the battery pack refers to the range of parameters such as voltage and current that the battery pack can maintain a safe state during charging and discharging; the quadratic programming algorithm is a mathematical optimization algorithm used to solve the optimal solution of a quadratic objective function under convex constraints; the optimal power allocation instruction set refers to the generator set and battery pack power allocation scheme obtained by solving the quadratic programming algorithm, which optimizes the superimposed fuel consumption rate.

[0114] In this embodiment of the application, obtaining the current market price of marine fuel oil includes: obtaining the current market price of marine fuel oil in real time by accessing the ship's information management system or connecting to an external market price database, for example, obtaining a market price of 5 yuan / kg.

[0115] In this embodiment, the calculation of the edible fuel mass per unit currency based on the measured lower heating value of the generator set and the market price includes: the measured lower heating value of the generator set is obtained in advance through professional equipment, for example, a measured lower heating value of 42,000 kJ / kg. The calculation method for the edible fuel mass per unit currency is 1 divided by the market price, i.e., the fuel mass that 1 yuan can buy. If the market price is 5 yuan / kg, then the edible fuel mass per unit currency is 1 / 5 = 0.2 kg / yuan.

[0116] In this embodiment of the application, the equivalent fuel loss is generated by dividing the unilateral loss compensation value by the consuming fuel mass corresponding to a unit currency. This includes: obtaining the unilateral loss compensation value obtained in step S5, for example, a unilateral loss compensation value of 40 yuan. Dividing this compensation value by the consuming fuel mass corresponding to a unit currency, i.e., 40 yuan divided by 0.2 kg / yuan, yields an equivalent fuel loss of 20 kg.

[0117] In this embodiment, an optimization model is established with the superimposed fuel consumption rate as the objective function. This model includes: the superimposed fuel consumption rate is the sum of the original fuel consumption rate obtained in step S1 and the rate converted from the equivalent fuel loss per unit time. For example, if the original fuel consumption rate is 36 kg / hour and the equivalent fuel loss is 20 kg (calculated over 1 hour), then the superimposed fuel consumption rate is 56 kg / hour. This superimposed rate is used as the objective function, with the goal of minimizing its value.

[0118] In this embodiment, the power limit of the generator set and the safety range of the battery pack are added as constraints. These constraints include: the power limit of the generator set is determined based on its design parameters and operating experience, for example, a power limit of 50-200 kW; and the safety range of the battery pack is determined according to the battery pack's specifications, for example, a voltage safety range of 200-250 volts and a current safety range of -150 to 150 amps. These parameter ranges are added as constraints to the optimization model to ensure that the solved power allocation scheme is within the safety range.

[0119] In this embodiment, a quadratic programming algorithm is used to solve for the optimal power allocation instruction set between the generator set and the battery pack. This includes inputting a pre-established optimization model with the superimposed fuel consumption rate as the objective function and the generator set power limit and battery pack safety range as constraints into the quadratic programming algorithm. The algorithm solves the model to obtain the power allocation values ​​between the generator set and the battery pack that optimize the objective function. For example, the solution might yield a generator set providing 120 kW of power and a battery pack providing 80 kW of power. These allocation values ​​constitute the optimal power allocation instruction set.

[0120] In this embodiment of the application, this step incorporates the hidden cost of battery wear into the fuel consumption consideration, making the power distribution of the ship more economical and reasonable, and solving the problem of poor overall economic efficiency caused by focusing only on instantaneous fuel consumption and ignoring the cost of battery aging in traditional methods.

[0121] like Figure 3 The diagram shown is a functional block diagram of a fuel optimization calculation system for ship energy management provided in an embodiment of the present invention.

[0122] The fuel optimization calculation system 100 for ship energy management described in this invention can be installed in an electronic device. Depending on the functions implemented, the fuel optimization calculation system 100 may include a data acquisition module 101, a battery loss quantification module 102, a high loss state determination module 103, a loss difference calculation module 104, a one-sided loss compensation module 105, and a power distribution optimization module 106. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0123] In this embodiment, the functions of each module / unit are as follows:

[0124] Data acquisition module 101 is used to collect data on the fuel consumption rate of the generator set, the charging and discharging current of the battery pack, and the ambient temperature in real time.

[0125] The battery loss quantification module 102 is used to determine the instantaneous charge-discharge rate factor of the battery pack based on the charge-discharge current, query the temperature-rate decay mapping table of the battery pack based on the instantaneous charge-discharge rate factor and the ambient temperature to output the basic decay coefficient, and associate the basic decay coefficient with the cycle life model of the battery pack to generate the actual loss rate.

[0126] The high loss state determination module 103 is used to mark the current battery pack as being in a high loss state when the actual loss rate exceeds a preset loss rate threshold.

[0127] The loss difference calculation module 104 is used to calculate the positive difference between the actual loss rate and the preset loss rate threshold in real time for a battery pack in a high loss state.

[0128] The one-sided loss compensation module 105 is used to map the positive difference into an accelerated aging life decay increment based on the three-dimensional relationship of current-temperature-life decay in the battery aging characteristic curve, and multiply it by the replacement cost coefficient of the battery pack to generate a one-sided loss compensation value.

[0129] The power distribution optimization module 106 is used to convert the unilateral loss compensation value into an equivalent fuel loss amount and add it to the fuel consumption rate, and generate a ship power distribution optimization command based on the superimposed fuel consumption rate.

[0130] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0131] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0132] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0133] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0134] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A fuel optimization calculation method for ship energy management, characterized in that, The method includes: Real-time data collection of generator set fuel consumption rate, battery pack charging and discharging current, and ambient temperature; The instantaneous charge / discharge rate factor of the battery pack is determined based on the charge / discharge current. Based on the instantaneous charge / discharge rate factor and the ambient temperature, the temperature-rate decay mapping table of the battery pack is queried to output the basic decay coefficient. The basic decay coefficient is associated with the cycle life model of the battery pack to generate the actual loss rate. When the actual loss rate exceeds the preset loss rate threshold, the current battery pack is marked as being in a high loss state. For battery packs in a high-loss state, the positive difference between the actual loss rate and the preset loss rate threshold is calculated in real time. Based on the three-dimensional relationship between current, temperature and lifespan decay in the battery aging characteristic curve, the positive difference is mapped to the accelerated aging lifespan decay increment, and multiplied by the battery pack replacement cost coefficient to generate a one-sided loss compensation value. The unilateral loss compensation value is converted into an equivalent fuel loss amount and superimposed on the fuel consumption rate. Based on the superimposed fuel consumption rate, a ship power distribution optimization command is generated.

2. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The real-time acquisition of the generator set's fuel consumption rate, battery pack's charging and discharging current, and ambient temperature includes: Real-time fuel flow signals from the diesel generator set are obtained through the ship's bus interface to generate fuel consumption rates. The charging and discharging current of the lithium-ion battery pack is collected through the battery management system. Temperature readings at various points within the battery compartment are obtained using a temperature sensor array, with the highest reading taken as the ambient temperature.

3. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The step of determining the instantaneous charge / discharge rate factor of the battery pack based on the charge / discharge current includes: Obtain the rated capacity value of the battery pack, divide the absolute value of the charging and discharging current by the rated capacity value, and output the instantaneous charge and discharge rate factor of the battery pack.

4. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The step of querying the temperature-rate degradation mapping table of the battery pack based on the instantaneous charge / discharge rate factor and the ambient temperature to output the basic degradation coefficient includes: The two-dimensional lookup table stored in the battery management system is invoked, wherein the horizontal axis of the two-dimensional lookup table is the rate factor and the vertical axis is the ambient temperature; Using the instantaneous charge / discharge rate factor and ambient temperature under the current operating conditions as joint index coordinates, the basic attenuation coefficient between 0 and 1 is output.

5. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The step of associating the basic attenuation coefficient with the cycle life model of the battery pack to generate the actual loss rate includes: Input the basic decay coefficient into the exponential lifetime decay function constructed based on the Arrhenius equation; The exponential life decay function is cumulatively corrected based on the number of cycles the battery pack has undergone, and the actual loss rate, which characterizes the rate at which the battery life is consumed, is output.

6. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The step of marking the current battery pack as being in a high-loss state when the actual loss rate exceeds a preset loss rate threshold includes: The upper limit of the battery pack's loss rate under normal operating conditions is determined based on statistics from the ship's historical operation database. By combining the accelerated aging critical conditions in the battery specifications, the rationality of the upper limit of the loss rate is verified, and the verified upper limit of the loss rate is solidified as a preset loss rate threshold. The actual loss rate is continuously compared with the preset loss rate threshold. When the actual loss rate is continuously greater than the preset loss rate threshold for a preset time, the current battery pack is marked as being in a high loss state.

7. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The current-temperature-lifetime degradation three-dimensional relationship based on the battery aging characteristic curve maps the positive difference to an accelerated aging lifetime degradation increment, and multiplies it by the battery pack replacement cost coefficient to generate a one-sided loss compensation value, including: Multi-condition cyclic aging tests were conducted on the same type of battery pack in a laboratory environment, and life decay data under different combinations of charge and discharge current and ambient temperature were recorded. Based on the lifetime decay data, and combined with the least squares method, a nonlinear decay surface with current-temperature dual dimensions is generated, wherein the nonlinear decay surface uses the charge and discharge current under the current operating condition as the X-axis coordinate and the ambient temperature as the Y-axis coordinate. Extract the accelerated aging lifetime decay increment corresponding to the positive difference from the nonlinear decay surface; The accelerated aging life decay increment is converted into a capacity decay percentage and multiplied by the total capacity of the battery pack to obtain the equivalent loss capacity. Multiply the equivalent loss capacity by the unit capacity replacement cost of the battery pack to output an economic compensation value as a one-sided loss compensation value.

8. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The step of converting the unilateral loss compensation value into an equivalent fuel loss includes: Obtain the current market price of marine fuel oil; Based on the measured lower heating value of the generator set and the market price, calculate the mass of edible fuel corresponding to one unit of currency. Divide the unilateral loss compensation value by the consuming fuel mass corresponding to the unit currency to generate the equivalent fuel loss amount for cost optimization.

9. The fuel optimization calculation method for ship energy management as described in claim 1, characterized in that, The process of generating ship power distribution optimization instructions based on the superimposed fuel consumption rates includes: Establish an optimization model with the superimposed fuel consumption rate as the objective function; Add the power limit of the generator set and the safety range of the battery pack as constraints; The optimal power allocation instruction set between the generator set and the battery pack is solved using a quadratic programming algorithm.

10. A fuel optimization calculation system for ship energy management, characterized in that, The system includes: The data acquisition module is used to collect data on the generator set's fuel consumption rate, battery pack charging and discharging current, and ambient temperature in real time. The battery loss quantification module is used to determine the instantaneous charge-discharge rate factor of the battery pack based on the charge-discharge current, query the temperature-rate decay mapping table of the battery pack based on the instantaneous charge-discharge rate factor and the ambient temperature to output the basic decay coefficient, and associate the basic decay coefficient with the cycle life model of the battery pack to generate the actual loss rate. The high loss state determination module is used to mark the current battery pack as being in a high loss state when the actual loss rate exceeds a preset loss rate threshold. The loss difference calculation module is used to calculate the positive difference between the actual loss rate and the preset loss rate threshold in real time for a battery pack in a high loss state. The unilateral loss compensation module is used to map the positive difference into an accelerated aging life decay increment based on the three-dimensional relationship of current-temperature-life decay in the battery aging characteristic curve, and multiply it by the replacement cost coefficient of the battery pack to generate a unilateral loss compensation value. The power distribution optimization module is used to convert the unilateral loss compensation value into an equivalent fuel loss amount and add it to the fuel consumption rate, and generate a ship power distribution optimization command based on the superimposed fuel consumption rate.

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