DC networking system for new energy ships and battery power control method

Abstract

New energy ship DC networking system and battery power control method, which is based on the principle that the remaining service lives of all lithium battery packs are consistent, that is, the remaining energies of each lithium battery pack are consistent. By statistically analyzing the health index of each lithium battery pack at the energy supply end in the DC networking system in real time, analyzing the remaining life of each current lithium battery pack, and allocating the load that each lithium battery pack should bear per unit time according to the amount of the remaining life, and then adjusting the output power of each lithium battery pack, so that the final output powers of each lithium battery pack tend to be consistent, thereby making the remaining service lives of each lithium battery pack reach consistency.

Description

Technical Field

[0001] The present invention relates to the field of power control for new energy ships, and particularly to a DC networking system for new energy ships and a battery power control method. Background Art

[0002] In a battery DC networking system, even if the nominal parameters of each lithium battery pack are exactly the same, during its use, due to various factors, the actual service life of each lithium battery will change. This means that even when the load power shared by each lithium battery pack is exactly the same, the actual remaining life of each lithium battery pack will be different. There will always be a lithium battery that runs out of power first or reaches a set threshold, resulting in a sudden increase in the power shared by the remaining lithium battery packs, which greatly affects the stability of the power grid.

[0003] In the field of new energy ships, due to the structural characteristics of the ship and the load distribution characteristics, the battery DC system is distributed on both sides of the ship's hull. The busbars on both sides are connected, and different loads are connected to each side. Controlling the battery life in this distribution situation is a new topic.

[0004] Chinese patent document CN 105548901 A discloses a method for predicting the power state of lithium titanate batteries for rail transit, and document CN 102866360 A discloses a method for estimating the allowable discharge power of a power battery pack. Both propose methods based on the state of charge (SOC) value of the battery to calculate the discharge power of the battery. The parameters analyzed by these methods are too single; patent document CN 108287317 A discloses a method and system for generating a battery power prediction model and a power prediction method and system, which propose to predict the battery power based on a convolutional neural network algorithm, referring to various parameters of the lithium battery, but fail to solve the power distribution between multiple lithium battery packs and the quantitative correlation between individual parameters; patent document CN 112332483 A discloses an energy management control method for a series-connected lithium battery pack, proposing a power adjustment method based on the SOC difference of the series-connected lithium battery pack, making the service life of each lithium battery basically the same, but unable to solve the application scenario of multiple parallel-connected lithium battery packs in a DC networking system. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a DC networking system for new energy ships and a battery power control method, which quantitatively measure the remaining life of each lithium battery pack by analyzing various parameters in the lithium battery pack, improve the safety of using the lithium battery pack, and make the remaining life of each lithium battery pack tend to be consistent.

[0006] To solve the above technical problems, the technical solutions adopted by the present invention are as follows:

[0007] As Figure 1 And2 As shown, the DC networking system of new energy ships includes two power units on the port side and starboard side with the same configuration. There is a DC bus in each of the port side power unit and starboard side power unit. The bus circuit breakers connect the DC buses on both sides. The power unit includes a power component and a load component. The power component includes multiple groups of battery branches arranged in parallel with the same configuration. Each battery branch includes a chopper and a lithium battery pack connected to the DC bus in sequence. An insulation testing device is also connected to the lithium battery pack. The load component includes a propulsion load and a daily power load, and the load component is electrically connected to the DC bus.

[0008] The above-mentioned propulsion load includes a propulsion inverter, a propulsion motor, and a propeller connected to the DC bus and arranged in sequence. The daily power load includes a daily inverter and a daily transformer connected to the DC bus and arranged in sequence. The daily transformer is connected to each daily load on the ship.

[0009] The battery power control method for the above-mentioned DC networking system of new energy ships includes the following steps:

[0010] Step1. Setting of the health index: Set the initial value of the health index of each lithium battery pack as S = 1. According to the actual usage conditions of the lithium battery pack, the factors affecting the health index include the remaining power, lithium battery temperature, voltage, and insulation status of the lithium battery pack, and analyze the proportion of each factor affecting the health index.

[0011] Step2. Initial power distribution: In this DC networking system, the initial states of all lithium battery packs are the same, that is, they have nominally the same health index S. According to the current stable power demand feedback by the load, the total power P is evenly distributed to each lithium battery pack, and the initial output power of each lithium battery pack is

[0012] Step3. Weighted analysis of the health index: According to the actual health index S of each lithium battery pack that changes dynamically j perform weighted adjustment on the initial output power of each lithium battery pack ;

[0013] Step4. Power adjustment: According to the weighted difference △P of the power adjustment of the lithium battery pack obtained in Step3 j , and perform differential control on it through the choppers on the branches where each lithium battery pack is located to change the output power value of each lithium battery pack;

[0014] Step5. Collect the parameters of each lithium battery pack and analyze the real-time health index S of each lithium battery pack j， Then repeat Step1 to Step4 to perform dynamic adjustment on each lithium battery pack, so that the remaining service lives of each lithium battery pack tend to be the same.

[0015] In Step 1 mentioned above, the specific method for the proportion analysis of each factor affecting the health index is as follows:

[0016] Step 1.1. Initial value setting: Denote the preset influence proportion of each influencing factor on the health index as where i = {1, 2, 3, 4} respectively represent the remaining power of the lithium battery pack, temperature, voltage, and insulation status;

[0017] Step 1.2. Measurement of lithium battery pack parameters: The central control system statistically measures the parameters of each lithium battery pack j at fixed intervals, where j = {1, 2, 3...n}, and the parameters include the remaining power value X of the lithium battery pack obtained by monitoring the battery j , the real-time temperature T of the lithium battery pack j , the real-time voltage U of the lithium battery pack j , the leakage current I of the lithium battery pack j ;

[0018] Step 1.3. Analysis of each influence coefficient: Analyze the parameters of each lithium battery pack in Step 1.2 to obtain the influence coefficient of each on each influencing factor

[0019] a. Influence coefficient of the remaining power of the lithium battery pack where x is the lowest threshold of the battery power. When the remaining power of the lithium battery is lower than x, the lithium battery pack no longer outputs power;

[0020] b. Influence coefficient of the real-time temperature of the lithium battery pack where t1 is the lowest temperature at which the lithium battery pack can work normally, and t2 is the highest temperature at which the lithium battery pack can work normally;

[0021] c. Influence coefficient of the real-time voltage of the lithium battery pack where u is the set voltage for stable operation of the system, and △U is the set voltage fluctuation threshold;

[0022] d. Influence coefficient of the insulation status of the lithium battery pack where I0 is the insulation limit leakage current of the lithium battery pack. When I j > I0, there is a short-circuit foreign object inside the lithium battery pack core;

[0023] Step 1.4. Health index calculation: According to the above analysis, the comprehensive influence coefficient of each lithium battery pack is Therefore, the health index of each battery pack is S j = K j S.

[0024] In Step 3 mentioned above, for the initial output power of each lithium battery pack The specific method for weighted adjustment is as follows:

[0025] The current actual life W of each lithium battery pack j = WS j , where W is the initial life of the lithium battery pack. It is recorded that within the unit time t, the weighted power of each lithium battery pack is ΔP1, ΔP2…ΔP n , and the weighting principle is that the lithium battery pack with a high health index outputs more power, and the lithium battery pack with a low health index outputs less power, that is In the formula, P j is the actual output power of each lithium battery pack; after the system runs for time t, the remaining life W j -ΔW j tends to be equal, where ΔW j = P j .t, that is, the health indexes tend to be equal;

[0026] Assume that there are m groups of lithium battery packs S j = 0, that is, there are m groups of lithium battery packs that do not participate in the load power distribution of the system. For the convenience of representation, these m groups of lithium battery packs are centrally numbered, recorded as starting from the fth and ending at the (f + m - 1)th, and the following formula is obtained:

[0027]

[0028] Express the power output by each lithium battery pack within the unit time t in terms of the output power of the first group of lithium battery packs, that is:

[0029]

[0030] It can be obtained that:

[0031]

[0032] That is, the actual output power of each group of lithium battery packs within the unit time t is:

[0033]

[0034] In the above Step1.1, the proportion of the influence of the remaining power of the lithium battery pack on the health index is The proportion of the influence of the temperature of the lithium battery pack on the health index is , and the proportion of the influence of the voltage of the lithium battery pack on the health index is The proportion of the influence of the insulation state of the lithium battery pack on the health index is

[0035] A DC networking system for new energy ships and a battery power control method provided by the present invention have the following beneficial effects:

[0036] 1. A method for evaluating the lifespan of a lithium battery pack based on a health index is proposed. By analyzing various parameters in the lithium battery pack, the influence of each parameter on the health index of the lithium battery pack is clarified. Through real-time detection of relevant parameters, the dynamic health index of the lithium battery pack is obtained, quantitatively measuring the remaining lifespan of each lithium battery pack and improving the safety of the use of the lithium battery pack.

[0037] 2. Based on the health index of each lithium battery pack, the load that each lithium battery pack should bear is analyzed, ensuring that the remaining lifespan of each lithium battery pack tends to be consistent when the system is running, facilitating the unified replacement of the lithium battery packs in the system and improving the stability of the system power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further described below in conjunction with the drawings and embodiments:

[0039] Figure 1 It is a schematic diagram of a DC networked battery power system for a new energy ship in the present invention;

[0040] Figure 2 It is a control diagram for detecting the power of the lithium battery in the present invention.

[0041] Among them: lithium battery pack 1, chopper 2, DC bus 3, bus circuit breaker 4, insulation test device 5, propulsion inverter 6, propulsion motor 7, propeller 8, daily use inverter 9, daily use transformer 10. SPECIFIC EMBODIMENTS

[0042] To make the purpose, technical solutions and advantages of the present invention clearer, the following content will describe the specific technical solutions of the present invention systematically and completely in conjunction with the drawings provided according to the present invention. Obviously, the described embodiments are some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0043] As Figure 1 and 2 shown, the DC networked system of a new energy ship includes two power units on the port side and starboard side with the same configuration. There is a DC bus 3 in the port side power unit and starboard side power unit. The bus circuit breaker 4 connects the DC buses 3 on both sides. The power unit includes a power component and a load component. The power component includes multiple battery branches arranged in parallel with the same configuration. The battery branch includes a chopper 2 and a lithium battery pack 1 connected to the DC bus 3 in sequence. An insulation test device 5 is also connected to the lithium battery pack 1. The load component includes a propulsion load and a daily use power load. The load component is electrically connected to the DC bus 3.

[0044] The above-mentioned propulsion load includes a propulsion inverter 6, a propulsion motor 7, and a propeller 8 that are connected to the DC bus 3 and arranged in sequence. The daily power load includes a daily inverter 9 and a daily transformer 10 that are connected to the DC bus 3 and arranged in sequence. The daily transformer 10 is connected to each daily load on the ship.

[0045] Using the battery power control method of the above-mentioned new energy ship DC networking system, the control method includes the following steps:

[0046] Step1. Setting the health index: Set the initial value of the health index of each lithium battery pack 1 as S = 1. According to the actual usage status of the lithium battery pack 1, the factors affecting the health index include the remaining power, lithium battery temperature, voltage, and insulation status of the lithium battery pack 1, and analyze the proportion of each factor affecting the health index.

[0047] Step1.1. Initial value setting: Denote the preset influence proportion of each influencing factor on the health index as , where i = {1, 2, 3, 4} respectively represent the remaining power, temperature, voltage, and insulation status of the lithium battery pack 1. The influence proportion of the remaining power of the lithium battery pack on the health index is , the influence proportion of the temperature of the lithium battery pack on the health index is The influence proportion of the voltage of the lithium battery pack on the health index is The influence proportion of the insulation status of the lithium battery pack on the health index is Determine the health status of the battery pack according to the remaining power, temperature, voltage, and insulation status of the lithium battery pack and their corresponding weights.

[0048] Step1.2. Measurement of lithium battery pack parameters: The central control system statistically measures the parameters of each lithium battery pack j at fixed intervals, where j = {1, 2, 3... n}. The parameters include the remaining power value X of the lithium battery pack obtained by the central control system monitoring the battery j , the real-time temperature T of the lithium battery pack measured by the temperature sensor j , the real-time voltage U of the lithium battery pack measured by the voltage meter at the chopper 2 lithium battery pack 1 end j , the leakage current I of the lithium battery pack measured by the insulation test device 5 of each lithium battery pack 1 j ;

[0049] Step1.3. Analysis of each influence coefficient: Analyze the parameters of each lithium battery pack in Step1.2 to obtain the influence coefficient of each on each influencing factor

[0050] a. Influence coefficient of the remaining power of the lithium battery pack Where x is the lowest threshold of the battery power. When the remaining power of the lithium battery is lower than x, the lithium battery pack will no longer output power. When the remaining power is greater than the lowest threshold power, the influence coefficient increases with the increase of the remaining power, indicating that the battery is healthier at present;

[0051] b. Influence coefficient of the real-time temperature of the lithium battery pack Where t1 is the lowest temperature at which the lithium battery pack can work normally, and t2 is the highest temperature at which the lithium battery pack can work normally;

[0052] c. Influence coefficient of the real-time voltage of the lithium battery pack Where u is the set voltage for stable operation of the system, and △U is the set voltage fluctuation threshold;

[0053] d. Influence coefficient of the insulation state of the lithium battery pack Where I0 is the insulation limit leakage current of the lithium battery pack. When I j >I0, there are short-circuit foreign objects inside the lithium battery pack cells;

[0054] Step1.4. Health index calculation: According to the foregoing analysis, the comprehensive influence coefficient of each lithium battery pack is Therefore, the health index of each battery pack is S j =K j S. Through the comprehensive judgment of the health index, the state parameters of the above four batteries are combined to comprehensively evaluate the battery state;

[0055] Step2. Initial power distribution. In this DC networking system, the initial states of each lithium battery pack 1 are the same, that is, they have the same nominal health index S. According to the current stable power demand feedback by the load, the total power P is evenly distributed to each lithium battery pack 1, and the initial output power of each lithium battery pack 1 is

[0056] Step3. Weighted analysis of the health index. According to the actual health index S of each lithium battery pack 1 that changes dynamically j The initial output power of each lithium battery pack 1 Is weighted and adjusted. By weighting, the more capable ones do more work, and the power output of the whole device of the lithium battery life is reasonably regulated;

[0057] The current actual life W of each lithium battery pack j =WS j , W is the initial life of the lithium battery pack. It is recorded that within the unit time t, the weighted powers of each lithium battery pack are ΔP1, ΔP2…ΔP n , and the weighting principle is that the lithium battery pack with a high health index outputs more power, and the lithium battery pack with a low health index outputs less power, that is Where Pj is the actual output power of each lithium battery pack; after the system runs for time t, the remaining life W of each lithium battery pack j -ΔW j tends to be equal, where ΔW j =P j .t, that is, the health index tends to be equal;

[0058] Assume that there are m groups of lithium battery packs S in the system j =0, that is, m groups of lithium battery packs do not participate in the load power distribution of the system. For the convenience of representation, these m groups of lithium battery packs are centrally numbered, denoted as starting from the f-th and ending at the (f + m - 1)-th, and the following formula is obtained:

[0059]

[0060] Express the power output by each lithium battery pack within unit time t in terms of the output power of the first group of lithium battery packs, that is:

[0061]

[0062] It can be obtained that:

[0063]

[0064] That is, the actual output power of each group of lithium battery packs within unit time t is:

[0065]

[0066] Step4. Power adjustment: According to the weighted difference ΔP of the power adjustment of lithium battery pack 1 obtained in Step3 j , and perform differential control on it through the chopper 2 on the branch where each lithium battery pack 1 is located to change the output power value of each lithium battery pack 1;

[0067] Step5. Collect the parameters of each lithium battery pack 1 and analyze the real-time health index Sj of each lithium battery pack 1, and then repeat Step1 to Step4 to perform dynamic adjustment on each lithium battery pack 1 to make the remaining service lives of each lithium battery pack 1 tend to be consistent.

Claims

1. A battery power control method for a DC networking system of a new energy ship. The DC networking system of the new energy ship includes two power units on the port side and the starboard side with the same configuration. A DC bus (3) is provided in each of the port side power unit and the starboard side power unit. A bus circuit breaker (4) connects the DC buses (3) on both sides. The power unit includes a power component and a load component. The power component includes multiple groups of battery branches arranged in parallel with the same configuration. Each battery branch includes a chopper (2) and a lithium battery pack (1) connected to the DC bus (3) in sequence. An insulation test device (5) is also connected to the lithium battery pack (1). The load component includes a propulsion load and a daily power supply load. The load component is electrically connected to the DC bus (3). It is characterized in that, The control method includes the following steps: Step1. Setting the health index: Set the initial value of the health index of each lithium battery pack (1) as S = 1. According to the actual usage conditions of the lithium battery pack (1), the factors affecting the health index include the remaining power, lithium battery temperature, voltage, and insulation status of the lithium battery pack (1), and analyze the proportion of each factor affecting the health index; Health index calculation: The comprehensive influence coefficient of each lithium battery pack is: ； Among them is the preset influence proportion of each influencing factor on the health index, where i ={1, 2, 3, 4} respectively represent the remaining power, temperature, voltage and insulation state of the lithium battery pack (1); j ={1, 2, 3… n} is the serial number of the lithium battery pack; Therefore, the health index of each battery pack is ; Step 2. Initial power distribution. In this DC networking system, the initial states of all lithium battery packs (1) are the same, that is, they have nominally the same health index S , according to the current stable power demand fed back by the load, the total power P is evenly distributed to each lithium battery pack (1), and the power initially output by each lithium battery pack (1) is ; Step 3. Health index weighted analysis. According to the actual health index that dynamically changes for each lithium battery pack (1), S j the initial output power of each lithium battery pack (1) P 0 j is weighted and adjusted; Step 4. Power adjustment: Based on the weighted difference in power adjustment of the lithium battery pack (1) obtained in Step 3 , and perform differential control on each lithium battery pack (1) through the chopper (2) on the branch where each lithium battery pack (1) is located to change the output power value of each lithium battery pack (1); Step 5. Collect the parameters of each lithium battery pack (1) and analyze the real-time health index of each lithium battery pack (1). S j， Then repeat Step1 to Step4 to dynamically adjust each lithium battery pack (1) so that the remaining service lives of each lithium battery pack (1) tend to be consistent.

2. The battery power control method of the DC networking system for new energy ships according to claim 1, wherein The propulsion load includes a propulsion inverter (6), a propulsion motor (7), and a propeller (8) that are connected to the DC bus (3) and arranged in sequence. The daily power load includes a daily inverter (9) and a daily transformer (10) that are connected to the DC bus (3) and arranged in sequence. The daily transformer (10) is connected to each daily load on the ship.

3. The battery power control method of the DC networking system for new energy ships according to claim 1, characterized in that, In the said Step1, the specific method for analyzing the proportion of each factor affecting the health index is: Step 1.

1. Initial value setting: Denote the preset influence proportion of each influencing factor on the health index as , where i = {1, 2, 3, 4} respectively represent the remaining power, temperature, voltage, and insulation state of the lithium battery pack (1); Step1.

2. Parameter measurement of the lithium battery pack: The central control system statistically measures the parameters of each lithium battery pack at fixed intervals j where j ={1, 2, 3… n}, and the parameters include the remaining power value of the lithium battery pack obtained by monitoring the battery X j , the real-time temperature of the lithium battery pack T j , the real-time voltage of the lithium battery pack U j , the leakage current of the lithium battery pack I j ; Step1.

3. Analysis of each influence coefficient: Analyze the parameters of each lithium battery pack in Step1.2 to obtain its influence coefficient on each influencing factor : a. Influence coefficient of remaining power of lithium battery pack , where x is the lowest threshold of battery power. When the remaining power of the lithium battery is lower than x , this lithium battery pack will no longer output power; b. Real-time temperature influence coefficient of lithium battery pack , where t 1 is the lowest temperature at which the lithium battery pack can work properly, t 2 is the highest temperature at which the lithium battery pack can work properly; c. Real-time voltage influence coefficient of lithium battery pack , where u is the set voltage during stable operation of the system, and △ U is the set voltage fluctuation threshold; d. Influence Coefficient of Insulation State of Lithium Battery Pack , where I 0 is the insulation limit leakage current of the lithium battery pack. When , there is a short-circuit foreign object inside the lithium battery pack cell; Step1.

4. Health index calculation.

4. The battery power control method of the DC networking system for new energy ships according to claim 3, characterized in that In the described Step 3, the initial output power of each lithium battery pack P 0 j The specific method for weighted adjustment is as follows: The current actual life of each lithium battery pack , is the initial life of the lithium battery pack. Denote that within the unit time t , the weighted power of each lithium battery pack is Δ P 1, Δ P 2…Δ P n . The weighting principle is that the lithium battery pack with a high health index outputs more power, and the lithium battery pack with a low health index outputs less power, that is . In the formula is the actual output power of each lithium battery pack; Make the system running time t After that, the remaining life of each lithium battery pack W j - Δ W j Tends to be equal, where Δ W j =P j . t , that is, the health index tends to be equal; Assume that there are a total of m groups of lithium battery packs in the system, that is, there are m groups of lithium battery packs that do not participate in the load power distribution of the system. For the convenience of representation, these m groups of lithium battery packs are centrally numbered, starting from the f th and ending at the f + m - 1 th, and the following formula is obtained: Express the power output by each lithium battery pack per unit time t in terms of the power output of the first lithium battery pack, i.e.: It can be obtained that: That is, the actual output power of each group of lithium battery packs per unit time t is as follows: 。 5. The battery power control method for the DC networking system of a new energy ship according to claim 3, characterized in that, In the described Step 1.1, the proportion of the remaining battery level of the lithium battery pack affecting the health index is , the proportion of the temperature of the lithium battery pack affecting the health index is , the proportion of the voltage of the lithium battery pack affecting the health index is , the proportion of the insulation state of the lithium battery pack affecting the health index is .

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