Heat recovery method based on operating condition data and related apparatus

Abstract

The application provides a heat recovery method based on working condition data and a related device, which is applied to a control unit of a battery system. The method comprises the following steps: obtaining first working condition data of a battery unit at present, wherein the first working condition data refers to a target load power of the battery unit at present; dividing a remaining time of a day into at least one first time period; predicting at least one target heat generation amount corresponding to at least one time period according to the target load power and the at least one first time period, wherein the target heat generation amount refers to a total heat generation of the battery unit in the corresponding time period; determining a heat recovery mode according to the at least one target heat generation amount; and recovering heat generated by the battery unit according to the heat recovery mode.

Description

Technical Field

[0001] This application belongs to the field of heat recovery technology, specifically relating to a heat recovery method and related apparatus based on operating condition data. Background Technology

[0002] Currently, existing technologies typically use heat recovery devices to directly recover the heat generated by batteries. However, when the battery load increases and a large amount of heat is generated rapidly, the heat recovery unit may not be able to recover the heat in time. This can lead to heat accumulation, causing the battery to heat up rapidly and affecting battery efficiency. Summary of the Invention

[0003] This application provides a heat recovery method and related apparatus based on operating condition data, with the aim of improving heat recovery efficiency.

[0004] In a first aspect, this application provides a control unit applied to a battery system; the method includes:

[0005] Obtain the current first operating condition data of the battery cell, where the first operating condition data refers to the battery cell's own parameters and environmental parameters under the current operating state;

[0006] Divide the remaining time of the day into at least one primary time period;

[0007] Based on the first operating condition data and the at least one first time period, predict at least one target heat generation corresponding to at least one time period, wherein each target heat generation refers to the total heat generation of the battery cell in the corresponding time period in the at least one time period;

[0008] The switching unit is invoked to control the switching state of the switching unit according to the at least one target heat generation, so as to adjust the type and number of the connected heat recovery units;

[0009] Heat is recovered from the battery cell using the adjusted heat recovery unit.

[0010] Secondly, this application provides a heat recovery device based on operating condition data, applied to the control unit of a battery system; the device includes:

[0011] The acquisition unit is used to acquire the current first operating condition data of the battery cell, wherein the first operating condition data refers to the battery cell's own parameters and environmental parameters under the current operating state.

[0012] A division unit is used to divide the remaining time of the day into at least one first time period;

[0013] The prediction unit is used to predict at least one target heat generation corresponding to at least one time period based on the first operating condition data and the at least one first time period. Each target heat generation refers to the total heat generation of the battery unit in the corresponding time period in the at least one time period.

[0014] A determining unit is used to call the switching unit to control the switching state of the switching unit according to the at least one target heat generation, so as to adjust the type and number of the connected heat recovery units;

[0015] A processing unit is used to recover heat from the battery cell according to the adjusted heat recovery unit.

[0016] Thirdly, this application provides an electronic device including a processor, a memory, a communication interface, and one or more programs, said one or more programs being stored in the memory and configured to be executed by the processor, said programs including instructions for performing the steps of any one of the first to third aspects of this application.

[0017] Fourthly, this application provides a computer storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in any one of the first to third aspects of this application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the architecture of a battery system provided in an embodiment of this application;

[0020] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0021] Figure 3 This is a schematic flowchart of a heat recovery method based on operating condition data provided in an embodiment of this application;

[0022] Figure 4 This is a flowchart illustrating a process for determining a correspondence according to an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of a preset heat generation process provided in an embodiment of this application;

[0024] Figure 6 This is a schematic diagram of a heat recovery device based on operating condition data provided in an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0026] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, systems, products, or apparatuses.

[0027] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0028] Currently, existing technologies typically use heat recovery devices to directly recover the heat generated by batteries. However, when the battery load increases and a large amount of heat is generated rapidly, the heat recovery unit may not be able to recover the heat in time. This can lead to heat accumulation, causing the battery to heat up rapidly and affecting battery efficiency.

[0029] To address the aforementioned issues, this application provides a heat recovery method based on operating condition data. This method can be applied to scenarios where a heat recovery method is determined and performed based on the current operating condition data of a battery cell. The method involves acquiring the current first operating condition data of the battery cell, where the first operating condition data refers to the current target load power of the battery cell; dividing the remaining time of the day into at least one first time period; predicting at least one target heat generation corresponding to each of the at least one time period based on the target load power and the at least one first time period, where the target heat generation refers to the total heat generated by the battery cell within the corresponding time period; determining a heat recovery method based on the at least one target heat generation; and recovering the heat generated by the battery cell according to the heat recovery method. This solution is applicable to various scenarios, including but not limited to the application scenarios mentioned above.

[0030] The system architecture involved in the embodiments of this application is described below.

[0031] This application provides a battery system 100, please refer to... Figure 1 The battery system 100 includes a battery unit 110, a control unit 120, a sensor unit 130, a switching unit 140, a switch unit, and N heat recovery units, where N is a positive integer greater than or equal to 2. Specifically, the control unit 120 is used to perform the following operations: acquire a first temperature value detected by the sensor unit 130 from the battery unit 110; determine the temperature level corresponding to the first temperature value, wherein the control unit 120 has multiple temperature levels, and each temperature level includes a temperature range; according to the temperature level, invoke the switching unit 140 to control the switching state of the switch unit to adjust the connection state of M heat recovery units among the N heat recovery units with the battery unit 110, where M is a positive integer less than or equal to N; and perform heat recovery on the battery unit 110 according to the M heat recovery units.

[0032] Please refer to the following for details. Figure 1The plurality of switches includes a first switch 151, a second switch 152, a third switch 153, a fourth switch 154, a fifth switch 155, and a sixth switch 156. One embodiment of the N heat recovery units includes heat recovery units 161, 162, and 163. The control unit 120 outputs a corresponding switching signal to the switching unit 140 according to a first temperature level. The switching unit 140 then controls the switching states of the corresponding switches among the first switch 151, second switch 152, third switch 153, fourth switch 154, fifth switch 155, and sixth switch 156, thereby forming a heat recovery loop between the battery unit 110 and the heat recovery units to recover heat from battery waste liquid according to a specific combination. Specifically, the battery unit 110 can be described as an immersed battery, dissipating heat through a coolant; the N heat recovery units can include at least one of a heat exchanger unit, a heat pipe unit, and a heat pump unit. It is understood that the N heat recovery units include more than just the heat recovery units 161, 162 and 163 mentioned above. This is just one implementation method, and it may also include more heat recovery units or more types of heat recovery units. There is no unique limitation here.

[0033] This application also provides an electronic device 10, such as... Figure 2 As shown, it includes at least one processor 11, a display screen 12, and a memory 13, and may also include a communications interface 15 and a bus 14. The processor 11, display screen 12, memory 13, and communications interface 15 can communicate with each other via the bus 14. The display screen 12 is configured to display a preset user guide interface in the initial setup mode. The communications interface 15 can transmit information. The processor 11 can call logical instructions in the memory 13 to execute the methods described in the above embodiments.

[0034] Optionally, the electronic device 10 may be a mobile electronic device, an electronic device or other device, and is not limited to a single type.

[0035] Furthermore, the logic instructions in the aforementioned memory 13 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0036] The memory 13, as a computer-readable storage medium, can be configured to store software programs, computer-executable programs, such as program instructions or modules corresponding to the methods in the embodiments of this disclosure. The processor 11 executes functional applications and data processing by running the software programs, instructions, or modules stored in the memory 13, thereby implementing the methods in the above embodiments.

[0037] The memory 13 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the electronic device 10. Furthermore, the memory 13 may include high-speed random access memory (RAM) and may also include non-volatile memory. For example, various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, may be used, or they may be transient storage media.

[0038] The specific methods will be described in detail below.

[0039] Please see Figure 3 This application also provides a heat recovery method based on operating condition data, applied to the control unit of a battery system; the method includes:

[0040] Step 201: Obtain the current first operating condition data of the battery cell, where the first operating condition data refers to the current target load power of the battery cell.

[0041] Step 202: Divide the remaining time of the day into at least one first time period.

[0042] In one possible embodiment, dividing the remaining time of the day into at least one first time period includes: determining the current first time point; determining the remaining first time length of the day based on the first time point; and dividing the first time length into at least one first time period based on the length of a preset time period, wherein the preset time period is a time period pre-divided on a daily basis, each period includes multiple preset time periods, and each preset time period has an equal length.

[0043] In practice, the current first time point can be determined based on a clock or obtained from the network; uniqueness is not a constraint here. For example, if the current first time point indicates 12:10, then it is currently 12:10 PM. After determining the first time point, the remaining length of the first time period for the day can be calculated. For instance, if the current time is 12:10, then the remaining length of the first time period for the day is 11 hours and 50 minutes. Assuming the preset time period length is 1 hour, meaning there are 24 preset time periods per day, then the first time period can be divided into 12 first time periods.

[0044] As can be seen, in this embodiment, using a day as a cycle and dividing each cycle into time periods allows for more precise prediction of the heat generation of the battery cells, thus improving prediction accuracy.

[0045] Step 203: Based on the target load power and the at least one first time period, predict at least one target heat generation corresponding to at least one time period.

[0046] Wherein, each of the at least one target heat generation refers to the total heat generated by the battery cell within the corresponding time period in the at least one time period.

[0047] In one possible embodiment, the first operating condition data includes load power; predicting at least one target heat generation corresponding to at least one time period based on the first operating condition data and the at least one first time period includes: determining the load power of the battery cell; and determining the target heat generation corresponding to each first time period based on the correspondence between the load power and each of the plurality of first time periods.

[0048] In specific implementation, the current load power of the battery unit is determined. Since the first time period is divided according to a preset time period, the first time period corresponds to the preset time period. Taking the above 12 first time periods as an example, the 12 first time periods are as follows: 12:11-13:00, 13:00-14:00, 14:00-15:00, 15:00-16:00, 16:00-17:00, 17:00-18:00, 18:00-19:00, 19:00-20:00, 20:00-21:00, 21:00-22:00, 22:00-23:00, 23:00-24:00. These time periods are divided using the same mechanism as the preset time periods. Therefore, the correspondence between the load power and the first time period can be determined directly based on the preset load power and the preset time period. Then, the heat generation corresponding to each first time period under the current load power can be obtained based on this correspondence, which is the target heat generation within the corresponding first time period.

[0049] As can be seen, in this embodiment, the target heat generation can be queried based on the relationship between load power and time period, which helps to predict the heat generation that the battery cell may generate. This provides a basis for determining the corresponding heat recovery method based on the heat generation, thereby improving the reliability of the battery system.

[0050] In one possible embodiment, such as Figure 4 As shown, the process of determining the correspondence includes: Step 301, obtaining the target historical working data of the battery cell, wherein the target historical working data includes multiple first historical working data and multiple second historical working data, the multiple first historical working data correspond one-to-one with the multiple first cycles, the multiple second historical working data correspond one-to-one with the multiple second cycles, the time interval between the first cycle and the current cycle is shorter than the time interval between the second cycle and the current cycle, each first historical working data includes multiple first load power and first heat generation data corresponding to each first load power, and each second historical working data includes multiple second load power and second heat generation data corresponding to each second load power;

[0051] Step 302: Separate the heat generation data corresponding to each identical first load power from multiple first historical working data sets, and summarize them to obtain multiple first heat generation data sets;

[0052] Step 303: Separate the heat generation data corresponding to each identical second load power from multiple second historical working data sets, and summarize them to obtain multiple second heat generation data sets;

[0053] Step 304: Based on the multiple first heat generation data sets and the multiple second heat generation data sets, calculate the average heat generation of the same load power and the same preset time period to obtain multiple preset heat generation;

[0054] Step 305: Establish the correlation between each load power and each corresponding preset time period and preset heat generation to obtain the correspondence.

[0055] In practice, the correspondence between load power, preset time period, and heat generation is obtained through extensive data calculations before actual application. Specifically, during battery cell testing, historical working data for each cycle is recorded. When the historical working data reaches a certain amount, a program to determine the correspondence is initiated. First, target historical working data is acquired, such as data for 7 days, 14 days, 20 days, and 30 days. The choice can be made based on the actual situation and is not limited to a single unique value. In this embodiment, a preferred example is selected for illustration, namely, acquiring 10 cycles (10 days) of historical working data. This 10-cycle historical working data is divided into two parts: one part is recent historical working data, i.e., the first historical working data; the other part is historical working data with a longer interval from the current cycle, i.e., the second historical working data. In this example, since the possibility of significant changes in battery function within 7 days is unlikely, the first historical working data can be set to 7 cycles, i.e., there are 7 first historical working data. Since the second historical working data is much longer than the current cycle and has less reference value compared to recent data, the second historical working data can be set to 3 cycles, i.e., 3 second historical working data.

[0056] As can be seen, in this embodiment, different sets are divided according to the time interval of historical working data, which provides a basis for subsequent calculation of preset heat generation and improves the reliability of the battery system.

[0057] Furthermore, in one possible embodiment, separating the heat generation data corresponding to each identical first load power from multiple first historical working data and summarizing them to obtain multiple first heat generation data sets includes: performing the following operations for each first load power: extracting N heat generation data corresponding to N preset time periods under the current first load power from the multiple first historical working data to obtain a first heat generation data set; determining the next first load power and continuing to perform the above operations until the multiple first heat generation data sets are obtained.

[0058] In the specific implementation, all first load powers from seven historical operating data points are statistically analyzed. For each first load power, the heat generated by the battery cell under each first load power is determined within each of the 24 preset time periods in a cycle. This results in 24 heat generation values ​​corresponding one-to-one with each of the 24 time periods, forming a correspondence of [first load power - 24 preset time periods - 24 heat generation values]. This correspondence is then placed into a set to obtain a first heat generation data set. The number of first load powers corresponds to the number of first heat generation data sets.

[0059] As can be seen, in this embodiment, a direct correspondence is established between each first load power, each preset time period, and each heat generation, providing a basis for subsequent calculation of preset heat generation and improving the reliability of the battery system.

[0060] In one possible embodiment, the step of separating the heat generation data corresponding to each identical second load power from multiple second historical working data and summarizing them to obtain multiple sets of second heat generation data includes:

[0061] Perform the following operations for each second load power:

[0062] From the multiple second historical working data, extract the N heat generation data corresponding to the N preset time periods under the current first load power to obtain the second heat generation data set;

[0063] Determine the next second load power and continue performing the above operations until the plurality of second heating data sets are obtained.

[0064] In the specific implementation, all second load powers in the three first historical working data sets are statistically analyzed. For each second load power, the heat generated by the battery cell under each second load power is determined within each of the 24 preset time periods, resulting in 24 heat generation values. The correspondence between the second load power, the 24 preset time periods, and the 24 heat generation values ​​is then placed into a set, resulting in a second heat generation data set. The number of second load powers determines the number of second heat generation data sets.

[0065] As can be seen, in this embodiment, a direct correspondence is established between each second load power, each preset time period, and each heat generation, providing a basis for subsequent calculation of preset heat generation and improving the reliability of the battery system.

[0066] In one possible embodiment, such as Figure 5As shown, the step of calculating the average heat generation of the same load power and the same preset time period based on the plurality of first heat generation data sets and the plurality of second heat generation data sets to obtain a plurality of preset heat generation includes: determining whether there is a second load power that is the same as the current first load power; if there is a second load power that is the same as the current first load power, then performing the following operations for the same first load power and second load power: extracting the heat generation of the first preset time period corresponding to the current first load power from each first heat generation set to obtain a plurality of third heat generation; and extracting the first preset time corresponding to the current second load power from each second heat generation set. The heat generation of a segment is used to obtain multiple fourth heat generation values; and, the multiple third heat generation values ​​are multiplied by a first weight to obtain multiple first weight values; and, the multiple fourth heat generation values ​​are multiplied by a second weight to obtain multiple second weight values; and, the average value of the multiple first weight values ​​and the multiple second weight values ​​is calculated to obtain the corresponding preset heat generation value; if there is no second load power with the same first load power as the current first load power, the average heat generation value of the same first load power and the same preset time period in the first heat generation data set and the average heat generation value of the same second load power and the same preset time period in the second data set are calculated to obtain the multiple preset heat generation values.

[0067] In practical implementation, if the first load power is equal to the second load power, then the corresponding first and second heat generation data sets need to be used together in the calculation of the preset heat generation. For example, assuming the first load power is 1 and the second load power is also 1, the weight assigned to the first heat generation data is 0.6, and the weight assigned to the second heat generation data is 0.4. If the heat generation of the first load power in the first preset time period (i.e., 00:00-01:00) of the first historical period is 60, then 60 * 0.6 = 36. If the heat generation of the first load power in the first preset time period (i.e., 00:00-01:00) of the second historical period is 50, then 50 * 0.6 = 30, and so on, the first load power in 7 periods is calculated. The heat generated in the first preset time period (i.e., 00:00-01:00) is multiplied by the weight corresponding to the first load power to obtain 7 first weight values; similarly, the heat generated in the first preset time period (i.e., 00:00-01:00) of the second load power in the 3 cycles is multiplied by the weight (0.4) corresponding to the second load power to obtain 3 second weight values; finally, the 7 first weight values ​​and the 3 second weight values ​​are added together and averaged to obtain a weighted average value, which is the preset heat generated by the first load power and the second load power in the first preset time period.

[0068] Furthermore, if the power of the first load is not equal to the power of the second load, then the weighted average of the seven weights and the weighted average of the three second weights can be calculated directly.

[0069] As can be seen, in this embodiment, the weighted average of a large amount of data is calculated, which improves the accuracy of the predicted preset heat output.

[0070] Step 204: Based on the at least one target heat generation, invoke the switching unit to control the switching state of the switching unit, so as to adjust the type and number of the connected heat recovery units.

[0071] In specific implementation, taking the aforementioned 12 first time periods as an example, at least 12 target heat generation values ​​are obtained by querying the corresponding relationships. Taking the first time period of 13:00-14:00 as an example, if the preset heat generation value corresponding to the 14th preset time period (i.e., 13:00-14:00) out of the 24 preset time periods corresponding to the target load power is queried in the corresponding relationship, this preset heat generation value is determined as the target heat generation value corresponding to 13:00-14:00. Based on this target heat generation value, the preset configuration table is queried to obtain the heat recovery unit corresponding to the target heat generation value, and then a control signal is sent to the switching unit, which then connects the heat recovery unit to the corresponding control switch. For example... Figure 1 As shown, when the current time reaches the corresponding first time period interval, if the heat recovery unit 161 needs to be connected to the current first time period, the control switching unit closes the first switch and the fifth switch, so that the heat recovery unit 161 and the battery unit 110 form a heat recovery loop. Similarly, the heat recovery units for the other 11 first time periods are determined in the same way, and when the current time reaches the corresponding first time period interval, the determined heat recovery units are connected.

[0072] Step 205: Perform heat recovery on the battery unit according to the adjusted heat recovery unit.

[0073] Specifically, after adjusting the heat recovery unit, heat recovery begins based on the adjusted unit.

[0074] The above primarily describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, mobile electronic devices include corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0075] This application embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0076] Please see Figure 6 This application also provides a heat recovery device 60 based on operating condition data, applied to the control unit of a battery system; the device includes:

[0077] The acquisition unit 61 is used to acquire the first operating condition data of the battery cell, wherein the first operating condition data refers to the battery cell's own parameters and environmental parameters under the current operating state.

[0078] Dividing unit 62 is used to divide the remaining time of the day into at least one first time period;

[0079] Prediction unit 63 is used to predict at least one target heat generation corresponding to at least one time period based on the first operating condition data and the at least one first time period, wherein each target heat generation refers to the total heat generation of the battery unit in the corresponding time period in the at least one time period.

[0080] The determining unit 64 is used to call the switching unit to control the switching state of the switching unit according to the at least one target heat generation, so as to adjust the type and number of the connected heat recovery units;

[0081] The processing unit 65 is used to recover heat from the battery cell according to the adjusted heat recovery unit.

[0082] As can be seen, in this embodiment, the heat generation is predicted based on the battery's operating conditions, and different heat recovery schemes are selected for heat recovery based on the heat generation. The most suitable heat recovery method is switched according to the heat generation to improve the heat recovery efficiency.

[0083] In one possible embodiment, the aspect of dividing the remaining time of the day into at least one first time period, the dividing unit 62 is specifically used for: determining the current first time point; determining the remaining first time length of the day based on the first time point; dividing the first time length into at least one first time period based on the length of a preset time period, wherein the preset time period is a time period pre-divided on a daily basis, each period includes multiple preset time periods, and each preset time period has an equal length.

[0084] In one possible embodiment, the first operating condition data includes load power; the aspect of predicting at least one target heat generation corresponding to at least one time period based on the first operating condition data and the at least one first time period, the prediction unit 63 is specifically configured to: determine the load power of the battery cell; and determine the target heat generation corresponding to each first time period based on the correspondence between the load power and each of the plurality of first time periods.

[0085] In one possible embodiment, regarding the process of determining the correspondence, the prediction unit 63 is specifically configured to: acquire target historical operating data of the battery cell, the target historical operating data including multiple first historical operating data and multiple second historical operating data, the multiple first historical operating data corresponding one-to-one with multiple first cycles, the multiple second historical operating data corresponding one-to-one with multiple second cycles, the time interval between the first cycle and the current cycle being shorter than the time interval between the second cycle and the current cycle, each first historical operating data including multiple first load powers and first heat generation data corresponding to each first load power, each second historical operating data including multiple second load powers and second heat generation data corresponding to each second load power; separate the heat generation data corresponding to each identical first load power from the multiple first historical operating data, and summarize them to obtain multiple sets of first heat generation data; separate the heat generation data corresponding to each identical second load power from the multiple second historical operating data, and summarize them to obtain multiple sets of second heat generation data; calculate the average heat generation of the same load power and the same preset time period based on the multiple sets of first heat generation data and the multiple sets of second heat generation data, and obtain multiple preset heat generation; establish the association relationship between each load power and each corresponding preset time period and preset heat generation, and obtain the correspondence relationship.

[0086] In one possible embodiment, the aspect of separating the heat generation data corresponding to each identical first load power from multiple first historical working data and summarizing them to obtain multiple first heat generation data sets, the prediction unit 63 is specifically used to: perform the following operations for each first load power: extract N heat generation data corresponding to N preset time periods under the current first load power from the multiple first historical working data to obtain a first heat generation data set;

[0087] Determine the next first load power and continue performing the above operations until the plurality of first heat generation data sets are obtained.

[0088] In one possible embodiment, the aspect of separating the heat generation data corresponding to each identical second load power from multiple second historical working data and summarizing them to obtain multiple second heat generation data sets, the prediction unit 63 is specifically used to perform the following operations for each second load power: extracting N heat generation data corresponding to N preset time periods under the current first load power from the multiple second historical working data to obtain a second heat generation data set; determining the next second load power, and continuing to perform the above operations until the multiple second heat generation data sets are obtained.

[0089] In one possible embodiment, the prediction unit 63, in the aspect of calculating the average heat generation of the same load power and the same preset time period based on the plurality of first heat generation data sets and the plurality of second heat generation data sets to obtain a plurality of preset heat generation amounts, is specifically configured to: determine whether there is a second load power that is the same as the current first load power; if there is a second load power that is the same as the current first load power, then perform the following operations for the same first load power and second load power: extract the heat generation of the first preset time period corresponding to the current first load power from each first heat generation set to obtain a plurality of third heat generation amounts; and extract the current second load power from each second heat generation set. The heat generated during a first preset time period corresponding to the power is used to obtain multiple fourth heat generation values; and the multiple third heat generation values ​​are multiplied by a first weight to obtain multiple first weight values; and the multiple fourth heat generation values ​​are multiplied by a second weight to obtain multiple second weight values; and the average of the multiple first weight values ​​and the multiple second weight values ​​is calculated to obtain the corresponding preset heat generation value; if there is no second load power with the same first load power as the current first load power, the average heat generation value of the same first load power and the same preset time period in the first heat generation data set and the average heat generation value of the same second load power and the same preset time period in the second data set are calculated to obtain the multiple preset heat generation values.

[0090] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0091] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes an electronic device.

[0092] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include an electronic device.

[0093] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0094] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for example, the division of units is merely a logical functional division, and other division methods may exist in actual implementation; for example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0095] The units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0096] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can be physically comprised separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware or in the form of hardware plus software functional units.

[0097] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, volatile memory, or non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM), etc., various media capable of storing program code.

[0098] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can easily conceive of variations or substitutions without departing from the spirit and scope of the present invention, and various modifications and alterations can be made, including combinations of the different functions and implementation steps described above, as well as software and hardware implementation methods, all of which are within the protection scope of the present invention.

Claims

1. A heat recovery method based on operating condition data, characterized in that, The method is applied to a control unit of a battery system; the method includes: Obtain the current first operating condition data of the battery cell, where the first operating condition data refers to the current target load power of the battery cell; Divide the remaining time of the day into at least one primary time period; Based on the target load power and the at least one first time period, predicting at least one target heat generation corresponding to at least one time period includes: determining the target load power of the battery cell; determining the target heat generation corresponding to each first time period based on the correspondence between the target load power and each first time period in the at least one first time period; each target heat generation in the at least one target heat generation refers to the total heat generation of the battery cell in the corresponding time period in the at least one time period; The process of determining the correspondence includes: acquiring target historical working data of the battery cell, wherein the target historical working data includes multiple first historical working data and multiple second historical working data, the multiple first historical working data correspond one-to-one with multiple first cycles, the multiple second historical working data correspond one-to-one with multiple second cycles, the time interval between the first cycle and the current cycle is shorter than the time interval between the second cycle and the current cycle, each first historical working data includes multiple first load power and first heat generation data corresponding to each first load power, and each second historical working data includes multiple second load power and second heat generation data corresponding to each second load power; separating the heat generation data corresponding to each identical first load power from the multiple first historical working data, and summarizing them to obtain multiple sets of first heat generation data; separating the heat generation data corresponding to each identical second load power from the multiple second historical working data, and summarizing them to obtain multiple sets of second heat generation data; calculating the average heat generation of the same load power and the same preset time period based on the multiple sets of first heat generation data and the multiple sets of second heat generation data, and obtaining multiple preset heat generation; establishing the association relationship between each load power and each corresponding preset time period and preset heat generation, and obtaining the correspondence relationship; The switching unit controls the switching state of the switching unit according to the at least one target heat generation, so as to adjust the type and number of the connected heat recovery units; Heat is recovered from the battery cell using the adjusted heat recovery unit.

2. The method according to claim 1, characterized in that, The division of the remaining time of the day into at least one first time period includes: Determine the current first point in time; Determine the remaining first time length of the day based on the first time point; The first time length is divided into at least one first time period according to the length of the preset time period. The preset time period is a time period pre-divided on a one-day cycle. Each cycle includes multiple preset time periods, and the length of each preset time period is equal.

3. The method according to claim 1, characterized in that, The process involves separating the heat generation data corresponding to each identical first load power from multiple first historical working data sets, and summarizing them to obtain multiple first heat generation data sets, including: Perform the following operations for each first load power: Extract the N heat generation data corresponding to the N preset time periods under the current first load power from the multiple first historical working data to obtain the first heat generation data set; Determine the next first load power and continue performing the above operations until the plurality of first heat generation data sets are obtained.

4. The method according to claim 3, characterized in that, The process involves separating the heat generation data corresponding to each identical second load power from multiple second historical working data sets, and summarizing them to obtain multiple second heat generation data sets, including: Perform the following operations for each second load power: From the multiple second historical working data, extract the N heat generation data corresponding to the N preset time periods under the current first load power to obtain the second heat generation data set; Determine the next second load power and continue performing the above operations until the plurality of second heating data sets are obtained.

5. The method according to claim 4, characterized in that, The step involves calculating the average heat generation of the same load power over the same preset time period based on the plurality of first heat generation data sets and the plurality of second heat generation data sets, to obtain a plurality of preset heat generation values, including: Determine if there are identical first and second load powers; Perform the following operations for each preset time period with the same first load power and second load power: From each first heat generation set, extract the heat generation corresponding to the current first load power for a first preset time period to obtain multiple third heat generation values; and from each second heat generation set, extract the heat generation corresponding to the current second load power for a first preset time period to obtain multiple fourth heat generation values; and multiply the multiple third heat generation values ​​by a first weight to obtain multiple first weight values; and multiply the multiple fourth heat generation values ​​by a second weight to obtain multiple second weight values; and calculate the average of the multiple first weight values ​​and the multiple second weight values ​​to obtain the corresponding preset heat generation value; For different first load power and second load power, the average heat generation of the same first load power and the same preset time period in the first heat generation data set is calculated, and the average heat generation of the same second load power and the same preset time period in the second data set is calculated, to obtain the multiple preset heat generation.

6. A heat recovery device based on operating condition data, characterized in that, The control unit applied to the battery system; the heat recovery device based on operating condition data includes: The acquisition unit is used to acquire the current first operating condition data of the battery cell, wherein the first operating condition data refers to the current target load power of the battery cell. A division unit is used to divide the remaining time of the day into at least one first time period; A prediction unit is configured to predict at least one target heat generation corresponding to at least one time period based on the target load power and the at least one first time period, including: determining the target load power of the battery unit; determining the target heat generation corresponding to each first time period based on the correspondence between the target load power and each first time period in the at least one first time period; each target heat generation refers to the total heat generation of the battery unit in the corresponding time period in the at least one time period; the process of determining the correspondence includes: acquiring target historical operating data of the battery unit, the target historical operating data including multiple first historical operating data and multiple second historical operating data, the multiple first historical operating data corresponding to multiple first cycles, the multiple second historical operating data corresponding to multiple second cycles, and the first cycle corresponding to the current cycle. The time interval is shorter than the time interval between the second period and the current period. Each first historical working data includes multiple first load powers and first heat generation data corresponding to each first load power. Each second historical working data includes multiple second load powers and second heat generation data corresponding to each second load power. Heat generation data corresponding to each identical first load power is separated from the multiple first historical working data, and these are aggregated to obtain multiple sets of first heat generation data. Heat generation data corresponding to each identical second load power is separated from the multiple second historical working data, and these are aggregated to obtain multiple sets of second heat generation data. Based on the multiple sets of first heat generation data and the multiple sets of second heat generation data, the average heat generation of the same load power within the same preset time period is calculated to obtain multiple preset heat generation values. A correlation is established between each load power and its corresponding preset time period and preset heat generation value to obtain the corresponding relationship. A determining unit is used to call a switching unit to control the switching state of a switching unit based on the at least one target heat generation, so as to adjust the type and number of connected heat recovery units; A processing unit is used to recover heat from the battery cell according to the adjusted heat recovery unit.

7. An electronic device, characterized in that, The method includes a processor, a memory, a communication interface, and one or more programs, said programs being stored in the memory and configured to be executed by the processor, said programs including instructions for performing the steps of the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, A computer program for storing electronic data interchange is provided, wherein the computer program causes a computer to execute instructions for the steps of the method as described in any one of claims 1-5.

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