Battery operating condition adjustment method and device

Abstract

This invention discloses a battery operating condition adjustment method and apparatus, relating to the field of battery technology. The method includes: acquiring runtime and expansion force data corresponding to at least one operating condition of the battery within a preset historical time period based on the current time, as well as environmental data within the preset historical time period; determining the equivalent expansion force data of the battery within the preset historical time period based on the runtime and expansion force data corresponding to each operating condition; predicting the first health state of the battery at the current time based on the equivalent expansion force data and a first mapping relationship; and adjusting the battery operating condition within a preset future time period based on the environmental data, the equivalent expansion force data, and the first health state. This invention improves the accuracy of battery operating condition adjustment, enabling timely identification of safety hazards before battery failure and adjustment of subsequent battery operating conditions.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and more specifically to a method and apparatus for adjusting battery operating conditions. Background Technology

[0002] With the widespread adoption of battery energy storage systems, higher demands are being placed on battery cycle life, throughput capacity, and operational safety. In practical applications, batteries operating under conditions such as high ambient temperatures, excessive charge / discharge rates, and prolonged high-cycle operation are prone to accelerated internal aging, leading to issues like cell micro-expansion, casing bulging, and performance degradation. This significantly shortens battery life and poses safety hazards such as thermal runaway. Currently, a passive maintenance model of reactive repair and fault replacement is typically adopted, lacking a mechanism for predicting battery health status and failing to intervene in subsequent battery usage conditions during micro-expansion and mild degradation stages. Summary of the Invention

[0003] This invention provides a battery condition adjustment method and apparatus, which enables accurate prediction of battery health status, early identification of safety hazards before battery failure, and timely adjustment of battery conditions.

[0004] In a first aspect, the present invention provides a battery operating condition adjustment method, the method comprising: Get the running time and expansion force data of the battery under at least one working condition within a preset historical time period based on the current time, as well as the environmental data within the preset historical time period; Based on the running time and expansion force data corresponding to each operating condition, the equivalent expansion force data of the battery within a preset historical time period is determined. Based on the equivalent expansion force data, and the preset first mapping relationship between the expansion force data and the battery health status, the first health status of the battery at the current moment is predicted. Based on environmental data, equivalent expansion force data, and the first health state, the battery's operating conditions are adjusted for a future time period preset based on the current moment.

[0005] The method provided by this invention determines the equivalent expansion force data of the battery within a preset historical time period based on the runtime and expansion force data of various operating conditions under multiple conditions. This characterizes the cumulative aging characteristics of the battery within the preset historical time period. Furthermore, based on the preset mapping relationship between the equivalent expansion force and the battery health status, the current health status of the battery is accurately predicted. Finally, using environmental data within the preset historical time period as a reference, the battery operating conditions are adjusted in a timely manner based on the predicted battery health status and equivalent expansion force data for future periods. Compared with the passive handling method of battery maintenance after the fact in related technologies, the method provided by this invention can accurately quantify the aging damage and expansion risks accumulated by the battery under various operating conditions, identify safety hazards in advance before battery failure, thereby changing the battery operating conditions, improving maintenance efficiency, and providing reliable data support for the safe operation and maintenance of batteries.

[0006] In one optional implementation, based on the running time and expansion force data corresponding to each operating condition, the equivalent expansion force data of the battery within a preset historical time period is determined, including: The total duration is determined based on the runtime corresponding to each operating condition. Based on the total duration and the duration of the first working condition, the duration percentage of the first working condition is determined, wherein the first working condition is one of at least one working condition; Once the duration percentage for each working condition is determined, the equivalent expansion force data is determined based on the duration percentage for each working condition and the expansion force data.

[0007] In one optional implementation, the expansion force data includes the expansion force and the change in expansion force before and after a charge-discharge cycle; after determining the time percentage corresponding to each of the operating conditions, the equivalent expansion force data is determined based on the time percentage corresponding to each of the operating conditions and the expansion force data, including: The equivalent expansion force is determined based on the time percentage and expansion force corresponding to each working condition. The equivalent expansion force change is determined based on the duration percentage and expansion force change for each of the various working conditions. The equivalent expansion force and the change in equivalent expansion force are defined as the equivalent expansion force data.

[0008] In one optional implementation, the change in battery expansion force under a second operating condition is obtained within a preset historical time period based on the current time. The second operating condition is one of at least one of the indicated operating conditions, including: Obtain the expansion force of the battery before and after multiple charge-discharge cycles under the second operating condition within a preset historical time period; Based on the expansion forces corresponding to the first charge-discharge cycle before and after the first charge-discharge cycle, the change in expansion force before and after the first charge-discharge cycle is determined, wherein the first charge-discharge cycle is one of multiple charge-discharge cycles under the second operating condition; After determining the changes in expansion force before and after multiple charge-discharge cycles, the changes in expansion force of the battery under the second operating condition are determined based on these changes in expansion force before and after multiple charge-discharge cycles.

[0009] In one optional implementation, based on equivalent expansion force data and a preset first mapping relationship between expansion force data and battery health status, the first health status of the battery at the current moment is predicted, including: Based on the equivalent expansion force data and the first mapping relationship, the second health state of the battery at the current moment is predicted; Obtain the preset lifespan of the battery under each operating condition; Based on the duration percentage of each operating condition and the preset lifespan, predict the third health state of the battery at the current moment. The first health state is determined based on the second and third health states.

[0010] In one optional implementation, based on the duration percentage of each operating condition and a preset lifespan, the third health state of the battery at the current moment is predicted, including: Based on the duration percentage of each operating condition and the preset lifespan, the equivalent lifespan of the battery at the current moment is determined. The third health state is determined based on the equivalent lifespan and the battery's preset maximum lifespan.

[0011] In one optional implementation, determining the first health state based on the second and third health states includes: The smaller of the second and third health states is defined as the first health state.

[0012] In one alternative implementation, before adjusting the battery's operating conditions for a future time period based on the current moment, according to environmental data, equivalent expansion force data, and a first health state, the method further includes: Acquire multiple historical operating condition data, as well as the corresponding historical environmental data, historical expansion force data, and historical health status for each historical operating condition data; Based on multiple historical operating condition data, and the corresponding historical environmental data, historical expansion force data, and historical health status for each historical operating condition data, a second mapping relationship is constructed. The second mapping relationship is used to characterize the impact of operating condition data and environmental data on expansion force data and health status.

[0013] In one optional implementation, based on environmental data, equivalent expansion force data, and a first health state, the battery's operating conditions are adjusted for a preset future time period based on the current moment, including: Using the second mapping relationship, environmental data, equivalent expansion force data, and the first health state are used as constraints. The optimization objective is to minimize the equivalent expansion force data within a preset future time period and maximize the health state after the preset future time period, thereby determining the adjusted operating condition data.

[0014] In one optional implementation, after predicting the first health state of the battery at the current moment based on equivalent expansion force data and a preset first mapping relationship between expansion force data and battery health state, the method includes: Acquire preset operating condition data for a future time period based on the current time; Based on preset operating condition data, environmental data, first health state, equivalent expansion force data, and second mapping relationship, the health state of the battery is predicted after a preset future time period.

[0015] In a second aspect, the present invention provides a battery operating condition adjustment device, the device comprising: The acquisition module is used to acquire the running time and expansion force data of the battery under at least one working condition within a preset historical time period based on the current time, as well as the environmental data within the preset historical time period. The determination module is used to determine the equivalent expansion force data of the battery within a preset historical time period based on the running time and expansion force data corresponding to each working condition; The prediction module is used to predict the first health state of the battery at the current moment based on the equivalent expansion force data and the preset first mapping relationship between the expansion force data and the battery health state. The adjustment module is used to adjust the battery's operating conditions within a preset future time period based on environmental data, equivalent expansion force data, and the first health state.

[0016] Using the aforementioned device, based on the battery's operating time and expansion force data under various operating conditions within a preset historical time period, the equivalent expansion force data of the battery within that period is determined, characterizing the battery's cumulative aging features. Furthermore, based on the preset mapping relationship between the equivalent expansion force and the battery's health status, the battery's current health status is accurately predicted. Finally, using environmental data from the preset historical time period as a reference, and based on the predicted battery health status and equivalent expansion force data, the battery's operating conditions are adjusted in a timely manner for future periods. Compared to the passive handling method of post-event maintenance in related technologies, the method provided by this invention can accurately quantify the aging damage and expansion risks accumulated by the battery under various operating conditions, identify safety hazards in advance before battery failure, thereby changing the battery's operating conditions, improving maintenance efficiency, and providing reliable data support for the safe operation and maintenance of batteries.

[0017] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the battery condition adjustment method of the first aspect or any corresponding embodiment described above.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the battery condition adjustment method of the first aspect or any corresponding embodiment described above.

[0019] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the battery condition adjustment method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic flowchart of a first method for adjusting battery operating conditions according to an embodiment of the present invention; Figure 2 This is a schematic diagram of detecting expansion force inside a battery according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a second process for adjusting battery operating conditions according to an embodiment of the present invention; Figure 4This is a structural block diagram of a battery condition adjustment device according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0024] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0025] First, the application scenarios of the embodiments of this application will be introduced by way of example.

[0026] In recent years, the application penetration rate of battery energy storage systems in various end-user scenarios has continued to rise, and end users have placed more stringent demands on the cycle life, effective throughput, operational stability, and safety performance of energy storage batteries. In practical applications, batteries are subjected to conditions such as high ambient temperatures, large fluctuations in charge and discharge rates, and high-frequency, high-cycle operation. These conditions continuously accelerate internal aging of the battery, causing continuous performance degradation, resulting in a significant decrease in battery health, remaining lifespan, and effective throughput. Furthermore, long-term battery aging combined with improper charge and discharge conditions can easily lead to safety hazards such as gas generation inside the cell and casing bulging and deformation.

[0027] Currently, battery maintenance primarily employs a reactive mechanism, only initiating repairs and replacements after significant swelling, deformation, substantial performance degradation, or fault alarms. This lack of effective means to proactively detect and predict battery health and expansion trends prevents timely intervention and adjustment of battery conditions during early stages of micro-swelling and mild performance degradation. Furthermore, multiple parameters, including charge / discharge rate, depth of charge / discharge, and operating temperature, significantly impact battery aging rates. Current technologies only passively regulate batteries by limiting cumulative depth of discharge and adjusting charge / discharge strategies based on electricity price timings, failing to accurately predict battery expansion characteristics.

[0028] In view of this, embodiments of this application provide a battery condition adjustment method to achieve accurate prediction of battery health status, identify potential safety hazards in advance before battery failure, and adjust battery conditions in a timely manner.

[0029] According to an embodiment of the present invention, a method for adjusting battery operating conditions is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] Figure 1 This is a flowchart of a battery operating condition adjustment method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: S101, obtain the running time and expansion force data of the battery under at least one working condition within a preset historical time period based on the current time, as well as the environmental data within the preset historical time period.

[0031] Specifically, the preset historical time period can be limited based on the actual situation. For example, one operating cycle of the battery can be used as the preset historical time period.

[0032] Battery operating conditions refer to various operating parameters that affect battery aging and expansion during operation, including but not limited to operating temperature, charge / discharge rate, depth of charge, and depth of discharge. For example, a battery operating at a high temperature of 45 degrees Celsius and a high charge / discharge rate of 1C.

[0033] The battery's runtime under a certain operating condition refers to the cumulative time the battery continuously operates under that condition. For example, if the battery first operates under operating condition 1 for 5 days within a preset historical time period, then operates under operating condition 2 for 10 days, and finally operates under operating condition 1 for 3 days, then the battery's runtime under operating condition 1 is 8 days, and its runtime under operating condition 2 is 10 days.

[0034] Expansion force data refers to the internal stress data generated in battery cells during long-term aging, internal gas generation, and micro-expansion deformation. It serves as a key parameter for quantifying the degree of battery expansion deformation and battery aging. For example, expansion force data includes, but is not limited to, expansion force and the amount of change in expansion force.

[0035] Expansion force refers to the real-time static stress generated inside the battery cell under a certain operating condition. It is a physical parameter that characterizes the degree of instantaneous expansion and deformation of the battery under that operating condition.

[0036] For example, expansion force data is collected in real time using a pressure sensor built into the battery. The change in expansion force before and after a charge-discharge cycle refers to the difference between the expansion force at the end of the cycle and the expansion force at the beginning of the cycle after the battery completes one charge-discharge cycle. This is used to quantify the increase in battery expansion caused by a single charge-discharge cycle, reflecting the increase in aging deformation of the battery in one cycle. For example, if the expansion force of the battery at the beginning of a certain charge-discharge cycle is 30N, and the expansion force rises to 32N after the cycle ends, then the change in expansion force for that cycle is 2N.

[0037] For example, the expansion force can be obtained using a pressure sensor built into the battery. Figure 2 As shown, multiple cells are arranged side by side inside the battery. Each cell has a cell terminal on top, and the cells are filled with inter-cell foam / aerogel. An expansion force sensor is installed on the outer wall of the outermost cell to collect the expansion force generated during the cell's operation.

[0038] For example, the change in expansion force is determined by the expansion force before and after a charge-discharge cycle.

[0039] Specifically, environmental data refers to the external environmental parameters in which the battery operates within a preset historical time period, which affect the battery cell's heating rate and expansion / aging speed. For example, environmental data includes, but is not limited to, ambient temperature and humidity.

[0040] S102, based on the running time and expansion force data corresponding to each working condition, determine the equivalent expansion force data of the battery within a preset historical time period.

[0041] Specifically, equivalent expansion force data integrates the expansion force data from all operating conditions of the battery within a preset historical time period. The impact of different operating conditions on the expansion force of the battery varies significantly. For example, the battery expansion rate is slow under normal operating conditions, while high temperature and high-rate charge / discharge conditions accelerate gas generation and structural deformation of the battery cells. By uniformly quantifying the expansion force data from different operating conditions and durations, the resulting equivalent expansion force data can reflect the expansion and aging characteristics of the battery under multiple operating conditions, providing a reliable basis for subsequent prediction of battery health status.

[0042] For example, equivalent expansion force data can be determined by weighting the expansion force data for each working condition.

[0043] S103, based on the equivalent expansion force data and the preset first mapping relationship between the expansion force data and the battery health state, predicts the first health state of the battery at the current moment.

[0044] For example, the first mapping relationship includes multiple sets of equivalent expansion force data intervals, and the corresponding State of Health (SOH) for each interval. Thus, the battery health state corresponding to the interval containing the equivalent expansion force data in the first mapping relationship is the first health state.

[0045] For example, the first mapping relationship can be a fitting function between the expansion force data and the battery health state constructed based on a large amount of experimental or simulation data. By substituting the equivalent expansion force data into the fitting function, the first health state can be obtained.

[0046] For example, by simulating different operating parameters, such as temperature, different rate of increase, and state of charge (SOC), the expansion force data and battery health status under different operating parameters are determined, and a database is constructed based on each operating parameter and the corresponding expansion force data and battery health status. A first mapping relationship between the expansion force data and battery health status is then established based on the expansion force data and battery health status in the database.

[0047] S104, based on environmental data, equivalent expansion force data, and the first health state, adjusts the battery's operating conditions for a future time period preset based on the current moment.

[0048] Here, the ambient temperature within a preset historical time period is used as a reference ambient temperature for the battery in the future. Equivalent expansion force data and the first health state reflect the current aging level of the battery. By combining ambient temperature, first health state, and equivalent expansion force data, the subsequent battery operating conditions are adjusted. This ensures that the adjusted operating conditions meet the battery's environmental conditions and accurately adjusts subsequent operating conditions based on the battery's current aging level. This avoids risks such as cell swelling and accelerated degradation that might occur from continuing with the original operating conditions, thus ensuring safe battery operation.

[0049] For example, by acquiring multiple historical operating condition data, each corresponding to historical environmental data, historical expansion force data, and historical health status, a second mapping relationship is constructed between environmental data, operating condition data, expansion force data, and health status. Further, environmental data within a preset historical time period is used as environmental data for a preset future time period. Combined with the currently predicted first health status and equivalent expansion force data, the optimal operating condition within the preset future time period is determined using the second mapping relationship. For example, using environmental data within the preset historical time period, the current first health status, and equivalent expansion force data as constraints, with the optimization objective of minimizing future equivalent expansion force and maximizing future battery health status, the optimal combination of operating condition parameters is re-solved using gradient descent and traversal optimization algorithms to obtain the latest operating condition data.

[0050] The method provided by this invention determines the equivalent expansion force data of the battery within a preset historical time period based on the runtime and expansion force data of various operating conditions under multiple operating conditions. This characterizes the cumulative aging characteristics of the battery within the preset historical time period. Furthermore, based on a preset first mapping relationship between the equivalent expansion force and the battery health status, the current health status of the battery is accurately predicted. Finally, using environmental data within the preset historical time period as a reference, the battery operating conditions are adjusted in a timely manner based on the predicted battery health status and equivalent expansion force data for future periods. Compared to the passive handling method of battery maintenance after the fact in related technologies, the method provided by this invention can accurately quantify the aging damage and expansion risks accumulated by the battery under various operating conditions, identify safety hazards in advance before battery failure, thereby changing the battery operating conditions, improving maintenance efficiency, and providing reliable data support for the safe operation and maintenance of batteries.

[0051] In some embodiments, based on the foregoing embodiments, the expansion force data includes the change in expansion force before and after a charge-discharge cycle. Obtaining the change in battery expansion force under a second operating condition within a preset historical time period, based on the current moment, specifically includes the following method steps: First, obtain the expansion force of the battery before and after multiple charge-discharge cycles under the second operating condition within a preset historical time period.

[0052] The second working condition is one of the at least one working condition shown.

[0053] Then, based on the expansion forces corresponding to the first charge-discharge cycle before and after the first charge-discharge cycle, the change in expansion force before and after the first charge-discharge cycle is determined.

[0054] The first charge-discharge cycle is one of multiple charge-discharge cycles under the second operating condition.

[0055] For example, the difference between the expansion force after the first charge-discharge cycle and the expansion force before the first charge-discharge cycle is used to obtain the change in expansion force before and after the first charge-discharge cycle.

[0056] Finally, after determining the changes in expansion force before and after multiple charge-discharge cycles, the changes in expansion force of the battery under the second operating condition are determined based on these changes in expansion force before and after multiple charge-discharge cycles.

[0057] For example, the average of the changes in expansion force before and after all charge-discharge cycles under the second operating condition is used to obtain the change in expansion force of the battery under the second operating condition.

[0058] For example, the depth and rate of each charge-discharge cycle under the second operating condition are obtained; based on the depth and rate of each charge-discharge cycle, the weight of each charge-discharge cycle under the second operating condition is determined; based on the weight of each charge-discharge cycle under the second operating condition, the changes in expansion force under the second operating condition are weighted and summed to obtain the changes in expansion force of the battery under the second operating condition.

[0059] For example, higher weights are given to charge-discharge cycles that cause greater damage, such as deep discharge and high-rate cycles, to better reflect the actual degree of aging damage.

[0060] In this embodiment of the application, for each working condition, the expansion force before and after the cycle is collected multiple times, and the change in expansion force before and after each cycle is calculated. The expansion force change of multiple cycles is further integrated to achieve accurate calculation of the expansion force change, avoiding the problem of inaccurate expansion force change caused by factors such as aging interference in a single cycle.

[0061] Figure 3 This is a flowchart of another battery operating condition adjustment method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: S301: Obtain the battery's operating time and expansion force data under at least one operating condition within a preset historical time period, based on the current time, as well as the environmental data within the preset historical time period; for details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0062] S302, based on the running time and expansion force data corresponding to each operating condition, determines the equivalent expansion force data of the battery within a preset historical time period.

[0063] In one possible implementation, S302 specifically includes: S3021, determine the total duration based on the running time corresponding to each working condition.

[0064] Specifically, the total duration is the sum of the independent running times of all types of working conditions within a preset historical time period.

[0065] S3022, Based on the total duration and the runtime of the first operating condition, determine the duration percentage of the first operating condition.

[0066] The first working condition is one of at least one working condition.

[0067] S3023, after determining the time percentage corresponding to each of the working conditions, the equivalent expansion force data is determined based on the time percentage corresponding to each of the working conditions and the expansion force data.

[0068] Optionally, the expansion force data includes the expansion force and the change in expansion force before and after charge-discharge cycles.

[0069] After determining the time percentage for each working condition, the equivalent expansion force data is determined based on the time percentage for each working condition and the expansion force data. This involves the following steps: First, the equivalent expansion force is determined based on the time percentage and expansion force corresponding to each of the various working conditions.

[0070] Specifically, the equivalent expansion force characterizes the overall steady-state expansion level of the battery within a preset historical time period.

[0071] For example, the duration percentage is used as a weight, and the various expansion forces are weighted and summed to obtain the equivalent expansion force.

[0072] Then, based on the duration percentage and expansion force change corresponding to each of the working conditions, the equivalent expansion force change is determined.

[0073] Specifically, the change in equivalent expansion force characterizes the overall rate of expansion and aging of the battery during operation within a preset historical time period.

[0074] For example, the duration percentage is used as the weight, and the changes in each expansion force are weighted and summed to obtain the equivalent change in expansion force.

[0075] Finally, the equivalent expansion force and the change in equivalent expansion force are determined as the equivalent expansion force data.

[0076] The expansion force under a certain operating condition can only reflect the local and instantaneous collision state of the battery, and cannot represent the overall expansion level of the battery within a preset historical time period. Different operating conditions have different durations within the preset historical time period, resulting in different impacts on battery expansion. By using the duration percentage as a weight, the expansion force data of each condition is weighted and calculated to obtain equivalent expansion force data. This accurately quantifies the contribution of each operating condition to the overall steady-state expansion of the battery within the preset historical time period, and accurately simulates the long-term expansion state of the battery.

[0077] S303, based on equivalent expansion force data and a preset mapping relationship between expansion force data and battery health state, predicts the battery's first health state at the current moment. For details, please refer to [link to relevant documentation]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0078] S304, based on environmental data, equivalent expansion force data, and the first health state, adjusts the battery's operating conditions for a pre-set future time period based on the current moment. For details, please refer to [link to relevant documentation]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0079] In this embodiment, the duration of each operating condition within a preset time period is determined, and the equivalent expansion force is obtained by fusing the duration of each operating condition with the expansion force data. This enables a differentiated assessment of the battery's aging contribution under multiple operating conditions, making the battery health status predicted based on the equivalent expansion force data more consistent with the actual aging and expansion evolution of the battery. This provides reliable data support for early safety hazards of the battery, helps to intervene in battery aging and degradation problems in advance, and reduces safety risks.

[0080] In some embodiments, based on any of the foregoing embodiments, the first health state of the battery at the current moment is predicted based on equivalent expansion force data and a preset first mapping relationship between expansion force data and battery health state, specifically including the following steps: a1, based on equivalent expansion force data and the first mapping relationship, predicts the second health state of the battery at the current moment.

[0081] Specifically, the second health state is a single-dimensional health state obtained based on the battery expansion and deformation characteristics. It focuses on the aging and risks caused by the physical swelling of the cell and gas generation deformation, and characterizes the structural aging damage of the battery.

[0082] a2, obtain the preset lifespan of the battery under each operating condition.

[0083] Specifically, different operating conditions correspond to different lifespan thresholds due to varying aging intensities. The preset lifespan for each operating condition refers to the theoretical lifespan the battery can achieve under that condition, serving as a benchmark parameter for quantifying lifespan loss under different operating conditions. Different operating conditions result in different levels of wear and tear, leading to variations in their corresponding preset lifespans. For example, the preset lifespan of a battery under high-temperature, high-rate conditions at 45℃ is 6 years, while the preset lifespan of a battery under high-temperature, high-rate conditions at 30℃ is 8 years.

[0084] For example, the preset lifespan of the battery under each operating condition can be obtained through simulation or calibrated through aging tests.

[0085] a3 predicts the battery's third health state at the current moment based on the duration percentage of each operating condition and the preset lifespan.

[0086] Specifically, the third health state refers to the battery health state assessed from the perspective of operating loss and battery life consumption based on the proportion of time spent in each operating condition and the preset lifespan, with a focus on the overall battery life degradation and capacity loss.

[0087] In one possible implementation, the third health state is determined as follows: First, based on the duration percentage of each operating condition and the preset lifespan, the equivalent lifespan of the battery at the current moment is determined.

[0088] Specifically, the equivalent service life is obtained based on the time proportion of each operating condition and the preset service life corresponding to each operating condition, ensuring the overall loss level of the battery under multiple operating conditions.

[0089] For example, the time percentage is used as the weight of each working condition, and the preset service life corresponding to each working condition is weighted and summed to obtain the equivalent service life.

[0090] Then, based on the equivalent lifespan and the battery's preset maximum lifespan, the third health state is determined.

[0091] For example, the smaller of the equivalent service life and the preset maximum service life is determined as the third health state. For instance, if the equivalent service life is 8 years and the preset maximum service life is 10 years, then the service life corresponding to the third health state is 8 years.

[0092] In this way, the duration of each operating condition reflects the weight of the impact of each operating condition on the battery, thereby uniformly describing the overall lifespan degradation rate of the battery under mixed operating conditions and objectively quantifying the long-term operating status of the battery under mixed operating conditions.

[0093] a4. Based on the second and third health states, determine the first health state.

[0094] Specifically, the first health state is a comprehensive health state that combines the second and third health states, which integrates the battery health assessment results from both physical deformation aging and lifespan performance degradation.

[0095] In one possible implementation, the smaller of the second and third health states is determined as the first health state.

[0096] In this way, the health state with more severe degradation and higher risk is identified as the first health state between the structural aging caused by cell expansion and the life performance degradation caused by operating conditions. This can promptly expose early micro-expansion or battery life degradation problems.

[0097] In another possible implementation, the first health state is obtained by weighted summing of the second and third health states. The weights for the second and third health states can be set according to the actual situation, and are not specifically limited here.

[0098] In this way, by taking into account both the impact of physical deformation and aging and the degradation of lifespan performance on the battery, a comprehensive and objective battery health assessment result can be obtained, avoiding misjudgments of battery health status caused by a single-dimensional assessment, and providing an accurate basis for subsequent battery maintenance.

[0099] In some embodiments, based on any of the foregoing embodiments, before adjusting the battery's operating conditions for a preset future time period based on environmental data, equivalent expansion force data, and a first health state, the method provided in this application embodiment further includes the following: First, acquire multiple historical operating condition data, as well as the corresponding historical environmental data, historical expansion force data, and historical health status for each historical operating condition data.

[0100] Specifically, historical operating condition data can be various real operating parameters recorded by the battery during past operating cycles, including but not limited to historical charge / discharge rates, depth of discharge, operating time, temperature, and other operating condition parameters that affect battery aging. Historical environmental data refers to environmental parameters corresponding to historical operating condition data, including but not limited to ambient temperature and humidity. Historical expansion force data refers to the cell expansion force data and changes in expansion force when the battery was running under corresponding historical operating conditions and environments, characterizing the degree of battery aging under those conditions and environments.

[0101] Then, based on multiple historical operating condition data, as well as the historical environmental data, historical expansion force data, and historical health status corresponding to each historical operating condition data, a second mapping relationship is constructed.

[0102] The second mapping relationship is used to characterize the impact of operating condition data and environmental data on expansion force data and health status.

[0103] Specifically, the second mapping relationship describes the aging expansion and health degradation patterns of batteries under different operating conditions and environments. For example, the second mapping relationship can be a quantitative correlation model trained using historical operating condition data, historical environmental data, expansion force data before operating conditions, and health status before operating conditions as input independent variables, and future expansion force data and future health status as output dependent variables. Through the second mapping relationship, the expansion level and health status of the battery under any operating condition and environment can be predicted. Of course, the second mapping relationship can also be used to determine the optimal operating conditions in the future, with the goal of minimizing expansion level and optimizing health status, thereby achieving real-time adjustment of operating conditions and avoiding the risks of battery aging damage and expansion.

[0104] In this way, by combining operating condition data, environmental data, expansion force data, and health status, a second mapping relationship is obtained to accurately describe the rules of battery aging and performance degradation under the combined effect of operating condition data and environmental data.

[0105] In one possible implementation, historical operating condition data, historical environmental data, pre-operational expansion force data, and pre-operational health status are used as multidimensional independent variables, while future expansion force data and future health status are used as dependent variables. A multiple linear regression model is constructed to fit the correlation between the dependent and independent variables, thereby obtaining the second mapping relationship.

[0106] In another possible implementation, a quadratic or higher polynomial fitting method is used to fit the nonlinear aging relationship between working conditions, environment, expansion force data, and health status, i.e., the second mapping relationship, thereby restoring the accelerated aging nonlinear characteristics under harsh working conditions such as high temperature and high rate.

[0107] In another possible implementation, machine learning algorithms such as random forest and gradient boosting regression are used. The model is trained by taking historical operating condition data, historical environmental data, expansion force data before operating condition, and health status before operating condition as inputs, and future expansion force data and future health status as labels. The model can be used to explore the aging law of multi-parameter coupling and adapt to energy storage scenarios with complex operating conditions, frequent switching, and large environmental fluctuations.

[0108] In this embodiment of the application, a second mapping relationship is constructed by acquiring a large amount of historical operating condition data, historical environmental data, historical expansion force data, and historical health status data, so as to provide accurate data support for subsequent operating condition adjustments.

[0109] Furthermore, by utilizing the second mapping relationship, environmental data, equivalent expansion force data, and the first health state are used as constraints. The optimization objective is to minimize the equivalent expansion force data within a preset future time period and maximize the health state after the preset future time period, thereby determining the adjusted operating condition data.

[0110] In one possible implementation, under the constraints of environmental data, equivalent expansion force data, and the first health state, all working condition data are traversed, and the second mapping relationship is input one by one. The equivalent expansion force data and health state corresponding to each group of working conditions are calculated respectively. The working condition data with the smallest expansion force and the highest health state are selected and determined as the adjusted working condition data.

[0111] In another possible implementation, the battery's current operating condition data is used as the initial iteration starting point. Within the range of preset constraints, the optimization gradient of the operating condition data is calculated based on the second mapping relationship. The operating condition data is iteratively optimized in the direction of reducing the equivalent expansion force data and improving the battery's health status until the preset iteration stopping conditions are met (such as reaching the preset number of iterations, or the equivalent expansion force data and the battery's health status meeting the corresponding preset thresholds, etc.), and the adjusted operating condition data is obtained.

[0112] In this way, based on the current actual aging condition of the battery and environmental data, the optimal operating conditions are adapted to suppress the accumulation of micro-expansion and the decline in the health status of the battery during future operation, and avoid the safety hazards of swelling caused by continuous operation under poor operating conditions.

[0113] For example, operating condition data includes charge / discharge rate and / or depth of discharge (DOD). The charge / discharge rate characterizes the speed of battery charging and discharging; a higher charge / discharge rate results in a larger charging / discharging current, leading to more severe cell heating and polarization, thus exacerbating cell gas expansion and capacity decay. The depth of discharge refers to the percentage of the battery's rated capacity released during a single discharge. A higher depth of discharge indicates greater loss of active materials and more pronounced cycle aging; prolonged deep discharge will exacerbate cell expansion and deformation.

[0114] Furthermore, based on equivalent expansion force data and a preset mapping relationship between expansion force data and battery health status, after predicting the battery's first health status at the current moment, the method provided in this application embodiment includes the following: First, obtain the preset operating condition data for a future time period based on the current time.

[0115] Specifically, the preset operating condition data can be user-defined operating condition data for future batteries.

[0116] Then, based on preset operating condition data, environmental data, first health state, equivalent expansion force data, and second mapping relationship, the health state of the battery after a preset future time period is predicted.

[0117] Specifically, the battery health status after a preset future time period is obtained based on the second mapping relationship, which can reflect the degree of performance degradation and aging of the battery in the future.

[0118] For example, preset operating condition data, environmental data, first health state, and equivalent expansion force data are input into the second mapping relationship to obtain the battery health state for a preset future time period.

[0119] This enables accurate prediction of battery degradation, expansion, and aging trends under different operating conditions and environments, providing data support for subsequent refined battery management and safe and stable operation.

[0120] This embodiment also provides a battery condition adjustment device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0121] This embodiment provides a battery condition adjustment device, such as... Figure 4 As shown, it includes: The acquisition module 401 is used to acquire the running time and expansion force data of the battery under at least one working condition within a preset historical time period based on the current time, as well as the environmental data within the preset historical time period. The determination module 402 is used to determine the equivalent expansion force data of the battery within a preset historical time period based on the running time and expansion force data corresponding to each working condition. The prediction module 403 is used to predict the first health state of the battery at the current moment based on the equivalent expansion force data and the preset first mapping relationship between the expansion force data and the battery health state. The adjustment module 404 is used to adjust the battery's operating conditions within a preset future time period based on environmental data, equivalent expansion force data, and the first health state.

[0122] Using the aforementioned device, based on the battery's operating time and expansion force data under various operating conditions within a preset historical time period, the equivalent expansion force data of the battery within that period is determined, characterizing the battery's cumulative aging features. Furthermore, based on the preset mapping relationship between the equivalent expansion force and the battery's health status, the battery's current health status is accurately predicted. Finally, using environmental data from the preset historical time period as a reference, and based on the predicted battery health status and equivalent expansion force data, the battery's operating conditions are adjusted in a timely manner for future periods. Compared to the passive handling method of post-event maintenance in related technologies, the method provided by this invention can accurately quantify the aging damage and expansion risks accumulated by the battery under various operating conditions, identify safety hazards in advance before battery failure, thereby changing the battery's operating conditions, improving maintenance efficiency, and providing reliable data support for the safe operation and maintenance of batteries.

[0123] In one possible implementation, module 402 is specifically used to determine the total duration based on the runtime corresponding to each working condition. Based on the total duration and the duration of the first working condition, the duration percentage of the first working condition is determined, wherein the first working condition is one of at least one working condition; Once the duration percentage for each working condition is determined, the equivalent expansion force data is determined based on the duration percentage for each working condition and the expansion force data.

[0124] In one possible implementation, the expansion force data includes the expansion force and the change in expansion force before and after a charge-discharge cycle; the determination module 402 is specifically used to determine the equivalent expansion force based on the duration percentage and expansion force corresponding to each of the various operating conditions. The equivalent expansion force change is determined based on the duration percentage and expansion force change for each of the various working conditions. The equivalent expansion force and the change in equivalent expansion force are defined as the equivalent expansion force data.

[0125] In one possible implementation, the acquisition module 401 is specifically used to acquire the expansion force of the battery before and after multiple charge-discharge cycles under the second working condition within a preset historical time period. Based on the expansion forces corresponding to the first charge-discharge cycle before and after the first charge-discharge cycle, the change in expansion force before and after the first charge-discharge cycle is determined, wherein the first charge-discharge cycle is one of multiple charge-discharge cycles under the second operating condition; After determining the changes in expansion force before and after multiple charge-discharge cycles, the changes in expansion force of the battery under the second operating condition are determined based on these changes in expansion force before and after multiple charge-discharge cycles.

[0126] In one possible implementation, the prediction module 403 is specifically used to predict the second health state of the battery at the current moment based on the equivalent expansion force data and the first mapping relationship. Obtain the preset lifespan of the battery under each operating condition; Based on the duration percentage of each operating condition and the preset lifespan, predict the third health state of the battery at the current moment. The first health state is determined based on the second and third health states.

[0127] In one possible implementation, the prediction module 403 is specifically used to determine the equivalent lifespan of the battery at the current moment based on the duration percentage corresponding to each of the various operating conditions and the preset lifespan. The third health state is determined based on the equivalent lifespan and the battery's preset maximum lifespan.

[0128] In one possible implementation, prediction module 403 is specifically used to determine the smaller of the second health state and the third health state as the first health state.

[0129] In one possible implementation, before adjusting the battery's operating conditions within a preset future time period based on environmental data, equivalent expansion force data, and first health state, the adjustment module 404 is also used to acquire multiple historical operating condition data, as well as the historical environmental data, historical expansion force data, and historical health state corresponding to each historical operating condition data. Based on multiple historical operating condition data, and the corresponding historical environmental data, historical expansion force data, and historical health status for each historical operating condition data, a second mapping relationship is constructed. The second mapping relationship is used to characterize the impact of operating condition data and environmental data on expansion force data and health status.

[0130] In one possible implementation, the adjustment module 404 is specifically used to utilize the second mapping relationship, taking environmental data, equivalent expansion force data, and the first health state as constraints, and taking minimizing the equivalent expansion force data within a preset future time period and maximizing the health state after the preset future time period as optimization objectives, to determine the adjusted operating condition data.

[0131] In one possible implementation, after the adjustment module 404 predicts the first health state of the battery at the current moment based on the equivalent expansion force data and the first mapping relationship between the preset expansion force data and the battery health state, it is also used to obtain preset operating condition data for a preset future time period based on the current moment. Based on preset operating condition data, environmental data, first health state, equivalent expansion force data, and second mapping relationship, the health state of the battery is predicted after a preset future time period.

[0132] The battery condition adjustment device provided in this embodiment of the invention can execute the battery condition adjustment method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0133] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0134] The following is a detailed reference. Figure 5 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from memory 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device. The processor 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0135] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0136] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a ROM 502. When the computer program is executed by the processor 501, it performs the functions defined in the battery condition adjustment method of the embodiments of the present invention.

[0137] Figure 5The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0138] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the battery condition adjustment method shown in the above embodiments is implemented.

[0139] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0140] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for adjusting battery operating conditions, characterized in that, The method includes: The system acquires the battery's runtime and expansion force data under at least one operating condition within a preset historical time period, based on the current time, as well as the environmental data within the preset historical time period. Based on the running time and expansion force data corresponding to each of the aforementioned operating conditions, the equivalent expansion force data of the battery within the preset historical time period is determined. Based on the equivalent expansion force data and the preset first mapping relationship between expansion force data and battery health status, the first health status of the battery at the current moment is predicted. Based on the environmental data, the equivalent expansion force data, and the first health status, the operating conditions of the battery are adjusted within a preset future time period based on the current time.

2. The method according to claim 1, characterized in that, The step of determining the equivalent expansion force data of the battery within the preset historical time period based on the running time and expansion force data corresponding to each of the aforementioned operating conditions includes: The total duration is determined based on the running time corresponding to each of the aforementioned operating conditions; Based on the total duration and the duration of the first working condition, the duration percentage of the first working condition is determined, wherein the first working condition is one of the at least one working condition; After determining the time percentage corresponding to each of the aforementioned working conditions, the equivalent expansion force data is determined based on the time percentage corresponding to each of the aforementioned working conditions and the expansion force data.

3. The method according to claim 2, characterized in that, The expansion force data includes the expansion force and the change in expansion force before and after a charge-discharge cycle; after determining the time percentage corresponding to each of the aforementioned operating conditions, the equivalent expansion force data is determined based on the time percentage corresponding to each of the aforementioned operating conditions and the expansion force data, including: Based on the duration percentage and expansion force corresponding to each of the aforementioned working conditions, the equivalent expansion force is determined. Based on the duration percentage and expansion force change corresponding to each of the aforementioned working conditions, the equivalent expansion force change is determined. The equivalent expansion force and the change in the equivalent expansion force are defined as the equivalent expansion force data.

4. The method according to claim 3, characterized in that, Obtain the change in expansion force of the battery under a second operating condition within the preset historical time period based on the current time, wherein the second operating condition is one of the at least one operating condition, including: Obtain the expansion force of the battery before and after multiple charge-discharge cycles under the second operating condition within the preset historical time period; Based on the expansion forces corresponding to the first charge-discharge cycle before and after the first charge-discharge cycle, the change in expansion force before and after the first charge-discharge cycle is determined, wherein the first charge-discharge cycle is one of multiple charge-discharge cycles under the second operating condition; After determining the changes in expansion force before and after the plurality of charge-discharge cycles, the changes in expansion force of the battery under the second operating condition are determined based on the changes in expansion force before and after the plurality of charge-discharge cycles.

5. The method according to any one of claims 2-4, characterized in that, The step of predicting the first health state of the battery at the current moment based on the equivalent expansion force data and a preset first mapping relationship between the expansion force data and the battery health state includes: Based on the equivalent expansion force data and the first mapping relationship, predict the second health state of the battery at the current moment; Obtain the preset lifespan of the battery under each of the operating conditions; Based on the duration percentage of each of the aforementioned operating conditions and the preset lifespan, the third health state of the battery at the current moment is predicted. The first health state is determined based on the second health state and the third health state.

6. The method according to claim 5, characterized in that, The prediction of the third health state of the battery at the current moment based on the duration percentage of each of the aforementioned operating conditions and the preset lifespan includes: Based on the duration percentage and preset lifespan of each of the aforementioned operating conditions, the equivalent lifespan of the battery at the current moment is determined. The third health state is determined based on the equivalent service life and the preset maximum service life of the battery.

7. The method according to any one of claims 2-4, characterized in that, Before adjusting the battery's operating conditions within a preset future time period based on the environmental data, the equivalent expansion force data, and the first health status, the method further includes: Acquire multiple historical operating condition data, as well as the historical environmental data, historical expansion force data, and historical health status corresponding to each of the historical operating condition data; Based on the multiple historical operating condition data, and the historical environmental data, historical expansion force data, and historical health status corresponding to each historical operating condition data, a second mapping relationship is constructed, wherein the second mapping relationship is used to characterize the impact of operating condition data and environmental data on expansion force data and health status.

8. The method according to claim 7, characterized in that, The adjustment of the battery's operating conditions within a preset future time period based on the environmental data, the equivalent expansion force data, and the first health status includes: Using the second mapping relationship, the environmental data, the equivalent expansion force data, and the first health status are used as constraints. The optimization objective is to minimize the equivalent expansion force data within a preset future time period and maximize the health status after the preset future time period, thereby determining the adjusted operating condition data.

9. The method according to claim 7, characterized in that, After predicting the first health state of the battery at the current moment based on the equivalent expansion force data and a preset first mapping relationship between the expansion force data and the battery health state, the method includes: Acquire preset operating condition data for a future time period based on the current time; Based on the preset operating condition data, the environmental data, the first health status, the equivalent expansion force data, and the second mapping relationship, the health status of the battery after the preset future time period is predicted.

10. A battery operating condition adjustment device, characterized in that, The device includes: The acquisition module is used to acquire the running time and expansion force data of the battery under at least one working condition within a preset historical time period based on the current time, as well as the environmental data within the preset historical time period. The determination module is used to determine the equivalent expansion force data of the battery within the preset historical time period based on the running time and expansion force data corresponding to each of the operating conditions. The prediction module is used to predict the first health state of the battery at the current moment based on the equivalent expansion force data and a preset first mapping relationship between the expansion force data and the battery health state. The adjustment module is used to adjust the operating conditions of the battery within a preset future time period based on the environmental data, the equivalent expansion force data, and the first health status.

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