Intelligent battery management method and system for heavy-load protection and computer equipment

Abstract

The invention discloses an intelligent battery management method and system for heavy-load protection and computer equipment. The method comprises the following steps: carrying out association analysis on historical operation data collected by a battery management system and a protection signal output by a complete machine controller to obtain a heavy load response mapping relation between the battery management system and the complete machine controller; performing unified calibration on protection configuration parameters in the battery management system and protection control parameters in the complete machine controller according to the heavy load response mapping relation to obtain a parameter configuration set for jointly judging a heavy load state; and performing synchronous coordination on the parameter configuration set to obtain a heavy load protection control instruction for coordinating heavy load response behaviors of the battery management system and the whole machine controller. On the basis, the cooperative protection capability of the battery management system and the whole machine controller in a heavy load state is realized, and the response consistency and the control coordination of the whole system are improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the technical field of intelligent battery management, and in particular to an intelligent battery management method and system for overload protection and a computer device. BACKGROUND

[0002] In the technical field of intelligent battery management, the collaborative control between the battery system and the main control system is involved, so as to realize the rapid response and protection to the overload state. In the related overload protection method, the overload identification and processing are realized by setting the protection threshold independently in the battery management system and the whole machine controller. However, this method has the disadvantages of inconsistent response, protection delay and poor coordination, thereby leading to the failure to realize accurate overload protection under complex load conditions, and affecting the stability and safety of system operation. SUMMARY

[0003] At least one embodiment of the present disclosure provides an intelligent battery management method for overload protection, comprising: correlatively analyzing historical running data collected by a battery management system and a protection signal output by a whole machine controller to obtain an overload response mapping relationship between the battery management system and the whole machine controller; calibrating protection configuration parameters in the battery management system and protection control parameters in the whole machine controller according to the overload response mapping relationship to obtain a parameter configuration set for jointly judging an overload state; synchronously coordinating the parameter configuration set to obtain an overload protection control instruction for coordinating overload response behaviors of the battery management system and the whole machine controller.

[0004] At least one embodiment of the present disclosure provides an intelligent battery management system for overload protection, comprising: a first analysis module configured to correlatively analyze historical running data collected by a battery management system and a protection signal output by a whole machine controller to obtain an overload response mapping relationship between the battery management system and the whole machine controller; a second analysis module configured to calibrate protection configuration parameters in the battery management system and protection control parameters in the whole machine controller according to the overload response mapping relationship to obtain a parameter configuration set for jointly judging an overload state; a generation module configured to synchronously coordinate the parameter configuration set to obtain an overload protection control instruction for coordinating overload response behaviors of the battery management system and the whole machine controller.

[0005] The computer device provided by at least one embodiment of the present disclosure comprises a memory for storing computer executable instructions, and a processor for running the computer executable instructions, wherein the computer executable instructions, when run by the processor, implement the overload protection intelligent battery management method according to any embodiment of the present disclosure.

[0006] The computer readable storage medium provided by at least one embodiment of the present disclosure stores computer executable instructions, and the computer executable instructions, when executed by a processor, implement the overload protection intelligent battery management method according to any embodiment of the present disclosure.

[0007] In the overload protection intelligent battery management method provided by at least one embodiment of the present disclosure, first, the overload response mapping relationship between the running state change of the battery and the protection control behavior is determined according to the association analysis of the historical running data and the protection signal; second, the parameter configuration set used for jointly judging the overload state is obtained by uniformly calibrating two types of system parameters according to the overload response mapping relationship, so as to ensure the consistency of the battery management system and the whole machine controller in the overload judgment logic; third, the overload protection control instruction with consistent triggering conditions and response logic is constructed according to the synchronization coordination of the parameter configuration set; based on this, the closed loop mechanism is constructed in three aspects of data association, parameter fusion and instruction coordination, and the collaborative protection capability of the battery management system and the whole machine controller in the overload state is realized, and the response consistency and control coordination of the whole system are improved. BRIEF DESCRIPTION OF DRAWINGS

[0008] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly introduced below. Obviously, the drawings described below only relate to some of the embodiments of the present disclosure, but not limit the present disclosure.

[0009] Figure 1 The schematic flowchart of the overload protection intelligent battery management method provided by at least one embodiment of the present disclosure is shown in the figure; Figure 2 The schematic block diagram of the overload protection intelligent battery management system provided by at least one embodiment of the present disclosure is shown in the figure; DETAILED DESCRIPTION In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, but not all the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present disclosure.

[0010] Unless otherwise defined, technical terms or scientific terms used in the present disclosure shall have the ordinary meaning as understood by a person of ordinary skill in the art to which the present disclosure pertains. The terms "first", "second", and similar terms used in the present disclosure do not denote any order, quantity, or importance, but are used to distinguish different components. The terms "include", "contain", and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and equivalents thereof, and do not exclude other elements or objects. The terms "connect" or "connected" or similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right", and the like are used only to indicate relative positional relationships, and when the absolute positions of the described objects are changed, the relative positional relationships can also be changed accordingly. In order to keep the following description of the embodiments of the present disclosure clear and concise, the detailed description of some known functions and known components is omitted.

[0011] At least one embodiment of the present disclosure provides a heavy load protection intelligent battery management method, system, computer device and storage medium. Figure 1 The schematic flow chart of the heavy load protection intelligent battery management method provided by at least one embodiment of the present disclosure includes steps S101 to S103.

[0012] Step S101, the historical running data collected by the battery management system and the protection signal output by the whole machine controller are associated and analyzed to obtain the heavy load response mapping relationship between the battery management system and the whole machine controller.

[0013] Among them, the battery management system represents a functional module set for monitoring, protecting and controlling the running state of the battery; the historical running data represents a time series data set about the running state of the battery collected and recorded by the battery management system in the past multiple running periods, for example, including the parameter change data of voltage, current, temperature and the like in different states such as charging, discharging, standby and the like.

[0014] Among them, the whole machine controller represents a master control module for managing and controlling the overall running state of the device; the protection signal represents a state alarm signal or control trigger signal sent by the whole machine controller to the external module when judging that the device enters an abnormal or dangerous state, to notify the battery management system to take corresponding protection control actions, for example, sending a control signal to start current limiting or disconnect power supply when the load is too high.

[0015] The heavy load response mapping relationship represents a set of mapping rules reflecting the corresponding logical relationship between the battery operating state change and the protection signal established between the battery management system and the machine controller, for example, a behavior record of issuing a protection signal by the machine controller when the current exceeds a certain threshold for 3 seconds is mapped to a certain mapping rule.

[0016] Optionally, first, the historical operation data collected by the battery management system and the protection signal output by the machine controller are subjected to time axis alignment processing, thereby preliminarily establishing the matching corresponding relationship between each type of battery operating state and the corresponding protection control behavior. Further, by analyzing the change process of each type of parameter in the historical operation data before and after the protection signal is triggered, the feature segments with obvious trend change characteristics are extracted, and these feature segments are associated with the corresponding protection signal, thereby identifying whether there is a direct corresponding relationship between the parameter fluctuation of the battery management system and the protection control behavior issued by the machine controller under a specific battery operating state. Further, if a certain historical operation data and a certain protection signal have a corresponding relationship, it indicates that there is a stable response relationship between the two, and then this type of state-signal pair can be summarized and sorted as a heavy load response behavior. Finally, by classifying, merging and sorting a plurality of heavy load response behaviors, the heavy load response mapping relationship for describing the response mechanism between the battery management system and the machine controller is finally formed; the heavy load response mapping relationship records the type of protection signal corresponding to the machine controller output when the battery operating state reaches a certain state threshold, the response time delay, and the continuity and other information.

[0017] In step S102, according to the heavy load response mapping relationship, the protection configuration parameters in the battery management system and the protection control parameters in the machine controller are uniformly calibrated to obtain a parameter configuration set for jointly judging the heavy load state.

[0018] The protection configuration parameters represent various set parameters for judging whether the battery operating state is abnormal and triggering a protection action in the battery management system, i.e., limiting the working boundary and safety threshold of the battery in the charging and discharging process to avoid damage or failure of the battery due to overload, over-temperature, over-current, etc.; for example, over-current protection threshold, voltage upper and lower limit value, temperature limit value, fault response delay time, etc.

[0019] The protection control parameters represent instruction logic parameters for identifying the machine operating state and coordinating the execution of protection operations by each sub-module in the machine controller, i.e., defining the response condition and control strategy of the machine controller to heavy load, over-voltage, power abnormality, etc.; for example, maximum allowable power limit value, judgment current threshold for triggering battery load reduction, load shutdown time setting, system power failure recovery strategy, etc.

[0020] The parameter configuration set for jointly judging the overload state represents a comprehensive parameter group for realizing the synchronized recognition and collaborative response of the battery management system and the overall controller to the overload scenario, so that the battery management system and the overall controller can make consistent decisions based on the same judgment basis and control logic under the overload scenario.

[0021] Optionally, first, the protection configuration parameters for limiting the charging and discharging behavior are extracted from the battery management system, and the protection control parameters for controlling the power output, running mode switching or sub-module scheduling are extracted from the overall controller, which reflect the execution logic and response strategy of the corresponding system under the overload state. Then, the parameters in the above two systems are uniformly converted in format to ensure consistency in description, unit definition and numerical resolution, so as to facilitate cross comparison and logic fusion. Further, according to the trigger sequence and corresponding mapping rule between the battery running state change and the protection control behavior reflected in the overload response mapping relationship, the parameters in the two systems are processed one by one to identify the parameter items that have deviations in execution logic or time differences in response strategy. Further, for the parameter items with differences, adaptive adjustment needs to be made according to the respective working boundaries and protection objects to make them consistent and coordinated in judging the overload state; in addition, the adjustment process should be based on the value distribution of the actual running data to ensure that each parameter has a clear action range and accurate trigger condition in the collaborative response process. Finally, all the parameters after calibration are arranged into a parameter configuration set in a preset format, which covers the key basis for the overload state recognition of the two systems in structure and has a unified logic judgment basis.

[0022] In step S103, the parameter configuration set is synchronized and coordinated to obtain an overload protection control instruction for coordinating the overload response behavior of the battery management system and the overall controller.

[0023] The overload protection control instruction represents a command sequence for coordinating the battery management system and the overall controller to execute specific protection actions under the overload scenario, i.e., instructing the battery management system and the overall controller to synchronously execute overload response behaviors such as limiting, cutting off, load shedding or alarming according to the preset logic after detecting the overload state.

[0024] Optionally, first, the triggering order and response level of each parameter in the parameter configuration set in the control flow are analyzed, and the control action points corresponding to each parameter and their execution order are sorted in combination with the existing control structures of the two systems. Subsequently, according to the overlapping area of the triggering conditions between the protection configuration parameters and the protection control parameters in the parameter configuration set, the primary overload response behavior after overload state identification is determined and set as the initial response node of the control instruction, and then the subsequent logical judgment and control output content are added in sequence according to the control action points corresponding to each parameter in the parameter configuration set and their execution order, and a complete control instruction flow is gradually constructed. Further, during the construction process, the triggering conditions, response logic and feedback mechanism in the control instruction are set item by item to ensure that the protection control behavior does not have logical conflicts or response delays during transmission between the two systems; especially in the case of multi-level response, the response priority and interruption strategy of the master system and the slave system should be clear to avoid instruction failure due to repeated use of control resources. In addition, after the control instruction structure is formed, the corresponding instruction state identifier and execution confirmation mechanism need to be set to synchronize the state and verify the results during the execution of the two systems. The final output of the overload protection control instruction needs to have clear triggering conditions, complete response logic and reliable feedback mechanism, and can achieve consistent execution and behavior synchronization of the control strategy between the battery management system and the whole machine controller, thereby supporting the system as a whole to have stable and coherent response capability when the overload state occurs.

[0025] In the above embodiment, first, according to the correlation analysis of the historical running data and the protection signal, the overload response mapping relationship between the battery running state change and the protection control behavior is determined; second, the two types of system parameters are calibrated according to the overload response mapping relationship to obtain a parameter configuration set for joint judgment of the overload state, thereby ensuring the consistency of the battery management system and the whole machine controller in the overload judgment logic; third, the overload protection control instruction with consistent triggering conditions and response logic is constructed according to the synchronization and coordination of the parameter configuration set. Based on this, by constructing a closed-loop mechanism at the levels of data correlation, parameter fusion and instruction coordination, the collaborative protection capability of the battery management system and the whole machine controller in the overload state is realized, and the response consistency and control coordination of the system as a whole are improved.

[0026] In some embodiments, the historical running data collected by the battery management system and the protection signal output by the whole machine controller are correlated and analyzed to obtain the overload response mapping relationship between the battery management system and the whole machine controller, including steps S201 to S203.

[0027] Step S201, feature extraction is performed on each physical quantity change sequence in the historical running data to obtain a waveform mode set representing various overload response behaviors of the battery management system.

[0028] Wherein, each physical quantity change sequence can contain the change sequence of key physical quantities such as current, voltage, power, etc., that is, the continuous numerical sequence of the key physical quantity collected by the battery management system over time during the running process.

[0029] Wherein, the waveform mode set represents a set of various waveform modes with representative and structural characteristics extracted from each physical quantity change sequence, such as current waveform with too fast rising rate, voltage waveform showing sharp decline, or electrical response characteristics showing periodic disturbance mode, etc.

[0030] Optionally, first, by dividing the time window of each physical quantity data of the battery management system running the whole process, so that each time window corresponds to a complete historical running data segment. Then, the differential calculation and trend identification are carried out on each physical quantity change curve in each time window, from which the waveform segments containing obvious change characteristics are identified, such as sudden rise, sharp decline, sustained fluctuation or periodic disturbance, etc. These waveform segments reflect the natural response process of the battery management system under external load mutation or internal abnormal state, that is, reflect the heavy load response behavior generated by the battery management system in the whole process of the battery management system running. Then, the above waveform segments are classified according to the corresponding change direction, duration, amplitude range and change slope, etc. From which a plurality of representative waveform modes are constructed, and then a waveform mode set is formed to describe the different response behavior characteristics of the battery management system under the trigger of different heavy load conditions, that is, one waveform mode corresponds to a plurality of heavy load response behaviors of the same type.

[0031] Step S202, according to the protection trigger time point in the protection signal and the signal control type, time alignment and trigger source classification are carried out on the waveform mode set, and the time sequence identification relationship table containing the mapping relationship between the various heavy load response behaviors of the battery management system and the various heavy load response behaviors of the whole machine controller is obtained.

[0032] Wherein, the protection trigger time point represents the specific time position of the whole machine controller outputting a specific protection signal during the running process, and the signal control type represents the classification label of the protection control behavior corresponding to each type of protection signal output by the whole machine controller.

[0033] The time sequence identification relationship table is a structured relationship record table for establishing the time sequence and type correspondence between the waveform mode set corresponding to the battery management system and the protection signals output by the whole machine controller, so as to clearly show the time sequence, correspondence and control type attribution between each waveform mode and the corresponding protection signal. For example, the time sequence identification relationship table shows that a certain current mutation waveform occurs in a certain specific time period, and the protection signal related to the power limiting signal output by the whole machine controller forms a continuous corresponding relationship on the time axis, thereby reflecting the response coupling between the two.

[0034] Optionally, first, all protection signal records output by the whole machine controller are extracted, and the protection trigger time point corresponding to each protection control behavior and the signal control type are obtained therefrom. After obtaining this information, the time axis analysis is performed on all waveform segments corresponding to various waveform modes in the waveform mode set, and the starting position, change peak or significant feature point of each waveform segment is compared with the protection trigger time point of the protection signal, so as to ensure that the response process of these waveform segments and the trigger event of the protection signal form a time sequence with a period of overlapping or a sequence of response relationship with associated significance. Further, by counting the matching relationship between the waveform segments contained in each type of waveform mode and various types of protection signals, it can be determined whether the type of waveform mode reflects the typical response behavior to the specific type of protection signal.

[0035] On this basis, after matching, the matched waveform mode also needs to be classified into different trigger source categories according to the signal control type of the protection signal, for example, the overload response behavior of the battery management system caused by different trigger source categories such as system overload, environmental temperature rise or communication abnormality is classified and processed, so as to distinguish the battery response behavior corresponding to different types of protection control behaviors, so as to form a set of response behavior mapping data with time identification and trigger source classification, which is used to reflect the mapping relationship between various overload response behaviors of the battery management system and various overload response behaviors of the whole machine controller.

[0036] Finally, all the response behavior mapping data are summarized, and the time sequence identification relationship table is formed thereby. The time sequence identification relationship table not only contains the statistical matching of each type of waveform mode and protection signal, but also clearly records the coverage range, trigger sequence and trigger source of each waveform segment in each type of waveform mode on the time axis, which is used to support the construction of the overload response mapping relationship between the battery management system and the whole machine controller.

[0037] Step S203: According to the time sequence identification relationship table, the behavior consistency analysis is performed on various overload response behaviors of the battery management system and the whole machine controller, and the overload response mapping relationship between the battery management system and the whole machine controller is obtained.

[0038] Optionally, the response behavior mapping data in the time sequence identification relationship table is read in a piece-by-piece manner, and the overload response behavior of the battery management system and the overload response behavior of the whole machine controller are logically associated and judged. Specifically, by analyzing whether the overload response behaviors of the two types of systems with mapping relationship have the same trigger logic and action trend, such as whether they both show power reduction, load switching or current suppression, etc., it can be judged whether the two have behavior consistency. At the same time, the behavior performance should also be quantitatively analyzed through response duration, trigger interval, response strength and other parameters, to further verify whether the time characteristics and intensity characteristics of the behavior consistency match. Based on this, if the corresponding overload response behavior of the two types of systems shows a clear behavior coupling relationship, and the trigger order and response process are consistent, the behavior coupling relationship can be summarized as a stable overload response mapping relationship, and thus recorded as the response mapping result between the battery management system and the whole machine controller, to support the subsequent cooperative identification and processing of the overload state in the control strategy.

[0039] As can be seen, the time sequence identification relationship table already contains the preliminary mapping relationship between the various overload response behaviors of the battery management system and the various overload response behaviors of the whole machine controller. This preliminary mapping relationship is based on the alignment result of the waveform fragments and the protection signals on the time axis and the signal control type classification processing, that is, it only shows that the overload response behaviors of the two types of systems have a coupling in time and logic on the surface, but it has not verified whether the overload response behaviors of the two types of systems truly exhibit coordinated and consistent control logic in intensity, trend, persistence, action mechanism, etc. Based on this, further behavior consistency analysis is needed for these overload response behaviors with preliminary mapping relationship, the purpose of which is to deeply compare the performance content of the behavior itself, and to confirm whether it exhibits synchronicity and complementarity in response amplitude, duration cycle, control effect, etc. This process not only can filter out the misfit behaviors that overlap in time but have inconsistent control logic in reality, but also can improve the reliability and structural effectiveness of the overall mapping relationship, to ensure that the finally formed overload response mapping relationship can truly reflect the cooperative control characteristics between the two types of systems.

[0040] In the above embodiment, firstly, according to the feature extraction of each physical quantity change sequence in the historical operation data, a waveform mode set capable of representing various overload response behaviors of the battery management system is constructed; secondly, according to the time alignment between the waveform mode set and the protection signal and the trigger source classification, a time sequence identification relationship table between the battery response behavior and the protection control behavior is established; thirdly, according to the behavior consistency analysis of various overload response behaviors based on the time sequence identification relationship table, a stable overload response mapping relationship between the battery management system and the whole machine controller is extracted; based on this, by constructing the time sequence mapping structure between the battery response behavior and the protection control behavior, the structural induction of the overload response logic between the battery management system and the whole machine controller is realized, which provides clear data basis and logical support for the subsequent collaborative setting of the control strategy.

[0041] In some embodiments, according to the behavior consistency analysis of various overload response behaviors of the battery management system and the whole machine controller based on the time sequence identification relationship table, the overload response mapping relationship between the battery management system and the whole machine controller is obtained, including steps S301 to S302.

[0042] Step S301, according to the behavior feature field alignment of various overload response behaviors of the battery management system and various overload response behaviors of the whole machine controller based on the time sequence identification relationship table, a behavior feature field set for representing the amplitude change, time sequence offset and execution structure is obtained.

[0043] Among them, the behavior feature field set represents a parameter field set for describing the behavior characteristics of various overload response behaviors of the battery management system and the whole machine controller, which includes amplitude change, time sequence offset and execution structure fields.

[0044] Among them, the amplitude change represents the numerical change range and trend characteristics of the key physical quantity in the overload response behavior occurring process; the time sequence offset represents the offset degree of the overload response behaviors of the two types of systems with mapping relationship on the time axis; the execution structure represents the trigger mode, action level and action path of a certain type of overload response behavior in the control logic, such as whether it is a single trigger behavior, whether it needs a pre-response condition, whether it is a linkage control behavior, etc.

[0045] Optionally, first, the maximum change value, change rate, and change process duration of the key physical quantity corresponding to the overload response behavior of the two types of systems in a specific time period are analyzed to obtain the amplitude change field of the two types of systems in the respective response processes, so as to evaluate the consistency of the overload response behavior of the two types of systems in intensity and direction. Further, the trigger time point and the end time point of the same group of overload response behaviors with mapping relationship are extracted from the time sequence identification relationship table, and the trigger time point and the end time point are aligned on the time axis to calculate the time offset and the overlap ratio between them, so as to obtain the time sequence offset field corresponding to the group of overload response behaviors, so as to describe the corresponding characteristics of the two in response priority and synchronization. Further, the logical level of each type of overload response behavior in the corresponding control path needs to be extracted from the time sequence identification relationship table, such as whether it is an initial response, whether it depends on other overload response behaviors to trigger, whether it behaves as a linkage behavior, and the like, and these information is abstracted as an execution structure field. Based on this, the above-mentioned various fields are combined into a behavior characteristic field set for comprehensively describing the key behavior performance of the two types of systems in the response process.

[0046] In step S302, the behavior characteristic field set is used to perform aggregation processing on each type of overload response behavior based on the mapping strength level, the response coupling degree level, and the repeated matching number level, to obtain the overload response mapping relationship between the battery management system and the whole machine controller.

[0047] Among them, the mapping strength level represents the numerical similarity degree between the fields corresponding to the overload response behaviors of the two types of systems; the response coupling degree level represents the linkage tightness between the overload response behaviors of the two types of systems in the execution logic, control target, and action path; and the repeated matching number level represents the consistent matching number of the same combination of overload response behaviors of the two types of systems in multiple historical running periods.

[0048] Optionally, firstly, in the mapping strength level, each group of overloaded response behaviors in the time sequence identification relationship table is given a numerical matching score by quantifying the similarity of amplitude variation, the coincidence rate of time sequence offset, and the symmetry of execution structure; that is, the higher the matching score, the closer the feature performance of the group of overloaded response behaviors in the execution process. Secondly, in the response coupling degree level, whether each group of overloaded response behaviors has a clear master-slave or complementary relationship is analyzed according to the alignment degree of each group of overloaded response behaviors in the behavior start and end time, control instruction transmission delay, and behavior interdependence, thereby constructing a logical dependence hierarchy to improve the logical integrity of behavior matching. Thirdly, in the repeated matching number level, whether each group of overloaded response behaviors repeatedly appears and maintains a stable relationship in different running periods is counted, thereby identifying the long-term stable response association. Based on this, the aggregation processing of the above three levels is carried out based on each group of overloaded response behaviors as the basic unit for aggregation, scoring and screening, and finally the behavior pairs with high scores, strong coupling and repeated appearance are retained, and the final overloaded response mapping relationship is formed.

[0049] In the above embodiment, firstly, according to the alignment processing of the amplitude variation, time sequence offset, and execution structure of the established mapping relationship of the overloaded response behaviors, the behavior feature field set that can be used to quantify the difference and similarity of the two types of system overloaded response behaviors is extracted; secondly, according to the behavior feature field set, the aggregation processing of each type of overloaded response behavior is carried out based on the mapping strength, response coupling degree, and repeated matching number level, thereby screening the behavior combination with stable consistency characteristics in multiple dimensions, and thus forming a high-credibility overloaded response mapping relationship; based on this, the overloaded response mapping relationship constructed by the feature field alignment and multi-dimensional aggregation mechanism can truly reflect the overloaded response coordination logic between the battery management system and the whole machine controller, and provide a mapping basis with clear structure and sufficient data support for the system cascade control strategy.

[0050] In some embodiments, according to the overloaded response mapping relationship, the protection configuration parameters in the battery management system and the protection control parameters in the whole machine controller are uniformly calibrated to obtain a parameter configuration set for jointly judging the overload state, including steps S401 to S403.

[0051] Step S401, field reconstruction processing is performed on the protection configuration parameters in the battery management system to obtain a first intermediate parameter set containing a protection threshold field and an action time sequence field.

[0052] The protection threshold field represents various physical quantity limit parameter fields in the battery management system for judging whether the overload state is reached, so as to define that the key physical quantities such as current, voltage, and temperature are considered normal or abnormal within a certain numerical range.

[0053] The action timing field represents the time control parameter field in the battery management system related to the protection control behavior, to describe the time characteristics in the response process of the protection mechanism, such as the start delay, action duration, and repeated trigger interval.

[0054] Optionally, first, various parameters inside the battery management system for identifying and responding to the overload state are extracted, including the set threshold values of physical quantities such as voltage, current, and temperature, and the action-related settings such as response delay, maintenance duration, and retry number corresponding to these set threshold values. Furthermore, since different parameters differ in setting methods, numerical units, and effective ranges, they need to be converted to a uniform scale and formatted, so that all parameters have consistent expression standards in structure. Subsequently, the normalized parameters are divided into fields according to their action types, the parameters for directly determining whether to exceed the limit are arranged into the protection threshold field, and the parameters for controlling the response timing logic are arranged into the action timing field. Based on this, the first intermediate parameter set containing the protection threshold field and the action timing field is obtained, which structurally represents the core judgment basis of the battery management system for identifying the overload state and the corresponding action logic description.

[0055] In step S402, the protection control parameters in the whole-machine controller are logically structured and extracted to obtain the second intermediate parameter set containing the control instruction range field and the trigger boundary field.

[0056] The control instruction range field represents the parameter field in the whole-machine controller for defining the action range of various protection control behaviors, to limit the maximum or minimum range of control operations such as power output, load capacity, or running mode switching.

[0057] The trigger boundary field represents the judgment threshold field in the whole-machine controller for determining whether to trigger a certain protection control behavior, to set the running state of the whole-machine controller under which the corresponding control logic should be started, such as the action start threshold, execution time window, and the like.

[0058] Optionally, first, the various protection control behaviors in the whole-machine controller related to the overload state are analyzed, such as load switching, power limiting, running mode changing, and the like, and further the logical structures of the input conditions, judgment thresholds, and feedback mechanisms corresponding to the protection control behaviors are disassembled and extracted one by one, and then classified according to the control content. Specifically, the parameters for limiting the action range of the protection control behaviors are arranged into the control instruction range field, and the judgment conditions for triggering the protection control behaviors are arranged into the trigger boundary field. Based on this, the second intermediate parameter set containing the control instruction range field and the trigger boundary field is obtained, which structurally represents the core judgment basis of the whole-machine controller for identifying the overload state and the boundary setting of the control strategy.

[0059] In step S403, the first intermediate parameter set and the second intermediate parameter set are subjected to field matching according to the overload response mapping relationship, to obtain a parameter configuration set for jointly judging the overload state.

[0060] Optionally, the first intermediate parameter set and the second intermediate parameter set are subjected to field matching with reference to the overload response mapping relationship, to thereby construct a unified parameter configuration set to support joint judgment of the overload state. Specifically, according to the overload response behaviors reflected by the overload response mapping relationship that there is a mapping relationship between the battery management system and the whole machine controller, the judgment conditions relied on by each group of overload response behaviors and the key parameter fields involved in the control logic are identified, and on this basis, the protection threshold field, the action timing field, the control instruction range field and the trigger boundary field corresponding to each group of overload response behaviors are extracted; thereby, based on the field name, the parameter type and the action direction, the corresponding fields in the first intermediate parameter set and the second intermediate parameter set are compared one by one for each group of overload response behaviors, to thereby establish a field matching relationship that meets the consistency of response behavior logic; further, the parameter fields that have passed the matching are merged, reconstructed and jointly expressed, to thereby obtain corresponding joint fields, so as to obtain a parameter configuration set that is structurally unified, logically closed-loop and can support cross-system overload identification and response according to each joint field.

[0061] In addition, in the matching process, if multiple fields that have both a cause-and-effect relationship in behavior logic and an associated boundary in parameter setting are identified, and these fields are integrated into a unified judgment item to be used as a whole for matching analysis with other fields or other field groups.

[0062] In the above embodiment, first, the field reconstruction processing of the protection configuration parameters in the battery management system is performed to obtain the first intermediate parameter set, to thereby obtain the protection threshold field and the action timing field that have comparability; further, the logic structure disassembly and extraction processing of the protection control parameters in the whole machine controller is performed to obtain the second intermediate parameter set, to thereby obtain the control instruction range field and the trigger boundary field that have comparability; further, the two intermediate parameter sets are subjected to field matching according to the overload response mapping relationship, to thereby construct a unified parameter configuration set that can be used for joint judgment of the overload state by the two systems; based on this, by realizing field-level fusion of the battery system and the whole machine controller at the parameter structure and response logic level, the overload determination basis with cross-system consistency is constructed, and the coordination and consistency control capability of the system-level overload identification is enhanced.

[0063] In some embodiments, the parameter configuration set is subjected to synchronization coordination to obtain an overload protection control instruction, including steps S501 to S502.

[0064] Step S501, the joint fields in the parameter configuration set are integrated based on the joint decision logic and response rule to obtain a control logic mapping structure for describing the coordination relationship between the battery management system and the whole machine controller.

[0065] The control logic mapping structure represents a relationship set of joint decision logic and corresponding response rules between the battery management system and the whole machine controller in a unified logical structure, and is used to describe how the battery management system and the whole machine controller coordinate the judgment results and trigger the protection control behavior under the same heavy load judgment condition.

[0066] Optionally, to realize the response coordination of the battery management system and the whole machine controller in the heavy load state, a unified control logic mapping structure needs to be constructed based on the joint fields in the parameter configuration set. Specifically, first, the joint decision logic embodied by each group of joint fields is identified, including the control function classification of each group of joint fields in the control strategy, the corresponding response object, and the action direction in the system linkage and other logical conditions. Then, the protection control behaviors that the battery management system and the whole machine controller should perform respectively under the premise of the joint decision logic are sorted out in combination with the response rules of each group of joint fields, and these logical conditions and protection control behaviors are organized into mapping entries according to the logical structure of “joint decision logic-response rule”. For example, when the battery current exceeds a certain set threshold and the whole machine controller judges that the system power is in the high load interval, the battery management system should perform current limiting operation, and the whole machine controller should perform brake load reduction operation at the same time. At this time, the logical structure of “joint decision logic-response rule” is expressed as a complete mapping relationship. Based on this, the mapping entries corresponding to each group of joint fields are summarized and sorted out by this processing method, so as to establish a control logic mapping structure with complete joint decision logic and response rules, for describing the response coordination mode of the double systems under the same heavy load judgment condition.

[0067] Step S502, the battery management state and the whole machine control state in the current running period are jointly analyzed according to the control logic mapping structure to obtain a heavy load protection control instruction containing the control object type, the trigger mode and the response priority.

[0068] The battery management state represents the running state set of the battery management system in the current running period, including the real-time expression of various electrical parameters, protection states and control flags; the whole machine control state represents the comprehensive expression of the control execution state, the task priority state and the system load level of the whole machine controller in the current running period, and other control decision related parameters.

[0069] Optionally, firstly, state data reflecting the battery management state in the current operation cycle is collected from the battery management system, such as the operation index value on the battery side, the protection action state, and the execution history flag, and state data reflecting the whole machine control state in the current operation cycle is collected from the whole machine controller, such as the load level on the whole machine side, the control mode state, and the feedback identifier, and the state data is standardized and converted to adapt to the input field format of the control logic mapping structure. Then, the mapping entries defined in the control logic mapping structure are matched one by one with the state data as the input, it is searched which joint field joint determination logic is established under the current battery management state and whole machine control state, and the corresponding response rule is triggered according to the matching result.

[0070] Furthermore, after judging that the response rule meets the triggering condition, the basic constituent elements of the control instruction, i.e., the control object type, the triggering mode, and the response priority, are further extracted, wherein: the control object type is used to define that the control instruction should act on the battery system, the whole machine system, or both, and to define the instantiated objects corresponding to the systems acted on, such as the battery current limiting class, the whole machine power reduction class, the linkage voltage limiting class, etc.; the triggering mode indicates whether the control instruction is single triggering, condition holding triggering, or nested linkage triggering; the response priority is used to sort and control the execution order when multiple control instructions meet the triggering condition at the same time. Finally, after all the control instruction constituent elements are determined, they should be packaged into a standardized overload protection control instruction structure to ensure the integrity, hierarchy, and clear division of the execution path when the control instruction is issued.

[0071] In the above embodiment, firstly, the control logic mapping structure capable of representing the response coordination and dependency relationship between the battery management system and the whole machine controller is constructed according to the integration processing of the joint fields in the parameter configuration set based on the joint determination logic and the response rule; secondly, the battery management state and the whole machine control state in the current operation cycle are jointly analyzed according to the control logic mapping structure, thereby generating the overload protection control instruction with the control object type, the triggering mode, and the response priority. Based on this, by constructing the control logic mapping structure for cross-system joint control and generating complete instructions in combination with real-time state driving, the consistency of response judgment and the synchronicity of control execution of the battery management system and the whole machine controller in the overload scenario are realized.

[0072] In some embodiments, the integration processing of the joint fields in the parameter configuration set based on the joint determination logic and the response rule is performed to obtain the control logic mapping structure for describing the coordination relationship between the battery management system and the whole machine controller, including steps S601 to S603.

[0073] Step S601, the joint decision logic of each group of joint fields in the parameter configuration set is classified in multiple dimensions of control dimension, response object and action direction, to obtain a coordination field set representing the execution path difference between the battery management system and the whole machine controller.

[0074] Wherein, the control dimension represents the parameter category or control function classification corresponding to the joint field in the control decision logic, for example, a certain joint field belongs to the current decision class, the temperature protection class or the power regulation class or any combination of control dimensions.

[0075] Wherein, the response object represents the target system responsible for executing the corresponding protection control behavior after the joint decision logic is established, for example, the protection control behavior is executed by the battery management system, the whole machine controller, or the two systems cooperatively.

[0076] Wherein, the action direction represents the execution path direction corresponding to the control decision logic, for example, the protection control behavior is outward action (such as output current limiting), inward feedback (such as state updating), or cross-system linkage (such as triggering whole machine power limiting).

[0077] Optionally, based on each group of joint fields in the parameter configuration set, the joint decision logic reflected thereby is classified in multiple dimensions of control dimension, response object and action direction, to accurately extract the execution path difference between the battery management system and the whole machine controller in the heavy load response control. Specifically, first, the belonging category of the parameters involved in each group of joint fields in the control decision logic is analyzed, that is, it is determined that it belongs to which control function in the physical index, for example, it is used to represent the control variables such as current, voltage, temperature or power, and it is classified into the corresponding control dimension, thereby realizing the standardized expression of the joint field in the parameter type level. Secondly, according to the actual action subject of the protection control behavior driven by the joint field in the system structure, it is judged whether the response object belongs to the battery management system or the whole machine controller, or whether it constitutes the linkage execution between the two, so as to determine the functional role of the joint field in the control decision logic. Finally, combined with the action direction of the joint field in the control decision logic, it is determined whether it is used for output behavior, feedback behavior or cross-module trigger behavior, thereby determining the execution path direction corresponding to the joint field.

[0078] Based on this, through the above multi-dimensional classification, the joint field originally embedded in the complex control decision logic can be structurally combed, so that the parameter attribute, action target and path positioning of each joint field are redefined as the corresponding coordination field, and further each coordination field is composed into a coordination field set. The coordination field set can completely express the execution path difference between the battery management system and the whole machine controller in the control dimension, response object and action direction dimensions under the heavy load control scene.

[0079] Step S602, according to the response relationship between each coordination field in the coordination field set, each coordination field is subjected to rule induction processing based on response rule combination, and an associated field set representing the response linkage relationship between the battery management system and the whole machine controller is obtained.

[0080] Optionally, based on the completed multi-dimensional classification of the coordination field set, the rule relationship between different coordination fields in the overload response behavior is identified, and rule induction processing is performed accordingly to construct the response linkage relationship between the battery management system and the whole machine controller with logical continuity. Specifically, first, the response timing and trigger condition of each coordination field in the control decision logic are combined to analyze whether there is a stable response linkage relationship between each coordination field, for example, whether the determination of a coordination field is established constitutes the premise of the response trigger of another coordination field, or whether a higher level of protection control behavior can be triggered when multiple coordination field combinations are met. On this basis, all joint fields with such response linkage relationship are induced and sorted, i.e. according to the logical structure of the response linkage relationship, different types such as sequential response, conditional nesting or interlocking linkage are classified to constitute the response linkage structure between the coordination fields. Subsequently, the above response linkage structure is reconstructed according to the response rule combination mode, i.e. the response timing, trigger condition and action range of each response rule involved in the response linkage structure are embedded in the field description to form the corresponding associated field. Based on this, each associated field is composed of an associated field set, and the associated field set is a logical extension of the coordination field set, which not only contains the response linkage relationship between the coordination fields, but also carries the linkage logic between the cross-system overload response behaviors.

[0081] Step S603, field layering is performed on the coordination field set and the associated field set to obtain a control logic mapping structure for describing the coordination relationship between the battery management system and the whole machine controller.

[0082] Optionally, first, the coordination fields in the coordination field set are grouped according to their control dimensions, response objects, and action directions to determine which fields are in the control entry of different systems in the logical structure and which fields assume the function of local judgment or collaborative judgment, thereby establishing a basic hierarchical framework of the control logic mapping structure. Then, in the basic hierarchical framework, the associated fields in the associated field set that have response linkage relationships are arranged vertically according to their front-back dependency relationship to form a field linkage path structure oriented by response priority order; at the same time, to avoid conflicts or overlaps between different field linkage path structures, the field groups with independent response relationships should be organized side by side in the horizontal layer to have the expression ability of control parallelism. Based on this, the finally formed control logic mapping structure not only realizes the ordered organization of multi-source fields in the logical order and system level, but also has the structural characteristics of being analyzable, extensible, and executable, and can support the efficient implementation of complex linkage control mechanisms across systems under unified logic.

[0083] In the above embodiment, first, the coordination field set that can distinguish the execution path difference between the battery management system and the machine controller is extracted according to the multi-dimensional classification of the control dimensions, response objects, and action directions of the joint fields; second, the associated field set that describes the response linkage relationship between systems is extracted according to the rule induction processing of the response linkage relationship between the coordination fields; third, the control logic mapping structure with logical order and system level is constructed according to the hierarchical organization structure of the coordination fields and the associated fields; based on this, through the system classification, dependency induction, and structured expression of the parameter configuration set, the complex linkage control mechanism across systems can be efficiently implemented under unified logic.

[0084] In some embodiments, the battery management state and the machine control state in the current running period are jointly analyzed according to the control logic mapping structure to obtain the overload protection control instruction containing the control object type, the trigger mode, and the response priority, including steps S701 to S704.

[0085] Step S701, according to the coordination fields representing the execution path difference between the battery management system and the machine controller in the control logic mapping structure, combining the battery management state and the machine control state in the current running period, the state classification of each coordination field is performed to obtain each control object type.

[0086] Optionally, the state data in the current operation cycle is collected from the battery management system and the whole machine controller respectively, and then the state data is mapped and matched with each coordination field in the coordination field set reflected by the control logic mapping structure at the field level. Specifically, in the matching process, the control dimension, response object and action direction corresponding to the coordination field are combined to determine whether the current battery management state and the whole machine control state satisfy the specific joint determination logic, and whether the coordination field is in the active state is determined accordingly. Subsequently, all coordination fields in the active state are classified according to their belonging system and control action, thereby generating each control object type for the control task in the current operation cycle, that is, not only distinguishing which system dominates or participates in the control task and which instantiation object it corresponds to, but also explicitly determining the response relationship between each system and its execution boundary under the current battery management state and the whole machine control state, thereby realizing the accurate projection of the control logic from the static mapping structure to the dynamic control object.

[0087] In step S702, the state change of each control object type is identified according to the response relationship between different coordination fields in the control logic mapping structure, and the trigger mode corresponding to each control object type is obtained.

[0088] Optionally, first, the state data corresponding to each control object type is obtained, and the change characteristics of the state data are analyzed, such as whether it is changed from a static determination state to a trigger state, whether it is in a boundary fluctuation interval, whether it satisfies a specific trigger condition, etc., thereby obtaining the state change result of each control object type. Further, the state change results are aligned with each coordination field in the coordination field set reflected by the control logic mapping structure, so as to identify whether each control object type is in an independent trigger, joint drive or other state change link in the state change link constructed according to the execution path difference relationship represented by the coordination field. For example, if the state change link of a control object type is completely driven by the system field and the state changes stably, it is marked as an independent trigger mode; if it depends on the response of another field, it is marked as a linkage trigger mode; if it needs to satisfy a specific time maintenance condition or a state maintenance condition, it should be marked as a delay trigger mode or a continuous trigger mode. Based on this, not only the state change link of each control object type in the logic structure can be determined, but also the protection control behavior can be behaviorally abstracted with the response mode as the dimension, thereby obtaining the trigger mode corresponding to each control object type.

[0089] The state change link constructed according to the execution path difference relationship represented by the coordination field indicates that the state transition path structure of the control object type in the overload protection process is constructed based on the logical and timing difference between the battery management system and the whole machine controller in the response process.

[0090] Step S703, according to the association field in the control logic mapping structure reflecting the response linkage relationship between the battery management system and the overall controller, the priority of each control object type and the corresponding trigger mode is sorted to obtain the response priority corresponding to each control object type.

[0091] Optionally, according to each association field in the association field set reflected by the control logic mapping structure, the response linkage relationship thereof is used to sort the priority of the control object type and the corresponding trigger mode, so as to ensure that each control object type has a clear execution order in the actual overload protection control process. Specifically, first, the dependency relationship of each control object type in the logical structure with other control object types is identified, for example, whether there is a control object type that responds first as a trigger premise, or whether its execution behavior must wait for other control object types to complete the corresponding state transition. In order to identify such dependency relationship, each association field is matched with the identified control object type and trigger mode one by one, to obtain the response sequence of each control object type based on the corresponding trigger mode. Further, the response sequence of each control object type is structured and analyzed, for example, if the trigger mode of a control object type is dependent on multiple other control object types, it means that it needs to be executed first, thereby giving it a higher response priority; on the contrary, if its trigger mode needs to be based on the execution result of other control object types, its response priority needs to be lowered. Finally, through the priority sorting process, the response priority corresponding to each control object type is obtained, thereby forming a response priority set reflecting the overall control coordination mechanism of the system. Step S704, combining and mapping the control object type, trigger mode and response priority according to the control format to obtain the overload protection control instruction.

[0092] Optionally, the control object type field, the trigger mode field and the response priority field are logically integrated, and through field combination and formatting processing, a control instruction entry with clear action target, response timing and execution priority is generated. In addition, in this process, it is necessary to ensure that the matching relationship between different dimensions of information is complete and consistent, so as to avoid behavior conflict or response ambiguity during instruction execution; at the same time, the integrity of the generated result needs to be verified to ensure that each type of field identified is effectively mapped to the final control instruction, and each field follows the system preset execution specification in structure. Finally, the obtained overload protection control instruction will be used as the direct input basis for the collaborative execution of the battery management system and the overall controller, to support the system to perform orderly and coordinated protection response under complex load conditions.

[0093] In the above embodiment, firstly, the coordination field in the control logic mapping structure is classified according to the current battery management state and the overall machine control state, so as to determine the types of each control object; secondly, the state change of each control object type is identified according to the response relationship between the coordination fields, so as to determine the trigger mode to be adopted by each control object under the current condition; thirdly, the control objects and the trigger modes are prioritized according to the response linkage relationship reflected by the association field in the control logic mapping structure, so as to ensure that the control instructions have a clear execution sequence in a multi-response scenario; fourthly, the control object type, the trigger mode and the response priority are structurally combined and processed, so as to generate complete and executable overload protection control instructions; based on this, by identifying and structurally packaging multi-dimensional control information, efficient generation and consistent issuance of linkage control instructions between the battery management system and the overall machine controller under a complex operating scenario are realized.

[0094] The present disclosure at least one embodiment also provides an intelligent battery management system for overload protection. Figure 2 A schematic block diagram of an intelligent battery management system for overload protection is provided for at least one embodiment of the present disclosure; the intelligent battery management system for overload protection comprises a first analysis module 201, a second analysis module 202 and a generation module 203.

[0095] Specifically, the first analysis module 201 can be used to implement Figure 1 the step S101 shown; the second analysis module 202 can be used to implement Figure 1 the step S102 shown; and the generation module 203 can be used to implement Figure 1 the step S103 shown. Therefore, the specific description of the functions that can be implemented by the first analysis module 201 can refer to the related description of the step S101 in the above embodiment of the intelligent battery management method for overload protection, the specific description of the functions that can be implemented by the second analysis module 202 can refer to the related description of the step S102 in the above embodiment of the intelligent battery management method for overload protection, and the specific description of the functions that can be implemented by the generation module 203 can refer to the related description of the step S103 in the above embodiment of the intelligent battery management method for overload protection, and the repeated parts will not be described herein. In addition, the intelligent battery management system for overload protection can achieve similar technical effects as the foregoing intelligent battery management method for overload protection, which will not be described herein.

[0096] Optionally, the specific description of the functions that can be implemented by the first analysis module 201 can also refer to the related description of the steps S201 to S203 in the above embodiment of the intelligent battery management method for overload protection, and can also refer to the related description of the steps S301 to S302 in the above embodiment of the intelligent battery management method for overload protection.

[0097] Optionally, the specific description about the functions that the second analysis module 202 can implement can also refer to the related description of steps S401 to S403 in the above-mentioned embodiments of the overload protection intelligent battery management method.

[0098] Optionally, the specific description about the functions that the generation module 203 can implement can also refer to the related description of steps S501 to S502 in the above-mentioned embodiments of the overload protection intelligent battery management method, and also can refer to the related description of steps S601 to S603 in the above-mentioned embodiments of the overload protection intelligent battery management method, and also can refer to the related description of steps S701 to S704 in the above-mentioned embodiments of the overload protection intelligent battery management method.

[0099] It should be noted that, in at least one embodiment of the present disclosure, the overload protection intelligent battery management system can include more or fewer circuits or units, and the connection relationship between the various circuits or units is not limited, and can be determined according to actual needs. The specific constituting manner of each circuit or unit is not limited, which can be constituted by an analog device according to the circuit principle, or can be constituted by a digital chip, or constituted in other applicable manners. For example, the overload protection intelligent battery management system can be realized in a hardware, software or combination of hardware and software manner, and the present disclosure does not make specific limitations in this regard.

[0100] At least one embodiment of the present disclosure provides a computer device, including: a memory for storing computer executable instructions; a processor for running the computer executable instructions; wherein the computer executable instructions are implemented when the processor is running one or more steps of the overload protection intelligent battery management method according to any embodiment of the present disclosure.

[0101] At least one embodiment of the present disclosure provides a computer readable storage medium, wherein the computer readable storage medium stores computer executable instructions, and the computer executable instructions are executed by the processor to implement one or more steps of the overload protection intelligent battery management method according to any embodiment of the present disclosure.

[0102] The flow diagrams and block diagrams in the drawings are illustrations of architectures, functional processes and operations for implementations of methods and systems in accordance with various embodiments of the present disclosure. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or combinations of special purpose hardware and

[0103] The units described in the embodiments of the present disclosure can be implemented by software, or by hardware. In some cases, the name of the unit does not constitute a limitation on the unit itself.

[0104] The above description is merely illustrative of the exemplary embodiments of the present disclosure and the principles of the technology involved. It should be understood by those skilled in the art that the disclosed scope of the present disclosure is not limited to the technical solutions formed by the specific combinations of the above technical features, and also covers other technical solutions formed by the combinations of the above technical features or equivalent features, without departing from the above disclosed concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features disclosed in the present disclosure (but not limited to) having similar functions.

[0105] In addition, although each operation is depicted in a particular order, this should not be understood as requiring the operations to be performed in the particular order shown or in sequential order. In some circumstances, multitasking and parallel processing can be advantageous. Similarly, although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments can also be combined in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented in multiple embodiments. The scope of the present disclosure is defined by the appended claims.

[0106] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

[0107] For the disclosure, there are several points to note: the drawings of the embodiments of the disclosure only relate to the structures involved in the embodiments of the disclosure, and other structures can be referred to the general design; in the case of no conflict, the embodiments of the disclosure and the features in the embodiments can be combined to obtain new embodiments; the above is only a specific implementation of the disclosure, but the protection scope of the disclosure is not limited to this, and the protection scope of the disclosure should be subject to the protection scope of the claims.

Claims

1. A heavy load protected intelligent battery management method, characterized in that, The method comprises: correlating analysis of historical operation data collected by a battery management system and protection signals output by a machine controller, to obtain a heavy load response mapping relationship between the battery management system and the machine controller; calibrating protection configuration parameters in the battery management system and protection control parameters in the machine controller according to the heavy load response mapping relationship, to obtain a parameter configuration set for jointly judging a heavy load state; synchronizing and coordinating the parameter configuration set to obtain a heavy load protection control instruction for coordinating heavy load response behaviors of the battery management system and the machine controller.

2. The method of claim 1, wherein, The correlating analysis of the historical operation data collected by the battery management system and the protection signals output by the machine controller to obtain the heavy load response mapping relationship between the battery management system and the machine controller comprises: extracting features from each physical quantity change sequence in the historical operation data to obtain a waveform mode set representing various heavy load response behaviors of the battery management system; aligning the waveform mode set in time and classifying trigger sources according to protection trigger time points and signal control types in the protection signals, to obtain a time sequence identification relationship table containing mapping relationships between various heavy load response behaviors of the battery management system and various heavy load response behaviors of the machine controller; performing behavior consistency analysis on various heavy load response behaviors of the battery management system and the machine controller according to the time sequence identification relationship table, to obtain the heavy load response mapping relationship between the battery management system and the machine controller.

3. The method of claim 2, wherein, The behavior consistency analysis on various heavy load response behaviors of the battery management system and the machine controller according to the time sequence identification relationship table to obtain the heavy load response mapping relationship between the battery management system and the machine controller comprises: aligning behavior feature fields of various heavy load response behaviors of the battery management system and the machine controller according to the time sequence identification relationship table, to obtain a behavior feature field set representing amplitude change, time sequence offset and execution structure; performing aggregation processing on various heavy load response behaviors based on mapping strength level, response coupling degree level and repeated matching number level according to the behavior feature field set, to obtain the heavy load response mapping relationship between the battery management system and the machine controller.

4. The method of claim 1, wherein, The calibrating protection configuration parameters in the battery management system and protection control parameters in the machine controller according to the heavy load response mapping relationship to obtain a parameter configuration set for jointly judging a heavy load state comprises: performing field reconstruction processing on the protection configuration parameters in the battery management system to obtain a first intermediate parameter set containing a protection threshold field and an action time sequence field; performing logic structure disassembly and extraction processing on the protection control parameters in the machine controller to obtain a second intermediate parameter set containing a control instruction range field and a trigger boundary field; According to the heavy load response mapping relationship, field matching is performed on the first intermediate parameter set and the second intermediate parameter set to obtain a parameter configuration set used for jointly judging a heavy load state.

5. The method of claim 1, wherein, The synchronization coordination on the parameter configuration set comprises: According to the control logic mapping structure, joint analysis is performed on the battery management state and the whole machine control state in a current running period to obtain a heavy load protection control instruction containing a control object type, a trigger mode and a response priority. The integration processing on each group of joint fields in the parameter configuration set based on the joint determination logic and the response rule comprises:

6. The method of claim 5, wherein, The multi-dimensional classification of the joint determination logic of each group of joint fields in the parameter configuration set in a control dimension, a response object and an action direction is performed to obtain a coordination field set representing an execution path difference between the battery management system and the whole machine controller; According to the response relationship between each coordination field in the coordination field set, rule induction processing is performed on each coordination field based on a response rule combination to obtain an association field set representing a response linkage relationship between the battery management system and the whole machine controller; The field layering is performed on the coordination field set and the association field set to obtain a control logic mapping structure used for describing a coordination relationship between the battery management system and the whole machine controller. The joint analysis on the battery management state and the whole machine control state in a current running period according to the control logic mapping structure comprises:

7. The method of claim 5, wherein, According to the coordination field representing the execution path difference between the battery management system and the whole machine controller in the control logic mapping structure, state classification is performed on each coordination field to obtain each control object type in combination with the battery management state and the whole machine control state in the current running period; According to the response relationship between different coordination fields in the control logic mapping structure, state change identification is performed on each control object type to obtain a trigger mode corresponding to each control object type; According to the association field representing the response linkage relationship between the battery management system and the whole machine controller in the control logic mapping structure, priority sorting processing is performed on each control object type and the corresponding trigger mode to obtain a response priority corresponding to each control object type; The control object type, the trigger mode and the response priority are combined and mapped according to a control format to obtain a heavy load protection control instruction. The system comprises:

8. A heavy load protected intelligent battery management system characterized by, ​ The first analysis module is configured to perform correlation analysis on historical operation data collected by the battery management system and protection signals output by the whole-machine controller, and obtain a heavy-load response mapping relationship between the battery management system and the whole-machine controller. The second analysis module is configured to perform unified calibration on protection configuration parameters in the battery management system and protection control parameters in the whole-machine controller according to the heavy-load response mapping relationship, and obtain a parameter configuration set for jointly judging a heavy-load state. The generation module is configured to perform synchronization coordination on the parameter configuration set, and obtain a heavy-load protection control instruction for coordinating heavy-load response behaviors of the battery management system and the whole-machine controller.

9. A computer device, comprising: The memory is configured to store computer executable instructions. The processor is configured to execute the computer executable instructions; and when the computer executable instructions are executed by the processor, the heavy-load protection intelligent battery management method in any one of claims 1 to 7 is implemented. The computer readable storage medium is configured to store computer executable instructions; and when the computer executable instructions are executed by the processor, the heavy-load protection intelligent battery management method in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that, ​

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