A lithium battery and super capacitor management system

Abstract

The present application relates to the technical field of energy storage element management, and discloses a lithium battery and super capacitor management system, comprising an energy storage module, a plurality of super capacitors and a plurality of lithium batteries, a coordination module for receiving the power allocation strategy output by the energy prediction module and coordinating the power of the plurality of super capacitors and the plurality of lithium batteries according to the power allocation strategy, and an energy prediction module provided with an energy storage monitoring unit, a hierarchical feedback unit and an automatic tuning unit, wherein the energy storage data of the plurality of super capacitors and the plurality of lithium batteries are predicted by the energy storage monitoring unit, the prediction result is output to the hierarchical feedback unit, the energy storage level of the energy storage module is identified by the hierarchical feedback unit, the power switching between the lithium battery and the super capacitor is adjusted in advance, and finally the total power prediction value of the super capacitor and the power allocation result are optimized by the automatic tuning unit, thereby improving the power transmission efficiency of the super capacitor and the lithium battery, and reducing the influence of power surplus and capacity overload on the system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage element management, and discloses a lithium battery and super capacitor management system. BACKGROUND

[0002] The existing lithium battery and super capacitor hybrid system has defects in dynamic power distribution, life management and response speed, the lithium battery is easily damaged when subjected to large voltage charging and discharging, the super capacitor can quickly respond to instantaneous power demand, but has low energy density, and is difficult to meet long endurance demand when used alone, the traditional system lacks fine monitoring of the health state of the energy storage unit, resulting in mismatch between the energy distribution strategy and the actual performance of the equipment, accelerating the aging risk, the early hybrid energy storage system mainly uses energy management methods based on experience or simple optimization, which is difficult to adapt to random loads and complex working conditions, the high material cost and complex integration process of the super capacitor limit its large-scale application, and the traditional hybrid system has efficiency loss when recovering energy, lacks a dynamic braking resistor adjustment mechanism, and causes energy waste. SUMMARY

[0003] This section aims to summarize some aspects of the embodiments of the present application and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of the specification to avoid obscuring the purpose of this section, abstract and title, and such simplifications or omissions cannot be used to limit the scope of the present application.

[0004] To solve the above technical problems, the main purpose of the present application is to provide a lithium battery and super capacitor management system, comprising:

[0005] The energy storage module, the coordination module and the energy prediction module, the energy storage module comprises a plurality of super capacitors and a plurality of lithium batteries;

[0006] The coordination module is used for receiving the energy distribution strategy output by the energy prediction module, and distributing the energy of the plurality of super capacitors and the plurality of lithium batteries according to the energy distribution strategy;

[0007] The energy prediction module sets an energy storage monitoring unit, a hierarchical feedback unit and an automatic tuning unit, predicts the energy storage data of the plurality of super capacitors and the plurality of lithium batteries through the energy storage monitoring unit, outputs the prediction result to the hierarchical feedback unit, identifies the energy storage level of the energy storage module by the hierarchical feedback unit, and adjusts the energy switching between the lithium battery and the super capacitor in advance, and finally optimizes the total power prediction value of the super capacitor and the energy distribution result by the automatic tuning unit.

[0008] As a preferred scheme of the lithium battery and super capacitor management system of the present application, wherein:

[0009] The plurality of lithium batteries comprises an emergency area, a standby area and a dynamic switching area;

[0010] The emergency area includes a plurality of lithium batteries, which are used to dynamically call the lithium battery group in the emergency area to supplement power when the super capacitor power is insufficient during the switching acceleration stage;

[0011] The dynamic switching area is arranged between the emergency area and the standby area, and is used to buffer the power flow from the standby area to the emergency area;

[0012] The other end of the standby area is connected to the power grid, and is used to receive power from the power grid.

[0013] As a preferred scheme of the lithium battery and super capacitor management system, wherein:

[0014] The coordination module is provided with a dynamic braking resistor adjusting unit, and the braking resistor includes a plurality of gears. If the coordination module receives the power allocation overflow output by the energy prediction module, the braking resistor value is dynamically adjusted, and the overflow power is consumed by the braking resistor;

[0015] If the total charging power of the plurality of super capacitors is greater than the total capacity of the plurality of lithium battery groups, the coordination module dynamically adjusts the braking resistor value, and the overflow power is consumed by the braking resistor.

[0016] As a preferred scheme of the lithium battery and super capacitor management system, wherein:

[0017] The energy storage monitoring unit is provided with a high-frequency ripple monitoring model and an equivalent series resistance identification model;

[0018] The high-frequency ripple monitoring model obtains the super capacitor charging and discharging ripple characteristics through a wideband voltage sensor, and obtains the super capacitor charging and discharging ripple energy distribution characteristics through wavelet packet decomposition, to generate a voltage waveform frequency band energy entropy value, and extract the ripple characteristic fingerprint from the voltage waveform frequency band energy entropy value.

[0019] The equivalent series resistance identification model injects a pseudo-random binary sequence excitation signal with controllable amplitude, and simultaneously calculates the equivalent series resistance of the super capacitor in real time through an adaptive forgetting factor;

[0020] The equivalent series resistance and the ripple characteristic fingerprint of the super capacitor are received through a double-channel deep residual network, and the super capacitor resistance and the output voltage ripple characteristics are captured through the double channel;

[0021] The first channel extracts the spatial features of the ripple characteristic fingerprint and the equivalent series resistance time sequence through a three-level convolutional layer, the second channel captures the time dependence through a gated recurrent unit, and outputs a fusion feature matrix through a cross-attention mechanism, to output a health state prediction value and a confidence.

[0022] As a preferred scheme of the lithium battery and super capacitor management system, wherein:

[0023] The energy storage monitoring unit further comprises a lithium battery partition monitoring system, which comprises a sub-area cooperative sensing and three-dimensional evaluation model;

[0024] The sub-area cooperative sensing comprises an emergency area configuration voltage sampling circuit and an integrated contact thermal sensitive film, which monitors the temperature mutation of the tab, and a dynamic switching area passes through a bidirectional power flow monitoring module to detect the bidirectional power impact of the dynamic switching area.

[0025] The three-dimensional evaluation model predicts the state of the lithium battery pack through a dynamic internal resistance cloud picture, battery thermal characteristics and power flow adaptation degree.

[0026] As a preferred scheme of the lithium battery and super capacitor management system, wherein:

[0027] The hierarchical feedback unit is configured with a double-way intelligent distribution interface in the emergency area, which is connected with the first super capacitor group and the second super capacitor group respectively, a bidirectional DC / DC converter cluster is arranged in the dynamic switching area for power bidirectional regulation, and a three-level power bus architecture is established, wherein the first-level bus emergency area is directly connected with the super capacitor group, the second-level bus dynamic switching area is interconnected with the emergency area, and the third-level bus standby area is connected with the power grid.

[0028] As a preferred scheme of the lithium battery and super capacitor management system, wherein:

[0029] The hierarchical feedback unit receives a plurality of super capacitor total power prediction values, and the automatic tuning unit corrects the plurality of super capacitor total power prediction values at the same time.

[0030] The corrected super capacitor total power prediction value is input into the automatic tuning unit, and the automatic tuning unit outputs a power allocation strategy.

[0031] As a preferred scheme of the lithium battery and super capacitor management system, wherein:

[0032] The power allocation strategy comprises:

[0033] If the plurality of super capacitor total power prediction values are greater than the emergency area, the bidirectional DC / DC converter cluster is switched to control the dynamic switching area to allocate the power flow to the emergency area.

[0034] If the plurality of super capacitor total power prediction values are less than or equal to the emergency area, the power flow is allocated from the emergency area to the plurality of super capacitors.

[0035] If the plurality of super capacitor total power prediction values are greater than the sum of the emergency area and the dynamic switching area, the bidirectional DC / DC converter cluster is switched to control the dynamic switching area to allocate the power flow to the emergency area, and the bidirectional DC / DC converter cluster is switched to control the power flow from the standby area to the dynamic switching area.

[0036] The power gap of the standby area is filled when the grid price is the lowest.

[0037] The hierarchical feedback unit is further provided with an energy storage redundancy circuit, if the total power prediction value of the plurality of supercapacitors is greater than the total energy of the emergency area and the dynamic switching area, the energy of the emergency area flows into the energy storage redundancy circuit, and the energy of the standby area is switched to the dynamic switching area, and the energy of the dynamic switching area is switched to the emergency area.

[0038] As a preferred scheme of the lithium battery and supercapacitor management system, wherein:

[0039] The automatic tuning unit receives a load curve, a real-time working condition and a supercapacitor health state prediction value, and corrects an actual energy allocation strategy.

[0040] The automatic tuning unit comprises a basic layer, a working condition correction layer and an emergency correction layer, the basic layer learns load period changes by using a neural learning network, the working condition correction layer constructs a multi-dimensional influence factor matrix, dynamically corrects actual power demand prediction values of the plurality of supercapacitors, and the emergency correction layer outputs a dynamic braking resistor conversion to a coordination module, and the coordination module adjusts the braking resistor.

[0041] As a preferred scheme of the lithium battery and supercapacitor management system, wherein:

[0042] The multi-dimensional influence factor matrix comprises a voltage fluctuation and a supercapacitor health state prediction value.

[0043] The energy flow direction is allocated by setting a composite power switch, and the composite power switch comprises a main channel, a redundancy channel and a node monitoring.

[0044] The present application has the following beneficial effects:

[0045] By partitioning lithium batteries and a multi-stage energy bus architecture, precise cooperation of supercapacitors and lithium batteries is achieved, the emergency area quickly supplements the instantaneous high power demand of supercapacitors, the dynamic switching area buffers energy flow, the standby area is connected to the grid to realize peak clipping and valley filling, a braking resistor dynamic adjustment unit is introduced, the resistance value range is automatically adjusted according to the energy overflow, and energy loss is reduced.

[0046] A high-frequency ripple monitoring model and an equivalent series resistance identification model are adopted, combined with a double-channel deep residual network, to realize real-time prediction of the health state of supercapacitors, avoid system failure caused by aging, and prolong the overall life by using a dynamic internal resistance cloud map, thermal characteristic analysis and other multi-dimensional data to early warn battery pack abnormalities.

[0047] The hierarchical feedback unit is combined with a three-level power bus architecture, dynamically allocates the power flow, automatically enables the backup area power grid to supplement energy when the super capacitor total power prediction value exceeds the emergency area capacity, optimizes the charging and discharging time sequence to match the time-of-use electricity price, reduces the operation cost, and automatically optimizes the unit through a neural learning network and a multi-dimensional influence factor matrix, analyzes the voltage fluctuation and the capacitor health state, and corrects the power prediction value in real time to adapt to complex working conditions. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. Among them:

[0049] Figure 1 The structure diagram of the lithium battery and super capacitor management system of the present application;

[0050] Figure 2 The collaborative work diagram of the lithium battery and super capacitor management system of the present application;

[0051] Figure 3 The flow chart of the multi-load operation of the lithium battery and super capacitor management system of the present application. DETAILED DESCRIPTION

[0052] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0053] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0054] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an independent or selective embodiment that excludes other embodiments.

[0055] As shown in Figure 1 A lithium battery and super capacitor management system, comprising:

[0056] energy storage module, coordination module and energy prediction module;

[0057] The energy storage module includes a plurality of supercapacitors and a plurality of lithium batteries;

[0058] The plurality of lithium batteries includes an emergency area, a standby area, and a dynamic switching area;

[0059] The emergency area includes a plurality of lithium batteries, which are used to dynamically call the lithium battery group in the emergency area to supplement power when the supercapacitor power is insufficient during the switching acceleration stage;

[0060] The dynamic switching area is arranged between the emergency area and the standby area, and is used to buffer the power flow from the standby area to the emergency area;

[0061] The other end of the standby area is connected to the power grid, and is used to receive power from the power grid.

[0062] A specific implementation method of an energy storage module includes:

[0063] The supercapacitor array adopts a modular parallel design, each group of supercapacitors is configured with an independent voltage equalization circuit and a temperature monitoring node, forming a distributed management network, which captures the charge and discharge ripple in real time through a wideband voltage sensor, extracts the ripple characteristic fingerprint through signal decomposition technology, and is used for health state evaluation.

[0064] Further, the emergency area is composed of high-rate lithium battery groups, which are directly connected to the supercapacitor array for instantaneous high-power power supply.

[0065] The dynamic switching area is located between the emergency area and the standby area, and a bidirectional DC / DC converter is deployed to realize the buffering and bidirectional transmission of energy flow.

[0066] The standby area is connected to the power grid and is configured with an intelligent charge and discharge interface to schedule the power grid energy according to the time-of-use electricity price strategy.

[0067] The intelligent charge and discharge interface supports bidirectional energy flow and integrates power quality monitoring function to adjust the grid-connected parameters in real time to match the grid demand.

[0068] The coordination module is used to receive the power allocation strategy output by the energy prediction module, and to allocate the power of the plurality of supercapacitors and the plurality of lithium batteries according to the power allocation strategy;

[0069] The coordination module is provided with a brake resistor dynamic adjustment unit, the brake resistor includes multiple gears, if the coordination module receives the power allocation overflow output by the energy prediction module, the brake resistor resistance value is dynamically adjusted, and the overflow power is consumed by the brake resistor;

[0070] If the total power of the plurality of supercapacitors is greater than the total capacity of the plurality of lithium batteries, the brake resistor resistance value is dynamically adjusted by the coordination module, and the overflow power is consumed by the brake resistor.

[0071] The function of the coordination module is equivalent to that of the control module, and the coordination module coordinates the multiple groups of supercapacitors and multiple groups of lithium batteries by receiving the power allocation strategy.

[0072] The coordination module establishes a communication link with the energy prediction module, receives the power allocation strategy in real time, then analyzes the logical rules in the power allocation strategy, generates specific control signals, and adjusts the energy flow between the supercapacitors and the lithium batteries in real time through the power switch matrix and the DC / DC converter cluster according to the requirements of the power allocation strategy.

[0073] Further, the coordination module adjusts the step resistance gear of the dynamic braking resistor, for example, high, medium and low gears, each gear corresponds to a different power overflow threshold range, and according to the overflow power, it is judged whether the total amount of supercapacitor charging exceeds the maximum energy storage capacity of the lithium battery, and at the same time the lithium battery cannot absorb the excess power, monitors the power overflow signal, identifies the overflow type, including strategy overflow or capacity overflow, automatically switches the braking resistor gear according to the overflow level, for example, the low gear consumes a small amount of overflow, and the high gear handles serious overflow, wherein the overflow level can include slight, moderate and serious, and the control braking resistor is connected to the circuit to convert the overflow power into heat energy consumption to avoid system overload.

[0074] The energy prediction module sets a energy storage monitoring unit, a hierarchical feedback unit and an automatic tuning unit, predicts the energy storage data of multiple groups of supercapacitors and multiple groups of lithium batteries through the energy storage monitoring unit, outputs the prediction results to the hierarchical feedback unit, identifies the energy storage level of the energy storage module, and adjusts the power switching between the lithium battery and the supercapacitor in advance, and finally optimizes the total power prediction value of the supercapacitor and the power allocation result by the automatic tuning unit.

[0075] The energy storage monitoring unit sets a high-frequency ripple monitoring model and an equivalent series resistance identification model;

[0076] The high-frequency ripple monitoring model obtains the supercapacitor charging and discharging ripple characteristics through a high-frequency sampling rate wide-band voltage sensor, decomposes the supercapacitor charging and discharging ripple energy distribution characteristics through a wavelet packet, generates voltage waveform frequency band energy entropy values, and extracts ripple characteristic fingerprints from the voltage waveform frequency band energy entropy values;

[0077] The equivalent series resistance identification model injects a pseudo-random binary sequence excitation signal with controllable amplitude, and simultaneously calculates the equivalent series resistance of the supercapacitor in real time through an adaptive forgetting factor;

[0078] The double-channel deep residual network receives the equivalent series resistance and ripple characteristic fingerprints of the supercapacitor, and captures the supercapacitor resistance and output voltage ripple characteristics through the double channels;

[0079] The first channel extracts ripple feature fingerprint and spatial features of equivalent series resistance time sequence through a three-level convolutional layer, the second channel captures time dependence through a gated recurrent unit, and a cross-attention mechanism is used to output a fusion feature matrix, and a health state prediction value and a confidence are output.

[0080] Exemplarily, the super capacitor charging and discharging ripple features are captured by a 100 kHz sampling rate wideband voltage sensor, and the energy distribution in the 0.1-10 MHz frequency band is extracted by combining the wavelet packet decomposition technology, which significantly improves the detection accuracy of high-frequency noise. Traditional ripple detection relies on low-pass filtering or simple peak detection, while the present application can accurately separate high-frequency ripple components through wideband coverage and wavelet packet decomposition, avoiding signal omission caused by frequency band limitation in traditional methods.

[0081] Compared with the fixed cutoff frequency filter circuit, the wavelet packet decomposition can flexibly adjust the frequency band energy analysis range according to the actual working condition, enhancing the adaptability of the system to complex working conditions.

[0082] The energy storage monitoring unit also includes a lithium battery partition monitoring system, which includes a sub-domain cooperative sensing and three-dimensional evaluation model;

[0083] The sub-domain cooperative sensing includes an emergency area configuration voltage sampling circuit and an integrated contact thermal sensitive film, which monitors the temperature mutation of the tab, and the dynamic switching area is monitored by a bidirectional power flow monitoring module to detect the bidirectional power impact of the dynamic switching area.

[0084] The three-dimensional evaluation model predicts the state of the lithium battery pack through dynamic internal resistance cloud map, battery thermal characteristics and power flow adaptation degree.

[0085] The hierarchical feedback unit is configured with a double-channel intelligent distribution interface in the emergency area, which is connected to the first super capacitor group and the second super capacitor group respectively, and a bidirectional DC / DC converter cluster is deployed in the dynamic switching area for power bidirectional regulation, establishing a three-level power bus architecture, wherein the first bus emergency area is directly connected to the super capacitor group, the second bus dynamic switching area is interconnected with the emergency area, and the third bus standby area is connected to the power grid.

[0086] The hierarchical feedback unit receives a plurality of super capacitor total power prediction values, and the automatic tuning unit corrects the plurality of super capacitor total power prediction values;

[0087] The corrected super capacitor total power prediction value is input into the automatic tuning unit, and the automatic tuning unit outputs an energy deployment strategy.

[0088] The energy deployment strategy includes:

[0089] If the total power prediction value of the plurality of supercapacitors is greater than the emergency area, the bidirectional DC / DC converter cluster is switched to control the dynamic switching area to allocate the power flow to the emergency area.

[0090] If the total power prediction value of the plurality of supercapacitors is less than or equal to the emergency area, the power flow is allocated from the emergency area to the plurality of supercapacitors.

[0091] If the total power prediction value of the plurality of supercapacitors is greater than the sum of the emergency area and the dynamic switching area, the bidirectional DC / DC converter cluster is switched to control the dynamic switching area to allocate the power flow to the emergency area, and the bidirectional DC / DC converter cluster is switched to control the standby area to allocate the power flow to the dynamic switching area.

[0092] The power gap of the standby area is filled when the grid price is the lowest.

[0093] The hierarchical feedback unit further provides an energy storage redundancy circuit. If the total power prediction value of the plurality of supercapacitors is greater than the sum of the emergency area and the dynamic switching area, the energy of the emergency area flows into the energy storage redundancy circuit, the energy of the standby area flows into the dynamic switching area, and the energy of the dynamic switching area flows into the emergency area.

[0094] As shown in Table 1, the district energy switching control table is shown in Table 1.

[0095] Table 1 District energy switching control table

[0096] Emergency zone -> super capacitor Power prediction value ≤ emergency zone available capacity Activate main channel IGBT, lock bidirectional DC / DC Dynamic switching zone -> emergency zone Power prediction value > emergency zone capacity Start bidirectional DC / DC boost mode Standby zone -> dynamic switching zone Low price valley period Synchronous control grid side PCS and DC / DC step-down module Energy storage redundancy circuit activation Total power prediction value > sum of emergency zone capacity and dynamic switching zone capacity Hierarchical cut-in redundancy channel, start forced air cooling system

[0097] Further, the automatic tuning unit receives a load curve, a real-time working condition, and a supercapacitor health state prediction value to correct an actual power allocation strategy.

[0098] The automatic tuning unit includes a basic layer, a working condition correction layer, and an emergency correction layer. The basic layer uses a neural learning network to learn load cycle changes. The working condition correction layer constructs a multi-dimensional influence factor matrix to dynamically correct actual power demand prediction values of the plurality of supercapacitors. The emergency correction layer outputs a dynamic braking resistor conversion to a coordination module, which adjusts the braking resistor.

[0099] The multi-dimensional influence factor matrix includes a voltage fluctuation and a supercapacitor health state prediction value.

[0100] By quantifying the influence degree of different dimension parameters on the system, a dynamic weight distribution mechanism is established to realize accurate correction of the prediction value. Voltage data as the basis, and supercapacitor health state, environmental parameters, etc. form a multi-dimensional coupling relationship, and the voltage fluctuation is decomposed into instantaneous fluctuation, periodic trend and abnormal mutation. Through standardization processing, the differences between the dimensions are eliminated. The mapping relationship between each dimension parameter and the power demand is established, and finally the contribution degree of each factor is adjusted according to the real-time system. The multi-dimensional influence factor matrix The specific expression of the construction logic is:

[0101]

[0102] wherein V(t) is a voltage state, including a voltage waveform frequency band energy entropy value Vi(t), a periodic trend component Vp(t) obtained by moving average decomposition, and a ripple energy distribution characteristic Va(t);

[0103] SOH(t) is a super capacitor health state prediction value, calculated based on an internal resistance ratio or a capacity attenuation model;

[0104] Specifically, the capacity attenuation model is used to evaluate the capacity attenuation degree of the super capacitor, and then calculate the super capacitor health state prediction value, and the input parameters come from the fine monitoring data of the energy storage monitoring unit on the super capacitor, specifically including:

[0105] The equivalent series resistance is obtained by an equivalent series resistance identification model, which injects a pseudo-random binary sequence excitation signal with controllable amplitude, and combines an adaptive forgetting factor to calculate the equivalent series resistance in real time. If the capacity of the super capacitor attenuates, the equivalent series resistance will increase.

[0106] The ripple characteristic fingerprint is extracted by a high-frequency ripple monitoring model. The charge and discharge ripple characteristics are obtained by a wideband voltage sensor, and the voltage waveform frequency band energy entropy value is generated by wavelet packet decomposition to form the ripple characteristic fingerprint. Capacity attenuation will cause changes in the charge and discharge ripple characteristics of the super capacitor.

[0107] E(t) is an environmental parameter, including temperature, humidity and other standardized values;

[0108] is a dynamic weight coefficient, wherein k=1,2,……,4, the dynamic weight distribution is scored by multi-dimensional state, and corrected by an LSTM network.

[0109] The correction amount of each super capacitor actual power demand prediction value is output by a multi-dimensional influence factor matrix, and the correction amount includes a single correction amount and a total correction amount, wherein the single correction amount is the product of a quantitative parameter and an adjustment coefficient and a parameter weight, wherein the quantitative parameter includes the prediction values of instantaneous fluctuation, periodic trend and abnormal mutation; the adjustment coefficient is set by a person skilled in the art according to actual demand and super capacitor rated parameters.

[0110] The total correction amount is equal to the sum of the products of all single correction amounts and the corresponding super capacitor health state prediction value.

[0111] The composite power switch is used to adjust the power flow direction, and the composite power switch includes a main channel, a redundant channel and a node monitoring.

[0112] The redundant channel adopts three-stage control: fast approximation stage, fine adjustment stage, and steady-state locking stage.

[0113] The node monitoring is used for suppressing voltage impact, and a distributed buffer inductance is configured, and the voltage change rate and the maximum allowed value are dynamically adjusted according to real-time voltage difference through an adaptive slope control algorithm, wherein, the current change rate is represented.

[0114] As shown in Figure 3 , multiple groups of super capacitors receive and store electric energy, and provide energy support for multiple load operations, such as multiple elevator operations.

[0115] When the system has an electric energy overflow, the total electric energy of the super capacitor charging exceeds the capacity of the lithium battery, or the energy prediction module determines the overflow, the brake resistance dynamic adjustment unit of the coordination module is started, and the excess electric energy is consumed by adjusting the resistance value of the brake resistance.

[0116] In the process, the energy allocation of the emergency area, the dynamic switching area, and the standby area of the multiple lithium batteries is combined to realize energy balance and stable supply during multiple load operations.

[0117] As shown in Figure 2 , the first super capacitor and the second super capacitor supply power to the first elevator and the second elevator respectively, and are connected to the functional module containing the emergency area, the dynamic switching area, and the standby area through a line. The functional module is also connected to the brake resistance, and the first switch and the second switch are respectively used for energy storage redundant circuit access and circuit on-off control, to realize electric energy distribution, state switching, and redundant energy storage functions, and to ensure elevator power supply and operation control.

[0118] Further, the first super capacitor supplies power to the first elevator through the first switch, and the second super capacitor supplies power to the second elevator through the second switch, to realize independent energy supply for the load.

[0119] The lithium battery group composed of the emergency area, the dynamic switching area, and the standby area is connected to the super capacitor group through a line; the emergency area is directly connected to the super capacitor, the dynamic switching area serves as an energy buffer hub, and the standby area is connected to the power grid.

[0120] The system accesses the energy storage redundant circuit and the brake resistance, to form a collaborative working network of load, energy, redundancy, and brake, and to ensure energy distribution and emergency switching during elevator operation.

[0121] It is important to note that the constructions and arrangements of the application shown in the various exemplary embodiments are illustrative only. Although only two embodiments have been described in detail in this disclosure, those skilled in the art who review this disclosure will readily appreciate that many modifications can be made to the embodiments without now departing from the spirit and scope of the application, for example, the size, shape, and relative positions of the elements, as well as the sizes and shapes of the various described structures, and the numerical values of its parameters, the mounting arrangements, the use of materials, colors, orientation, and the like can all be changed to provide yet further embodiments which fall within the scope of the present application. For example, an element shown as integrally formed can be constructed of multiple parts or elements, the position of an element can be reversed or otherwise changed, and the nature or number of elements or positions can be modified or changed. Accordingly, all such modifications are intended to be included within the scope of the application. The order or sequence of any process or method steps can be changed or re-sequenced without departing from the scope of the application. Any "means plus function" clauses are intended to cover the structures described herein as performing the recited functions and not only structural equivalents but also equivalent structures. Other substitutions, modifications, changes, and omissions can be made in the design, operating conditions, and arrangement of the exemplary embodiments without departing from the scope of the application. Accordingly, the application is not limited to the particular embodiments described and shown herein, but extends to all structures that fall within the scope of the application.

[0122] Furthermore, in order to provide a concise description of exemplary embodiments, not all features of an actual implementation can be described (i.e., those not pertinent to the best mode for carrying out the application as currently contemplated).

[0123] It is understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions can be made. Such development efforts can inevitably lead to a number of specific implementation decisions, which can vary from one implementation to another. Nonetheless, it is submitted that any such implementation decisions do not base the inventive subject matter of this application, which is set forth in the claims.

[0124] It should be noted that the above examples are intended to be illustrative only and not limiting of the technical solutions of the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and all such modifications and equivalents should be included in the scope of the present application.

Claims

1. A lithium battery and supercap management system, characterized in that, The system comprises a storage module, a coordination module and an energy prediction module, the storage module comprises a plurality of supercapacitors and a plurality of lithium batteries; The coordination module is used for receiving the energy allocation strategy output by the energy prediction module, and allocating the energy of the plurality of supercapacitors and the plurality of lithium batteries according to the energy allocation strategy; The energy prediction module is provided with a storage monitoring unit, a hierarchical feedback unit and an automatic tuning unit, the storage monitoring unit is used for predicting the storage energy data of the plurality of supercapacitors and the plurality of lithium batteries, outputting the prediction result to the hierarchical feedback unit, identifying the storage energy level of the storage module by the hierarchical feedback unit, and adjusting the power switching between the lithium battery and the supercapacitor in advance, and finally optimizing the total power prediction value of the supercapacitor and the power allocation result by the automatic tuning unit; The storage monitoring unit is provided with a high-frequency ripple monitoring model and an equivalent series resistance identification model; The high-frequency ripple monitoring model obtains the supercapacitor charging and discharging ripple characteristics through a wideband voltage sensor, decomposes the supercapacitor charging and discharging ripple energy distribution characteristics through a wavelet packet, generates voltage waveform frequency band energy entropy values, and extracts ripple characteristic fingerprints from the voltage waveform frequency band energy entropy values; The equivalent series resistance identification model injects a pseudo-random binary sequence excitation signal with controllable amplitude, and simultaneously calculates the equivalent series resistance of the supercapacitor in real time through an adaptive forgetting factor iterative calculation; The double-channel deep residual network receives the equivalent series resistance and ripple characteristic fingerprints of the supercapacitor, and captures the supercapacitor resistance and output voltage ripple characteristics through the double-channel; The first channel extracts the spatial characteristics of the ripple characteristic fingerprints and the equivalent series resistance time sequence through a three-level convolutional layer, the second channel captures the time dependence through a gated recurrent unit, and outputs a fusion feature matrix through a cross-attention mechanism, and outputs a health state prediction value and a confidence.

2. The lithium battery and supercapacitor management system according to claim 1, wherein: The plurality of lithium batteries comprises an emergency area, a standby area and a dynamic switching area; The emergency area comprises a plurality of lithium batteries, which are used to dynamically call the lithium battery group in the emergency area to supplement power when the supercapacitor power is insufficient during the switching acceleration stage; The dynamic switching area is arranged between the emergency area and the standby area, and is used to buffer the power flow from the standby area to the emergency area; The other end of the standby area is connected to the power grid, and is used to receive power from the power grid.

3. The lithium battery and supercapacitor management system according to claim 1, wherein: The coordination module is provided with a dynamic braking resistance adjustment unit, the braking resistance comprises a plurality of gears, if the coordination module receives the power allocation overflow output by the energy prediction module, the resistance value of the braking resistance is dynamically adjusted, and the overflow power is consumed by the braking resistance; If the total charging power of the plurality of supercapacitors is greater than the total capacity of the plurality of lithium batteries, the resistance value of the braking resistance is dynamically adjusted by the coordination module, and the overflow power is consumed by the braking resistance.

4. The lithium battery and supercapacitor management system according to claim 1, wherein: The storage monitoring unit further comprises a lithium battery partition monitoring system, the lithium battery partition monitoring system comprises a domain cooperative perception and a three-dimensional evaluation model; ​ The sub-domain cooperative perception includes an emergency area configuration voltage sampling circuit and an integrated contact thermal sensitive film, monitors the temperature mutation of the tab, dynamically switches the area through a bidirectional power flow monitoring module, and detects the bidirectional power impact of the dynamic switching area; The three-dimensional evaluation model predicts the state of the lithium battery pack through a dynamic internal resistance cloud chart, battery thermal characteristics, and electric energy flow adaptation degree. 5.The lithium battery and super capacitor management system of claim 4, characterized in that: The hierarchical feedback unit is configured with a double-path intelligent distribution interface in the emergency area, which is connected to the first super capacitor group and the second super capacitor group respectively, a bidirectional DC / DC converter cluster is arranged in the dynamic switching area for power bidirectional regulation, and a three-level electric energy bus architecture is established, wherein the first-level bus is directly connected to the super capacitor group in the emergency area, the second-level bus is interconnected with the emergency area in the dynamic switching area, and the third-level bus is connected to the power grid in the standby area. 6.The lithium battery and super capacitor management system of claim 5, characterized in that: The hierarchical feedback unit receives a plurality of super capacitor total power prediction values, and simultaneously corrects the plurality of super capacitor total power prediction values through the automatic tuning unit; The corrected super capacitor total power prediction values are input into the automatic tuning unit, and the electric energy allocation strategy is output by the automatic tuning unit. 7.The lithium battery and super capacitor management system of claim 6, characterized in that: The electric energy allocation strategy includes: If the plurality of super capacitor total power prediction values are greater than the emergency area, the bidirectional DC / DC converter cluster is switched to control the dynamic switching area to allocate electric energy to the emergency area; If the plurality of super capacitor total power prediction values are less than or equal to the emergency area, the electric energy is allocated from the emergency area to the plurality of super capacitors; If the plurality of super capacitor total power prediction values are greater than the sum of the emergency area and the dynamic switching area, the bidirectional DC / DC converter cluster is switched to control the dynamic switching area to allocate electric energy to the emergency area, and the bidirectional DC / DC converter cluster is switched to control the standby area to allocate electric energy to the dynamic switching area; The energy gap in the standby area is filled by the power grid when the power price is the lowest; The hierarchical feedback unit is also provided with an energy storage redundancy circuit, and if the plurality of super capacitor total power prediction values are greater than the sum of the emergency area and the dynamic switching area, the emergency area electric energy flows into the energy storage redundancy circuit, and the standby area electric energy flows to the dynamic switching area, and the dynamic switching area electric energy flows to the emergency area. 8.The lithium battery and super capacitor management system of claim 7, characterized in that: The automatic tuning unit receives a load curve, real-time working conditions, and a super capacitor health state prediction value to correct the actual electric energy allocation strategy; The automatic tuning unit includes a basic layer, a working condition correction layer, and an emergency correction layer, the basic layer uses a neural learning network to learn the load cycle change, the working condition correction layer constructs a multi-dimensional influence factor matrix to dynamically correct the actual electric quantity demand prediction value of the plurality of super capacitors, and the emergency correction layer outputs a dynamic braking resistor to a coordination module, which adjusts the braking resistor. 9.The lithium battery and super capacitor management system of claim 8, characterized in that: The multi-dimensional influence factor matrix includes voltage fluctuation and super capacitor health state prediction value; The power flow is regulated by setting a composite power switch, which includes a main channel, a redundant channel and a node monitor.

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