Solid-state battery power supply control method and device and storage medium

Abstract

The invention relates to the technical field of battery power supply control, in particular to a solid-state battery power supply control method and device and a storage medium, and the method comprises the steps: dividing thermal runaway risk levels; extracting current characteristics in the monitoring period, and constructing a solid electrolyte degradation model according to the current characteristics and the accumulated charge-discharge cycle times to determine a battery attenuation coefficient; determining a hydraulic power demand, and determining a dynamic control strategy based on the thermal management parameter, the battery attenuation coefficient and the hydraulic demand of the next monitoring period; extracting a frequency spectrum component of a torque signal of the lifting motor in each time window in the monitoring period, constructing a frequency spectrum energy ratio, and adjusting a dynamic control strategy according to the frequency spectrum energy ratio; and analyzing equipment operation parameters based on the equipment lifting acceleration and the driving road slope acquired in the monitoring period, and updating the adjustment process of the dynamic control strategy according to the equipment operation parameters. The power supply control efficiency of the solid-state battery is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery power control, and particularly to a solid-state battery power control method, device and storage medium. Background Art

[0002] With the rapid development of new energy technologies, solid-state batteries have become key energy carriers in fields such as electric vehicles, energy storage systems, and special equipment due to their advantages of high energy density, low thermal runaway risk, and long cycle life. However, there are still many technical challenges in the practical application of solid-state batteries. On the one hand, although their thermal stability is better than that of traditional liquid electrolyte batteries, under extreme working conditions or rapid charge and discharge scenarios, the local temperature of the interface between the solid electrolyte and the electrode may still rise suddenly, which may trigger potential thermal runaway hazards. Existing thermal management strategies mostly rely on single temperature monitoring (such as the surface temperature of the battery cell) or fixed cooling thresholds, and fail to effectively integrate multi-dimensional parameters such as ambient temperature and the flow state of the cooling medium, resulting in a lag or excessive redundancy in thermal risk assessment and making it difficult to achieve hierarchical early warning and precise control.

[0003] Currently, some studies have attempted to optimize battery management through multi-sensor fusion or data-driven algorithms, but most of the existing solutions still have the following limitations: (1) The thermal runaway early warning model does not fully consider the coupled effects of ambient temperature changes and active cooling effects on local heat conduction; (2) The degradation assessment lacks quantitative analysis of the dynamic current spectrum characteristics, resulting in insufficient generalization of the model; (3) The power distribution strategy is fixed as an independent closed-loop control, making it difficult to adaptively adjust the collaborative requirements of multiple systems such as hydraulic pressure and motors while ensuring safety. Therefore, there is an urgent need to construct a set of dynamic control methods for solid-state batteries that integrate multi-domain coupling of heat, electricity, and machinery to solve the problems of collaborative optimization of safety, life, and energy efficiency under complex working conditions. Summary of the Invention

[0004] The purpose of the present invention is to provide a solid-state battery power control method, device and storage medium to solve at least one of the problems existing in the prior art.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions: A solid-state battery power control method, comprising: Extracting the current characteristics within a monitoring period, and constructing a solid electrolyte degradation model based on the current characteristics and the cumulative number of charge and discharge cycles to determine the battery attenuation coefficient; Determining the hydraulic power demand based on the collected outlet pressure and flow rate of the equipment oil pump, and determining a dynamic control strategy based on the thermal management parameters, battery attenuation coefficient and hydraulic demand in the next monitoring period; Extracting the spectral components of the lifting motor torque signal in each time window within the monitoring period, and constructing a spectral energy ratio, and adjusting the dynamic control strategy according to the spectral energy ratio; The adjustment process of analyzing the equipment operation parameters based on the equipment lifting acceleration and the driving road surface slope collected within the monitoring period, and updating the dynamic control strategy according to the equipment operation parameters.

[0006] Optionally, it further includes: constructing thermal management parameters based on the collected surface temperature of the solid electrolyte film, the external environment temperature of the battery compartment, and the coolant flow rate, and dividing the thermal runaway risk level according to the thermal management parameters; Collect N surface temperature data of the solid electrolyte film, and denote the surface temperature of the i-th solid electrolyte film as Ti; construct the thermal management parameter Qt based on the surface temperature of the solid electrolyte film, the external environment temperature Te of the battery compartment, and the coolant flow rate Vc, and compare the thermal management parameter Qt with the thermal runaway discrimination factors p1 and p2 to divide the thermal runaway risk level. If Qt is less than or equal to p1, the thermal runaway level is divided into level one. If Qt is greater than p1 and less than p2, the thermal runaway level is divided into level two. If Qt is greater than or equal to p2, the thermal runaway level is divided into level three; When the thermal runaway level is level one, no thermal runaway warning is given. When the thermal runaway level is level two, a mild thermal runaway risk warning is given. When the thermal runaway level is level three, a severe thermal runaway risk warning is given.

[0007] Optionally, extract the peak and valley values of the current in the discharge pulse waveform, denote the peak value as Imax, and denote the valley value as Imin; construct a solid electrolyte degradation model based on the peak value Imax, valley value Imin of the current in the discharge pulse waveform, and the cumulative charge and discharge cycle times Hc, and set the battery attenuation coefficient as Sj. The expression of Sj is: Sj = exp(3×Hc / H0 - 3)×tanh[(Imax - Imin) / (Iz×Re)]; In the formula, HO is the reference cycle number, Iz is the reference current value, and Re is the damage factor.

[0008] Optionally, determine the hydraulic power demand Ph according to the outlet pressure Yp and the oil pump flow rate Lq of the equipment oil pump collected in the next monitoring period. Ph = (Yp×Lq) / (60×β), where β is the efficiency factor.

[0009] Optionally, construct a regulation factor based on the thermal management parameter Qt and the battery attenuation coefficient Sj within the monitoring period. The expression of the regulation factor is: ; In the formula, K is the regulation factor, A is the sensitive attenuation factor, and Pm is the maximum theoretical power of the hydraulic system.

[0010] Optionally, when the thermal runaway level is level three within the monitoring period, forcibly set K to 0; Set the discharge power of the solid-state battery in the next monitoring period to Pu, and set Pu = K × Pe, where Pe is the rated discharge power of the solid-state battery; Compare the discharge power Pu of the solid-state battery in the next monitoring period with the hydraulic power demand Ph. When Pu is less than Ph, limit the lifting speed of the device to D × tz, where D is the nominal lifting speed of the device and tz is the speed limit factor.

[0011] Optionally, perform a fast Fourier transform on the lifting motor torque signal in each time window within the monitoring period, and obtain the frequency spectrum in the 0 - 50 Hz frequency band. Set the main frequency component of the i-th time window to Ezi; set the high-frequency oscillation component of the i-th time window to Ehi; X(f) is the amplitude of the spectrum component at frequency f after Fourier transform; Take the ratio of Ezi to Ehi as the spectrum energy ratio NLi of the i-th time window, and denote the average value of the spectrum energy ratios of each time window within the monitoring period as NLj. If NLj is less than or equal to the energy discrimination factor b0, do not adjust the dynamic control strategy. Otherwise, when the thermal runaway level is level one or two, adjust the control factor to K'.

[0012] Optionally, denote the average value of the device lifting acceleration collected within the monitoring period as ap, and compare ap with the acceleration threshold a0 to determine the acceleration factor JA. If ap is less than or equal to a0, set JA to 0. Otherwise, set JA = (ap - a0) / (ap + a0); Analyze the device operation parameter BY based on the acceleration factor JA and the driving road surface slope m1. The expression of the device operation parameter is BY = x1 × JA + x2 × m1 / m0, where x1 is the acceleration weight, x2 is the slope weight, m0 is the slope threshold, and x1 + x2 = 1; Compare the device operation parameter BY with the operation parameter determination threshold by. If BY is less than or equal to by, do not update the adjustment process of the dynamic control strategy. If BY is greater than by, update the energy discrimination factor b0 to b1.

[0013] In another aspect of the present application, a solid-state battery power control device is provided, including: A level division unit for constructing a thermal management parameter based on the collected surface temperature of the solid electrolyte film, the external environment temperature of the battery compartment, and the coolant flow rate, and dividing the thermal runaway risk level according to the thermal management parameter; A feature extraction unit for extracting the current feature within the monitoring period, and constructing a solid electrolyte degradation model based on the current feature and the cumulative charge and discharge cycle times to determine the battery attenuation coefficient; A strategy determination unit, configured to determine the hydraulic power demand based on the collected outlet pressure and flow rate of the device oil pump, and determine a dynamic control strategy based on the thermal management parameters, battery attenuation coefficient, and hydraulic demand in the next monitoring period; A spectrum analysis unit, configured to extract the spectral components of the lifting motor torque signal in each time window within the monitoring period, construct a spectral energy ratio, and adjust the dynamic control strategy according to the spectral energy ratio; An operation analysis unit, configured to analyze the device operation parameters based on the collected device lifting acceleration and driving road surface gradient within the monitoring period, and update the adjustment process of the dynamic control strategy according to the device operation parameters.

[0014] In another aspect of the present application, there is provided a computer-readable storage medium storing a computer program, wherein the computer program is used to control the electronic device where the computer-readable storage medium is located to execute the solid-state battery power control method when running.

[0015] The beneficial effects of the present invention are as follows: Through multi-dimensional parameter fusion monitoring and closed-loop control mechanism, the safety, efficiency, and adaptability of the battery system are significantly improved. Integrating thermal management parameters to divide the thermal runaway risk level in real time, realizing three-level dynamic early warning and rapid response, and effectively preventing thermal diffusion; Combining current characteristics and cycle times to construct a degradation model, accurately quantifying the battery attenuation state, and optimizing the charge and discharge strategy to delay life decline. Innovatively introducing dynamic matching of hydraulic power and spectral energy ratio analysis to achieve coordinated control of mechanical load characteristics and power supply output, avoiding overload risks. Through multi-dimensional environmental perception of lifting acceleration and road surface gradient, adaptively adjusting the control strategy to enhance the system robustness under complex working conditions. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 It is a schematic flowchart of the solid-state battery power control method in this embodiment.

[0018] Figure 2 It is a schematic flowchart of the method for dividing the thermal runaway risk level in this embodiment.

[0019] Figure 3 It is a schematic flowchart of the method for determining the dynamic control strategy in this embodiment.

[0020] Figure 4Schematic diagram of the structure of the solid-state battery power control device of this embodiment.

[0021] Figure 5 Schematic diagram of the structure of the electronic device of this embodiment. DETAILED DESCRIPTION

[0022] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] Specifically, the solid-state battery power control method, device and storage medium described in the present application are applied to the multi-modal collaborative safety regulation of the solid-state battery system of an electric forklift. Thermal management parameters are constructed based on the battery surface temperature, ambient temperature and coolant flow rate, and the thermal runaway risk level is divided to trigger graded warnings in a targeted manner. The battery attenuation coefficient is calculated in combination with the charge and discharge current characteristics and the number of cycles to quantify the degree of solid-state electrolyte performance degradation. According to the real-time thermal risk level, battery attenuation status and hydraulic load requirements, the discharge power or equipment operating speed is automatically limited to avoid chain failures caused by overload. Parameters such as lifting acceleration and road slope are incorporated to dynamically correct the control strategy to balance safety and operating efficiency.

[0025] See also Figure 1 As shown, it is a flow chart of the solid-state battery power control method of this embodiment, including: Step S101, constructing thermal management parameters based on the collected solid electrolyte film surface temperature, the ambient temperature outside the battery compartment and the coolant flow rate, and dividing the thermal runaway risk level according to the thermal management parameters.

[0026] Exemplarily, in this embodiment, the surface temperature of the solid electrolyte film and the external environment temperature of the battery compartment can be collected in real time through a temperature sensor, and the fluid velocity in the coolant circulation pipeline can be measured through a flow velocity sensor; in this embodiment, the data collection method is not specifically limited, and those skilled in the art can freely set it according to requirements.

[0027] Please refer to Figure 2 as shown, the method for dividing the thermal runaway risk level includes: Step S201, constructing a thermal management parameter based on the collected surface temperature of the solid electrolyte film, the external environment temperature outside the battery compartment, and the coolant flow rate.

[0028] Specifically, collect N surface temperature data of the solid electrolyte film, and record the surface temperature of the i-th solid electrolyte film as Ti; Construct a thermal management parameter based on the surface temperature of the solid electrolyte film, the external environment temperature Te outside the battery compartment, and the coolant flow rate Vc. The expression of the thermal management parameter is: ; In the formula, Qt is the thermal management parameter, α1 is the first weight coefficient, α2 is the second weight coefficient, α1 + α2 = 1, De is the surface temperature factor, Tc is the environmental temperature threshold, and V0 is the flow rate factor.

[0029] Specifically, the thermal management parameter constructed by integrating multi-dimensional data such as the surface temperature of the solid electrolyte film, the external environment temperature outside the battery compartment, and the coolant flow rate enhances the comprehensiveness and real-time nature of battery thermal state monitoring. At the same time, it comprehensively considers the dynamic effects of internal and external heat sources and heat dissipation conditions, provides a quantitative comprehensive index for subsequent risk grading, avoids the limitations of single temperature threshold judgment, and improves the sensitivity and accuracy of thermal anomaly identification.

[0030] Exemplarily, in this embodiment, N can be set to 5, α1 can be set to 0.6, α2 can be set to 0.4, the surface temperature factor can be set to 8 °C, the environmental temperature threshold can be set to 50 °C, and the optimal value of V0 is 0.8 m / s; in this embodiment, the setting of the above data is not specifically limited, and those skilled in the art can freely set it according to requirements.

[0031] Please continue to refer to Figure 2 as shown, the method for dividing the thermal runaway risk level further includes: Step S202, dividing the thermal runaway risk level according to the thermal management parameter.

[0032] Specifically, the thermal management parameter Qt is compared with the thermal runaway discrimination factors p1 and p2 to divide the thermal runaway risk level. If Qt is less than or equal to p1, the thermal runaway level is classified as level one. If Qt is greater than p1 and less than p2, the thermal runaway level is classified as level two. If Qt is greater than or equal to p2, the thermal runaway level is classified as level three. When the thermal runaway level is level one, no thermal runaway warning is given. When the thermal runaway level is level two, a mild thermal runaway risk warning is given. When the thermal runaway level is level three, a severe thermal runaway risk warning is given.

[0033] Specifically, based on the threshold division mechanism of the thermal management parameter, a three-level dynamic warning of thermal runaway risk is realized. Through stepped grading, the system can adopt different response strategies for different risk levels: avoid excessive intervention at low risk, give early warning and initiate preventive measures at medium risk, and forcibly trigger the protection mechanism at high risk. This hierarchical control not only ensures the safety of battery operation, but also reduces unnecessary system performance derating and optimizes the resource allocation efficiency.

[0034] Exemplarily, in this embodiment, p1 can be set to 0.5 and p2 can be set to 0.8. There is no specific limitation on the setting of the above data in this embodiment, and those skilled in the art can freely set it according to needs.

[0035] Please continue to refer to Figure 1 As shown, the solid-state battery power control method further includes: Step S102, extract the current characteristics within the monitoring period, and construct a solid electrolyte degradation model based on the current characteristics and the cumulative charge and discharge cycle times to determine the battery attenuation coefficient.

[0036] Specifically, extract the peak value and valley value of the current in the discharge pulse waveform, denote the peak value as Imax, and denote the valley value as Imin; Construct a solid electrolyte degradation model with the peak value Imax, valley value Imin of the current in the discharge pulse waveform and the cumulative charge and discharge cycle times Hc, and set the battery attenuation coefficient as Sj. The expression of Sj is Sj = exp(3×Hc / H0 - 3)×tanh[(Imax - Imin) / (Iz×Re)]; In the formula, HO is the reference cycle number, Iz is the reference current value, and Re is the damage factor.

[0037] Specifically, a degradation model is constructed for the current pulse characteristics and the cumulative number of cycles, realizing the dynamic quantitative evaluation of the battery attenuation coefficient. By extracting the differences between the peak and valley values of the charge and discharge pulses, as well as the cumulative effect of the number of cycles, this method can identify in advance the decline trend of the ion transport ability inside the solid electrolyte, providing real-time input of the life state for subsequent control strategies, avoiding overcharge and overdischarge from accelerating chemical side reactions, and delaying the irreversible attenuation of battery performance.

[0038] Exemplarily, in this embodiment, the charge and discharge pulse waveforms can be collected by a current sensor, and the peak and valley currents within a period can be extracted. The cumulative number of charge and discharge cycles can be recorded by a pulse counter. In this embodiment, no specific limitation is imposed on the data acquisition method, and those skilled in the art can freely set it according to requirements.

[0039] Exemplarily, in this embodiment, the reference number of cycles can be set to 1000 times, the reference current value can be set to 1.2 times the rated current, and the damage factor can be set to 0.9. In this embodiment, no specific limitation is imposed on the values of the above data, and those skilled in the art can freely set it according to requirements.

[0040] Please continue to refer to Figure 1 As shown, the solid-state battery power control method further includes: Step S103, determining the hydraulic power demand based on the collected outlet pressure and flow rate of the equipment oil pump, and determining a dynamic control strategy based on the thermal management parameters, the battery attenuation coefficient, and the hydraulic demand in the next monitoring period.

[0041] Exemplarily, in this embodiment, the outlet pressure of the equipment oil pump can be measured by a pressure sensor, and the flow rate of the oil pump can be monitored by a flow meter. In this embodiment, no specific limitation is imposed on the data acquisition method of the above, and those skilled in the art can freely set it according to requirements.

[0042] Please refer to Figure 3 As shown, the method for determining the dynamic control strategy includes: Step S301, determining the hydraulic power demand based on the collected outlet pressure and flow rate of the equipment oil pump.

[0043] Specifically, in step S301, the hydraulic power demand Ph is determined based on the outlet pressure Yp and the flow rate Lq of the equipment oil pump collected in the next monitoring period, and Ph = (Yp × Lq) / (60 × β), where β is the efficiency factor.

[0044] Specifically, by calculating the hydraulic power demand in combination with the outlet pressure and flow rate of the oil pump, an accurate dynamic model of the equipment load characteristics is achieved. This method provides a dynamic power reference for the core control strategy by real-time monitoring of the actual energy consumption demand of the hydraulic system, ensuring the precise matching of the battery output power and the hydraulic demand, and avoiding energy waste or equipment performance fluctuations caused by overloading or underloading.

[0045] Exemplarily, in this embodiment, the efficacy factor can be set to 0.85; in this embodiment, no specific limitation is imposed on the setting of the efficacy factor, and those skilled in the art can freely set it according to requirements.

[0046] Please continue to refer to Figure 3 As shown, the method for determining the dynamic control strategy further includes: Step S302, determining a regulation factor based on the thermal management parameters, battery attenuation coefficient within the monitoring period, and the hydraulic demand in the next monitoring period.

[0047] Specifically, in step S302, the thermal management parameter Qt and the battery attenuation coefficient Sj within the monitoring period are used to construct a regulation factor, and the expression of the regulation factor is: ; In the formula, K is the regulation factor, A is the sensitive attenuation factor, and Pm is the maximum theoretical power of the hydraulic system.

[0048] Specifically, by fusing the thermal management parameters and the battery attenuation coefficient to generate an adaptive regulation factor, collaborative decision-making for multi-dimensional states is achieved. The regulation factor not only reflects the constraint of the battery thermal state on safe output but also incorporates the limitation of battery life attenuation on available power, solving the decision-making deviation problem of only considering a single factor in traditional control. The design of its non-linear function enhances the sensitivity to extreme working conditions, ensuring that the control strategy actively derates under the deterioration of battery health or high heat risk, and extending the overall life of the system.

[0049] Exemplarily, in this embodiment, the sensitive attenuation factor can be set to 0.3; in this embodiment, no specific limitation is imposed on the setting of the sensitive attenuation factor, and those skilled in the art can freely set it according to requirements.

[0050] Specifically, in this embodiment, the maximum theoretical power of the hydraulic system can be obtained through interaction.

[0051] Please continue to refer to Figure 3 As shown, the method for determining the dynamic control strategy further includes: Step S303, determining a dynamic control strategy based on the regulation factor.

[0052] Specifically, in step S303, when the thermal runaway level is three in the monitoring period, K is forcibly set to 0; Set the discharge power of the solid-state battery in the next monitoring period to Pu, and set Pu = K × Pe, where Pe is the rated discharge power of the solid-state battery; Compare the discharge power Pu of the solid-state battery in the next monitoring period with the hydraulic power demand Ph. When Pu is less than Ph, limit the lifting speed of the device to D × tz, where D is the nominal lifting speed of the device and tz is the speed limit factor.

[0053] Specifically, through the linkage mechanism between the regulation factor and the hydraulic power demand, dynamic hierarchical limitation of the discharge power and adaptive adjustment of the lifting speed are achieved. When high risks are detected, the power is forcibly limited to ensure the fusing ability of the system; under normal operating conditions, the output is flexibly adjusted according to real-time demands to avoid equipment shutdown or action lag caused by rigid load reduction. This strategy achieves a dynamic balance between safety and performance, improving the system robustness and user experience under complex operating conditions.

[0054] Exemplarily, in this embodiment, the speed limit factor can be set to 0.7; in this embodiment, the setting of the speed limit factor is not specifically limited, and those skilled in the art can freely set it according to requirements.

[0055] Please continue to refer to Figure 1 As shown, the solid-state battery power control method of the example further includes: Step S104, extract the spectral components of the lifting motor torque signal in each time window within the monitoring period, construct the spectral energy ratio, and adjust the dynamic control strategy based on the spectral energy ratio.

[0056] Exemplarily, in this embodiment, the lifting motor torque signal can be collected by a torque sensor. After FFT analysis, calculate the energy of the main frequency and high-frequency oscillation components in the range of 0 - 50 Hz. The real-time signal is collected by a high-precision torque sensor at a sampling rate of 200 Hz. After applying a Hanning window to the signal of each 1-second time window to reduce spectral leakage, perform a fast Fourier transform (FFT) to convert the time-domain torque signal into a frequency-domain complex spectrum, take the absolute value to obtain the amplitude X(f) at each frequency point, and each f corresponds to the amplitude at a specific frequency point of the FFT result; in this embodiment, the above data collection method is not specifically limited, and those skilled in the art can freely set it according to requirements.

[0057] Specifically, in step S104, perform a fast Fourier transform on the lifting motor torque signal in each time window within the monitoring period, obtain the spectrum in the frequency band of 0 - 50 Hz, and set the main frequency component of the i-th time window to Ezi, ; set the high-frequency oscillation component of the i-th time window to Ehi, ; X(f) is the amplitude of the spectral component at the frequency f after Fourier transform; Take the ratio of Ezi to Ehi as the spectral energy ratio NLi of the i-th time window, and denote the average value of the spectral energy ratios of each time window within the monitoring period as NLj. If NLj is less than or equal to the energy discrimination factor b0, the dynamic control strategy is not adjusted. Otherwise, when the thermal runaway level is at the first or second level, the regulation factor is adjusted to K', where K' = K - ln[2×(NLj - b0) + 1] / ln5.

[0058] Exemplarily, in this embodiment, the energy discrimination factor can be set to 0.4; in this embodiment, the setting of the energy discrimination factor is not specifically limited, and those skilled in the art can freely set it according to requirements.

[0059] Specifically, based on the monitoring of the spectral energy ratio of the lifting motor torque signal, a closed-loop mechanism for the mechanical load characteristic to feedback to the power control is realized. By extracting the energy ratio of the main frequency and high-frequency components, the system can indirectly sense the abnormal vibration or jamming of the mechanical transmission chain and adjust the regulation factor in time to suppress the resonance risk.

[0060] Please continue to refer to Figure 1 As shown, the solid-state battery power control method of this example further includes: Step S105, analyze the equipment operation parameters based on the equipment lifting acceleration and the driving road surface slope collected within the monitoring period, and update the adjustment process of the dynamic control strategy according to the equipment operation parameters.

[0061] Exemplarily, in this embodiment, an acceleration sensor can be used to measure the equipment lifting acceleration, and an inclination sensor or GPS elevation data can be used to collect the driving road surface slope; in this embodiment, the data collection method is not specifically limited, and those skilled in the art can freely set it according to requirements.

[0062] Specifically, in step S105, denote the average value of the equipment lifting acceleration collected within the monitoring period as ap, and compare ap with the acceleration threshold a0 to determine the acceleration factor JA. If ap is less than or equal to a0, set JA to 0. Otherwise, set JA = (ap - a0) / (ap + a0); Analyze the equipment operation parameter BY based on the acceleration factor JA and the driving road surface slope m1. The expression of the equipment operation parameter is BY = x1×JA + x2×m1 / m0, where x1 is the acceleration weight, x2 is the slope weight, m0 is the slope threshold, and x1 + x2 = 1; Compare the equipment operation parameter BY with the operation parameter determination threshold by. If BY is less than or equal to by, the adjustment process of the dynamic control strategy is not updated. If BY is greater than by, update the energy discrimination factor b0 to b1, where b1 = b0×(1 + BY 2 ), 0.3 < by < 0.4.

[0063] Specifically, by associating the lifting acceleration with the road surface slope to update the control strategy in real time, the adaptability of the system to the dynamic environment and operating scenarios is enhanced. The lifting acceleration reflects the transient load change trend of the actuator, while the road surface slope represents the additional constraint of the external environment on the equipment stability. After integrating the two into the equipment operation parameters, the system can actively correct the energy discrimination factor in the original strategy, prevent control lag or misjudgment under extreme conditions, and ensure the coordinated convergence of the lifting action smoothness and the battery power output.

[0064] Exemplarily, in this embodiment, the acceleration threshold can be set to 0.2 m / s², the slope threshold can be set to 30°, the acceleration weight can be set to 0.45, the slope weight can be set to 0.55, and the operation parameter determination threshold can be set to 0.36; in this embodiment, no specific limitations are imposed on the settings of the above data, and those skilled in the art can freely set them according to requirements.

[0065] Exemplarily, in this embodiment, the monitoring period can be set to 10 seconds, and the time window can be set to 1 second; in this embodiment, no specific limitations are imposed on the settings of the monitoring period and the time window, and those skilled in the art can freely set them according to requirements.

[0066] Specifically, the equipment in this embodiment is an electric forklift.

[0067] Please refer to Figure 4 As shown, the solid-state battery power control device includes: A level division unit, configured to construct thermal management parameters based on the surface temperature of the solid electrolyte film, the external environment temperature outside the battery compartment, and the coolant flow rate collected, and divide the thermal runaway risk level according to the thermal management parameters; A feature extraction unit, configured to extract the current features within the monitoring period, and construct a solid electrolyte degradation model based on the current features and the cumulative charge and discharge cycle times to determine the battery attenuation coefficient; A strategy determination unit, configured to determine the hydraulic power demand based on the outlet pressure and flow rate of the equipment oil pump collected, and determine the dynamic control strategy based on the thermal management parameters, the battery attenuation coefficient, and the hydraulic demand in the next monitoring period; A spectrum analysis unit, configured to extract the spectrum components of the lifting motor torque signal in each time window within the monitoring period, construct a spectrum energy ratio, and adjust the dynamic control strategy according to the spectrum energy ratio; An operation analysis unit, configured to analyze the equipment operation parameters based on the lifting acceleration of the equipment and the road surface slope of the driving collected within the monitoring period, and update the adjustment process of the dynamic control strategy according to the equipment operation parameters.

[0068] The embodiment of the present application further provides an electronic device, which is used to execute the solid-state battery power control method. As Figure 5As shown in the figure, the electronic device includes: a processor 501, a memory 502, a communication interface 503, and a system bus 504. The processor includes at least one of a central processing unit (CPU), a graphics processing unit (GPU), or a field-programmable gate array (FPGA), and is configured to call computer programs and data stored in the memory and generate control instructions; the memory includes a random access memory (RAM) and / or a non-volatile memory (NVM), and the NVM includes a flash memory, a solid-state drive (SSD), or a combination thereof, and is used to store computer programs, intermediate processing data, and a historical data set; the communication interface includes a wired communication module and a wireless communication module, the wired communication module supports Ethernet or RS-485 protocols and is used to connect to a sensor network; the wireless communication module supports LoRa, 5G, or satellite communication protocols and is used to transmit processing results to a remote server; the system bus adopts a PCI Express or AXI bus architecture to achieve high-speed data interaction and clock synchronization between the processor, the memory, and the communication interface.

[0069] Another embodiment of the present invention provides a computer-readable storage medium. The medium physically stores computer-executable instructions. When the instructions are transmitted to a processing unit via an integrated circuit substrate, they are encapsulated and processed through a data channel of a bus system and then solidified into a non-volatile storage area of a storage module. The executable instructions are configured to implement the complete technical solution of the solid-state battery power control method when executed by a processor.

[0070] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, rather than limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to enumerate all the implementation manners here. Any obvious changes or modifications derived from the technical solutions of the present invention still fall within the protection scope of the present invention.

Claims

1. A solid-state battery power control method, characterized in that: include: Extract the current characteristics during the monitoring period, and build a solid electrolyte degradation model based on the current characteristics and the cumulative number of charge and discharge cycles to determine the battery attenuation coefficient; Determine the hydraulic power demand based on the collected equipment oil pump outlet pressure and oil pump flow, and determine the dynamic control strategy based on thermal management parameters, battery attenuation coefficient and hydraulic demand of the next monitoring cycle; Extract the spectral components of the lifting motor torque signal in each time window within the monitoring period, construct the spectral energy ratio, and adjust the dynamic control strategy according to the spectral energy ratio; The equipment operating parameters are analyzed based on the equipment lifting acceleration and road slope collected during the monitoring period, and the adjustment process of the dynamic control strategy is updated according to the equipment operating parameters.

2. The solid-state battery power control method according to claim 1, characterized in that: Also includes: The thermal management parameters are constructed based on the collected solid electrolyte film surface temperature, ambient temperature outside the battery compartment, and coolant flow rate, and the thermal runaway risk level is divided according to the thermal management parameters; Collect N solid electrolyte film surface temperature data, and record the i-th solid electrolyte film surface temperature as Ti; construct a thermal management parameter Qt based on the solid electrolyte film surface temperature, the ambient temperature Te outside the battery compartment, and the coolant flow rate Vc, and compare the thermal management parameter Qt with the thermal runaway discrimination factors p1 and p2 to classify the thermal runaway risk level. If Qt is less than or equal to p1, the thermal runaway level is classified as level one; if Qt is greater than p1 and less than p2, the thermal runaway level is classified as level two; if Qt is greater than or equal to p2, the thermal runaway level is classified as level three; When the thermal runaway level is level one, no thermal runaway warning is issued. When the thermal runaway level is level two, a mild thermal runaway risk warning is issued. When the thermal runaway level is level three, a severe thermal runaway risk warning is issued.

3. The solid-state battery power control method according to claim 2, characterized in that: The peak and valley values ​​of the current in the discharge pulse waveform are extracted, and the peak value is recorded as Imax, and the valley value is recorded as Imin; the peak value Imax, valley value Imin and cumulative charge and discharge cycle number Hc of the current in the discharge pulse waveform are used to construct a solid electrolyte degradation model, and the battery attenuation coefficient is set to Sj. The expression of Sj is: Sj=exp(3×Hc / H0-3)×tanh[(Imax-Imin) / (Iz×Re)]; Where HO is the reference cycle number, Iz is the reference current value, and Re is the damage factor.

4. The solid-state battery power control method according to claim 3, characterized in that: The hydraulic power demand Ph is determined based on the equipment oil pump outlet pressure Yp and the oil pump flow Lq collected in the next monitoring cycle, where Ph=(Yp×Lq) / (60×β), where β is the efficiency factor.

5. The solid-state battery power control method according to claim 4, characterized in that: The thermal management parameter Qt and battery attenuation coefficient Sj within the monitoring period are used to construct the control factor, and the expression of the control factor is: ； Where K is the control factor, A is the sensitive attenuation factor, and Pm is the maximum theoretical power of the hydraulic system.

6. The solid-state battery power control method according to claim 5, characterized in that: When the thermal runaway level is level 3 during the monitoring period, K is forcibly set to 0; The discharge power of the solid-state battery in the next monitoring cycle is set to Pu, and Pu=K×Pe is set, where Pe is the rated discharge power of the solid-state battery; The discharge power Pu of the solid-state battery in the next monitoring cycle is compared with the hydraulic power demand Ph. When Pu is less than Ph, the lifting speed of the equipment is limited to D×tz, where D is the nominal lifting speed of the equipment and tz is the speed limit factor.

7. The solid-state battery power control method according to claim 6, characterized in that: Perform fast Fourier transform on the lifting motor torque signal in each time window within the monitoring period, and obtain the 0-50Hz frequency band spectrum, set the main frequency component of the i-th time window to Ezi; set the high-frequency oscillation component of the i-th time window to Ehi; X(f) is the amplitude of the spectrum component at frequency f after Fourier transform; The ratio of Ezi to Ehi is taken as the spectrum energy ratio NLi of the i-th time window, and the average value of the spectrum energy ratio of each time window in the monitoring period is recorded as NLj. If NLj is less than or equal to the energy discrimination factor b0, the dynamic control strategy is not adjusted. Otherwise, when the thermal runaway level is level one or level two, the control factor is adjusted to K'.

8. The solid-state battery power control method according to claim 7, characterized in that: The average value of the equipment lifting acceleration collected during the monitoring period is recorded as ap, and ap is compared with the acceleration threshold a0 to determine the acceleration factor JA. If ap is less than or equal to a0, JA is set to 0, otherwise, JA is set to (ap-a0) / (ap+a0); The equipment operating parameter BY is analyzed based on the acceleration factor JA and the road slope m1. The expression of the equipment operating parameter is BY=x1×JA+x2×m1 / m0, where x1 is the acceleration weight, x2 is the slope weight, m0 is the slope threshold, and x1+x2=1; The equipment operating parameter BY is compared with the operating parameter judgment threshold by. If BY is less than or equal to by, the adjustment process of the dynamic control strategy is not updated. If BY is greater than by, the energy judgment factor b0 is updated to b1.

9. A solid-state battery power control device, characterized in that: include: A level classification unit is used to construct thermal management parameters based on the collected solid electrolyte film surface temperature, the ambient temperature outside the battery compartment, and the coolant flow rate, and to classify the thermal runaway risk level according to the thermal management parameters; A feature extraction unit is used to extract the current characteristics within the monitoring period and to construct a solid electrolyte degradation model based on the current characteristics and the cumulative number of charge and discharge cycles to determine the battery attenuation coefficient; A strategy determination unit is used to determine the hydraulic power demand based on the collected equipment oil pump outlet pressure and oil pump flow, and determine the dynamic control strategy based on thermal management parameters, battery attenuation coefficient and hydraulic demand of the next monitoring cycle; A spectrum analysis unit is used to extract the spectrum components of the lifting motor torque signal in each time window within the monitoring period, construct a spectrum energy ratio, and adjust the dynamic control strategy according to the spectrum energy ratio; The operation analysis unit is used to analyze the equipment operation parameters based on the equipment lifting acceleration and the road slope collected during the monitoring period, and to update the adjustment process of the dynamic control strategy according to the equipment operation parameters.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program is used to control the electronic device where the computer-readable storage medium is located to execute the solid-state battery power control method according to any one of claims 1 to 8 during operation.

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