1265 results about "Open-circuit voltage" patented technology

The present invention relates to the technical field of lithium battery state estimation, and in particular to a fuzzy EKF-AH algorithm-based state of charge (SOC) estimation and correction method for a lithium iron phosphate battery. The method comprises: by taking a certain startup of an energy storage device as a start, a BMS reading an SOC and a state of health (SOH) at the previous shutdown, and on the basis of a standby time, selecting an open circuit voltage (OCV) or an EKF algorithm to correct the SOC; using an EKF-AH algorithm to estimate the SOC, establishing, on the basis of fuzzy control, a fuzzy rule library associated with the SOC and the SOH, and dynamically adjusting a weight and a measurement noise deviation of the EKF-AH algorithm; and calculating estimation differences between the EKF algorithm and an ampere-hour integration method, and if the sum of the estimation differences is greater than a corresponding threshold, issuing an SOH correction warning. The present invention improves the estimation accuracy of the entire life cycle of the lithium iron phosphate battery, and assists the correction of the SOH.

The invention relates to the technical field of performance testing, in particular to an electrochemical performance testing system and method for an energy storage device, and the system comprises a time synchronization triggering module, an impedance track acquisition module, a degradation state recognition module, an electrochemical abnormity monitoring module and a performance testing judgment module. According to the invention, multi-channel concurrent synchronous acquisition of voltage, current, impedance and temperature is realized by calculating sampling delay compensation time, and lithium precipitation, micro short circuit and electrode interface damage trend can be accurately identified by calculating a gradient absolute difference sequence of a voltage change rate and a current change rate and linking an impedance abrupt change rate and short-period abnormal fluctuation. In the process of judging the state of the energy storage device, open-circuit voltage distribution, charging and discharging current stability and impedance change trend are considered in a combined manner, the recognition accuracy of an active state, a degradation state and an abnormal state is improved, and the precision and reliability of electrochemical performance testing are improved.

The invention provides a three-junction quantum well solar cell epitaxial structure and a manufacturing method thereof, the three-junction quantum well solar cell epitaxial structure comprises a substrate serving as a first sub-cell, a first tunnel junction, a second sub-cell, a second tunnel junction and a third sub-cell which are sequentially stacked from bottom to top, and the three sub-cells are connected through the tunnel junctions; wherein the first sub-cell is a Ge cell, the second sub-cell is an InGaAs cell, the third sub-cell is a GaInP / AlGaInP quantum well cell, the third sub-cell comprises a (Al < x > 1 < Ga < 1-x > 1 < y > 1 < In < 1-y > 1 < P) back field layer, a quantum well base region, a (Al < x > 4 < Ga < 1-x > 4 < y > 4 < In < 1-y > 4 < P) emitter region and an Al < x > 5 < In < 1-y > 5 window layer which are sequentially stacked from bottom to top, the quantum well base region is composed of a Ga < x > 2 < In < 1-x > 2 layer and a (Al < x > 3 < Ga < 1-x > 3 < y > 3 < In < 1 x is larger than or equal to 0.5 and smaller than or equal to 0.8, y is larger than or equal to 0.5 and smaller than or equal to 0.8, y is equal to 0.5, the GaInP / AlGaInP quantum well structure is used for replacing a traditional AlGaInP material to serve as a top cell material, the open-circuit voltage of the solar cell is increased, and meanwhile the defect that the short-circuit current of the AlGaInP / GaAs / Ge solar cell is insufficient is overcome.

The invention belongs to the technical field of back contact photovoltaic cells, and particularly relates to a back contact photovoltaic cell with high-concentration co-doped regions and a manufacturing method and application thereof.The back contact photovoltaic cell with the high-concentration co-doped regions is characterized in that N-type doped regions and P-type doped regions which are alternately distributed are arranged on the backlight face of an intrinsic amorphous silicon layer, and the high-concentration co-doped regions are arranged between the N-type doped regions and the P-type doped regions; a doping source of the co-doped region comprises doping source phosphorus of the N-type doped region and doping source boron of the P-type doped region, the co-doped region, the doping source of the N-type doped region and the doping source of the P-type doped region form a specific concentration gradient structure, and the specific concentration gradient structure meets the condition that the doping concentration of phosphorus contained in the co-doped region is greater than that of phosphorus contained in the N-type doped region; the doping concentration of boron contained in the co-doped region is greater than the doping concentration of boron in the P-type doped region. The carrier transport and collection efficiency is optimized, the fill factor and open-circuit voltage are improved, the cell conversion efficiency and stability are improved, the preparation process is simple, and multiple times of opening etching are not needed.

The invention discloses a trimethoxy-substituted PTAA copolymer as well as a preparation method and application thereof. The structural formula of the trimethoxy-substituted PTAA copolymer is shown as a formula (I), the perovskite solar cell prepared from the trimethoxy-substituted PTAA copolymer disclosed by the invention has relatively high open-circuit voltage, and the energy conversion efficiency of the perovskite solar cell is effectively improved.

The invention discloses a liquid metal enhanced triboelectric material with a bionic surface and a preparation method of the liquid metal enhanced triboelectric material, and belongs to the technical field of triboelectric materials. The preparation method comprises the following steps: mixing an interface stabilizer TEMPO oxidized nanocellulose with a liquid metal gallium-indium alloy to obtain TOCNF (at) LM liquid metal-based micro-nano liquid drops; and doping the obtained TOCNF-coated LM liquid metal-based micro-nano liquid drops into a base material waterborne polyurethane, and constructing a bionic rose petal micro-mastoid process structure by adopting a template method, so as to obtain the liquid metal enhanced triboelectric material with a bionic surface. The composite material with the rose petal micro-nano structure is prepared through bionic design, the micro-mastoid structure of rose petals is successfully re-carved, and the triboelectric property of the waterborne polyurethane is remarkably improved by utilizing TOCNF at LM liquid metal-based micro-nano liquid drops, so that the open-circuit voltage of the prepared composite material reaches 250V, the short-circuit current reaches 8.19 mu A, and the triboelectric property of the waterborne polyurethane is remarkably improved. The short-circuit transfer charge quantity reaches 95nC, and theoretical and practical guidance is provided for the design of a high-performance triboelectric material.

The invention relates to the technical field of battery management, and particularly discloses a dynamic control method for an intelligent balance management system of a lithium battery module, which comprises the following steps of: acquiring load current of the battery module and end voltage signals of each monomer in real time; calculating instantaneous internal resistance and polarization voltage parameters of each single battery in real time; the terminal voltage is compensated in real time, and a purified open-circuit voltage signal is generated; fusing the charge state reference value with the current integral result, dynamically calculating a confidence index according to a current standing condition and voltage stability so as to perform adaptive weighting, and outputting a smooth charge state estimation value; calculating a balance urgency degree index by combining the estimated value, the real-time temperature and the inconsistency change trend, and generating a differentiated balance control instruction; an energy transfer path is established and controlled according to the instruction, the rate is dynamically adjusted in the process, and operation is terminated when the duration or state consistency condition is met; according to the method, the stability of state estimation and the accuracy, safety and efficiency of balance control under the dynamic working condition are improved.

The invention discloses a storage battery grouping online capacity checking method and system fusing a health degree evolution model, and relates to the technical field of storage battery management, and the method comprises the following steps: S1, building a sensitive baseline, injecting a controlled short pulse, and measuring a voltage hysteresis area and a platform repetition rate for a tiny circulation working condition at the end of each charging and discharging period; generating a memory early warning index; s2, after the memory early warning index is obtained, an induction test is executed, and a grading threshold value is formed by comparing the capacity hysteresis residual error, the internal resistance transition rate and the open-circuit voltage deviation in the short-time charging and discharging process. According to the method, high-precision online health accounting and grouping differentiation operation limitation are realized through multi-parameter dynamic detection and grading judgment, and synchronous iteration of a management system and working conditions is guaranteed by matching operation result real-time write-back and baseline self-adaptive updating. The system can identify high-risk monomers in advance and dynamically group and reconstruct the high-risk monomers, thereby preventing failure and improving the safety and energy efficiency utilization rate of the battery pack.

The invention provides a lithium ion battery charge state estimation method and device, equipment and a medium, and the method comprises the steps: obtaining a battery end voltage measurement value and a platform interval query table collected at a current moment when a charge state estimation request for a to-be-estimated battery is received, and determining a prior charge state estimation value; determining a platform interval attribute result corresponding to the priori state-of-charge estimation value; adjusting an observation noise covariance matrix based on the platform interval attribute result, the real-time slope of the open-circuit voltage-state-of-charge relation curve at the priori state-of-charge estimation value and the battery working current change rate; and updating the Kalman gain based on the adjusted observation noise covariance matrix, correcting the priori state-of-charge estimated value by using the updated Kalman gain to obtain the target state-of-charge estimated value at the current moment, and obtaining the target state-of-charge estimated value at the current moment through platform interval identification and a multi-parameter adaptive adjustment mechanism. And the estimation precision and stability of the state of charge of the lithium ion battery are improved.

Disclosed in the present application are a method and apparatus for estimating the state of charge of a battery, and a device and a storage medium. The method comprises: by means of a Thevenin equivalent circuit model, constructing a Thevenin equivalent circuit state space model for a lithium battery; on the basis of a preset high-order polynomial, performing fitting on the state of charge and open-circuit voltage of the lithium battery, and determining a non-linear relationship curve between the state of charge and the open-circuit voltage; collecting real-time operating state data of the lithium battery, and on the basis of the real-time operating state data, using an extended Kalman filter algorithm to perform online parameter identification on the Thevenin equivalent circuit state space model, so as to obtain an estimated state variable value; and constructing an adaptive double-power sliding mode observer, and inputting the non-linear relationship curve and the estimated state variable value into the adaptive double-power sliding mode observer, so that the adaptive double-power sliding mode observer calculates an estimated state-of-charge value of the lithium battery in real time. Compared with the prior art, the technical solution of the present application can improve the accuracy of estimating the state of charge of a lithium battery.

The invention discloses a battery peak power prediction method and system based on multi-modal data coupling mapping, and relates to the technical field of lithium ion power battery management. The method comprises the following steps: acquiring electrochemical parameters and thermophysical parameters of a battery to be detected, and constructing a single-particle thermal coupling model; injecting a plurality of sinusoidal current disturbances with different frequencies into the battery to be detected, synchronously sampling voltage and current, and extracting an impedance real part under each frequency; mapping an impedance real part and the decomposed total DC internal resistance according to a mapping relation among impedance, temperature and aging; performing closed-loop correction by using an extended Kalman filter to obtain a dynamic total internal resistance; and calculating the maximum allowable current according to the dynamic total internal resistance based on the current open-circuit voltage and cut-off voltage constraint, and further outputting the instantaneous peak power of the load end. According to the method, accurate online estimation is carried out on the instantaneous peak power of the battery under the conditions of the full life cycle and the full weather of the vehicle.

The invention provides a hysteresis coefficient calibration method for a battery, and the method comprises the following steps: discharging the battery from a first initial charge state to a first target charge state through a plurality of unequal discharge currents, and measuring the open-circuit voltage, corresponding to the first target charge state, of the battery after standing for a preset period of time; the measured open-circuit voltage is compared with a reference open-circuit voltage determined according to a reference OCV-SOC corresponding relation to determine a hysteresis coefficient, and the hysteresis coefficient represents the deviation degree of the OCV-SOC corresponding relation of the battery relative to the reference OCV-SOC corresponding relation caused by the hysteresis effect; and determining a corresponding relationship between the discharge currents and the hysteresis coefficients based on the plurality of discharge currents and the corresponding hysteresis coefficients. The present application also proposes a state of charge determination method for a battery, a computer program product, an electronic device, and a vehicle. According to the invention, the state of charge of the battery can be determined more accurately.

The invention provides a power battery equalization control method, device and equipment and a medium, and relates to the technical field of battery management systems.The method comprises the steps that the total capacity of a battery pack and the open-circuit voltage of each single battery are obtained, and an equalization capacity difference initial value and a charging tail end charge state threshold value are set at the same time; when the single battery is in a non-plateau period, according to a corresponding relation between the open-circuit voltage and a preset open-circuit voltage-state-of-charge characteristic curve, calculating the state of charge of the single battery; a difference value between the single body charge state and the minimum charge state is calculated to form a charge state range, and the charge state range is compared with a preset charge state deviation threshold value to judge whether equalization operation needs to be executed or not; when it is judged that equalization operation needs to be executed, the equalization electric quantity is calculated according to the charge state range, the single body rated capacity and the health state coefficient; and determining equalization time based on the proportional relation between the equalization electric quantity and the equalization current, and executing equalization operation according to the equalization time. According to the invention, active equalization control of the power battery can be realized.

The invention discloses a full-working-condition driving force optimal distribution control method based on an HCU, and relates to the technical field of new energy automobile control, and the method comprises the following steps: building a long slope energy flux analysis model, generating a time sequence envelope curve of recovery power based on a slope, an automobile speed and a wheel end inertia, and extracting a local peak value interval in the time sequence envelope curve; and in the peak value interval, based on the open-circuit voltage, pulse current and impedance spectrum information of the power battery, online identifying the absorption capacity of the power battery, correcting the upper limit of the state of charge of the power battery, determining a rechargeable current threshold value, carrying out coupling analysis on the threshold value and the recovery power envelope curve, and identifying the reverse current risk time period of the inverter. According to the method, real-time constraint on the absorption capacity of the power battery under the long-slope deceleration working condition is achieved, the inverter reverse irrigation risk is recognized, a peak clipping track and a transient discharge channel are constructed, micro-pulse, accessory absorption and super-capacitor shunting are fused, energy closed-loop control is formed, and the safety of the whole vehicle and the energy utilization efficiency are improved.

The invention provides a preparation method of a surface structure of a back contact battery, which relates to the technical field of back contact batteries, and comprises the following steps: S1, carrying out double-sided polishing on the surface of a silicon wafer: firstly carrying out rough polishing, removing a damaged layer on the surface of the silicon wafer, then cleaning with acid and ozone, then carrying out fine polishing, then cleaning with a mixed solution of hydrogen peroxide and alkali, and then carrying out acid pickling with ozone, then cleaning with a mixed solution of acid and hydrogen peroxide, and finally washing and drying; sequentially depositing a tunneling oxide layer and amorphous silicon on a single surface at high temperature; and performing high-temperature diffusion on the surface to form a crystallized first semiconductor region and a mask layer BSG. According to the invention, the specific suede structure is formed on the front surface, and the polished surface is formed on the back isolation base region, so that high reflectivity of the back isolation base region is ensured, the specific suede structure on the front surface can be independently designed, and meanwhile, a double-surface ozone oxidation process is added; therefore, the open-circuit voltage and the short-circuit current of the cell are improved, and the photoelectric conversion efficiency of the cell is improved.

The invention discloses a lithium battery residual capacity prediction method based on an LSTM-GNN fusion model, and belongs to the technical field of lithium battery residual capacity prediction, and the method specifically comprises the steps: collecting the fluctuation data of voltage, current, temperature, internal resistance and the like during the charging and discharging of a lithium battery in real time, and carrying out the preprocessing; carrying out pulse current test, acquiring voltage step response data to extract rebound characteristic parameters, and forming a battery state characteristic vector by utilizing an internal resistance-open-circuit voltage correlation model and impedance spectroscopy analysis; inputting the preprocessed battery fluctuation data, the preprocessed rebound characteristic parameter and the preprocessed battery state characteristic vector into an LSTM network according to a time sequence to obtain a hidden state; meanwhile, abstracting an internal physical structure of the battery into a graph structure, inputting related parameters as node features into the GNN network, and outputting node feature representation; and finally, fusing the hidden state of the LSTM and GNN node feature representation, and outputting a predicted value of the residual capacity of the lithium battery after full connection layer processing, so that the prediction accuracy is improved.

The invention provides a battery SOC calculation method and device, a battery management system and a computer readable storage medium, and the calculation method comprises the steps: calculating an initial electric quantity based on an initial voltage, charging and discharging parameters and a cell OCV-SOC curve model; calculating an open-circuit voltage at the current moment based on the voltage, the current and the fusion impedance at the current moment; based on the electric quantity variable quantity at the current moment, calculating a circuit accumulated measurement deviation and an effective capacity deviation of the battery cell, and calculating a calibration electric quantity at the current moment; and predicting the actual electric quantity at the current moment based on the target electric quantity and the charging and discharging parameters, secondarily calibrating the actual electric quantity at the current moment by combining the calibration electric quantity, and realizing electric quantity and state synchronization. According to the battery SOC calculation method, accurate and real-time calculation and updating of the battery SOC are achieved by fusing the battery model, the operation parameters and the charging and discharging parameters, the method has the advantages of being high in precision, low in power consumption, real-time and reliable, SOC changes can be rapidly responded in the charging and discharging process, and the applicability is wide.

The invention discloses a group III chloride ex-situ doped cadmium telluride thin film solar cell and a preparation method thereof, and the cadmium telluride thin film solar cell comprises a substrate layer, a transparent conductive oxide thin film layer, a high-resistance buffer layer, a cell window layer, a cell layer, a back contact layer and a back electrode layer which are sequentially arranged from bottom to top. The cell layer comprises an absorption layer and a IIICl3 layer coated on the upper surface of the cell window layer, and IIICl3 is chloride of the III main group element. According to the III-group chloride ex-situ doping method provided by the invention, the III-group chloride can be dissolved in an organic solution, room-temperature solution deposition is allowed, III-group cations are easy to diffuse at a relatively low annealing temperature, and a complex annealing process is not needed to activate a dopant; through a simple solution process and low-temperature activation, efficient doping of the CdTe absorption layer is effectively realized, and the open-circuit voltage and the overall photoelectric conversion efficiency of the cell are remarkably improved.

The invention discloses a PTAA copolymer as well as a preparation method and application thereof. The structural formula of the PTAA copolymer is shown as a formula (I), the perovskite solar cell prepared from the PTAA copolymer has high open-circuit voltage, and the energy conversion efficiency of the perovskite solar cell is effectively improved.

A processor of a battery apparatus estimates an internal resistance of a battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open circuit voltage of the battery, and a measured temperature of the battery, and estimates a resistance state of the battery based on the estimated internal resistance and a beginning of life (BOL) resistance at the reference temperature when the battery is in a BOL state.

The invention discloses an energy storage battery SOC and SOH joint estimation method based on adaptive double extended Kalman filtering, and the method comprises the steps: constructing a second-order RC equivalent circuit model of an energy storage battery, and building a state-space equation of a battery state and a battery parameter; measuring the open-circuit voltage of the energy storage battery under different SOCs through a pulse discharge experiment, and fitting a polynomial function relationship between the SOC and the open-circuit voltage by using a least square method; establishing a battery capacity model and an internal resistance model for energy storage battery SOH estimation; the measurement noise variance is dynamically adjusted based on an improved Sage-Husa adaptive algorithm, and joint estimation of the SOC and the SOH of the energy storage battery is realized through an iteration mode. According to the method, a relatively large state estimation error caused by fixed measurement noise is avoided, self-adaptive adjustment of the measurement noise is realized, and the reliability and the accuracy of SOC and SOH joint estimation of the energy storage battery are improved.

The invention discloses a method for researching an external short-circuit current impact damage mechanism of a lithium ion battery, and the method comprises the steps: testing the limit short-circuit current of the battery through a fitting mode, and determining the time upper limit of short-circuit current impact through an uncontrolled time short-circuit experiment; millisecond-level short-circuit current impact tests of different time scales are carried out on the battery, and performance tests are carried out on the battery every N times of impact so as to monitor recession characteristics of parameters such as capacity and internal resistance of the battery; performing prediction and quantitative calculation on damage mechanisms such as positive and negative electrode active material loss and lithium ion loss by combining a capacity increment curve and an open-circuit voltage curve; and disassembling the battery in an inert gas atmosphere, carrying out microstructure, morphology and element distribution characterization on the electrode and the diaphragm, and verifying a damage mechanism. According to the method, electrochemical testing and material characterization are combined, the corresponding relation and evolution law of battery performance degradation and internal material damage under external short-circuit current impact are disclosed, and a basis is provided for safety design and reliability evaluation of a battery system.

The embodiment of the invention provides a battery open-circuit voltage correction method and device, a vehicle, a medium and a product. The method comprises the following steps: when the standing time of a to-be-tested battery represents that the to-be-tested battery does not enter a steady-state response, determining the polarization voltage of the to-be-tested battery in the standing time according to the polarization attenuation degree of the to-be-tested battery; the polarization attenuation degree of the to-be-detected battery is determined according to the standing time and the polarization time constant of the to-be-detected battery; and according to the polarization voltage of the to-be-measured battery in the standing time, correcting the open-circuit voltage of the to-be-measured battery obtained in the standing time to obtain the corrected open-circuit voltage of the to-be-measured battery. The method is used for achieving the effect of improving the measurement accuracy of the OCV.

The invention discloses a power battery active equalization control system based on SOC prediction, belongs to the technical field of battery management, and aims to solve the defect that the capacity fading of a battery pack cannot be fundamentally solved by a traditional voltage equalization strategy. According to the system, a dual-active half-bridge equalizer topology is adopted, a second-order RC equivalent circuit model and an FFRLS-EKF joint algorithm are combined to achieve high-precision SOC estimation, and the error is reduced by more than 20% compared with a traditional open-circuit voltage method; a phase shift and duty ratio combined control strategy is innovatively provided, the on-off state of an MOSFET and PWM signal parameters are adjusted in real time, the equalization current is cooperatively regulated and controlled, and the problem of pseudo equalization is solved. According to the method, the SOC of the battery pack can be quickly converged under the working conditions of standing, charging and discharging, the maximum deviation is reduced to 1.49% from 63.2%, the equalization efficiency is improved by more than 10%, and the method has the characteristics of simple circuit, efficient algorithm and strong expansibility, and is suitable for scenes such as a power battery system and an energy storage power station.

The invention discloses a method for evaluating the health state of a LiFePO4 battery, and belongs to the field of prediction of the health state of a battery of a peak regulation energy storage system. The implementation method comprises the following steps: acquiring initial electric quantity according to open-circuit voltage of a battery, and calculating SOH by combining full-charge charging capacity; a differential voltage curve is obtained by performing differential processing on a charging curve, an inflection point between a high-voltage platform and a low-voltage platform in the charging curve is accurately positioned by using valley voltage between high-voltage characteristic peaks and low-voltage characteristic peaks, and SOH is calculated by accumulating electric quantity before and after the inflection point. Under the same multiplying power and electric quantity interval, an average charging and discharging voltage value is taken to construct an average charging and discharging curve, an inflection point is positioned through differential processing, and SOH is estimated through accumulation of electric quantity before and after the inflection point. And intelligently distributing weight coefficients of the three groups of SOH estimation results based on a fuzzy theory to obtain a final SOH value of the battery. According to the method, the accuracy and the reliability of LiFePO4 battery health state evaluation can be remarkably improved, and fault diagnosis and service life prediction of a battery system are facilitated.

The application discloses a SOC estimation method and system of an energy storage battery, which collects working current and small power consumption current through a double-current sampling loop, and obtains fusion current data through smooth switching; the starting SOC value is calibrated based on the standby open circuit voltage when the energy storage battery is at rest; the preliminary SOC estimation value is obtained through ampere-hour integration combining the fusion current and the corresponding integral coefficient; the voltage data is compensated through temperature and current, and the reference SOC value is obtained to modify the preliminary SOC; finally, the SOC is calibrated at the end or directly output according to whether the single voltage enters the end interval of charging and discharging, so that the precise estimation is realized. The application can effectively improve the accuracy of SOC estimation.

The invention relates to a photovoltaic cell and a preparation method of the photovoltaic cell. The photovoltaic cell comprises: a substrate having a textured surface, the textured surface comprising a plurality of first pyramids and a plurality of second pyramids, the plurality of second pyramids being arranged between the plurality of first pyramids; the tower footing size of the second pyramid is larger than that of the first pyramid, and the tower height of the second pyramid is larger than that of the first pyramid. According to the invention, the scattering capability of broadband light can be enhanced, the problem that the traditional single-scale pyramid texture surface is insufficient in scattering of long-wave light is effectively improved, and the light capturing and absorbing effects of the photovoltaic cell are improved; the dual-scale pyramid suede can be better matched with the passivation contact layer, so that the surface recombination phenomenon is reduced, and the high open-circuit voltage of the photovoltaic cell can be maintained; the second pyramid can also provide an adaptive contact basis for the metal electrode, and the contact resistance between the electrode and the substrate is reduced. Therefore, the photoelectric conversion efficiency of the photovoltaic cell can be effectively improved.

The invention discloses a dynamic reconfigurable battery energy storage system active equalization method and device based on open-circuit voltage detection, and belongs to the technical field of battery energy storage systems. Open-circuit voltage data of all single batteries are collected in real time in a high-precision mode, battery states are dynamically grouped through an improved K-means clustering algorithm, circuit topology is flexibly adjusted through a reconfigurable switch array, and energy priority transfer between groups is achieved. Multi-step shortest path control is adopted in the equalization process, and high-efficiency charge adjustment is achieved; the system is provided with a self-adaptive monitoring mechanism, balancing is automatically stopped when the single voltage difference converges to a set threshold value, and key data are filed. The method can also automatically detect and isolate abnormal single batteries, improves the safety and reliability of the system, is suitable for a multi-scale energy storage scene, and has the advantages of high equalization speed, high precision, strong adaptability and the like.

The invention provides a battery charging control method and device, a medium and a product, and relates to the technical field of battery management, and the method comprises the steps: collecting the voltage, current and temperature of a target cell in a constant current charging stage, and calculating the dynamic DC internal resistance and internal resistance growth rate. And determining a basic lithium precipitation boundary voltage according to the temperature, and correcting by using an internal resistance growth rate to obtain a lithium precipitation upper-limit terminal voltage value. And determining a current open-circuit voltage value by looking up a table based on the charge state, the temperature and the internal resistance growth rate. And calculating the maximum charging current value by combining the lithium precipitation upper limit terminal voltage value, the current open-circuit voltage value and the dynamic direct-current internal resistance value. And when the real-time charging current is greater than the maximum charging current, calculating a difference value as an adjusting current value, and converting the adjusting current value into a PWM signal to drive the target bypass shunt circuit to shunt. According to the scheme, the technical problem that an existing charging control strategy is difficult to adapt to physical characteristic changes in the whole life cycle of the battery is solved.

The invention belongs to the technical field of battery management, and particularly discloses a parameter identification method of an equivalent circuit model and an SOC estimation method and system.The parameter identification method of the equivalent circuit model comprises the steps that the equivalent circuit model in the charging direction and the discharging direction is built; respectively carrying out mixed pulse tests on the equivalent circuit models in the charging direction and the discharging direction of each SOC point to be tested to obtain voltage and current data of the parameter identification test of each SOC point to be tested; and obtaining key parameters of the equivalent circuit model in the charging direction and the discharging direction by using a multiple linear regression method. The SOC estimation method comprises the following steps: determining a battery SOC estimation path according to an open-circuit voltage change rate; and according to the key parameters and the SOC estimation path of the battery, establishing simulation models in the charging direction and the discharging direction, and obtaining SOC estimation values in the charging direction and the discharging direction of the battery by using the simulation models. The accuracy of the equivalent circuit model can be improved, the SOC estimation precision is further improved, and the method is more suitable for actual working conditions.