1750 results about "Open-circuit voltage" patented technology

The invention discloses a self-assembled monomolecular layer hole transport material, a hole transport layer and a battery thereof. According to the present invention, the compound having different anchoring groups and represented by the formula (I) can be subjected to firm self-assembly with the substrate surface through the chemical bonding manner, such that the good coverage rate is provided, the film forming quality is increased, and the transmission performance is improved; and meanwhile, the material has a rigid conjugate large-plane condensed ring core structure, so that the hole transmission performance of the material is ensured, and the photovoltaic performance is favorably improved. When the material is applied to a perovskite solar cell to prepare a hole transport layer, the hole extraction capability can be enhanced, and the open-circuit voltage, the filling factor and the photoelectric conversion efficiency of a device can be improved.

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 field of photovoltaic technology, in particular to a solar cell, a photovoltaic module and a preparation method of the solar cell, the solar cell comprises a substrate, the substrate comprises a first surface and a second surface, the first surface comprises a first area and a second area, and the second surface comprises a third area and a fourth area, the first diffusion layer is located on the first area or located in the substrate corresponding to the first area, the first diffusion layer is opposite to the substrate in conductive type, the second diffusion layer is located in the substrate corresponding to the third area, the second diffusion layer is opposite to the first diffusion layer in conductive type, and the first passivation layer is located on the third area and the fourth area. The first passivation layer covers the second diffusion layer and is in contact with the substrate, the first electrode electrically connected with the first diffusion layer is arranged on the first area, the second electrode electrically connected with the second diffusion layer is arranged on the third area, and the open-circuit voltage and the short-circuit current of the solar cell are improved through the design, and the photoelectric conversion efficiency is improved.

The invention relates to the technical field of power batteries, in particular to a power battery pack health state detection method and system. The power battery pack health state detection method comprises the following steps: acquiring open-circuit voltage change data and terminal voltage fluctuation data of a battery under micro current pulse excitation, recording a change curve of voltage along with time through high-precision time sequence acquisition equipment, and obtaining an initial data set of voltage dynamic response; acquiring magnetic field intensity distribution and magnetic field gradient change data of the surface of the battery in a weak alternating magnetic field, and acquiring spatial magnetic field information through a magnetic sensor array to obtain a three-dimensional distribution diagram reflecting magnetic field nonuniformity; through a three-dimensional distribution diagram of magnetic field intensity distribution and magnetic field gradient change, a defect detection algorithm is adopted to analyze a mapping relation between magnetic field non-uniformity and internal micro cracks, and correlation distribution of defect positions and internal resistance growth rates is determined.

The invention discloses a first-order ECM-based parameter and SOC joint estimation method and system, and the method comprises the steps: constructing a first-order RC equivalent circuit model, and constructing a state-space equation of a lithium ion battery based on the first-order RC equivalent circuit model; corresponding open-circuit voltage OCV values under different SOCs are collected according to an HPPC experiment, and the OCV values are fitted to obtain an OCV-SOC relation curve; constructing a state-space equation based on model parameters, performing parameter identification on the model by using a Kalman filtering algorithm optimized based on a suburb wolf algorithm, and calculating a terminal voltage value through an identification result to verify the identification precision; updating a state-space equation related to the SOC based on a parameter identification result; and on the basis of the state-space equation, rapid convergence from the SOC estimated value to the SOC actual value is realized by using a self-adaptive Kalman filtering algorithm based on an innovation matrix. The method is high in estimation precision.

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 relates to a lithium battery state-of-charge and state-of-health joint estimation method, and belongs to the technical field of lithium ion batteries. The method comprises the following steps: performing a cyclic aging experiment on a battery under a cyclic working condition; an open-circuit voltage curve is extracted through data analysis, a first-order equivalent circuit model is selected to construct a circuit, and a state equation is written; carrying out parameter identification by adopting a multi-forgetting factor recursive least square algorithm, and constructing an SOC estimator of an unscented Kalman filter based on a state equation and an observation equation to carry out SOC estimation; constructing an SOH estimation observer based on an extended Kalman filter, and estimating the SOH by using the estimated SOC; carrying out segmented dynamic identification on the open-circuit voltage curve by adopting an average moving method in combination with recursive least squares; and coupling the SOC estimator and the SOH estimator, and realizing SOC and SOH joint online estimation by applying the dynamically identified open-circuit voltage curve.

The invention discloses a method for passivating a perovskite solar cell by using diphenylamine ammonium salt and a derivative thereof, and belongs to the technical field of perovskite solar cells. According to the method, diphenylamine ammonium salt and a derivative thereof are introduced as an interface modification layer of perovskite through a solution spin-coating process, so that in-situ passivation is realized. The diphenylamino ammonium salt and the derivative thereof can effectively reduce surface defects of perovskite, passivate uncoordinated lead ions, supplement iodine vacancies, significantly reduce non-radiative recombination of a perovskite layer and promote charge extraction by virtue of unique properties of the diphenylamino ammonium salt and the derivative thereof, so that the open-circuit voltage and fill factors of the perovskite solar cell are improved. Meanwhile, large-volume ammonium cations can be gathered on a crystal boundary, so that the defect of the crystal boundary is filled, and ion migration is inhibited. In addition, after passivation, moisture can be effectively prevented from invading the three-dimensional perovskite structure, and the humidity stability and the storage stability of a cell device are remarkably improved. The invention aims at improving the photoelectric conversion efficiency of the perovskite solar cell and realizing the long-term stability of the device performance.

The invention provides a lithium battery internal short circuit diagnosis method based on interpretable machine learning, and the method comprises the steps: collecting voltage, current and time data of a battery in a constant-current charging process under different internal short circuit degrees, and building an experiment data set; preprocessing and filtering the voltage data, calculating the ratio of the voltage increment to the capacity increment, and obtaining the IC curve characteristics of the capacity increment; extracting a battery state-of-charge-open-circuit voltage relationship, and establishing a battery equivalent circuit model for a constant current stage; estimating the state of charge of the battery through an extended Kalman filtering algorithm and battery charging data; extracting characteristic parameters from the IC curve, wherein the characteristic parameters comprise a peak value, a peak position and an area between peaks; time sequence features are extracted based on a state of charge estimation result, and a multi-dimensional feature space is constructed; carrying out standardization processing on the extracted features, and constructing a classification model; and a Shapril additive feature interpretation method is introduced to realize interpretability analysis of a classification model decision process.

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 discloses a power battery box positioning and monitoring method based on low power consumption application, relates to the technical field of battery box positioning and monitoring, and is used for solving the problem of high power consumption in a power battery box monitoring process. According to the method, the battery remaining capacity is calculated through voltage, current and temperature data, temperature compensation and open-circuit voltage correction are combined, high-reliability electric quantity characteristics are constructed, the motion state is detected according to the three-axis acceleration sensor, the charge level, the environmental risk and the moving event are fused to generate a dynamic decision vector, and the geographical fence range is intelligently adjusted. A monitoring area is expanded when the electric quantity is high, a safety core area is contracted when the electric quantity is low, a global positioning technology or an indoor positioning technology is automatically switched based on indoor and outdoor scenes, invalid positioning energy consumption is reduced through a mobile triggering mechanism, a positioning state is analyzed in real time, a graded response signal is generated, and redundant positioning is started under abnormal conditions to guarantee monitoring continuity. And the balance of full-period safety protection and low-power-consumption operation of the power battery box is realized, and the cruising ability is improved.

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 decommissioned battery virtual high capacity scoring and screening method and system, relates to the technical field of battery detection and evaluation, and aims to solve the problem that decommissioned battery virtual high capacity identification is difficult, and the method comprises the following steps: S1, performing discharge operation on a battery and standing, and monitoring an open-circuit voltage in a standing process in real time to obtain a voltage recovery curve; s2, extracting a multi-modal dynamic feature from the voltage recovery curve, wherein the multi-modal dynamic feature comprises a voltage recovery time constant and a curve fitting residual error; s3, performing weighted fusion on the multi-modal dynamic features and outputting a standardized score value to obtain a health score; and S4, comparing the health score with a preset threshold value, and outputting a virtual high-capacity risk grade screening result.

The invention relates to a photovoltaic cell preparation method, a photovoltaic cell, a laminated cell and a photovoltaic cell module. Providing an initial battery piece; depositing and forming a protective layer on the surface; carrying out laser treatment twice; printing and sintering to form an electrode; and carrying out at least two times of laser-assisted sintering on the electrode. According to the photovoltaic cell preparation method, the protection layer at the first area is removed, the doping concentration at the first area is improved, and at least two times of laser-assisted sintering are combined, so that on one hand, the metal contact area is optimized, the usage amount of silver paste is reduced, the material cost is reduced, and meanwhile, paste contact sintering is enhanced; damage caused by laser grooving doping is removed; and on the other hand, the doping concentration is optimized, the contact resistance is remarkably reduced, the open-circuit voltage and the filling factor are favorably improved, the shading loss is reduced, and the current collection efficiency is ensured, so that the photoelectric conversion efficiency and the reliability of the cell are remarkably improved, the production process is simplified, and the production cost is reduced.

The invention provides a state of charge estimation method, electronic equipment, a storage medium and a program product, which are applied to a battery system of a pure electric heavy truck. The method comprises the following steps: acquiring current temperatures, open-circuit voltages and current currents of a plurality of single batteries of a battery pack in a battery system, and a working mode of a battery box; aiming at each single battery, according to the current temperature and the open-circuit voltage, respectively determining a state-of-charge initial value and available capacity from a first mapping table and a second mapping table; according to the current, the state-of-charge initial value and the available capacity, determining a state-of-charge target value of the single battery; determining a first charge state estimated value of the battery pack according to the charge state target values of all the single batteries; and based on the working mode and a preset correction requirement, carrying out correction processing on the first charge state estimation value to obtain a second charge state estimation value of the battery pack. According to the invention, the battery system management efficiency of the pure electric heavy truck is optimized by improving the precision and adaptability of SOC estimation.

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.

A method for estimating current-dependent non-linear equivalent circuit model (ECM) parameters of a battery may include measuring a battery voltage across terminals of the battery and a battery current drawn from the battery, deriving linear ECM parameters for modeling a linear ECM of the battery with multiple resistive-capacitive elements with different time constants to characterize temporal behaviors of the battery, continuously tracking an impedance for each of the multiple resistive-capacitive elements and an open circuit voltage of the battery, continuously monitoring the battery current to detect high current events, continuously tracking a deviation for each of the multiple resistive-capacitive elements during the high current events, and deriving non-linear online ECM parameters based on the linear ECM parameters and the deviations for the multiple resistive-capacitive elements during the high current events.

The invention relates to the technical field of charging, and particularly discloses a method for dynamically optimizing the full charge capacity of a lithium battery in an unbalanced state. Dynamically adjusting the standing duration according to the average temperature and the cycle index of the current battery pack, standing to eliminate the polarization effect, and obtaining stable open-circuit voltage of each monomer; inquiring a pre-established open-circuit voltage-state-of-charge characteristic table based on the obtained minimum monomer voltage to obtain the state of charge of the minimum-capacity monomer; generating a segmentation correction formula based on a segmentation threshold value and a gain coefficient dynamically determined by utilizing a large number of full charge capacity correction examples; updating the full-charge capacity by adopting a segmented correction formula and the charge state of the minimum-capacity monomer to obtain a full-charge capacity dynamic optimization result; the accuracy of full charge capacity calculation is effectively improved, the real full charge capacity of the lithium battery in an unbalanced state is better reflected, the service life of the battery is prolonged, and the use efficiency of the battery is 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.

The invention provides a parameter identification method of a lithium battery fractional order model, a medium and equipment, which can determine output data of the fractional order model according to open-circuit voltage correction data and initial values of model parameters, and determine a target function value according to the output data and data used for fitting under various working conditions. Determining a used model optimization algorithm and a search range corresponding to the model parameters according to the convergence trend of the target function value, adjusting the initial values of the model parameters according to the search range, and continuously fitting the model parameters of the fractional order model according to the open-circuit voltage correction data and the data used for fitting under various working conditions, according to the method, the precision and the stability of the model in the state of charge estimation process can be improved, the internal real electrochemical reaction environment can be better reflected through optimization and adjustment of the model parameters, the local precision and the global optimal performance can be considered, and the method is suitable for large-scale popularization and application. And the optimization convergence speed is accelerated.

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 discloses a system for improving multi-series parallel power generation of photovoltaic cells, and relates to the technical field of photovoltaic power supply, the system comprises photovoltaic panels, photovoltaic optimizers, a photovoltaic gateway and an inverter, the power output of a photovoltaic array is optimized through a multi-stage cooperative control strategy, each photovoltaic panel is connected with an independent photovoltaic optimizer, and the photovoltaic panels are connected with the photovoltaic gateways. A working point is dynamically adjusted by adopting an MPPT algorithm, real-time data interaction with a photovoltaic gateway is carried out in a wireless or wired communication mode, the photovoltaic gateway automatically detects open-circuit voltage differences of parallel strings, dynamically adjusts the MPPT voltage range of each string and ensures the overlapping proportion of output voltages, the photovoltaic gateway monitors the duty ratio change of the strings, and when shielding is detected, the photovoltaic gateway is switched on and switched off. The MPPT parameters of the affected string are automatically adjusted, and the generating capacity of the system is improved.

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 simple lithium ion battery physical dynamic modeling method for fast charging. The method comprises the following steps: S01, designing a characteristic test signal; S02, constructing an ohmic impedance response module; S03, constructing a diffusion dynamic voltage drop module; s04, an open-circuit voltage lookup table module is constructed; and S05, a lithium ion battery model is composed of three parts including an ohmic impedance dynamic response module, a diffusion dynamic voltage drop module and the open-circuit voltage lookup table module, and modeling is carried out on the terminal voltage, the positive electrode and the negative electrode of the whole battery. According to the method, ohmic impedance dynamic response, diffusion dynamic voltage drop and a full battery (OCV) are simulated based on a model, then the terminal voltage, the positive electrode and the negative electrode of the full battery are modeled, it is verified that the diffusion behavior of the negative electrode is a key influence factor of a low SOC error through a constant-current discharge experiment, and the dynamic response characteristic of the battery model is verified through simulation; and a feasible basis is provided for optimization of a fast charging strategy of the lithium ion battery.

The invention discloses a health assessment method of a vehicle-mounted battery system and a vehicle. The method comprises the following steps: under the condition of determining that a charge state value of a battery system meets a preset discharge condition, discharging the battery system until the voltage of a single battery of the battery system meets a preset calibration condition; calibrating the state-of-charge value of the battery system based on the relation curve of the state-of-charge value and the open-circuit voltage and the open-circuit voltage of the battery system; charging the calibrated battery system until the state-of-charge value of the battery system meets a preset full charge condition; and evaluating the health state of the battery system based on the original capacity and the actual charging capacity of the battery system, and generating a health evaluation result of the battery system. According to the invention, the technical problems of difficult long-term running vehicle battery state capacity test and insufficient test precision in the prior art are solved.

The present application relates to a method for equalization control of a battery pack, comprising: detecting an open-circuit voltage of each battery cell of the battery pack after a charging cycle of the battery pack is ended (S1); when the first open-circuit voltage of the first battery cell is lower than a predetermined voltage threshold value, a second battery cell with the highest open-circuit voltage is discharged, and the discharge amount W of the second battery cell is determined as the difference between the first deviation X and the discharge adjustment amount M. A first deviation X between a first charge state of charge of the first battery cell and a second charge state of charge of the second battery cell is determined on the basis of the charge SOC-OCV curve and the detected open circuit voltage of the battery cells, and a discharge adjustment amount M is determined on the basis of at least the charge and discharge SOC-OCV curve of the battery cells (S2). According to the invention, the charging and discharging cycle period number of the battery can be greatly reduced in the equalization process of the battery pack, and the efficiency of the equalization process of the battery pack is effectively improved.