CN117175747B - High-voltage energy storage power system and battery cluster state accurate sensing method thereof - Google Patents
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Abstract
The invention provides a high-voltage energy storage power system and a battery cluster state accurate sensing method thereof, comprising the following steps: the system comprises a battery cluster, a starting protection circuit, a PCS unit, a fault bypass circuit, a direct-current side filter inductor, a bus capacitor, a PCS unit sub-controller and a BMS; the direct-current side positive electrode of the PCS unit is sequentially connected with a direct-current side starting protection circuit, a battery cluster and a direct-current side filter inductor in series and then is connected with the direct-current side negative electrode of the PCS unit; the alternating-current side anodes of the PCS units are sequentially connected in series; the bus capacitor is connected in parallel with two poles of the direct current side of the PCS unit; the PCS unit sub-controller is respectively connected with the fault bypass circuit, the PCS unit, the starting protection circuit and the BMS; the BMS is connected with the battery cluster.
Description
Technical Field
The invention relates to the technical field of electric automation equipment, in particular to a high-voltage energy storage power system and a battery cluster state accurate sensing method thereof, and more particularly relates to a high-voltage energy storage power module with the battery cluster state accurate sensing capability and a combined capacity expansion method thereof.
Background
Existing battery energy storage systems can be broadly divided into two main categories, low voltage energy storage systems and high voltage energy storage systems, the low voltage energy storage systems being composed of a battery stack and battery management system (battery management system, BMS), a low voltage inverter (power conversion system, PCS) and a boost transformer. The single-machine capacity can be improved only by increasing the serial-parallel scale of the battery cells in the battery stack. However, the serial-parallel connection scale of the battery cells is limited by technologies such as battery materials, battery groups, BMS and the like, and the economic and safe capacity of the battery stack is generally in the order of hundreds of kilowatts. Hundreds of devices are generally connected in parallel on a low-voltage alternating-current side for building the hundred-megawatt energy storage power station, and the energy storage power station is complex in current collection and information system, difficult in cooperative control, poor in stability and long in instruction response time, and cannot meet future development demands.
The high-voltage high-capacity battery energy storage system divides mass battery cells required by the system into a plurality of battery clusters (formed by connecting the battery cells in series) through a high-voltage direct-hanging PCS, is connected to the direct-current side of a power module in a scattered manner, and increases the output voltage of the PCS and the single-machine capacity through cascading of the alternating-current side of the battery clusters, so that a high-voltage power grid of 35kV and above grade can be hung without a transformer. The high-voltage energy storage system has a highly modularized structure, can theoretically realize the single-machine large-capacity requirement of the energy storage system, takes a double star-shaped parallel structure as an example, and can reach hundred megawatts in the single-machine maximum capacity theory when a 35kV power grid is hung directly, thereby being more suitable for the future large-scale development requirement of new energy. However, in practical application, parameters of a mass battery core of the high-voltage energy storage system continuously change in the service process, the degree of inconsistency is gradually increased, the wooden barrel effect is aggravated, the risk of over-charging and over-discharging of local battery cores is increased, the whole system is withdrawn from operation due to the phenomenon that a certain battery core is over-charged and discharged or fails, and the utilization rate and the safety of a battery system (the battery system is formed by dispersed battery clusters) are reduced. In addition, the variation of the battery cells directly causes significant difference of parameters such as effective capacity, internal resistance and the like of each battery cluster, but the current high-voltage direct-hanging PCS is mainly responsible for charge and discharge control of the battery, the BMS is mainly responsible for balanced control of the battery cells in the battery module and state management of the battery cells, and the battery cells are insufficient in real-time state sensing capability of the battery clusters on the whole life cycle, so that reasonable energy balanced control among the battery clusters with inconsistent parameters cannot be achieved, and safety and high efficiency management and control of massive battery cells are not facilitated.
The premise of realizing the safe, efficient and balanced control of the energy of the battery clusters at different levels by the high-voltage direct-hanging PCS is that key parameters such as the internal resistance, the effective capacity and the like of a plurality of dispersed battery clusters can be accurately obtained in real time. At present, PCS mainly obtains battery cluster parameters through BMS, but BMS can not realize on-line measurement of battery cluster internal resistance, and the acquisition of real-time internal resistance information is a precondition of accurate perception of key parameters such as effective capacity, state of charge (SOC) and the like. At present, the information transmitted by the BMS to the PCS for energy balance of the battery system only has SOC (state of charge), which is the only control basis for the PCS to realize energy balance of the battery cluster, and the SOC balance control mode is only suitable for the condition of better consistency of battery parameters in the initial stage of service. However, as the service time is prolonged, the inconsistency of the parameters such as the effective capacity, the internal resistance, the voltage and the like of the battery cluster is gradually increased due to the variation of the parameters of the battery cells, and the inconsistent parameters are comprehensively considered according to the control basis of energy balance.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a high-voltage energy storage power system and a battery cluster state accurate sensing method thereof.
According to the present invention, there is provided a high voltage stored energy power system comprising: the system comprises a battery cluster, a starting protection circuit, a PCS unit, a fault bypass circuit, a direct-current side filter inductor, a bus capacitor, a PCS unit sub-controller and a BMS;
the direct-current side positive electrode of the PCS unit is sequentially connected with a direct-current side starting protection circuit, a battery cluster and a direct-current side filter inductor in series and then is connected with the direct-current side negative electrode of the PCS unit; the alternating-current side anodes of the PCS units are sequentially connected in series; the bus capacitor is connected in parallel with two poles of the direct current side of the PCS unit;
the PCS unit sub-controller is respectively connected with the fault bypass circuit, the PCS unit, the starting protection circuit and the BMS;
the BMS is connected with the battery cluster.
Preferably, the PCS unit is implemented using a half-bridge or full-bridge topology.
Preferably, the battery cluster is formed by connecting a plurality of battery cells in series.
Preferably, the application scene, the single-machine capacity and the selected battery type influence factors are comprehensively considered, and the star-shaped chain type, the triangle-shaped chain type and the double-star-shaped parallel chain type are selected to realize the alternating-current side cascade combination capacity expansion of the high-voltage energy storage power system.
According to the battery cluster state accurate sensing method provided by the invention, the high-voltage energy storage power system is utilized to realize the following steps:
step S1: the PCS unit sub-controller realizes active pulse power injection of the PCS unit to the battery cluster by superposing different frequency harmonic voltages in the PCS unit modulation wave;
step S2: acquiring battery pulsating voltage and current information, identifying battery internal resistance model parameters through the acquired battery pulsating voltage and current information, and transmitting the identified battery internal resistance model parameters to the BMS;
step S3: and the BMS utilizes the identified battery internal resistance model parameter and the PCS unit sub-controller to jointly perform effective capacity on-line estimation of the battery cluster.
Preferably, the step S1 employs: determining a harmonic voltage frequency sequence which is injected into an alternating current port of the PCS unit and does not affect the normal operation of the PCS unit; the PCS unit sub-controller realizes active pulse power injection of the PCS unit to the battery cluster by superposing different frequency harmonic voltages in the PCS unit modulation wave.
Preferably, the step S2 employs:
step S2.1: collecting battery pulsating voltage and current information, and carrying out Fourier decomposition on the battery pulsating voltage and current to obtain voltage and current components of the battery under different pulsating frequencies;
step S2.2: calculating impedance amplitude and phase angle under different pulsation frequencies;
step S2.3: and calculating based on impedance amplitude values and phase angles under different pulsation frequencies to obtain battery internal resistance model parameters, and transmitting the battery internal resistance model parameters to the BMS.
Preferably, the step S3 employs: the BMS uses an extended Kalman filtering algorithm to estimate the polarization voltage drop on the RC parallel branch and the open circuit voltage of the battery cluster on line according to the battery internal resistance model parameters, and carries out SOC estimation according to the open circuit voltage at the charge and discharge end according to an OCV-SOC curve measured off line, and simultaneously estimates the effective capacity of the battery cluster on line at the charge and discharge end through a charge transfer method.
Preferably, the energy state of the battery cluster is represented according to the estimated effective capacity, terminal voltage and SOC parameters of the battery cluster.
Preferably, the OCV-SOC curves of the battery clusters under different working conditions are normalized by considering the difference of the effective capacity of the lithium battery and the ambient temperature, so that the OCV-SOC curve under any state of any battery cluster is obtained by performing the OCV-SOC test only once.
Compared with the prior art, the invention has the following beneficial effects:
1. the online accurate sensing method for the parameters of the battery system by the cooperation of the high-voltage direct-hanging PCS and the BMS is provided. The on-line identification of the internal resistance of the battery cluster is carried out through PCS active broadband pulse power injection, BMS and PCS realize the accurate estimation of the effective capacity and the SOC of the battery cluster by utilizing the cooperation of real-time internal resistance information, and the short plates which are difficult to accurately estimate the battery state under the battery cell parameter variation background only by the BMS are compensated through the deep fusion of the two.
2. The safe and efficient utilization of the whole life cycle of the battery cluster can be achieved through the accurate sensing of the state of the battery cluster.
3. The single-machine capacity of the system can be greatly improved by the alternating current measurement cascade combined capacity expansion method of the high-voltage energy storage power module, and the theory of the single-machine capacity can reach hundred megawatts.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings.
Fig. 1 is a schematic diagram of a high voltage energy storage power module with accurate sensing capability of a battery cluster state.
Fig. 2 is a flowchart of online accurate sensing of key parameters of a battery system with a high-voltage direct-hanging PCS and BMS.
Fig. 3 is a schematic diagram of battery cluster pulsed power injection.
Fig. 4 is a schematic diagram of a battery cluster equivalent circuit model.
Fig. 5 is a flowchart for establishing a battery cluster discretization state and observation based on an EKF algorithm.
FIG. 6 is a schematic diagram of normalized adaptive fit of OCV-SOC curves.
Fig. 7 is a schematic diagram of a star-chain high-voltage energy storage system.
Fig. 8 is a schematic diagram of a high-voltage energy storage system with a triangular chain structure.
Fig. 9 is a schematic diagram of a high-voltage energy storage system with a double star-shaped parallel structure.
Fig. 10 is a schematic diagram of a half-bridge power module.
Fig. 11 is a schematic diagram of a full bridge power module.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present invention.
Example 1
According to the present invention, there is provided a high voltage stored energy power system comprising: the system comprises a battery cluster, a starting protection circuit, a PCS unit, a fault bypass circuit, a direct-current side filter inductor, a bus capacitor, a PCS unit sub-controller and a BMS;
the direct-current side positive electrode of the PCS unit is sequentially connected with a direct-current side starting protection circuit, a battery cluster and a direct-current side filter inductor in series and then is connected with the direct-current side negative electrode of the PCS unit; the alternating-current side anodes of the PCS units are sequentially connected in series; the bus capacitor is connected in parallel with two poles of the direct current side of the PCS unit;
the PCS unit sub-controller is respectively connected with the fault bypass circuit, the PCS unit, the starting protection circuit and the BMS;
the BMS is connected with the battery cluster.
Specifically, the high-voltage energy storage power system externally displays an alternating current power port and an information communication port.
Specifically, the PCS unit is implemented in a half-bridge or full-bridge topology.
Specifically, the battery cluster is formed by connecting a plurality of battery monomers in series.
Specifically, the application scene, the single-machine capacity and the influence factors of the selected battery types are comprehensively considered, and the star-shaped chain type, the triangle-shaped chain type and the double-star-shaped parallel chain type are selected to realize the alternating-current side cascade combination capacity expansion of the high-voltage energy storage power system.
According to the battery cluster state accurate sensing method provided by the invention, the high-voltage energy storage power system is utilized to realize the following steps:
step S1: the PCS unit sub-controller realizes active pulse power injection of the PCS unit to the battery cluster by superposing different frequency harmonic voltages in the PCS unit modulation wave;
step S2: acquiring battery pulsating voltage and current information, identifying battery internal resistance model parameters through the acquired battery pulsating voltage and current information, and transmitting the identified battery internal resistance model parameters to the BMS;
step S3: and the BMS utilizes the identified battery internal resistance model parameter and the PCS unit sub-controller to jointly perform effective capacity on-line estimation of the battery cluster.
Specifically, the step S1 employs: determining a harmonic voltage frequency sequence which is injected into an alternating current port of the PCS unit and does not affect the normal operation of the PCS unit; the PCS unit sub-controller realizes active pulse power injection of the PCS unit to the battery cluster by superposing different frequency harmonic voltages in the PCS unit modulation wave.
Specifically, the step S2 employs:
step S2.1: collecting battery pulsating voltage and current information, and carrying out Fourier decomposition on the battery pulsating voltage and current to obtain voltage and current components of the battery under different pulsating frequencies;
step S2.2: calculating impedance amplitude and phase angle under different pulsation frequencies;
step S2.3: and calculating based on impedance amplitude values and phase angles under different pulsation frequencies to obtain battery internal resistance model parameters, and transmitting the battery internal resistance model parameters to the BMS. According to the number of equivalent circuit model parameters, 2m+1 impedance solving equation sets for solving the internal resistance equivalent circuit model parameters; wherein,representing the battery cluster equivalent circuit model order.
Specifically, the step S3 employs: the BMS uses an extended Kalman filtering algorithm to estimate the polarization voltage drop on the RC parallel branch and the open circuit voltage of the battery cluster on line according to the battery internal resistance model parameters, and carries out SOC estimation according to the open circuit voltage at the charge and discharge end according to an OCV-SOC curve measured off line, and simultaneously estimates the effective capacity of the battery cluster on line at the charge and discharge end through a charge transfer method.
Specifically, the energy state of the battery cluster is represented according to the estimated effective capacity, terminal voltage and SOC parameters of the battery cluster.
Specifically, the OCV-SOC curves of the battery clusters under different working conditions are normalized by considering the difference of the effective capacity of the lithium battery and the ambient temperature, so that the OCV-SOC test is only needed to be carried out once for any battery cluster to obtain the OCV-SOC curve under any state.
Example 2
Example 2 is a preferred example of example 1
Referring to fig. 1, a high-voltage energy storage power system with a battery cluster state accurate sensing capability is disclosed in the invention, wherein a dotted arrow in fig. 1 represents an information flow interaction with a BMS; solid arrows represent the flow of interaction information with the sub-controllers; the internal structure of the high-voltage energy storage power system comprises: the power conversion system comprises a battery cluster S, a power conversion unit, a bus capacitor, a direct current side filter inductor, a power buffer link K, a fault bypass circuit, a starting circuit, a power conversion unit sub-controller, a BMS and the like. The direct current side positive electrode of the H-bridge or half-bridge power unit is sequentially connected with the direct current side pre-charging device L, the direct current fuse G, the battery cluster and the direct current side filter inductor in series and then is connected with the direct current side negative electrode of the H-bridge or half-bridge power unit, the alternating current side positive electrode of the H-bridge or half-bridge power unit is sequentially connected with the direct current side positive electrode of the H-bridge or half-bridge power unit in series, and the bus capacitor is connected with the two poles of the direct current side of the H-bridge or half-bridge power unit in parallel. Based on the standard sub-modules, high-voltage high-capacity energy storage equipment with different requirements can be conveniently constructed through the configuration of the upper main control system. The high-voltage energy storage power system externally shows an alternating current power port and an information communication port, the depth cooperation of the PCS unit F and the BMS is realized in the high-voltage energy storage power system to accurately identify the battery state, the PCS unit F performs internal resistance identification of the battery cluster through active pulse power injection, and the BMS performs online estimation of the effective capacity of the battery cluster by utilizing the measured real-time internal resistance information and the PCS unit F. Referring to fig. 2-6, a high-voltage direct-hanging PCS and BMS cooperative battery system key parameter online accurate sensing technology roadmap is provided for the invention. The specific implementation of the time division four steps is as follows:
step S0: determining a pulsating power frequency sequence injected into the battery cluster by the power conversion unit;
as shown in fig. 3, where O represents ac-side fundamental frequency voltage and current; p represents DC power;i dc representing the direct current bus current of the power module;representing DC bus capacitanceC sm Is set to be a current of (a);L sm representing the direct current side filter inductance;i b representing a battery cluster current; first determining that the PCS unit AC port injection is not affected by the positive thereofAnd analyzing the relation between the frequency of the injected harmonic voltage and the frequency of the pulsating power entering the battery cluster, wherein the injection control of the broadband pulsating power and the solution of the internal resistance information are mainly completed by sub-controllers of PCS units, and each PCS unit comprises one sub-controller. Assume that the injection frequency into the battery cluster isf 0 Is generated at a frequency off 1 Is generated at a frequency of both the voltage and the current of the battery clusterf 1 By detecting the amplitude and phase angle of the voltage and current components, the impedance amplitude of the battery cluster at the frequency can be calculatedZ f1 Phase angleθ f1 As shown in formula (1), the frequency isf 1 2 internal resistance parameter solving equations can be established under the pulsating power of the frequency converter, and the equations can be also established under the pulsating power of other frequencies;
(1)
wherein,representing the frequency asf 1 Is a battery voltage ripple magnitude, ">Representing the frequency asf 1 Is>Representing the frequency asf 1 Is>Representing the frequency asf 1 The phase of the battery ripple current;
step S1: establishing a battery cluster equivalent circuit model and a model parameter solving equation set;
the on-line detection of the internal resistance of the battery cluster is a precondition for on-line accurate sensing of the effective capacity and the SOC. Comprehensively considering model precision and modelingThe complexity adopts a second-order equivalent circuit model, and the high-voltage direct-hanging PCS is taken as an illustration to carry out the on-line detection process of the internal resistance of the battery cluster. With reference to figure 2 of the drawings,R b is equivalent ohmic internal resistance of the battery cluster, which is ohmic internal resistance of all the series-connected battery cellsR s And the internal connection line resistance of the battery clusterR L And (3) summing.R 1 、R 2 In order to polarize the resistance of the resistor,C 1 、C 2 in order to polarize the capacitance of the capacitor,R 1 andC 1 the parallel circuit characterizes the electrochemical polarization phenomenon,R 2 andC 2 the parallel circuit characterizes concentration polarization phenomenon.u 1 Andu 2 in order to polarize the voltage drop,u R is the ohmic internal resistance voltage drop,u b andi b for the battery cluster operating voltage and current,Uocv is the cell cluster open circuit voltage. The model parameters to be detected areR b ，R 1 ，R 2 ，C 1 ，C 2 . At least 5 different equations are established to solve 5 different internal resistance parameters, at least three different frequencies of pulsating power are injected into the battery cluster, so that the frequency of the injected pulsating power can be increased, the corresponding internal resistance parameter solving equation can be increased, at the moment, the internal resistance solving results under different equation sets can be cross-verified and averaged to reduce measurement errors. The direct current side of the half-bridge power module is provided with a fundamental frequency V1 and a double frequency pulsating power V2, and the fundamental frequency pulsating power V1 and the double frequency pulsating power V2 are inherent pulsating power; the pulsating power V3 of other frequencies can be generated by injecting a harmonic voltage V of a specific frequency on the ac side of the module as required. And carrying out Fourier decomposition on the current and terminal voltage of the battery cluster to obtain the amplitude and the phase of the pulsating voltage and the current with different frequencies, establishing impedance amplitude and phase equations under different frequencies according to the amplitude and the phase, establishing equivalent circuit model parameters to solve equation sets by combining the impedance amplitude and the phase equations under different frequencies, and solving the internal resistance of the battery cluster under real-time working conditions. At a specific frequencyf 1 The established amplitude and phase equations are:
(2)
wherein,indicating a pulsation frequency off 1 Is included in the pulse component angular frequency of the pulse component.
Step S2: and establishing a battery cluster discretization state and an observation equation based on an extended Kalman filtering algorithm, and carrying out on-line estimation of the SOC and the SOH of the battery cluster.
BMS can identify the average value of the pulse period of the polarized voltage by using the real-time internal resistance parameters obtained through identification through an extended Kalman filtering algorithmU 1 AndU 2 the discrete state space equation of the battery cluster is established under the extended Kalman filtering algorithm as follows:
(3)
wherein,is thatkState variable of time system->In the form of a state transition matrix,T s for cell cluster current period averageI bk Is used for the sampling period of (a),τ 1 =R 1 C 1 andτ 2 =R 2 C 2 is two in numberRCTime constant of the parallel loop. u (u) k =I bk To at the same timekInput of the time of day system->For the input matrix of the system,ηfor the coulombic efficiency of the battery,Qis the battery cluster capacity. />To at the same timekSystem output at time,/->For the system output matrix>Is a feed forward matrix of the system. />For the process noise of the system->For observation noise affected by the sensor accuracy and the outside, both noises are gaussian white noise with an average value of 0 and independent from each other. A is that k-1 ，X k-1 ，B k-1 ，u k-1 ，w k-1 Respectively representing the corresponding physical magnitude at time k-1. ThenkThe open circuit voltage of a battery cluster at a time can be estimated as:
(4)
the real-time internal resistance information obtained through PCS active test is used in the open circuit voltage estimation, so that the open circuit voltage estimation accuracy can be ensured.
After the estimation of the open-circuit voltage of the battery cluster is completed, the off-line measured OCV-SOC curve can be used for estimating the SOC of the battery cluster at the charge and discharge end of the battery cluster according to the open-circuit voltage and estimating the effective capacity of the battery cluster according to a state-of-charge transfer methodQ e As shown in formula (5). Since the accuracy of SOC estimation is high at the charge and discharge end according to the OCV-SOC curve, the estimation accuracy of effective capacity can be ensured.
(5)
The PCS performs normalization processing on the OCV-SOC curve according to the estimated effective capacity, namely, the actual effective capacity obtained by online estimation is used as the calibration basis of the SOC of each battery cluster, and the effective capacity is adjusted according to the ambient temperature, as shown in a formula (6), whereinλ T For different ringsThe proportionality coefficient of the effective capacity of the battery cluster at the ambient temperature can be obtained through static capacity test data fitting.
(6)
By adopting the OCV-SOC curve normalization method, for any battery module, under the condition of knowing the effective capacity and certain ambient temperature, the OCV-SOC curve in any state can be obtained by only performing an OCV test once. The related research results can be popularized and borrowed into the OCV-SOC curve test of the battery cluster, so that the OCV-SOC curve test process of the battery cluster with different aging degrees can be simplified, and the adaptability of the OCV-SOC curve to the parameter variation of the battery cluster is improved.
Step S3: and carrying out energy state characterization of the battery clusters of different levels according to the battery cluster state parameters obtained through online estimation.
After the on-line sensing of the parameters of the battery clusters is completed, in order to realize safe and efficient cooperative control of the battery clusters with inconsistent parameters, the energy states of the battery clusters are characterized according to the identification parameters and are used as the basis for real-time power distribution of the battery clusters of each level. After the capacity reference value of each battery cluster is changed, the residual capacity of each battery cluster cannot be accurately reflected by taking the SOC as a unique variable, so that the residual capacity needs to be measured together by using the SOC and the actual effective capacity at the same time. In addition, the voltage of the battery cluster also has certain discreteness, and it is also necessary to incorporate the battery cluster voltage into the energy state characterization parameter. Thus introducing an energy state characterization factor represented by formula (7)E m It is reasonable to represent the real-time energy state of the battery cluster.
(7)
And calculating energy state characterization factors of battery clusters of all levels to obtain energy state characterization of the battery clusters in the bridge arm, energy state characterization of the battery clusters among the bridge arms and energy state characterization of the battery clusters among the phases.
Referring to fig. 7-11, therein is included: the battery cluster S, the high-voltage power grid M and the power module N are the inventionThe provided alternating current measurement cascade combined capacity expansion method of the high-voltage energy storage power module with the battery cluster state accurate sensing capability provides three capacity expansion schemes including a star chain type, a triangle chain type, a double star parallel chain type and the like, and the half-bridge power module is only applicable to a double star parallel structure high-voltage energy storage system; the full-bridge power module is suitable for a star-shaped chain-type structure high-voltage energy storage system, a triangle-shaped chain-type structure high-voltage energy storage system and a double-star-shaped parallel-type structure high-voltage energy storage system, and the specific capacity expansion scheme is selected by comprehensively considering influencing factors such as application scenes, single-machine capacity, selected battery types and the like. The system inner submodules under different combined capacity expansion schemes are all cascaded through an alternating current side to form a phase bridge arm, and the difference is the connection relation between the bridge arms. In figures 7 and 8 of the drawings,v sa ,v sb ,v sc respectively the voltages of the three-phase power grid,i a ,i b ,i c the three phases of output currents of the converter are respectively,v a ,v b ,v c the three-phase output voltage of the converter. In FIG. 9i pa ,i pb ,i pc The current of the upper bridge arm of the system is respectively,i na ,i nb ,i nc the current of the lower bridge arm of the system is respectively,v pa ,v pb ,v pc respectively outputting voltage to upper bridge arm of the system,v na ,v nb ,v nc and respectively outputting voltages to the lower bridge arm of the system.
Those skilled in the art will appreciate that the systems, apparatus, and their respective modules provided herein may be implemented entirely by logic programming of method steps such that the systems, apparatus, and their respective modules are implemented as logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc., in addition to the systems, apparatus, and their respective modules being implemented as pure computer readable program code. Therefore, the system, the apparatus, and the respective modules thereof provided by the present invention may be regarded as one hardware component, and the modules included therein for implementing various programs may also be regarded as structures within the hardware component; modules for implementing various functions may also be regarded as being either software programs for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the invention. The embodiments of the present application and features in the embodiments may be combined with each other arbitrarily without conflict.
Claims (7)
1. The battery cluster state accurate sensing method is characterized by comprising the following steps of:
step S1: the PCS unit sub-controller realizes active pulse power injection of the PCS unit to the battery cluster by superposing different frequency harmonic voltages in the PCS unit modulation wave;
step S2: acquiring battery pulsating voltage and current information, identifying battery internal resistance model parameters through the acquired battery pulsating voltage and current information, and transmitting the identified battery internal resistance model parameters to the BMS;
step S3: BMS utilizes the identified battery internal resistance model parameter and PCS unit sub-controller to jointly carry out effective capacity on-line estimation of the battery cluster;
the high voltage stored energy power system comprises: the system comprises a battery cluster, a starting protection circuit, a PCS unit, a fault bypass circuit, a direct-current side filter inductor, a bus capacitor, a PCS unit sub-controller and a BMS;
the direct-current side positive electrode of the PCS unit is sequentially connected with a direct-current side starting protection circuit, a battery cluster and a direct-current side filter inductor in series and then is connected with the direct-current side negative electrode of the PCS unit; the alternating-current side anodes of the PCS units are sequentially connected in series; the bus capacitor is connected in parallel with two poles of the direct current side of the PCS unit;
the PCS unit sub-controller is respectively connected with the fault bypass circuit, the PCS unit, the starting protection circuit and the BMS;
the BMS is connected with the battery cluster;
the step S2 adopts:
step S2.1: collecting battery pulsating voltage and current information, and carrying out Fourier decomposition on the battery pulsating voltage and current to obtain voltage and current components of the battery under different pulsating frequencies;
step S2.2: calculating impedance amplitude and phase angle under different pulsation frequencies;
step S2.3: calculating based on impedance amplitude values and phase angles under different pulsation frequencies to obtain battery internal resistance model parameters, and transmitting the battery internal resistance model parameters to the BMS;
the step S3 adopts: the BMS uses an extended Kalman filtering algorithm to estimate the polarization voltage drop on the RC parallel branch and the open circuit voltage of the battery cluster on line according to the battery internal resistance model parameters, and carries out SOC estimation according to the open circuit voltage at the charge and discharge end according to an OCV-SOC curve measured off line, and simultaneously estimates the effective capacity of the battery cluster on line at the charge and discharge end through a charge transfer method.
2. The battery cluster state accurate sensing method of claim 1, wherein the PCS unit is implemented using a half-bridge or full-bridge topology.
3. The method for accurately sensing the state of a battery cluster according to claim 1, wherein the battery cluster is formed by connecting a plurality of battery cells in series.
4. The method for accurately sensing the state of the battery cluster according to claim 1, wherein application scenes, single-machine capacity and selected battery type influence factors are comprehensively considered, and star-shaped chain type, triangle-shaped chain type and double-star-shaped parallel chain type are selected to realize the alternating-current side cascade combination capacity expansion of the high-voltage energy storage power system.
5. The method of claim 1, wherein the step S1 uses: determining a harmonic voltage frequency sequence which is injected into an alternating current port of the PCS unit and does not affect the normal operation of the PCS unit; the PCS unit sub-controller realizes active pulse power injection of the PCS unit to the battery cluster by superposing different frequency harmonic voltages in the PCS unit modulation wave.
6. The method for accurately sensing the state of the battery cluster according to claim 1, wherein the energy state of the battery cluster is represented according to the estimated effective capacity, terminal voltage and SOC parameters of the battery cluster.
7. The battery cluster state accurate sensing method according to claim 1, wherein the battery clusters are subjected to normalization processing by considering the difference of the effective capacity of the lithium battery and the ambient temperature, so that the OCV-SOC curve of any battery cluster is obtained by performing one OCV-SOC test only for any battery cluster.
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| EP1777794A2 (en) * | 2005-10-20 | 2007-04-25 | Samsung SDI Co., Ltd. | Battery management system and method of determining a state of charge of a battery |
| CN106199431A (en) * | 2014-12-18 | 2016-12-07 | 神华集团有限责任公司 | A kind of exchange monitoring method based on battery electron module and system |
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| EP1777794A2 (en) * | 2005-10-20 | 2007-04-25 | Samsung SDI Co., Ltd. | Battery management system and method of determining a state of charge of a battery |
| CN106199431A (en) * | 2014-12-18 | 2016-12-07 | 神华集团有限责任公司 | A kind of exchange monitoring method based on battery electron module and system |
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