CN110716148A - Real-time safety monitoring system for composite power energy storage - Google Patents
Real-time safety monitoring system for composite power energy storage Download PDFInfo
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
Abstract
The invention provides a compound power energy storage health management system which comprises a lithium battery pack, a super capacitor set, a data acquisition module, a compound power energy storage system main control module, a safety management module, a communication module and an upper computer, wherein the data acquisition module is respectively and electrically connected with the lithium battery pack and the super capacitor set and used for acquiring various running state information of a lithium battery and the super capacitor, and the data acquisition module comprises a total voltage acquisition module, a charging and discharging current acquisition module, a monomer voltage acquisition module and a temperature acquisition module. The invention utilizes the sensor to acquire the state parameters of the energy storage system, improves the sampling precision and adopts corresponding protective measures to protect the energy storage system.
Description
Technical Field
The invention relates to the technical field of energy storage system monitoring, in particular to a composite power energy storage real-time safety monitoring system.
Background
The lithium battery and the super capacitor are connected in parallel to be used as a composite power system of the vehicle, so that the advantages of the lithium battery and the super capacitor can be fully exerted, and respective defects are made up. The energy storage system is monitored safely in real time, so that drivers and operation departments can know the real-time state of the energy storage system conveniently, early faults of the energy storage system are processed, and accidents such as vehicle late and the like are avoided.
The conventional patent CN102842963A provides a secondary battery and super capacitor hybrid energy storage management system, which comprises a battery management subsystem, a super capacitor management subsystem, a centralized management subsystem and an upper computer. The battery management subsystem is composed of a battery management subunit and is responsible for acquiring state signals of single batteries in the system, estimating SOC (state of charge), balancing voltage, processing and transmitting data and monitoring the working state of the bidirectional converter of the battery pack. The super capacitor management subsystem is composed of a super capacitor subunit and is responsible for state signal acquisition, balance, SOC estimation, data transmission and the like of a super capacitor in the system and monitoring the working state of the bidirectional converter of the super capacitor bank. The centralized management subsystem is responsible for summarizing the state data of the batteries and the super capacitors in the system and adjusting the number of the battery combination super capacitor banks connected to the bus at any time.
And the upper computer displays the state information of all batteries and super capacitors in the system. The technology has the advantages that the state of the energy storage system can be effectively collected, the service life of the energy storage system is prolonged, overvoltage and overcurrent protection is not performed on the energy storage system, when overvoltage and overcurrent faults occur in the energy storage system, the operation state of the system is influenced, and safety accidents can also occur in serious cases; when the temperature is too high or too low, corresponding treatment measures are not taken, if the treatment measures are not taken, the service life of the energy storage system is influenced to a certain extent, and the lower computer part does not have a display module, so that maintenance personnel can not conveniently perform corresponding maintenance on the energy storage system.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a composite power energy storage real-time safety monitoring system, overcomes the defects of the conventional composite power energy storage monitoring system, and takes corresponding measures to protect an energy storage battery.
The invention adopts the following technical scheme:
a compound power energy storage real-time safety monitoring system comprises:
the system comprises a lithium battery pack, a super capacitor pack, a data acquisition module, a composite power energy storage system control module, a safety management module, a communication module and an upper computer;
the data acquisition module is respectively and electrically connected with the lithium battery pack and the super capacitor pack and used for acquiring various running state information of the lithium battery and the super capacitor, and the data acquisition module comprises a total voltage acquisition module, a charging and discharging current acquisition module, a monomer voltage acquisition module and a temperature acquisition module.
The control module of the composite power energy storage system comprises a master control unit and a slave control unit, wherein the slave control unit is responsible for acquiring the monomer voltage of the lithium battery pack and the monomer voltage and temperature information of the super capacitor pack and uploading the information to the master control unit, the master control unit is responsible for acquiring the total voltage and the charging and discharging current of the composite power energy storage system and is used for an upper computer to estimate the residual electric quantity and the service life of the vehicle-mounted composite energy storage system, the upper computer downloads information to the master control module, and the master control module sends a balance control instruction to the slave control unit according to the comparison result of the monomer voltage of the lithium battery pack and the monomer.
The safety management module is electrically connected with the composite power energy storage system control module through the relay and performs corresponding actions according to commands of the composite power energy storage system control module, and the safety management module comprises a charge-discharge protection unit, an overvoltage protection unit, a fan and a heater unit.
The communication module comprises a CAN communication module and an RS485 communication module, the composite power energy storage system control module uploads various data of the composite power energy storage system to an upper computer (of a whole vehicle monitoring system) through a CAN bus, the data are displayed on a display screen in a serial port communication mode, a main control unit of the composite power energy storage system control module communicates with a slave control unit in a communication mode of an internal CAN bus, and the RS485 communication module serves as a standby communication mode to prevent data from being redundant.
Preferably, the super capacitor combined lithium battery pack is connected with the total voltage acquisition module, the charge-discharge current acquisition module, the monomer voltage acquisition module and the temperature acquisition module by adopting a shielding cable.
Preferably, the CAN communication module is connected with the control module of the composite energy storage power system, the monomer voltage, the total voltage, the current, the temperature, the balance information, the charge state and the residual service life information of the lithium battery pack and the super capacitor pack are uploaded to the whole vehicle monitoring system, the display screen displays the state information of the composite energy storage power system in a serial port communication mode, and the RS485 is used as a standby communication mode to prevent the data transmission from generating redundancy.
A monitoring method of a hybrid power energy storage health management system comprises the following 5 steps:
(1) establishing a composite power energy storage health management system and initializing the system;
(2) the data acquisition module monitors various state information of the composite power energy storage system;
(3) storing the state monitoring information in the step (2) through a main control module of a composite power energy storage system control module;
(4) uploading the stored information to an upper computer by a main control module of the composite power energy storage system control module, and comparing and judging the monitored data by the upper computer according to a preset threshold value for estimating the residual electric quantity and the service life of the composite power energy storage system;
(5) the upper computer sends the data processing result to the composite power energy storage system control module main control module, and the composite power energy storage system control module main control module takes corresponding processing measures according to the comparison and judgment result and transmits the data to the safety management module for adjusting the running state of the vehicle.
Preferably, the data acquisition module monitors each item running state information of the lithium battery pack and the super capacitor bank, including the monomer voltage that adopts monomer voltage acquisition module to gather lithium battery pack and super capacitor bank, adopt the temperature of all lithium battery packs and super capacitor bank of temperature acquisition unit collection, monitor the total voltage of hybrid power energy storage system through total voltage acquisition module, adopt current acquisition module to monitor the charge-discharge current of hybrid power energy storage system.
Preferably, the storage module stores the data acquired by the data acquisition module, so that the working personnel can know the operating condition of the energy storage system in a certain period of time in the later period.
Preferably, the master control module of the composite power energy storage system uploads the data of the data acquisition module to an upper computer for processing, the upper computer estimates the residual electric quantity and the service life of the composite power energy storage system, and a balance control instruction is sent to a slave control module of the composite power energy storage system according to a threshold comparison result to balance the voltage between the lithium battery pack monomer and the super capacitor pack monomer; and controlling the actions of the fan and the heater to enable the composite power energy storage system to work in a stable temperature range.
Preferably, the display screen displays the state data acquired by the data acquisition module, and displays the voltage balance information of the single lithium battery pack and the single super capacitor pack.
The invention has the beneficial effects that:
1. the running state information of the composite energy storage system is collected in real time through the data collection module, the running state information comprises a single voltage, a total voltage, a current and a temperature, the running state information is balanced and temperature-controlled through the comparison of state parameters and threshold values, the fault is alarmed and simply processed, the charge state and the service life of the composite energy storage system are predicted according to collected data, real-time safety monitoring of the composite energy storage system is achieved, a driver can conveniently know the running state of the composite energy storage system in time, later-stage workers can conveniently maintain the composite energy storage system, safe running of the composite energy storage system is guaranteed, and the service life of the composite energy storage system is prolonged.
2. The lithium battery pack is adopted as a power supply, so that the structure is easy to realize; without the use of super capacitor power, because super capacitor is a power density type element, if it is used for vehicle cruising, its characteristic will be weakened, thus reducing its service life.
3. The single voltage sensor of the system adopts an LTC6811-1 chip produced by Liner company, the chip completely meets the use requirement of a composite power system, the measurement error is only 1.2mV, the voltages of all the single bodies can be measured only by 290 microseconds, and meanwhile, the chip has good expansibility and can complete the voltage measurement of a plurality of sections of single bodies. The current sensor adopts LTC350-SF of LEM company, and the sensor has high monitoring precision, low temperature drift, linearity and high response speed. The DS18B20 digital temperature sensor is adopted to collect temperature, the temperature measuring range is-55 ℃ to +125 ℃, the precision is +/-0.5 ℃, and the unique single bus technology can be used for connecting 8 sensors on one line to communicate with the processor. The combined use of the components not only increases the monitoring precision and accuracy of the monitoring system, but also can accurately estimate the charge states of the lithium battery and the super capacitor, diagnose and process the fault of the super capacitor single body, accurately estimate the service life and the replacement time of the lithium battery and realize the health management of the composite power energy storage system compared with the existing system through the parameters.
Drawings
FIG. 1 is a topological structure diagram of a composite power energy storage real-time safety monitoring system according to the present invention;
FIG. 2 is a block diagram of a hardware structure of a main control module of the composite power energy storage real-time safety monitoring system according to the present invention;
FIG. 3 is a block diagram of a hardware structure of a control unit of a lithium ion battery pack of a slave control unit of the composite power energy storage real-time safety monitoring system according to the invention;
FIG. 4 is a block diagram of a hardware structure of a control unit of a super capacitor bank of a slave control unit of the composite power energy storage real-time safety monitoring system according to the present invention;
fig. 5 is a monitoring flow chart of the composite power energy storage real-time safety monitoring system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention are described below clearly and completely, and it is obvious that the described embodiments are some, not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 and 2, a hybrid power energy storage health management system includes a lithium battery pack, a super capacitor pack, a data acquisition module, a hybrid power energy storage system control module, a safety management module, and a communication module.
The composite power energy storage system is composed of a plurality of lithium battery combined super capacitor banks, and each lithium battery combined super capacitor bank is provided with a control unit.
The data acquisition module is electrically connected with the lithium battery combined super capacitor bank and used for monitoring state information of the lithium battery pack and the super capacitor bank, and the data acquisition module comprises a total voltage acquisition module, a charge-discharge current acquisition module, a monomer voltage acquisition module and a temperature acquisition module.
The composite power energy storage system control module is electrically connected with the data acquisition module, the master control module is connected with the slave control module through the internal CAN bus, the slave control module transmits acquired data back to the master control module, and the master control module stores the acquired data and the data acquired by the slave control module and uploads the data to the upper computer.
The safety management module comprises an overvoltage and overcurrent protection module, a fan and heater module and is used for protecting the hybrid power energy storage system to enable the hybrid power energy storage system to work in a safe environment.
The communication module comprises a CAN communication module and an RS485 communication module, the composite power energy storage system control module uploads the running state information of the lithium battery pack and the supercapacitor to an upper computer of the whole vehicle monitoring system through the CAN communication module, the RS485 communication module prevents data redundancy as a standby communication mode, and the whole vehicle monitoring adopts a serial port communication mode to transmit the information of the lithium battery pack and the supercapacitor pack to a display screen for displaying.
As shown in fig. 3, the slave control unit for the lithium battery pack comprises a single voltage acquisition unit, a temperature monitoring unit, a thermal management unit and a balance control unit, and is used for acquiring single voltage and temperature of the lithium battery pack, transmitting information back to the master control module, thermally managing the lithium battery pack when the temperature of the lithium battery pack exceeds a threshold value, and performing balance control on the lithium battery pack when the voltage difference between the single lithium battery packs exceeds the threshold value.
As shown in fig. 4, the slave control unit of the supercapacitor bank comprises a voltage acquisition unit of a supercapacitor bank monomer, a voltage monitoring chip of temperature data and a temperature sensor, the slave control unit transmits acquired data to a master control module through an internal CAN bus, and a safety management module is electrically connected with a control module of a hybrid power energy storage system through a relay and used for adjusting the operating temperature of the supercapacitor bank so as to enable the supercapacitor bank to be in a safe working condition.
Fig. 5 shows the monitoring steps of the hybrid energy storage health management system, which includes:
(1) establishing a composite power energy storage health management system and initializing the system;
(2) the data acquisition module monitors various state information of the composite power energy storage system;
(3) storing the state monitoring information in the step (2) through a main control module of a composite power energy storage system control module;
(4) uploading the stored information to an upper computer by a main control module of the composite power energy storage system control module, and comparing and judging the monitored data by the upper computer according to a preset threshold value for estimating the residual electric quantity and the service life of the composite power energy storage system;
(5) the upper computer sends the data processing result to the composite power energy storage system control module main control module, and the composite power energy storage system control module main control module takes corresponding processing measures according to the comparison and judgment result and transmits the data to the safety management module for adjusting the running state of the vehicle.
The state monitoring module comprises a lithium battery pack monitoring module and a super capacitor pack monitoring module, and comprises a voltage monitoring module for monitoring the total voltage of the lithium battery pack super capacitor pack, a current monitoring module for charging and discharging current, a single voltage monitoring module and a single temperature monitoring module, wherein the state monitoring module is mainly used for monitoring the running state information of the lithium battery pack and the super capacitor pack.
The main control module of the composite power energy storage system is a central control unit, and is responsible for receiving the data monitored by the state monitoring module through the data acquisition module and storing the state information, so that the follow-up staff can conveniently know the running state information of the composite power energy storage system within a period of time.
The main control module of the composite power energy storage system uploads the data of the state monitoring module to an upper computer, the upper computer compares the information with a given threshold value, and when the lithium battery pack or the super capacitor pack has overvoltage and overcurrent conditions, corresponding protective measures are taken and the information is transmitted to the whole vehicle monitoring system, so that the damage to the energy storage system is reduced; when the voltage difference between the lithium battery pack single bodies or the super capacitor pack single bodies exceeds a threshold value, the balancing module is controlled to act, the wooden barrel effect is reduced, and the service life of the energy storage system is prolonged; and meanwhile, the state of charge (SOC) and the service life (SOH) of the lithium battery pack and the super capacitor pack are estimated, so that a driver can know the real-time state of the energy storage system conveniently.
The main control module of the composite power energy storage system displays the data and processing measures of the state monitoring module through a display screen, so that subsequent workers can maintain the energy storage system conveniently; uploading state information of the composite power energy storage system, including total voltage, charging and discharging current, monomer voltage, monomer temperature, charge state and service life information of the lithium battery pack and the super capacitor pack, to an upper computer of a vehicle monitoring system through a CAN bus; when the main control module of the composite power energy storage system control module takes corresponding processing measures for the composite power energy storage system, the processing information is transmitted to an upper computer of the whole vehicle monitoring system; RS485 communication is used as a standby communication mode to prevent data transmission from generating redundancy; and a communication interface with other monitoring systems is reserved on the main control module of the composite power energy storage system control module, so that the composite power energy storage health management system can be conveniently communicated with other monitoring systems.
A monitoring method of a hybrid power energy storage health management system comprises the following steps: the upper computer adopts a latest charge state estimation algorithm, adopts a method of combining ampere-hour integration and open-circuit voltage to estimate the charge state of the lithium battery, adopts a double-Kalman filtering algorithm to estimate the charge state of the super capacitor, and comprises the following steps:
1) the following can be obtained by an ampere-hour integration method:
2) in order to be applied to a Kalman filtering algorithm, formula (1) is discretized, and sampling time delta t is taken to obtain an expression:
3) according to the circuit model of the super capacitor, the discrete space state model of the SOC of the super capacitor is obtained as follows:
4) the Kalman filtering SOC estimation process comprises the following steps:
and (3) time updating:
x(k|k-1)＝Ax(k-1|k-1)+Bik-1
Px(k|k-1)＝APx(k-1|k-1)AT+Qk-1(4)
and (3) observation updating:
x(k|k)＝x(k|k-1)+kg(k)·(y(k)-h(x(k|k-1),uk))
Px(k|k)＝(I-kg(k)Ck)Px(k|k-1) (5)
5) estimating the state of charge of the supercapacitor by using a double-Kalman filtering algorithm, alternately estimating the system state by using a model and estimating the model parameters again by using the system state, and respectively estimating the system state and the parameters by using two independent Kalman filters;
6) the dual kalman filter algorithm steps are as follows:
and (3) initialization assignment: r0(0|0),PR(0|0),x(0|0),Px(0|0)
And (3) time updating: r0(k|k-1)＝R0(k-1|k-1)；x(k|k-1)＝Ax(k-1|k-1)+Bik-1
Covariance matrix: rR(k|k-1)＝RR(k-1|k-1)+Mk-1；RR(k|k-1)＝ARx(k-1|k-1)AT+Qk-1Updating the Kalman gain: k0(k),Kg(k)
Updating the Kalman gain: k0(k),Kg(k)
And (3) observation updating: r0(k|k)＝R0(k|k-1)+Kg(k)·(y(k)-h(x,u,R0))
x(k|k)＝x(k|k-1)+Kg(k)·(y(k)-h(x,u,R0))
And (3) observation updating: r0(k|k)＝(I-K0(k)CR)+R0(k|k-1)
Rx(k|k)＝(I-K0(k)Ck)+Rx(k|k-1)
Preferably, the estimation method of the state of charge of the supercapacitor set comprises the steps of identifying the model parameters by using a limited memory least square method, and performing prediction, correction and prediction on a state space equation of the supercapacitor set by using the double-kalman filter algorithm, so that the state of charge of the supercapacitor set can be estimated in real time.
And according to the characteristics of the lithium battery and the super capacitor, predicting the service life of the lithium battery by adopting a particle filter algorithm and a genetic calculation model, and comprising the following steps of:
1) establishing a lithium ion battery capacity degradation model, wherein the model is as follows:
Ck＝a×exp(b×k)+c×exp(d×k) (6)
in the above formula, a, b, C and d are model parameters, k is a period, and one time of completing battery charging and discharging is a period CkIs the battery capacity;
2) aiming at the ionic cell capacity double-exponential empirical degradation model established by the formula (6), fitting model parameters by adopting nonlinear least squares;
3) the method combining the particle filter algorithm and the genetic algorithm is adopted, the genetic algorithm is introduced into the resampling process of the particle filter algorithm, and the problem of particle degradation of the particle filter algorithm is solved;
4) estimating the SOH of the ion battery by adopting a particle filter algorithm, wherein the particle filter algorithm is a stochastic tracking prediction algorithm, and a spatial model of the particle filter algorithm is as follows:
in the formula (7), f (-) is a state transition equation, h (-) is an observation equation, and xk、yk、uk、vkRespectively representing the system state, the observed value, the process noise and the observation noise, Xk＝x0:k＝{x0,x1,…,xkAnd Yk＝y1:k＝{y1,…,ykMeans forState and observation at each moment;
5) the particle filter algorithm is a Bayes filter algorithm based on Monte Carlo simulation, and comprises two processes of prediction and updating:
prior probability density obtained by bayesian filtering: p (x)k|Yk-1)＝∫p(xk|xk-1)p(xk-1|Yk-1)dxk-1
The posterior probability density obtained after updating the Bayes formula is as follows:
6) the particle filter algorithm comprises two important processes of random sampling and resampling, wherein the resampling is to introduce an importance probability density function q (x)k|Yk) Determining the weight value
7) The SOH estimation method for the health state of the lithium ion battery comprises the steps of firstly establishing a double-exponential empirical degradation model of a capacity degradation model, and tracking and predicting the health state of the lithium ion battery based on the established capacity degradation model in combination with a particle filter algorithm and a genetic algorithm;
the method comprises the following steps of adopting a fault diagnosis algorithm for the super capacitor, adopting a principal component analysis method to extract fault characteristics, and adopting a binary K-means clustering method to diagnose the fault of the super capacitor, wherein the method comprises the following steps:
1) sampling calculation;
2) extracting feature vectors of the clustering samples by applying PCA;
3) calculating the variance of the feature vector, and ending when the condition is not met;
4) carrying out binary k-means clustering by using the training sample, and preliminarily determining a clustering center;
5) calculating Euclidean distance between the test sample and the training sample cluster center, classifying according to the distance, and updating the cluster center.
Preferably, in order to accurately detect the faulty supercapacitor and solve the problems of high difficulty in parameter identification and large data collection amount of the conventional fault diagnosis method, a principal component analysis method is adopted to extract fault characteristics, and a binary K-means clustering method is used for diagnosing faults.
The fault diagnosis of the super capacitor bank based on PCA and binary K-means clustering comprises the steps of obtaining a sample of each sampling period, calculating the sample obtained in each sampling period to obtain a characteristic vector of a super capacitor module sample, and solving the variance of the characteristic vector. When the variance of the feature vector is larger than the threshold value, the sample contains fault capacitance, and a clustering method is needed for fault diagnosis. And comparing the test sample with Euclidean distances of two types of centers, namely a normal super capacitor and a fault super capacitor, dividing the test sample into the types represented by the clustering centers closest to the test sample, and updating the clustering centers after adding the sample to be diagnosed again so as to further improve the diagnosis model.
The system is particularly suitable for novel urban rail vehicles powered by the energy storage system, and can improve the safety of the energy storage system and prolong the service life of the energy storage system.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A compound power energy storage health management system is characterized by comprising a lithium battery pack, a super capacitor pack, a data acquisition module, a compound power energy storage system control module, a safety management module, a communication module and an upper computer, wherein the lithium battery pack is connected with the super capacitor pack through a communication module;
the data acquisition module is electrically connected with the lithium battery pack and the super capacitor pack by twisted pairs respectively and is used for acquiring various running state information of the lithium battery and the super capacitor, the data acquisition module is electrically connected with the composite power energy storage system control module by twisted pairs and is used for transmitting the acquired state information, and the data acquisition module comprises a total voltage acquisition module, a charging and discharging current acquisition module, a single voltage acquisition module and a temperature acquisition module;
the control module of the hybrid power energy storage system comprises a master control unit and a slave control unit, wherein the slave control unit is responsible for acquiring the monomer voltage of the lithium battery pack and the monomer voltage and temperature information of the super capacitor pack through a data acquisition unit, the slave control unit uploads the acquired data to the master control unit, the master control unit is responsible for acquiring the total voltage and charging and discharging current of the hybrid power energy storage system through the data acquisition unit and uploads the total voltage and charging and discharging current to an upper computer, the upper computer estimates the residual electric quantity and service life of the vehicle-mounted hybrid energy storage system and downloads the residual electric quantity and the service life to the master control module, and the master control module sends a balance control instruction to the slave control unit according to the comparison result of;
the safety management module is respectively and electrically connected with the composite power energy storage system control module and the data acquisition module through a relay, corresponding actions are carried out according to commands of the composite power energy storage system control module, and the safety management module comprises a charge-discharge protection unit, an overvoltage protection unit, a fan and a heater unit;
the communication module comprises a CAN communication module and an RS485 communication module, the composite power energy storage system control module uploads various data of the composite power energy storage system to an upper computer through the CAN communication module, the data are displayed on a display screen in a serial port communication mode, a master control unit and a slave control unit of the composite power energy storage system control module are communicated in an internal CAN bus communication mode, and the RS485 communication module serves as a standby communication mode to prevent data redundancy;
2. the hybrid energy storage health management system of claim 1, wherein the supercapacitor bank and the lithium battery bank are connected to the data acquisition module by shielded cables.
3. A monitoring method of a hybrid power energy storage health management system is characterized by comprising the following steps:
(1) establishing a composite power energy storage health management system and initializing the system;
(2) the data acquisition module monitors various state information of the composite power energy storage system;
(3) storing the state monitoring information in the step (2) through a main control module of a composite power energy storage system control module;
(4) uploading the stored information to an upper computer by a main control module of the composite power energy storage system control module, and comparing and judging the monitored data by the upper computer according to a preset threshold value for estimating the residual electric quantity and the service life of the composite power energy storage system;
(5) the upper computer sends the data processing result to the composite power energy storage system control module main control module, and the composite power energy storage system control module main control module takes corresponding processing measures according to the comparison and judgment result and transmits the data to the safety management module for adjusting the running state of the vehicle.
4. The monitoring method of the hybrid power energy storage health management system according to claim 3, wherein in the step (4), the upper computer estimates the remaining capacity and the life of the hybrid power energy storage system, a method combining an ampere-hour integration method and an open-circuit voltage method is adopted to estimate the remaining capacity of the lithium ion battery pack, a dual Kalman filtering algorithm is adopted to estimate the state of charge of the super capacitor, specifically, the dual Kalman filtering algorithm estimates the state of charge of the super capacitor, a discrete space state model of the SOC of the super capacitor is alternately used to estimate the state of charge of the super capacitor, and the state of charge of the super capacitor is used to re-estimate model parameters, two independent Kalman filters are used to estimate the system state and parameters respectively, and the dual Kalman filtering algorithm comprises the following steps:
and (3) initialization assignment: r0(0|0),PR(0|0),x(0|0),Px(0|0)
And (3) time updating: r0(k|k-1)＝R0(k-1|k-1)；x(k|k-1)＝Ax(k-1|k-1)+Bik-1
Covariance matrix: rR(k|k-1)＝RR(k-1|k-1)+Mk-1；Rx(k|k-1)＝ARx(k-1|k-1)AT+Qk-1
Updating the Kalman gain: k0(k),Kg(k)
Updating the Kalman gain: k0(k),Kg(k)
And (3) observation updating: r0(k|k)＝R0(k|k-1)+Kg(k)·(y(k)-h(x,u,R0))
x(k|k)＝x(k|k-1)+Kg(k)·(y(k)-h(x,u,R0))
And (3) observation updating: r0(k|k)＝(I-K0(k)CR)+R0(k|k-1)
Rx(k|k)＝(I-K0(k)Ck)+Rx(k|k-1)
PxFor the Kalman estimation error covariance matrix, A is the state transition matrix, B is the input gain matrix, KgFor Kalman gain, RsIs an equivalent series resistance, Q, of a super capacitorkIs a process excitation noise covariance matrix, K0Representing the initial Kalman gain, R0Is an initial value of the equivalent series resistance, PR(0|0) is the initial covariance matrix, RxTo observe the update value, Mk-1Covariance matrix, PRIs a state covariance matrix, CkFor the observation matrix, kg (k) is the Kalman gain at time k, h (x, u, R)0) Is an observation matrix.
5. The monitoring method of the hybrid power energy storage health management system according to claim 4, wherein the construction step of the discrete space state model of the super capacitor SOC comprises the following steps:
1) obtaining a super-capacitor SOC model by an ampere-hour integration method:
wherein eta is charge-discharge efficiency, i is current, C is rated capacity of the super capacitor, SOC represents calculated state of charge of the super capacitor, and SOC0An initial calculated value representing the state of charge of the supercapacitor;
2) in order to be applied to a Kalman filtering algorithm, formula (1) is discretized, and sampling time delta t is taken to obtain an expression:
wherein eta is charge-discharge efficiency, i is current, delta t is sampling time, C is rated capacity of the super capacitor, and SOC iskRepresents the calculated value of the state of charge at the moment k of the super capacitor, SOCk-1Represents a calculated value of the state of charge at the moment k-1 of the super capacitor, ik-1Represents the current value at the time of k-1;
3) according to the circuit model of the super capacitor, the discrete space state model of the SOC of the super capacitor is obtained as follows:
in the formula, RpIs an equivalent parallel resistance of a super capacitor, CpIs an equivalent parallel capacitance of a super capacitor, TsTo sample time, CNRated capacity of the super capacitor, eta is charge-discharge efficiency, WkRepresenting process noise, I, generated by system sensorskRepresents the current at time k, UpEquivalent parallel capacitance terminal voltage and SOC for super capacitork+1Representing a calculated state of charge value of the super capacitor at the moment k + 1;
4) a discrete space state model of the super capacitor SOC is estimated through Kalman filtering:
and (3) time updating:
x(k|k-1)＝Ax(k-1|k-1)+Bik-1
Px(k|k-1)＝APx(k-1|k-1)AT+Qk-1(4)
and (3) observation updating:
x(k|k)＝x(k|k-1)+kg(k)·(y(k)-h(x(k|k-1),uk))
Px(k|k)＝(I-kg(k)Ck)Px(k|k-1) (5)
in the above formulas (4) and (5), x (k) is the true value, Px(k) A Kalman estimation error covariance matrix is adopted, A is a state transition matrix, and B is an input gain matrix; qkIs a process excitation noise covariance matrix, KgFor Kalman gain, I is the current, kg (k) is the Kalman gain at time k, RkIs k time series resistance value of the super capacitor, CkFor the observation matrix, y (k) is the output value at time k, h (-) is the observation matrix, ukRepresenting the control matrix, x (k | k) represents the state observation update at time k:
wherein eta is the charge-discharge efficiency, RpIs an equivalent parallel resistance of a super capacitor, CpIs an equivalent parallel capacitance of a super capacitor, wherein AkRepresenting the state transition matrix in the prediction update, BkTo control the quantity coefficient matrix, CkFor the observation matrix, T is the observation time,
the equivalent parallel capacitance terminal voltage of the super capacitor at the moment k.
6. The monitoring method of the hybrid energy storage health management system according to claim 3, wherein the host computer in the step (4) estimates the remaining capacity and the life of the hybrid energy storage system, and estimates the life of the lithium battery pack, and the method comprises the following steps:
according to the characteristics of the lithium battery and the super capacitor, the service life of the lithium battery is predicted by adopting a particle filter algorithm and a genetic algorithm, and the method comprises the following steps: 1) establishing a lithium ion battery capacity degradation model, wherein the model is as follows:
Ck＝a×exp(b×k)+c×exp(d×k) (6)
in the above formula, a, b, C and d are model parameters, k is a period, and one time of completing battery charging and discharging is a period CkIs the battery capacity;
2) aiming at the ionic cell capacity double-exponential empirical degradation model established by the formula (6), fitting model parameters by adopting nonlinear least squares;
3) the method combining the particle filter algorithm and the genetic algorithm is adopted, the genetic algorithm is introduced into the resampling process of the particle filter algorithm, the particle degradation problem of the particle filter algorithm is solved, and the health state of the lithium ion battery is tracked and predicted.
7. The monitoring method of the hybrid energy storage health management system according to claim 6, wherein the particle filtering algorithm in the step 3) is a stochastic tracking prediction algorithm, and the spatial model thereof is as follows:
in the formula (7), f (-) is a state transition equation, h (-) is an observation equation, and xk、yk、uk、vkRespectively representing the system state, the observed value, the process noise and the observation noise, Xk＝x0:k＝{x0,x1,…,xkAnd Yk＝y1:k＝{y1,…,ykRepresents the state and observation value at each moment;
the particle filter algorithm is a Bayes filter algorithm based on Monte Carlo simulation, and comprises two processes of prediction and updating:
prior probability density obtained by bayesian filtering: p (x)k|Yk-1)＝∫p(xk|xk-1)p(xk-1|Yk-1)dxk-1
In the formula, xkIs the system state, ykIs an observed value;
the posterior probability density obtained after updating the Bayes formula is as follows:
in the formula, xkIs the system state, ykIs an observed value;
the particle filter algorithm comprises two important processes of random sampling and resampling, wherein the resampling is to introduce an importance probability density function q (x)k|Yk) Determining the weight value
In the formula, xkIs the system state, ykAs an observed value, wkIs the weight of the particle, δ (x-x)k) Is a unit impulse function.
8. The monitoring method of the hybrid power energy storage health management system according to claim 3, wherein in the step (4), the upper computer estimates the remaining capacity and the service life of the hybrid power energy storage system and estimates the fault of the supercapacitor, the method comprises the following steps of adopting a fault diagnosis algorithm for the supercapacitor, adopting a principal component analysis method to extract fault characteristics, and adopting a binary K-means clustering method to diagnose the fault of the supercapacitor, and comprises the following steps:
1) sampling calculation;
2) extracting feature vectors of the clustering samples by applying PCA;
3) calculating the variance of the feature vector, and ending when the condition is not met;
4) carrying out binary k-means clustering by using the training sample, and preliminarily determining a clustering center;
5) calculating Euclidean distance between the test sample and the training sample cluster center, classifying according to the distance, and updating the cluster center.
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