CN114379386B - Fuel cell and lithium battery hybrid system collaborative recession control method and system - Google Patents

Fuel cell and lithium battery hybrid system collaborative recession control method and system Download PDF

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CN114379386B
CN114379386B CN202210297522.7A CN202210297522A CN114379386B CN 114379386 B CN114379386 B CN 114379386B CN 202210297522 A CN202210297522 A CN 202210297522A CN 114379386 B CN114379386 B CN 114379386B
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fuel cell
soh
lithium battery
data
change rate
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CN114379386A (en
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李建威
杨璐铭
鲍欢欢
王薛超
范志先
蒋尚峰
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Beijing Institute of Technology BIT
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L50/00—Electric propulsion with power supplied within the vehicle
    • B60L50/50—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells
    • B60L50/75—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using propulsion power supplied by both fuel cells and batteries
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L50/00—Electric propulsion with power supplied within the vehicle
    • B60L50/40—Electric propulsion with power supplied within the vehicle using propulsion power supplied by capacitors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/16—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/40—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for controlling a combination of batteries and fuel cells
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/40—Application of hydrogen technology to transportation, e.g. using fuel cells

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Fuel Cell (AREA)

Abstract

The invention relates to a fuel cell and lithium battery hybrid system collaborative recession control method and a system, relating to the field of fuel cells and lithium batteries, wherein the method comprises the following steps: acquiring vehicle speed data, fuel cell data and lithium battery data of a vehicle; determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value according to the data of the fuel cell and the data of the lithium cell; determining a power demand bearing result of an energy source to the vehicle according to the vehicle speed data; performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis comprise wavelet orders and decomposition orders; and adjusting the power bearing results of the fuel cell, the lithium cell and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value so as to realize cooperative decline of the vehicle power system, and prolonging the service lives of the two cells by enabling the decline degrees of the fuel cell and the lithium cell to be consistent.

Description

Fuel cell and lithium battery hybrid system collaborative recession control method and system
Technical Field
The invention relates to the field of fuel cells and lithium batteries, in particular to a cooperative degradation control method and a cooperative degradation control system for a fuel cell and lithium battery hybrid system.
Background
Compared with a starting power battery automobile, the fuel cell electric automobile has the advantages of high efficiency, low noise, no pollution, high charging speed and the like. Therefore, fuel cell electric vehicles are becoming the focus of research. The current control management strategy for fuel cell electric vehicles has three levels of problems. First, most strategies target only minimal fuel consumption or minimal total cost, and do not take into account energy source life issues at all. Second, in a conventional fuel cell + battery system, the battery rapidly degrades to failure due to the high frequency and high power loads that the battery commonly serves as an auxiliary power source to protect the fuel cell. Furthermore, the fuel cell alone bears all the operating condition loads and also rapidly declines to fail. The net result is that even if it is desired to extend the life of the fuel cell, in practice the cell and the fuel cell fail one after the other, both failing to operate to the upper life limit. And finally, a third energy source is added into part of the system to protect the battery and prolong the service life of the battery, but the third energy source is only used for bearing the requirement of severe working conditions to achieve the protection effect. No relevant research or invention explores the problem of consistency of the life decay conditions of the fuel cell and the battery under the three-source system, and no research or invention tries to control the decay of the two to achieve the life consistency.
In the prior art, a fuel cell, a lithium battery and an electrodynamic flywheel battery are driven and controlled by a composite energy system, so that the peak output power of the fuel cell can be reduced under a large-load driving working condition, and the service life is prolonged; under the low-load working condition, the fuel cell can be ensured to work in an efficient working range, and the energy states of the lithium cell and the flywheel are also ensured. The strategy does not consider the life decline phenomenon of the lithium battery, does not consider the cooperative decline of the fuel battery and the battery, and inevitably leads to the early decline phenomenon of the lithium battery and the fuel battery. In the prior art, the performance degradation of the solid oxide fuel cell and the capacity attenuation of the lithium battery are considered, the lowest operation cost is realized by using a dynamic particle swarm optimization algorithm, and the degradation trend of the system is slowed down. The method does not consider the cooperative degradation of the fuel cell and the battery, and cannot give full play to the energy source performance.
Therefore, there is a need for a method that can ensure consistent degradation of both fuel cells and lithium batteries, thereby extending the life of both batteries.
Disclosure of Invention
The invention aims to provide a cooperative degradation control method and a cooperative degradation control system for a fuel cell and lithium battery hybrid system, which can prolong the service life of the fuel cell and the lithium battery by enabling the degradation degrees of the fuel cell and the lithium battery to be consistent.
In order to achieve the purpose, the invention provides the following scheme:
a cooperative recession control method for a fuel cell and lithium battery hybrid system comprises the following steps:
acquiring vehicle speed data, fuel cell data and lithium battery data of a vehicle;
determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value according to the data of the fuel cell and the data of the lithium cell;
determining a power demand bearing result of an energy source to the vehicle according to the vehicle speed data; the energy source comprises a fuel cell, a lithium battery and a super capacitor;
performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis comprise wavelet orders and decomposition orders;
and adjusting the power bearing results of the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value so as to realize cooperative decline of a vehicle power system.
Optionally, the determining a fuel cell SOH change rate, a lithium cell SOH change rate and an SOH difference according to the fuel cell data and the lithium cell data specifically includes:
obtaining the SOH of the fuel cell at different moments by using a fuel cell decline model according to the data of the fuel cell;
determining the SOH change rate of the fuel cell according to the SOH of the fuel cell at different moments;
obtaining lithium battery SOH at different moments by using a lithium battery recession model according to the lithium battery data;
determining the SOH change rate of the lithium battery according to the SOH of the lithium battery at different moments;
and determining the SOH difference value according to the SOH of the fuel cell and the SOH of the lithium battery at the same moment.
Optionally, the construction process of the lithium battery degradation model specifically includes:
obtaining an equivalent circuit model of the lithium battery;
and constructing a lithium battery recession model according to the equivalent circuit model.
Optionally, the construction process of the fuel cell degradation model specifically includes:
acquiring historical degradation data of the fuel cell;
performing wavelet analysis on the historical decline data of the fuel cell to obtain a plurality of sub-waveforms;
constructing a plurality of sub-regression models according to a plurality of the sub-waveforms, time, load current, relative humidity, temperature and hydrogen pressure;
optimizing the plurality of sub-regression models by using a genetic algorithm to obtain a plurality of optimal regression models;
and combining the optimal regression models to obtain a fuel cell regression model.
Optionally, the determining, according to the vehicle speed data, a power demand bearing result of an energy source for the vehicle specifically includes:
judging whether the vehicle speed data is greater than or equal to a set threshold value or not to obtain a first judgment result;
if the first judgment result is negative, controlling the lithium battery and the super capacitor to bear power requirements;
and if the first judgment result is yes, controlling the fuel cell, the lithium battery and the super capacitor to bear the power requirement.
Optionally, the adjusting the power undertaking results of the fuel cell, the lithium battery and the super capacitor according to the frequency division requirement signal, the power requirement undertaking result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value to realize cooperative degradation of a vehicle power system specifically includes:
when the power demand assuming result of the energy source to the vehicle represents that the fuel cell, the lithium battery and the super capacitor undertake power demand, distributing the power demand to the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal;
judging whether the SOH change rate of the fuel cell is greater than the SOH change rate of the lithium battery or not to obtain a second judgment result;
if the second judgment result is yes, judging whether the SOH difference value is larger than 0 to obtain a third judgment result;
if the third judgment result is yes, increasing the wavelet order to protect the fuel cell;
if the third judgment result is negative, reducing the range of the operating speed of the fuel cell in the frequency division demand signal and increasing the wavelet order;
if the second judgment result is negative, judging whether the SOH difference value is larger than 0 to obtain a fourth judgment result;
if the fourth judgment result is yes, increasing the decomposition order;
and if the fourth judgment result is negative, increasing the wavelet order and the decomposition order.
A fuel cell and lithium battery hybrid system cooperative degradation control system comprises:
the acquisition module is used for acquiring vehicle speed data, fuel cell data and lithium battery data of the vehicle;
the determining module is used for determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value according to the data of the fuel cell and the data of the lithium cell;
the power demand bearing result determining module is used for determining a power demand bearing result of the energy source for the vehicle according to the vehicle speed data; the energy source comprises a fuel cell, a lithium battery and a super capacitor;
the wavelet analysis module is used for performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis comprise wavelet orders and decomposition orders;
and the adjusting module is used for adjusting the power bearing results of the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value so as to realize cooperative decline of a vehicle power system.
Optionally, the determining module specifically includes:
the fuel cell SOH determining unit is used for obtaining the SOH of the fuel cell at different moments by utilizing a fuel cell recession model according to the data of the fuel cell;
a fuel cell SOH change rate determining unit for determining the change rate of the fuel cell SOH according to the fuel cell SOH at different times;
the lithium battery SOH determining unit is used for obtaining the SOH of the lithium battery at different moments by utilizing a lithium battery recession model according to the lithium battery data;
the lithium battery SOH change rate determining unit is used for determining the SOH change rate of the lithium battery according to the SOH of the lithium battery at different moments;
and the SOH difference determining unit is used for determining the SOH difference according to the SOH of the fuel cell and the SOH of the lithium cell at the same moment.
Optionally, the construction process of the lithium battery degradation model specifically includes:
obtaining an equivalent circuit model of the lithium battery;
and constructing a lithium battery recession model according to the equivalent circuit model.
Optionally, the construction process of the fuel cell degradation model specifically includes:
acquiring historical decline data of the fuel cell;
performing wavelet analysis on the historical decline data of the fuel cell to obtain a plurality of sub-waveforms;
constructing a plurality of sub-regression models according to a plurality of the sub-waveforms, time, load current, relative humidity, temperature and hydrogen pressure;
optimizing the plurality of sub-regression models by using a genetic algorithm to obtain a plurality of optimal regression models;
and combining the optimal regression models to obtain a fuel cell regression model.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value according to the data of the fuel cell and the data of the lithium cell; determining a power demand bearing result of an energy source to the vehicle according to the vehicle speed data; performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis comprise wavelet orders and decomposition orders; and adjusting the power bearing results of the fuel cell, the lithium cell and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value so as to realize cooperative decline of the vehicle power system, and prolonging the service lives of the two cells by enabling the decline degrees of the fuel cell and the lithium cell to be consistent.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a cooperative degradation control method for a fuel cell and lithium battery hybrid system according to the present invention;
FIG. 2 is a schematic flow chart of a cooperative degradation control method for a fuel cell and lithium battery hybrid system according to the present invention;
FIG. 3 is a schematic view of a bus power system configuration provided by the present invention;
FIG. 4 is a schematic diagram of an equivalent circuit model of a battery according to the present invention;
FIG. 5 is a flowchart illustrating a method for controlling cooperative degradation of a fuel cell and lithium battery hybrid system according to the present invention;
FIG. 6 is a graph of fuel cell efficiency;
FIG. 7 is a diagram illustrating a simulation curve of SOH variation trend of a dual-source system;
FIG. 8 is a diagram illustrating a simulation curve of SOH variation trend of a three-source system.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
The invention aims to provide a cooperative degradation control method and a cooperative degradation control system for a fuel cell and lithium battery hybrid system, which can prolong the service life of the fuel cell and the lithium battery by enabling the degradation degrees of the fuel cell and the lithium battery to be consistent.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, the cooperative degradation control method for a fuel cell and lithium battery hybrid system provided by the present invention includes:
step 101: and acquiring vehicle speed data, fuel cell data and lithium battery data of the vehicle.
Step 102: and determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value according to the data of the fuel cell and the data of the lithium cell.
Step 102, specifically comprising:
and obtaining the SOH of the fuel cell at different moments by using a fuel cell decline model according to the data of the fuel cell.
Determining the fuel cell SOH change rate according to the fuel cell SOH at different moments in time.
And obtaining the SOH of the lithium battery at different moments by utilizing a lithium battery recession model according to the lithium battery data.
And determining the SOH change rate of the lithium battery according to the SOH of the lithium battery at different moments.
And determining the SOH difference value according to the SOH of the fuel cell and the SOH of the lithium battery at the same moment.
The construction process of the lithium battery recession model specifically comprises the following steps:
obtaining an equivalent circuit model of the lithium battery; and constructing a lithium battery recession model according to the equivalent circuit model.
The construction process of the fuel cell degradation model specifically comprises the following steps:
acquiring historical decline data of the fuel cell; performing wavelet analysis on the historical decline data of the fuel cell to obtain a plurality of sub-waveforms; constructing a plurality of sub-regression models according to a plurality of the sub-waveforms, time, load current, relative humidity, temperature and hydrogen pressure; optimizing the plurality of sub-regression models by using a genetic algorithm to obtain a plurality of optimal regression models; and combining the optimal regression models to obtain a fuel cell regression model.
Step 103: determining a power demand bearing result of an energy source to the vehicle according to the vehicle speed data; the energy source includes a fuel cell, a lithium battery, and a super capacitor.
Step 103, specifically comprising:
and judging whether the vehicle speed data is greater than or equal to a set threshold value or not to obtain a first judgment result.
If the first judgment result is negative, controlling the lithium battery and the super capacitor to bear power requirements;
and if the first judgment result is yes, controlling the fuel cell, the lithium battery and the super capacitor to bear the power requirement.
Step 104: performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis include wavelet order and decomposition order.
Step 105: and adjusting the power bearing results of the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value so as to realize cooperative decline of a vehicle power system.
Step 105, specifically comprising:
and when the power demand assuming result of the energy source to the vehicle represents that the fuel cell, the lithium battery and the super capacitor undertake power demand, distributing the power demand to the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal.
And judging whether the SOH change rate of the fuel cell is greater than the SOH change rate of the lithium battery or not to obtain a second judgment result.
If the second judgment result is yes, judging whether the SOH difference value is larger than 0 to obtain a third judgment result; if the third judgment result is yes, increasing the wavelet order to protect the fuel cell; if the third judgment result is negative, reducing the range of the operating speed of the fuel cell in the frequency division demand signal and increasing the wavelet order.
If the second judgment result is negative, judging whether the SOH difference value is larger than 0 to obtain a fourth judgment result; if the fourth judgment result is yes, increasing the decomposition order; and if the fourth judgment result is negative, increasing the wavelet order and the decomposition order.
The invention also provides a cooperative decline control system of the fuel cell and lithium battery hybrid system, which comprises:
the acquisition module is used for acquiring vehicle speed data, fuel cell data and lithium battery data of the vehicle.
And the determining module is used for determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value according to the data of the fuel cell and the data of the lithium cell.
The power demand bearing result determining module is used for determining a power demand bearing result of the energy source for the vehicle according to the vehicle speed data; the energy source includes a fuel cell, a lithium battery, and a super capacitor.
The wavelet analysis module is used for performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis include wavelet order and decomposition order.
And the adjusting module is used for adjusting the power bearing results of the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value so as to realize cooperative decline of a vehicle power system.
As an optional implementation manner, the determining module specifically includes:
the fuel cell SOH determining unit is used for obtaining the SOH of the fuel cell at different moments by utilizing a fuel cell recession model according to the data of the fuel cell; a fuel cell SOH change rate determining unit for determining the change rate of the fuel cell SOH according to the fuel cell SOH at different times; the lithium battery SOH determining unit is used for obtaining the SOH of the lithium battery at different moments by utilizing a lithium battery recession model according to the lithium battery data; the lithium battery SOH change rate determining unit is used for determining the SOH change rate of the lithium battery according to the SOH of the lithium battery at different moments; and the SOH difference determining unit is used for determining the SOH difference according to the SOH of the fuel cell and the SOH of the lithium cell at the same moment.
As an optional implementation manner, the construction process of the lithium battery degradation model specifically includes:
acquiring the configuration and system parameters of a whole vehicle system; the whole vehicle system configuration comprises an equivalent circuit model of a lithium battery; and constructing a lithium battery recession model according to the equivalent circuit model.
As an alternative embodiment, the process of constructing the fuel cell degradation model specifically includes:
acquiring historical decline data of the fuel cell; performing wavelet analysis on the historical decline data of the fuel cell to obtain a plurality of sub-waveforms; constructing a plurality of sub-decay models according to a plurality of the sub-waveforms, time, load current, relative humidity, temperature and hydrogen pressure; optimizing the plurality of sub-regression models by using a genetic algorithm to obtain a plurality of optimal regression models; and combining the optimal regression models to obtain a fuel cell regression model.
The method comprises the steps of firstly, determining specific parameters of each part of a three-source system and the configuration of a whole vehicle system; secondly, establishing a fuel cell and an aging degradation model of the cell according to known parameters and historical data; thirdly, obtaining the vehicle speed information and obtainingSOH、dSOH fc 、dSOH b And△SOHa value; fourthly, establishing a dynamic regulation mechanism based on rules, and dynamically regulating the start-stop speed and the wavelet analysis parameter values of the fuel cell through the characteristic values obtained by the modelSynergistic decline is achieved. The invention firstly carries out decline control and service life protection from the perspective of the whole life cycle of the fuel cell and the battery, so that the decline of the fuel cell and the battery tends to be consistent, the problem of the final double-early scrapping caused by the successive decline of the battery and the fuel cell caused by the existing strategy is avoided, the service life cost is effectively saved, and the used model and strategy have real-time performance and applicability.
The method and the system provided by the invention aim to protect the battery by introducing the super capacitor, so that the degradation degrees of the fuel battery and the battery are consistent on the whole life cycle of the energy source, the phenomena that the battery and the fuel battery degrade successively and both are scrapped in advance are avoided, the service lives of the battery and the fuel battery are prolonged, and the total operation cost is reduced. As shown in fig. 2 and 5, a specific flow of the present invention in practical application is also provided, and the steps are as follows:
and step one, specific parameters of each part of the system and the configuration of the whole vehicle system are determined. The energy source parameters comprise maximum power, maximum charge-discharge current, rated voltage and SOC range; the parameters of the driving motor comprise maximum power, maximum rotating speed, maximum torque and efficiency; the whole vehicle structure is as follows: the fuel cell, the battery and the super capacitor are respectively connected with a DC/DC converter, three DC/DC converters are merged into a bus and connected with a driving motor through an AC/DC converter, and the motor is connected with driving wheels of the bus through a main speed reducer.
The invention is applied to a motor coach of a certain type, wherein the energy source parameters of the motor coach of the certain type are shown in tables 1-4. The overall vehicle system configuration is consistent with fig. 3.
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Step two, establishing a battery decline model based on the equivalent circuit model and an empirical formula; a fuel cell degradation model is established based on the historical degradation data of the fuel cell.
Aiming at the decline of the battery, an equivalent circuit model fused with an empirical decline formula is adopted, wherein the battery equivalent circuit model is shown as figure 4, and the state space model is as follows:
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wherein the content of the first and second substances,
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in order to be a state of charge that varies with time,
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is a current that varies with time and is,
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for the purpose of charging the capacity of the battery,
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is composed oftThe current passing through the parallel resistor in the equivalent circuit model at the moment,R p is a resistor connected in parallel with the resistor,C P is a parallel capacitor.
The equivalent circuit model and the constraint conditions are as follows:
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wherein the content of the first and second substances,
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for the voltage of the battery to be varied with time,OCVis a voltage of an open circuit, and,R S is a series resistor.
The voltage decay empirical formula is based on the work of schmalstein et al, specifically:
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wherein the content of the first and second substances,
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in order to account for the lost energy capacity of the battery,
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and
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for the equivalent circuit model degradation parameter,
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is the average voltage of the battery and is,
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in order to be the total simulation time,
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is the elapsed simulation time.
The decay cost is specifically as follows:
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wherein the content of the first and second substances,
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in order to reduce the cost of the energy degradation of the battery,Nas to the number of the battery cells,
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is the declining cost.
Thus, the battery obtained from the modelSOH b Comprises the following steps:
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wherein the content of the first and second substances,
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is the battery energy capacity.
For the degradation of the fuel cell, a degradation model based on historical data drive is adopted, since the degradation mechanism of the fuel cell is not completely studied.
The method comprises the following steps of firstly, performing wavelet analysis on a known historical voltage aging waveform, adopting a Daubechies sixth-order wavelet function, decomposing the waveform of historical data into a plurality of sub-waveforms with the decomposition level of 3.
And secondly, establishing a decline model of each sub-waveform through an extreme learning machine. The model establishment needs to consider five parameters of time, load current, relative humidity, temperature and hydrogen pressure, and the output of the model is the fuel cell voltage:
Figure 849458DEST_PATH_IMAGE027
wherein the content of the first and second substances,
Figure 581659DEST_PATH_IMAGE028
is the voltage of the fuel cell and is,tas a matter of time, the time is,
Figure 116546DEST_PATH_IMAGE029
in order to be the load current,
Figure 308624DEST_PATH_IMAGE030
in order to be the relative humidity,
Figure 30592DEST_PATH_IMAGE031
it is the temperature that is set for the purpose,
Figure 832064DEST_PATH_IMAGE032
is the hydrogen pressure.
And thirdly, coding the input weight of the established degeneration model and the hidden layer neuron threshold value in a binary form to generate an initial population, and automatically and iteratively adjusting the population through a genetic algorithm to obtain the optimal input weight and the hidden neuron threshold value so as to obtain the optimal degeneration model.
And fourthly, combining the decay models of the wavelets to obtain a total decay model of the fuel cell.
The model has the advantages of considering the influence of actual working conditions on the fuel cell, along with high precision, short calculation time and real-time property. Of fuel cellsSOHThe values are predicted by the model through historical aging data collected in the actual operation process.
Training a fuel cell aging model according to historical aging data, establishing a battery aging model according to an equivalent circuit and an empirical formula, and obtaining the fuel cell and the battery in the running process of the vehicleSOHThe value is obtained.
Step three, acquiring real-time vehicle speed information; for obtaining real-time fuel cells and batteriesSOHValue, and then obtaindSOH fc 、dSOH b And△SOHas a follow-up rule judgment parameter.
Step four, establishing a dynamic regulation mechanism based on rules, and judgingdSOH fc 、dSOH b And△SOHthe value is used for dynamically adjusting the starting and stopping speed of the fuel cell and the wavelet analysis parameter value to achieve cooperative decline.
The general idea is that a battery protects a fuel cell, and a super capacitor protects the battery. Protection of the fuel cell is of highest priority, followed by protection of the cell, forming a framework for gradient protection.
Firstly, obtaining the fuel cell and the degradation model of the cell in real time according to the established degradation model of the fuel cell and the cellSOHValue, and then getSOHRate of change andSOHdifference, is recorded as fuel cellSOHRate of changedSOH fc Lithium batterySOHRate of changedSOH b AndSOHdifference value△SOH：
Figure 362402DEST_PATH_IMAGE033
Figure 974649DEST_PATH_IMAGE034
Wherein the content of the first and second substances,
Figure 465804DEST_PATH_IMAGE035
of fuel cells at the present momentSOH，
Figure 290541DEST_PATH_IMAGE036
For fuel cells at the time of last data acquisitionSOH，
Figure 49287DEST_PATH_IMAGE037
For batteries at the present timeSOH，
Figure 566856DEST_PATH_IMAGE038
For batteries at the time of last data acquisitionSOH，TThe period of the strategy is corrected for collecting data once.
And secondly, performing wavelet analysis on the power demand signal input into the power system to obtain decomposed signal components with different frequencies, wherein the low-frequency sub demand power signal after frequency division is borne by a fuel cell, the medium-frequency signal is borne by a battery, and the high-frequency signal is borne by a super capacitor. Wavelet analysis has two important parameters: wavelet orderaAnd a decomposition stageb. According to the principle of wavelet analysis, the higher the wavelet order is, the smoother the decomposed sub-signals are, and the less frequency fluctuation and mutation are contained; the larger the number of decomposition stages, the larger the number of subsignals into which the original signal is decomposed, and the finer the frequency division. The principle formula of the continuous wavelet transform is as follows:
Figure 482991DEST_PATH_IMAGE039
Figure 219740DEST_PATH_IMAGE040
wherein
Figure 318146DEST_PATH_IMAGE041
，
Figure 819666DEST_PATH_IMAGE042
Is a wavelet
Figure 252790DEST_PATH_IMAGE043
The fourier transform of (a) the signal,
Figure 232379DEST_PATH_IMAGE044
in order to be a process of a wavelet transform,
Figure 185291DEST_PATH_IMAGE045
in order to be a fourier transform of the original function,
Figure 910843DEST_PATH_IMAGE046
for the fourier transform of the wavelet function, m and n are wavelet transform parameters, wherein,
Figure 67149DEST_PATH_IMAGE047
. i is an imaginary unit, where complex numbers are represented in the form of an index of e,
Figure 302958DEST_PATH_IMAGE048
to be composed of
Figure 94066DEST_PATH_IMAGE049
Is a frequency domain form wavelet function fourier transform of frequency,
Figure 389918DEST_PATH_IMAGE050
for frequency domain transformation of the function
Figure 33520DEST_PATH_IMAGE051
The latter expression. If a wavelet is assumed
Figure 73020DEST_PATH_IMAGE052
Satisfying the acceptable conditions:
Figure 843268DEST_PATH_IMAGE053
wherein the content of the first and second substances,
Figure 450967DEST_PATH_IMAGE054
in order to accept the condition judgment value,
Figure 113023DEST_PATH_IMAGE055
in order to be the frequency of the radio,
Figure 690635DEST_PATH_IMAGE056
is the Fourier change of the wavelet function in the frequency domain.
Then continuous wavelet transform
Figure 144750DEST_PATH_IMAGE057
Reversible within its scope:
Figure 500514DEST_PATH_IMAGE058
wherein the content of the first and second substances,
Figure 899134DEST_PATH_IMAGE059
the function of the original function is the function of the original function,
Figure 500011DEST_PATH_IMAGE060
is a wavelet function Fourier transform in a time domain form.
During initial operation, db sixth-order wavelet analysis and three-level decomposition are carried out on the power demand signal, the obtained sub-signals are distributed to three energy sources, then two parameters of a fuel cell working speed interval and the wavelet analysis are adjusted according to a given rule in a full life cycle, the fuel cell and the cell decline rate are controlled, and cooperative decline is achieved.
Third, a rule-based dynamic adjustment mechanism is established by comparing fuel cell to battery△ dSOHAnd△SOHand adjusting the start-stop speed interval of the fuel cell and the parameter values of wavelet analysis, and indirectly adjusting the signal frequency range born by the energy source and the quality degree of the requirement to control the degradation rate of the fuel cell and the cell so as to achieve cooperative degradation.
As shown in fig. 6, the optimum efficiency power range is approximately in the range of 10kw to 40kw according to the fuel cell efficiency curve, so that the fuel cell is initially set to operate only in the vehicle speed range of 10km/h or more, and the battery and the supercapacitor respond to the load at the full speed range. According to related documents, when the bus power demand signal is subjected to wavelet analysis decomposition, the initial value is set to six-order db wavelet, and the three-level decomposition level is proper. Since the strategy is designed for a fuel cell and a full life cycle of the cell, the period for collecting data once and correcting the strategy once is 24 h.
The specific rule is as follows: in that
Figure 667687DEST_PATH_IMAGE061
On the premise of, if
Figure 725511DEST_PATH_IMAGE062
Increasing the wavelet orderaThe requirement of the burden of the fuel cell is milder so as to protect the fuel cell; if it is used
Figure 345848DEST_PATH_IMAGE063
The range of the vehicle speed interval in which the fuel cell operates is reduced while increasingWavelet orderaTo further protect the fuel cell. In that
Figure 750416DEST_PATH_IMAGE064
On the premise of, if
Figure 772598DEST_PATH_IMAGE065
Increasing the number of decomposition stagesbThe battery bears medium and low frequency components in a plurality of wavelets, and the demand sub-signal with a larger frequency range is borne by the super capacitor to protect the battery; if it is not
Figure 735744DEST_PATH_IMAGE066
Increasing the wavelet order at the same timeaAnd number of decomposition stagesbThe purpose of simultaneously protecting the fuel cell and the battery is achieved.
a，bAndvthe expression of (c) is as follows. Wherein
Figure 984323DEST_PATH_IMAGE067
The coefficients are empirically given. v is a lower limit value of the speed interval at which the fuel cell starts to operate.
Figure 707428DEST_PATH_IMAGE068
Figure 334850DEST_PATH_IMAGE069
Figure 485208DEST_PATH_IMAGE070
Figure 329405DEST_PATH_IMAGE071
Figure 731568DEST_PATH_IMAGE072
Is wavelet orderThe value of the variation of a is,
Figure 197184DEST_PATH_IMAGE073
is a conversion value of the lower speed limit of the fuel cell operation zone,
Figure 269177DEST_PATH_IMAGE074
the variation value of the number of steps b is decomposed.
The relevant parameters are adjusted in real time in the life cycle of the whole vehicle by adopting the rules, so that the fuel cell and the battery can be ensureddSOHThe working conditions are highly followed in the whole process and basically kept consistent, and the cooperative decline is achieved. In particular, whena，bWhen any item reaches 10 or the lower limit of the speed interval reaches 20km/h, all the parameters are reset to the initial values.
The UDDS working condition is selected, and the two-source system without adding the super capacitor and the three-source system used in the present invention are simulated respectively, and the obtained result schematic diagrams are shown in fig. 7 and 8. Wherein, fig. 7 is a diagram of a simulation curve of SOH variation trend of the dual-source system, and fig. 8 is a diagram of a simulation curve of SOH variation trend of the three-source system, it can be seen that the strategy of the present invention indeed achieves the synergistic degradation of the fuel cell and the battery and the life of both of them is prolonged.
The invention has the following beneficial effects:
decline management and control and life protection are carried out for the first time from the perspective of the full life cycle of the fuel cell and the battery, so that the decline of the fuel cell and the battery tends to be consistent, the problem that the battery and the fuel cell decline successively and finally double-advanced scrapping is avoided, the working life is effectively prolonged, the life cost is saved, and the total operation cost is reduced. A dynamic regulation mechanism based on rules is established, through
Figure 351402DEST_PATH_IMAGE075
Is compared with
Figure 399998DEST_PATH_IMAGE076
Dynamically adjusting wavelet order and decomposition level number of wavelet analysis to make decay rates of fuel cell and battery tend to be consistent, and realizing synergistic decay. The adopted fading model and the adjustment strategy have real-time property and applicability.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A fuel cell and lithium battery hybrid system collaborative recession control method is characterized by comprising the following steps:
acquiring vehicle speed data, fuel cell data and lithium battery data of a vehicle;
determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value of the fuel cell SOH and the lithium cell SOH at the same moment according to the data of the fuel cell and the data of the lithium cell;
determining a power demand bearing result of an energy source to the vehicle according to the vehicle speed data; the energy source comprises a fuel cell, a lithium battery and a super capacitor;
performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis comprise wavelet orders and decomposition orders;
and adjusting the power bearing results of the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value so as to realize cooperative decline of a vehicle power system.
2. The cooperative degradation control method for the fuel cell and lithium battery hybrid system according to claim 1, wherein the determining a change rate of a fuel cell SOH, a change rate of a lithium battery SOH, and a SOH difference between the fuel cell SOH and the lithium battery SOH at the same time according to the fuel cell data and the lithium battery data specifically comprises:
obtaining the SOH of the fuel cell at different moments by using a fuel cell decline model according to the data of the fuel cell;
determining the SOH change rate of the fuel cell according to the SOH of the fuel cell at different moments;
obtaining lithium battery SOH at different moments by using a lithium battery recession model according to the lithium battery data;
determining the SOH change rate of the lithium battery according to the SOH of the lithium battery at different moments;
and determining the SOH difference value according to the SOH of the fuel cell and the SOH of the lithium battery at the same moment.
3. The cooperative degradation control method for the fuel cell and lithium battery hybrid system according to claim 2, wherein the construction process of the degradation model for the lithium battery specifically comprises:
obtaining an equivalent circuit model of the lithium battery;
and constructing a lithium battery recession model according to the equivalent circuit model.
4. The cooperative degradation control method for the fuel cell and lithium battery hybrid system according to claim 2, wherein the construction process of the fuel cell degradation model specifically comprises:
acquiring historical decline data of the fuel cell;
performing wavelet analysis on the historical decline data of the fuel cell to obtain a plurality of sub-waveforms;
constructing a plurality of sub-regression models according to a plurality of the sub-waveforms, time, load current, relative humidity, temperature and hydrogen pressure;
optimizing the plurality of sub-regression models by using a genetic algorithm to obtain a plurality of optimal regression models;
and combining the optimal regression models to obtain a fuel cell regression model.
5. The cooperative degradation control method for the fuel cell and lithium battery hybrid system according to claim 1, wherein the determining a power demand bearing result of an energy source to the vehicle according to the vehicle speed data specifically comprises:
judging whether the vehicle speed data is greater than or equal to a set threshold value or not to obtain a first judgment result;
if the first judgment result is negative, controlling the lithium battery and the super capacitor to bear power requirements;
and if the first judgment result is yes, controlling the fuel cell, the lithium battery and the super capacitor to bear the power requirement.
6. The cooperative degradation control method for the fuel cell and lithium battery hybrid system according to claim 2, wherein the adjusting the power undertaking results of the fuel cell, the lithium battery and the super capacitor according to the frequency dividing requirement signal, the power requirement undertaking result, the fuel cell SOH change rate, the lithium battery SOH change rate and the SOH difference value to realize cooperative degradation of the vehicle power system specifically comprises:
when the power demand assuming result of the energy source to the vehicle represents that the fuel cell, the lithium battery and the super capacitor undertake power demand, distributing the power demand to the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal;
judging whether the SOH change rate of the fuel cell is greater than the SOH change rate of the lithium battery or not to obtain a second judgment result;
if the second judgment result is yes, judging whether the SOH difference value is greater than 0 or not to obtain a third judgment result;
if the third judgment result is yes, increasing the wavelet order to protect the fuel cell;
if the third judgment result is negative, reducing the range of the operating speed of the fuel cell in the frequency division demand signal and increasing the wavelet order;
if the second judgment result is negative, judging whether the SOH difference value is larger than 0 to obtain a fourth judgment result;
if the fourth judgment result is yes, increasing the decomposition order;
and if the fourth judgment result is negative, increasing the wavelet order and the decomposition order.
7. A fuel cell and lithium battery hybrid system collaborative recession control system is characterized by comprising:
the acquisition module is used for acquiring vehicle speed data, fuel cell data and lithium battery data of a vehicle;
the determining module is used for determining the SOH change rate of the fuel cell, the SOH change rate of the lithium cell and the SOH difference value of the fuel cell SOH and the lithium cell SOH at the same moment according to the fuel cell data and the lithium cell data;
the power demand bearing result determining module is used for determining a power demand bearing result of the energy source for the vehicle according to the vehicle speed data; the energy source comprises a fuel cell, a lithium battery and a super capacitor;
the wavelet analysis module is used for performing wavelet analysis on the power demand of the vehicle to obtain a frequency division demand signal; the parameters of the wavelet analysis comprise wavelet orders and decomposition orders;
and the adjusting module is used for adjusting the power bearing results of the fuel cell, the lithium battery and the super capacitor according to the frequency division demand signal, the power demand bearing result, the SOH change rate of the fuel cell, the SOH change rate of the lithium battery and the SOH difference value so as to realize cooperative decline of a vehicle power system.
8. The cooperative degradation control system of the hybrid system of a fuel cell and a lithium cell as claimed in claim 7, wherein the determining module specifically comprises:
the fuel cell SOH determining unit is used for obtaining the SOH of the fuel cell at different moments by utilizing a fuel cell decline model according to the fuel cell data;
a fuel cell SOH change rate determining unit for determining the change rate of the fuel cell SOH according to the fuel cell SOH at different times;
the lithium battery SOH determining unit is used for obtaining the SOH of the lithium battery at different moments by utilizing a lithium battery recession model according to the lithium battery data;
the lithium battery SOH change rate determining unit is used for determining the SOH change rate of the lithium battery according to the SOH of the lithium battery at different moments;
and the SOH difference determining unit is used for determining the SOH difference according to the SOH of the fuel cell and the SOH of the lithium battery at the same moment.
9. The cooperative degradation control system of the fuel cell and lithium battery hybrid system according to claim 8, wherein the construction process of the lithium battery degradation model specifically comprises:
obtaining an equivalent circuit model of the lithium battery;
and constructing a lithium battery recession model according to the equivalent circuit model.
10. The system for controlling cooperative degradation of a fuel cell and lithium battery hybrid system according to claim 8, wherein the process for constructing the degradation model of the fuel cell specifically comprises:
acquiring historical decline data of the fuel cell;
performing wavelet analysis on the historical decline data of the fuel cell to obtain a plurality of sub-waveforms;
constructing a plurality of sub-decay models according to a plurality of the sub-waveforms, time, load current, relative humidity, temperature and hydrogen pressure;
optimizing the plurality of sub-regression models by using a genetic algorithm to obtain a plurality of optimal regression models;
and combining the optimal regression models to obtain a fuel cell regression model.
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