CN115602891A - Multi-stack fuel cell output power distribution method and system based on water activity correction - Google Patents
Multi-stack fuel cell output power distribution method and system based on water activity correction Download PDFInfo
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Abstract
The invention relates to a multi-stack fuel cell output power distribution method and system based on water activity correction, and belongs to the technical field of multi-stack fuel cell power distribution.
Description
Technical Field
The invention relates to the technical field of multi-stack fuel cell power distribution, in particular to a multi-stack fuel cell output power distribution method and system based on water activity correction.
Background
With the increasing environmental problems in the world, countries in the world seek new clean energy sources in an attempt to reduce the emission of harmful gases in the use of existing energy sources, and international energy transformation advances along the way from high carbon to low carbon. Hydrogen is the most ideal energy carrier and clean energy provider recognized at present, and is known as the ultimate energy of the 21 st century. At present, a common use mode of hydrogen is to generate electricity through a proton exchange membrane fuel cell, the hydrogen releases electric energy through a chemical reaction of the hydrogen and oxygen, is not limited by Carnot cycle, and has the advantages of high energy conversion rate, high energy density, high starting speed, low noise, zero emission and the like.
However, the power output of the fuel cell is smooth, the power level is not high, and the output voltage drops rapidly under the condition of large current, so that the performance is reduced and the service life is reduced, so that many researchers focus on coordinating a plurality of single-stack fuel cells at present to construct a plurality of fuel cells to solve the problems of high power requirement and durability. The prior art discloses a multi-stack distributed control method based on fuel cell health degree correction, which collects voltage and current signals at a demand side, evaluates the real-time operation performance of fuel cells through the obtained voltage, current and power of the output end of the fuel cells, quantifies the health degree of each fuel cell, calculates a real-time self-setting factor related to the current performance state of each fuel cell according to the health degree calculation result of the fuel cells by combining the circuit of a direct current supply network and current-carrying characteristics, and finally completes the self-adaptive adjustment of the output power of the fuel cells through the quick correction of a voltage outer ring and a current inner ring under the change of the real-time self-setting factor to realize the distributed control among the multi-stack fuel cells.
Disclosure of Invention
The invention aims to provide a multi-stack fuel cell output power distribution method and system based on water activity correction.
In order to achieve the purpose, the invention provides the following scheme:
a multi-stack fuel cell output power distribution method based on water activity correction, the distribution method comprising:
acquiring the relative humidity of each sub-electric pile in the multi-pile fuel cell to obtain real-time water activity;
for each sub-electric pile, calculating a real-time health factor of the sub-electric pile according to the real-time water activity;
and distributing power to be distributed according to the real-time health factors of the sub-galvanic piles, and determining the output power of each sub-galvanic pile.
A multi-stack fuel cell output power distribution system based on water activity correction, the distribution system comprising:
the information acquisition module is used for acquiring the relative humidity of each sub-electric pile in the multi-pile fuel cell to obtain real-time water activity;
the health factor calculation module is used for calculating the real-time health factor of each sub-electric pile according to the real-time water activity;
and the distribution module is used for distributing power to be distributed according to the real-time health factors of the sub-galvanic piles and determining the output power of each sub-galvanic pile.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a multi-stack fuel cell output power distribution method and system based on water activity correction.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, 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 that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method of an allocation method according to embodiment 1 of the present invention;
fig. 2 is a control schematic diagram of the allocation method provided in embodiment 1 of the present invention;
fig. 3 is a schematic view of an application scenario of the allocation method provided in embodiment 1 of the present invention;
fig. 4 is a control schematic diagram of power allocation provided in embodiment 1 of the present invention;
fig. 5 is a system block diagram of the distribution system provided in embodiment 2 of the present invention.
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 multi-stack fuel cell output power distribution method and system based on water activity correction, which are more specific, free from oscillation and good in stability.
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.
Example 1:
on one hand, when the power request is increased, the hydrogen-oxygen fuel cell causes the temperature of the stack to be increased, the water activity to be reduced, the water content in the membrane to be reduced, the conductivity of the membrane to be reduced and the ohmic loss to be increased, so that the output voltage is reduced and the performance of the stack is reduced. On the other hand, the water activity is reduced, the concentration of the reactant is reduced relative to the concentration of the product, the reactant in the catalytic layer is consumed along with the reaction, the concentration of the reactant is reduced, the concentration of the reactant in the flow channel is kept unchanged, the concentration difference is formed between the inside and the outside of the electrode, the reactant in the outer area is diffused to the catalytic layer under the action of the concentration gradient, and similarly, the product is accumulated in the catalytic layer, the concentration is increased, and is diffused outwards from the catalytic layer. In summary, ohmic loss and concentration loss are all linked to water activity, and when there is a better output voltage according to the current water activity, or when the temperature is too high (water activity is too low), the output voltage drops faster, so the health factor is derived according to the water activity to adjust the output power, so that the water activity is in a better range, and the stack performance is maintained, that is, the link between the water activity and the stack output voltage drop can be established, and the health factor is derived, and the health factor is used as the basis for power distribution among the fuel cells in multiple stacks, so as to maintain the good performance of the stack, and realize the distribution management and control of the output power of the fuel cells in multiple stacks.
Based on this, the present embodiment is configured to provide a multi-stack fuel cell output power distribution method based on water activity correction, as shown in fig. 1, the distribution method includes:
s1: acquiring the relative humidity of each sub-electric pile in the multi-pile fuel cell to obtain real-time water activity;
specifically, the relative temperature of each sub-stack can be collected by a humidity sensor, and the relative humidity is the real-time water activity.
The formula for defining water activity (essentially relative humidity) is as follows:
wherein a is water activity;
is the current actual waterPartial pressure of vapor; p sat The saturated water vapor partial pressure at the current temperature.
S2: for each sub-electric pile, calculating a real-time health factor of the sub-electric pile according to the real-time water activity;
in this embodiment, the calculation formula of the real-time health factor for measuring the performance of the fuel cell is as follows:
wherein H is a real-time health factor; a is the real-time water activity; a is acute Is a water activity preset value; delta a is the real-time water activity a and the preset value of water activity a acute Is equal to a-a acute 。
The preset water activity value of this embodiment is the water activity at the severe water activity point determined based on the offline test, and the severe water activity point is defined as: when the temperature rise interval is N ℃, the output voltage drop of the later point and the current point is at least the preset multiple of the output voltage drop of the current point and the previous point, and the current point at the moment is the point with severe water activity.
Further, in this embodiment, the off-line testing process of the severe water activity point of the fuel cell includes the following steps:
(1) Performing voltage-current test on the fuel cell with good performance, acquiring output voltage and water activity of the fuel cell at a plurality of different temperatures, and constructing a first output voltage set and a first water activity set; the adjacent temperatures are spaced by N degrees centigrade.
(2) And respectively interpolating the first output voltage set and the first water activity set by utilizing a Lagrange interpolation method to obtain a second output voltage set and a second water activity set, wherein the temperature intervals between adjacent output voltages of the second output voltage set are M DEG C, the temperature intervals between adjacent water activities of the second water activity set are M DEG C, and M is less than N.
In this embodiment, the first output voltage set and the second output voltage set are both sets obtained by sorting all output voltages in order of temperature from small to large, and only N degrees celsius are provided between adjacent output voltages of the first output voltage set, and M degrees celsius is provided between adjacent output voltages of the second output voltage set; the first water activity set and the second water activity set are sets obtained by sequencing all water activities according to the order of the temperature from small to large, and only the interval between the adjacent water activities of the first water activity set is N degrees centigrade, and the interval between the adjacent water activities of the second water activity set is M degrees centigrade.
For a fuel cell system, the expression of the lagrange interpolation is: y (k) = f (x (k), x) S ，y s ) (ii) a Wherein y (k) is an interpolation function value and respectively corresponds to the output voltage and the water activity of the fuel cell at the interval of M DEG C; x (k) is data to be interpolated, corresponding to points spaced at M DEG C, x s ＝[x 0 ，x 1 ，x 2 ，...，x i-1 ，x i ，x i+1 ，...x n ]The node variable data are corresponding to temperature data at intervals of N degrees centigrade; y is s ＝[y 0 ，y 1 ，y 2 ，...，y i-1 ，y i ，y i+1 ，...，y n ]And the node function values respectively correspond to the output voltage and the water activity data of the fuel cell at intervals of N degrees centigrade.
Basis functions l of Lagrange interpolation i The expression of (x (k)) is:
the expression of the interpolating polynomial y (k) is:
based on the interpolation polynomial, the output voltage and the water activity can be interpolated.
(3) For each first output voltage of the second output voltage set, determining a second temperature and a third temperature which are separated from the first temperature by N degrees centigrade according to the first temperature corresponding to the first output voltage, and calculating a first voltage drop between the first output voltage and the second output voltage corresponding to the second temperature and a second voltage drop between the first output voltage and the third output voltage corresponding to the third temperature; judging whether the ratio of the first voltage drop to the second voltage drop is greater than or equal to a preset ratio or not; if so, the first temperature is the water activity intensity point, and the water activity corresponding to the first temperature is the preset water activity value.
The second temperature is a temperature which is lower than the first temperature and is separated from the first temperature by N degrees centigrade, and the third temperature is a temperature which is higher than the first temperature and is separated from the first temperature by N degrees centigrade.
In this embodiment, N may be 1 degree celsius, M may be 0.1 degree celsius, the preset ratio may be 1.8, that is, the collected output voltage and water activity are at an interval of 1 degree celsius, the output voltage and water activity after interpolation are at an interval of 0.1 degree celsius, a plurality of voltage drops may be formed by subtracting the output voltage signals at an interval of 1 degree celsius from each other, and then the process of traversing and retrieving the water activity sharp point may include: subtracting the output voltage data subjected to Lagrange interpolation at 10 points (namely at 1 ℃ interval) to obtain voltage drops, and then dividing each voltage drop by the previous voltage drop to obtain a ratio capable of representing the voltage drop speed, wherein if the ratio is greater than or equal to 1.8, the point is a water activity violent point, and the water activity corresponding to the point is a preset water activity value. For example, for the voltage drop between the 10 th point and the 20 th point, the previous voltage drop refers to the voltage drop between the 10 th point and the 0 th point, if the ratio of the two voltage drops is greater than or equal to 1.8, the 10 th point is the point with severe water activity, and the water activity corresponding to the 10 th point is the preset value of water activity. The traversal retrieval process of the embodiment is performed according to the sequence of temperature from low to high, when the severe water activity point is determined, traversal retrieval is stopped, each sub-stack correspondingly performs the offline test process, and then the only severe water activity point of each sub-stack can be determined through the steps.
Through the operation, the problem of inaccurate detection caused by too small interval of collected signals is avoided, collection points can be reduced, and the workload of offline testing is reduced. Compared with the prior art that a large number of data points need to be tested offline to identify performance characterization parameters of the fuel cell, the ideal voltage-current relationship is obtained and is used as a basis for good performance, the testing work is complex, the point with severe water activity in the embodiment is offline testing, the number of test points is small, the work is simple, the water activity can be calculated by acquiring temperature and humidity signals through temperature and humidity sensors during actual operation, and the method is easy to implement.
The code for traversing and searching the water activity fierce point is as follows:
in this embodiment, real-time health factors representing the real-time operation performance of each sub-electric pile are quantified according to the acquired real-time water activity of each sub-electric pile and by combining with the water activity intensity points of each sub-electric pile determined by the offline test.
S3: and distributing power to be distributed according to the real-time health factor of each sub-galvanic pile, and determining the output power of each sub-galvanic pile.
Preferably, as shown in fig. 2, S3 may include:
(1) Judging whether the real-time health factor of each sub-electric pile is 1; if not, taking the sub-electric pile as a first sub-electric pile; if so, taking the sub-electric pile as a second sub-electric pile;
(2) For each first sub-galvanic pile, taking the real-time health factor of the first sub-galvanic pile as input, driving a PWM signal generator to generate a PWM signal by utilizing a self-adaptive fuzzy setting PID control algorithm, adjusting a DC-DC converter based on the PWM signal, and determining the output power of the first sub-galvanic pile;
as shown in FIG. 3, each sub-stack of the multi-stack fuel cell is connected to a voltage bus through a DC-DC converter in parallel, in the embodiment, a real-time health factor is calculated through relative humidity collected at the output end of the sub-stack, the real-time health factor is subtracted from a reference value 1 to obtain an error and an error change rate, and a proportional coefficient k is obtained through an adaptive fuzzy setting PID control algorithm p Integral coefficient of action k i Differential coefficient of action k d And three parameters are used for controlling the PWM signal generator to generate a PWM signal, and regulating and controlling the output power of each sub-cell stack by regulating the DC-DC converter through the PWM signal.
Specifically, as shown in fig. 4, the adaptive fuzzy PID control algorithm includes a fuzzy controller and a PID controller, and the driving the PWM signal generator to generate the PWM signal by using the adaptive fuzzy PID control algorithm with the real-time health factor of the first sub-stack as an input may include:
1) Calculating the difference value between the real-time health factor of the first sub-galvanic pile and 1 to obtain an error and an error change rate;
the error is the difference between the health factor and 1, the error change rate is the difference between the error at the current moment and the error at the previous moment divided by the time interval between the current moment and the previous moment, namely the error change rate is equal to [ e (tau) -e (tau-1) ]/delta tau, and e (tau) is the error at the time tau; e (tau-1) is the error of tau-1 time; Δ τ is the time interval between time τ and time τ -1.
2) Taking the error and the error change rate as input, and calculating control parameters of a PID controller by using a fuzzy controller, wherein the control parameters comprise a proportional coefficient, an integral action coefficient and a differential action coefficient;
in this embodiment, the error e and the range of change of the error change rate ec are defined as the domain of discourse on the fuzzy set, the domain of discourse of e is { -1,0,1}, and the domain of discourse of ec is { -1,0,1}.
Considering the simplification of the test work to make the implementation easier, the fuzzy subset used by the fuzzy controller is { NB, ZE, PB }, NB represents negative (< 0), ZE represents zero (= 0), and PB represents positive (> 0), i.e. the elements in the subset represent negative, zero, positive, respectively.
Membership functions for the respective fuzzy subsets may be selected from Sigmoid-type functions and trigonometric-type functions.
Based on the fuzzy subset, there are 9 control rules for fuzzy control, i.e. the control rules used by the fuzzy controller include:
if the error is NB and the error change rate is NB, the proportional coefficient is PB, the integral action coefficient is NB and the differential action coefficient is ZE;
if the error is NB and the error change rate is ZE, the proportional coefficient is PB, the integral action coefficient is NB and the differential action coefficient is NB;
if the error is NB and the error change rate is PB, the proportional coefficient is ZE, the integral action coefficient is ZE and the differential action coefficient is ZE;
if the error is ZE and the error change rate is NB, the proportional coefficient is PB, the integral action coefficient is NB and the differential action coefficient is ZE;
if the error is ZE and the error change rate is ZE, the proportional coefficient is ZE, the integral action coefficient is ZE and the differential action coefficient is ZE;
if the error is ZE and the error change rate is PB, the proportional coefficient is NB, the integral action coefficient is PB and the differential action coefficient is ZE;
if the error is PB and the error change rate is NB, the proportional coefficient is ZE, the integral action coefficient is ZE and the differential action coefficient is PB;
if the error is PB and the error change rate is ZE, the proportional coefficient is NB, the integral action coefficient is PB and the differential action coefficient is PB;
if the error is PB and the error change rate is PB, the proportional coefficient is NB, the integral action coefficient is PB and the differential action coefficient is PB.
The expression of the above 9 fuzzy rules is as follows:
If(e is NB)and(ec is NB)，then(k p is PB)(k i is NB)(k d is ZE)；
If(e is NB)and(ec is ZE)，then(k p is PB)(k i is NB)(k d is NB)；
If(e is NB)and(ec is PB)，then(k p is ZE)(k i is ZE)(k d is ZE)；
If(e is ZE)and(ec is NB)，then(k p is PB)(k i is NB)(k d is ZE)；
If(e is ZE)and(ec is ZE)，then(k p is ZE)(k i is ZE)(k d is ZE)；
If(e is ZE)and(ec is PB)，then(k p is NB)(k i is PB)(k d is ZE)；
If(e is PB)and(ec is NB)，then(k p is ZE)(k i is ZE)(k d is PB)；
If(e is PB)and(ec is ZE)，then(k p is NB)(k i is PB)(k d is PB)；
If(e is PB)and(ec is PB)，then(k p is NB)(k i is PB)(k d is PB)；
calculating the control parameters of the PID controller using the fuzzy controller with the error and the error change rate as inputs based on the above universe of discourse, fuzzy subset, membership function and fuzzy rule may include: fuzzifying the error and the error change rate by a membership function to obtain a fuzzification result, calculating the membership degree of the control parameter according to the fuzzification result and a pre-established fuzzy rule, and then performing deblurring processing on the membership degree of the control parameter to obtain a corrected value of the control parameter, wherein the deblurring processing can be performed by an area center method, an area bisection method and a maximum membership degree method (maximum value, minimum value or average value), the above processes can be completed by a fuzzy inference machine, namely, a proportional coefficient k is obtained by the fuzzy inference machine p Integral coefficient of action k i Differential coefficient of action k d Correction value Δ k of p (e(k)，ec(k))、Δk i (e (k), ec (k)) and Δ k d (e (k), ec (k)), and substituting the formula to obtain the optimized output k of the control parameter p (k)、k i (k)、k d (k)，
k p (k)＝k p (0)+Δk p (e(k)，ec(k))；
k i (k)＝k i (0)+Δk i (e(k)，ec(k))；
k d (k)＝k d (0)+Δk d (e(k)，ec(k))；
Wherein k is p (0)、k i (0)、k d (0) Are each k p 、k i 、k d Is taken as the initial value.
3) And driving the PWM signal generator to generate the PWM signal by using the PID controller based on the control parameter.
The Pulse Width Modulation (PWM) method (e.g., SPWM, SVPWM, etc.) obtains a desired pulse output by controlling the on/off (i.e., on/off) of the switching tube, and a corresponding control strategy needs to be designed for controlling the on/off of the switching tube. In the embodiment, the PWM signal can be generated through commercial software such as matlab, and the Fuzzy control part can be quickly built through a Fuzzy toolbox.
The DC-DC converter is regulated and controlled by the self-adaptive fuzzy setting PID control algorithm, repeated debugging work can be avoided, control parameters can be continuously adjusted along with the change of the characteristics of a controlled system and the change of the environment, and a self-adaptive control rule can be formed on the premise of ensuring the stability of the system.
(3) Calculating the difference value between the power to be distributed and the sum value of the output power of all the first sub-electric piles to obtain the residual power; and (4) carrying out average distribution on the residual power to obtain the output power of each second sub-electric pile.
After each first sub-electric pile is controlled, the output voltage and the output current of each first sub-electric pile can be obtained by utilizing a plurality of current sensors and voltage sensors which are arranged on a voltage bus, and the product of the output voltage and the output current is calculated, so that the output power of each first sub-electric pile can be obtained. And calculating the sum of the output power of all the first sub-electric piles, and subtracting the sum from the power to be distributed to obtain the residual power. And (4) carrying out average distribution on the residual power to obtain the output power of each second sub-electric pile. At this time, the output power of each second sub-stack is still adjusted through the PWM signal generator and the DC-DC converter, specifically, the PWM signal generator generates a corresponding PWM signal based on the output power of the second sub-stack, and the DC-DC converter is controlled by using the PWM signal, so that the adjustment process of the output power of the second sub-stack can be completed.
According to the power distribution strategy provided by the embodiment, the sub-electric piles deviating from the set health factor 1 are compared with the health factor and the reference value 1 to obtain errors and error change rates according to the health factor, and a k is obtained through a self-adaptive fuzzy tuning PID algorithm p 、k i 、k d The optimal value of the power distribution coefficient is used for regulating and controlling the PWM signal generator to obtain a PWM signal, then the DC-DC converter is regulated through the PWM signal, and the average power distribution is carried out on the rest sub-electric piles to realize the self-adaptive distribution of the output power of the fuel cell, so that each sub-electric pile works in a linear section and the good performance of each sub-electric pile is kept.
In order to solve the performance and durability problems of the multi-stack fuel cell, the present embodiment provides a multi-stack fuel cell output power allocation method based on fuel cell water activity correction, which includes monitoring the water activity of the fuel cell system, calculating a real-time health factor, and performing power adjustment on a portion (the second half of a polarization curve) where the performance of the fuel cell decreases faster according to the real-time health factor, so as to keep the fuel cell stack operating in a linear section to maintain the good performance of the stack, and increase the system life. Considering the change of the working environment and the state of the fuel cell, adjusting k by adopting a PID (proportion integration differentiation) parameter online optimization setting algorithm based on self-adaptive fuzzy setting p 、k i 、k d The three parameters are used for measuring the time and frequency of the pulse,the PWM signal transmitted to the DC-DC controller is adaptively adjusted, the output power distribution of the multi-pile fuel cell is realized, and each sub-pile returns to the set health factor 1 through the power distribution, so that the purposes of stably operating each sub-pile under the appropriate condition and prolonging the service life are achieved.
In the embodiment, the health factor is used for judging the degree of deviation of the galvanic pile from a severe water activity point (namely a critical point with fast output voltage drop), the health factor is used as the input of a fuzzy distribution algorithm to correct three control parameters for regulating and controlling a PWM signal so as to complete a distribution process, the control is mainly performed on the rear half section of a polarization curve with fast fuel cell performance drop, the performance can be adjusted on the premise of keeping the stable operation of the galvanic pile, and the adjustment oscillation can be avoided. The non-oscillation is that the distribution algorithm responds only when the critical point is exceeded, and the distribution algorithm keeps stable operation after being adjusted, compared with the distribution strategy of the optimal distribution class, the distribution algorithm and the optimal distribution strategy are adjusted according to the optimal path under a certain working condition, and due to the hysteresis of the output power response of the fuel cell, the working condition point is changed (if the working condition points of the two times of adjustment are mutually the working condition points adjusted by the opposite side or close) possibly due to the adjustment effect of the last time point, and then the readjustment is initiated to circulate.
Example 2:
the present embodiment is configured to provide a multi-stack fuel cell output power distribution system based on water activity correction, as shown in fig. 5, the distribution system includes:
the information acquisition module M1 is used for acquiring the relative humidity of each sub-electric pile in the multi-pile fuel cell to obtain real-time water activity;
the health factor calculation module M2 is used for calculating a real-time health factor of each sub-galvanic pile according to the real-time water activity;
and the distribution module M3 is used for distributing power to be distributed according to the real-time health factors of the sub-electric piles and determining the output power of each sub-electric pile.
The embodiment collects real-time water activity to evaluate the performance of the current fuel cell working section and derives the health factor as powerThe basis of control; combining a self-adaptive fuzzy setting PID algorithm, taking the health factor deviation as input, k p 、k i 、k d The PWM signal is output and regulated, and then the DC-DC converter is controlled to achieve the self-adaptive regulation of the output power, the control is mainly carried out aiming at the second half section of the polarization curve with fast performance reduction of the fuel cell, the performance can be regulated on the premise of keeping the stable operation of the galvanic pile, and the regulation oscillation is avoided.
In the description, each embodiment is mainly described as different 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 principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea 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 (7)
1. A method for allocating output power of a multi-stack fuel cell based on water activity correction, the method comprising:
acquiring the relative humidity of each sub-electric pile in the multi-pile fuel cell to obtain real-time water activity;
for each sub-electric pile, calculating a real-time health factor of the sub-electric pile according to the real-time water activity;
and distributing power to be distributed according to the real-time health factor of each sub-galvanic pile, and determining the output power of each sub-galvanic pile.
2. The assignment method of claim 1, wherein the real-time health factor is calculated by:
wherein H is a real-time health factor; a is the real-time water activity; a is acute The water activity is a preset value; Δ a is the difference between the real-time water activity and the preset water activity value.
3. The dispensing method according to claim 2, wherein the preset value of water activity is the water activity at the intense point of water activity determined on the basis of an off-line test;
the offline test comprises the following steps:
performing a voltage-current test on the fuel cell, acquiring output voltage and water activity of the fuel cell at a plurality of temperatures, and constructing a first output voltage set and a first water activity set; the interval between the adjacent temperatures is N degrees centigrade;
respectively interpolating the first output voltage set and the first water activity set by using a Lagrange interpolation method to obtain a second output voltage set and a second water activity set; the temperature intervals between the temperatures corresponding to the adjacent output voltages of the second output voltage set are M degrees centigrade, and the temperature intervals between the temperatures corresponding to the adjacent water activities of the second water activity set are M degrees centigrade; m is less than N;
for each first output voltage of the second output voltage set, determining a second temperature and a third temperature which are N degrees centigrade apart from the first temperature according to the first temperature corresponding to the first output voltage, and calculating a first voltage drop between the first output voltage and the second output voltage corresponding to the second temperature and a second voltage drop between the first output voltage and the third output voltage corresponding to the third temperature; judging whether the ratio of the first voltage drop to the second voltage drop is greater than or equal to a preset ratio or not; if so, the first temperature is the water activity intensity point; and the water activity corresponding to the first temperature is the preset water activity value.
4. The allocation method according to claim 1, wherein the allocating power to be allocated according to the real-time health factor of each sub-stack, and the determining the output power of each sub-stack specifically comprises:
judging whether the real-time health factor of each sub-electric pile is 1 or not; if not, taking the sub-electric pile as a first sub-electric pile; if so, taking the sub-electric pile as a second sub-electric pile;
for each first sub-galvanic pile, taking a real-time health factor of the first sub-galvanic pile as an input, driving a PWM signal generator to generate a PWM signal by using an adaptive fuzzy setting PID control algorithm, adjusting a DC-DC converter based on the PWM signal, and determining the output power of the first sub-galvanic pile;
calculating the difference value between the power to be distributed and the sum value of the output power of all the first sub-electric piles to obtain the residual power; and evenly distributing the residual power to obtain the output power of each second sub-electric pile.
5. The distribution method according to claim 4, wherein the adaptive fuzzy PID control algorithm comprises a fuzzy controller and a PID controller, and the driving of the PWM signal generator to generate the PWM signal by using the adaptive fuzzy PID control algorithm with the real-time health factor of the first sub-stack as an input specifically comprises:
calculating the difference value between the real-time health factor of the first sub-galvanic pile and 1 to obtain an error and an error change rate;
calculating control parameters of the PID controller by using the fuzzy controller by taking the error and the error change rate as input; the control parameters comprise a proportional coefficient, an integral action coefficient and a differential action coefficient;
and driving a PWM signal generator to generate a PWM signal by using the PID controller based on the control parameter.
6. The allocation method according to claim 5, wherein the fuzzy subset used by the fuzzy controller is { NB, ZE, PB }, NB representing negative, ZE representing zero, PB representing positive;
the control rules used by the fuzzy controller include:
if the error is NB and the error change rate is NB, the proportional coefficient is PB, the integral action coefficient is NB and the differential action coefficient is ZE;
if the error is NB and the error change rate is ZE, the proportional coefficient is PB, the integral action coefficient is NB and the differential action coefficient is NB;
if the error is NB and the error change rate is PB, the proportional coefficient is ZE, the integral action coefficient is ZE and the differential action coefficient is ZE;
if the error is ZE and the error change rate is NB, the proportional coefficient is PB, the integral action coefficient is NB and the differential action coefficient is ZE;
if the error is ZE and the error change rate is ZE, the proportional coefficient is ZE, the integral action coefficient is ZE and the differential action coefficient is ZE;
if the error is ZE and the error change rate is PB, the proportional coefficient is NB, the integral action coefficient is PB and the differential action coefficient is ZE;
if the error is PB and the error change rate is NB, the proportional coefficient is ZE, the integral action coefficient is ZE and the differential action coefficient is PB;
if the error is PB and the error change rate is ZE, the proportional coefficient is NB, the integral action coefficient is PB and the differential action coefficient is PB;
if the error is PB and the error change rate is PB, the proportional coefficient is NB, the integral action coefficient is PB, and the differential action coefficient is PB.
7. A multi-stack fuel cell output power distribution system based on water activity correction, the distribution system comprising:
the information acquisition module is used for acquiring the relative humidity of each sub-electric pile in the multi-pile fuel cell to obtain real-time water activity;
the health factor calculation module is used for calculating a real-time health factor of each sub-galvanic pile according to the real-time water activity;
and the distribution module is used for distributing power to be distributed according to the real-time health factors of the sub-electric piles and determining the output power of each sub-electric pile.
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