CN114420983A - Method, device and system for evaluating health of fuel cell stack and electronic equipment - Google Patents
Method, device and system for evaluating health of fuel cell stack and electronic equipment Download PDFInfo
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Abstract
The invention provides a method, a device, a system and electronic equipment for evaluating the health of a fuel cell stack, wherein the method comprises the following steps: collecting real-time volt-ampere parameters of a fuel cell stack based on a preset first time interval; determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state; determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types; and if the ratio of the number of the single health degrees changing to the number of the working condition types is larger than a preset calculation threshold, updating the comprehensive health degree according to the single health degree. The method and the device can comprehensively evaluate the change condition of the volt-ampere data of the fuel cell stack within a period of time, and can avoid the interference of transient changes (such as water logging, hydrogen shortage and oxygen shortage) of different operation conditions of the fuel cell stack and the like on the evaluation of the health degree of the stack.
Description
Technical Field
The invention relates to the technical field of fuel cells, in particular to a method, a device and a system for evaluating the health of a fuel cell stack and electronic equipment.
Background
With the rise of proton exchange membrane fuel cells, more and more people are put into their research, but there is still no method for accurately and real-timely determining the lifetime of proton exchange membrane fuel cells.
At present, the performance of the galvanic pile is basically judged by detecting the output voltage of the galvanic pile under rated current, or the water transmission of key materials such as a proton membrane, a catalyst, a gas diffusion layer and the like in the proton exchange membrane fuel cell is analyzed, so that the service life of the galvanic pile is determined; however, the first scheme cannot detect the performance of the galvanic pile in real time, the operation steps are complicated, and the service life error measured by the second scheme is large.
Disclosure of Invention
Based on this, the application provides a fuel cell stack health assessment method, device, system and electronic equipment, and the application utilizes real-time volt-ampere characteristic curve to assess the fuel cell to assess the health degree of the cell in real time, and the scheme can avoid the interference of the transient changes (such as water logging, hydrogen shortage and oxygen shortage) of different operation conditions of the stack and the like on the stack life prediction.
In a first aspect, the present invention provides a method for assessing the health of a fuel cell stack, the method comprising: collecting real-time volt-ampere parameters of a fuel cell stack based on a preset first time interval; determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state; determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types; and if the ratio of the number of the single health degrees changing to the number of the working condition types is larger than a preset calculation threshold, updating the comprehensive health degree according to the single health degree.
In an alternative embodiment, before the step of acquiring the real-time voltammetry parameters of the fuel cell stack based on the preset first time interval, the method further includes: if the fuel cell stack is in initial operation after leaving a factory, acquiring initial volt-ampere parameters of the fuel cell stack within a preset second time interval; wherein the second time interval is greater than the first time interval; and correcting the pre-collected factory volt-ampere parameters according to the initial volt-ampere parameters to obtain corrected volt-ampere parameters and corrected health degree.
In an optional embodiment, the step of determining the operating condition types, the number of the operating condition types, and the sampling times of each operating condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameter or the preset operating condition state includes: determining the output power of the fuel cell stack according to the real-time volt-ampere parameters or the preset working condition state; and determining the working condition types, the number of the working condition types and the sampling times according to the output power, wherein the states of the fuel cell stacks with the same output power are the same type of working conditions.
In an optional embodiment, the step of determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameter, the sampling times, the working condition types and the number of the working condition types includes: determining continuous sampling time of a single working condition according to the sampling times and the first time interval; and if the continuous sampling time is greater than or equal to a preset third time interval, calculating the single health degree under the single working condition.
In an alternative embodiment, the single health at a single operating condition is calculated based on the following equation:
(ii) a Wherein,
the health degree of the patient is a single health degree,
is a real-time voltage value in the real-time volt-ampere parameter,
is a rated voltage value under a single working condition when leaving a factory,
the sampling times under a single working condition.
In an alternative embodiment, the overall health is determined based on the following equation:
(ii) a Wherein,
in order to integrate the degree of health,
the number of the working condition types.
In an optional embodiment, the method further comprises: and determining the current correction operation corresponding to the current abnormal condition according to the historical abnormal condition of the fuel cell stack and the historical correction operation corresponding to the tester.
In a second aspect, the present invention provides an apparatus for evaluating the health of a fuel cell stack, the apparatus comprising: the real-time acquisition module is used for acquiring real-time volt-ampere parameters of the fuel cell stack based on a preset first time interval; the working condition determining module is used for determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state; the single health degree determining module is used for determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types; and the comprehensive health degree determining module is used for updating the comprehensive health degree according to the single health degree if the ratio of the number of the single health degree changes to the number of the working condition types is greater than a preset calculation threshold value.
In a third aspect, the present invention provides a fuel cell stack health assessment system for performing the fuel cell stack health assessment method according to any one of the preceding embodiments; the system includes a vehicle, a fuel cell stack, and a stack health subsystem.
In a fourth aspect, the present invention provides an electronic device comprising a processor and a memory, the memory storing machine executable instructions capable of being executed by the processor, the processor executing the machine executable instructions to implement the method for assessing fuel cell stack health of any one of the preceding embodiments.
The embodiment of the invention has the following beneficial effects:
the invention provides a method, a device, a system and electronic equipment for evaluating the health of a fuel cell stack, wherein the method comprises the following steps: collecting real-time volt-ampere parameters of a fuel cell stack based on a preset first time interval; determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state; determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types; and if the ratio of the number of the single health degrees changing to the number of the working condition types is larger than a preset calculation threshold, updating the comprehensive health degree according to the single health degree. The method and the device can comprehensively evaluate the change condition of the volt-ampere data of the fuel cell stack within a period of time, and can avoid the interference of transient changes (such as water logging, hydrogen shortage and oxygen shortage) of different operation conditions of the fuel cell stack and the like on the evaluation of the health degree of the stack.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention as set forth above.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for evaluating the health of a fuel cell stack according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for assessing fuel cell stack health according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a factory voltammogram and a calibration voltammogram provided in an embodiment of the present invention;
FIG. 4 is a 220A current output accumulated operating data statistical chart of a fuel cell stack according to an embodiment of the present invention;
FIG. 5 is a graph of the 370A current output cumulative operating data for a fuel cell stack according to an embodiment of the present invention;
FIG. 6 is a graph illustrating the 310A current output cumulative operating data of a fuel cell stack according to an embodiment of the present invention;
fig. 7 is a schematic diagram illustrating a comparison between the factory volt-ampere characteristic parameter and the volt-ampere characteristic parameter attenuated to 90% according to the embodiment of the present invention;
fig. 8 is a schematic diagram of a third method for evaluating the health of a fuel cell stack according to an embodiment of the present invention;
fig. 9 is a schematic diagram of an apparatus for evaluating the health of a fuel cell stack according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a system for evaluating the health of a fuel cell stack according to an embodiment of the present invention;
fig. 11 is a schematic view of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
With the rise of proton exchange membrane fuel cells, more and more people are put into their research, but there is still no very accurate method for determining the lifetime of proton exchange membrane fuel cells.
At present, the performance of the stack is basically determined by detecting the output voltage of the stack under the rated current, or the service life of the stack is determined by analyzing the water transmission of key materials such as a proton membrane, a catalyst, a gas diffusion layer and the like in the proton exchange membrane fuel cell. However, the first scheme cannot detect the performance of the fuel cell stack in real time, and the operation steps are complex, the second scheme generally needs to set up a test bed, the fuel cell system runs for a long time in the whole kilometer range, the mass flow of the water content of each part in the running process of the fuel cell system is calculated, the actual service life of the fuel cell stack is recorded, the performance parameters of the fuel cell system are compared with the mass flow of the water content, a map of the performance of the fuel cell stack and the mass flows of the four water contents is fitted through correction and comparison, and then the performance of the fuel cell system is calculated by using the map, so that the service life (or the health degree) of the fuel cell system is estimated. The second solution has the disadvantage that the measurement of the water content of the fuel cell stack is difficult. Secondly, under different operating conditions of the fuel cell and different temperatures of the galvanic pile, the water content of the proton exchange membrane of the galvanic pile is different, so that the method for evaluating the service life of the galvanic pile through the water content of the galvanic pile is inaccurate. And thirdly, the galvanic pile may be flooded when running, and when the galvanic pile is flooded, the service life error of the galvanic pile is estimated by the water content of the galvanic pile to be larger. Fourthly, when the life of the galvanic pile is attenuated, predicting the life of the galvanic pile by a method for evaluating the water content of the galvanic pile has larger errors (the water content and the attenuation of the life of the galvanic pile are not in a linear relation), carrying out bench test on the system before loading the system to obtain an initial map, and realizing the prediction of the life of the subsequent galvanic pile based on the initial map, wherein the method is complex.
Based on this, the present application provides a fuel cell stack health assessment method, device, system and electronic device, and the scheme utilizes a real-time volt-ampere characteristic curve to assess the fuel cell so as to assess the health degree of the cell in real time, and can avoid the interference of the transient changes (such as water flooding, hydrogen shortage, oxygen shortage) of different operation conditions of the stack and the like on the stack life prediction. The technology is applied to the technical scene of predicting the health degree and the service life of the battery.
Example one
An embodiment of the present invention provides a method for evaluating the health of a fuel cell stack, as shown in fig. 1, where the method includes:
and S102, collecting real-time volt-ampere parameters of the fuel cell stack based on a preset first time interval.
In particular, the first time interval refers to a sampling frequency, such as collecting the voltammetric parameters every 2 seconds. The real-time volt-ampere parameters refer to the real-time output current and the real-time output voltage of the fuel cell stack.
And step S104, determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state.
Specifically, the operating condition refers to the output power of the fuel cell stack, and the output power can be obtained by using the output current and the output voltage in the real-time volt-ampere parameter. The states with the same output power are the same kind of working conditions. Throughout the use of the fuel cell, a total number of samples under any type of operating condition needs to be recorded.
And S106, determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types.
Specifically, the single health degree refers to the health condition of the battery under any type of working condition. The above single health degree may be changed, that is, the battery health may be improved or may be attenuated or may not be changed. In addition, the single health degree can be recalculated only when the continuous sampling time exceeds a certain time interval (the sampling time of a certain working condition is discontinuous, and the sum of the fragmented sampling time is the continuous sampling time), otherwise, the numerical value of the single health degree is not changed.
And S108, if the ratio of the number of the single health degrees changing to the number of the working condition types is larger than a preset calculation threshold, updating the comprehensive health degree according to the single health degree.
Specifically, the number of the working condition types refers to how many output powers the fuel cell has in the total test time, for example, in the total test time, the vehicle may have various operating states such as acceleration, smooth driving, deceleration, braking, and the like, and accordingly, the number of the working condition types is 5 if there may be 5 working conditions of 10 kw, 50 kw, 80 kw, 100 kw, and 200 kw for the output power of the fuel cell. If the preset calculation threshold is 60%, if the health degree under 3 working conditions is found to be changed, executing step S108; if the health degree under 1 or 2 working conditions is found to be changed, the health state of the fuel cell stack is considered to be unchanged, and the step S108 is not executed. The volt-ampere characteristic curve is in a linear relation with the service life of the galvanic pile, and when the service life of the galvanic pile is reduced, the volt-ampere characteristic curve of the galvanic pile is also reduced, so that the service life reduction condition of the galvanic pile can be evaluated only by evaluating the initial volt-ampere characteristic curve of the system and the volt-ampere characteristic curve of the system after the system is used for a period of time. The method and the device can comprehensively evaluate the change condition of the volt-ampere data of the fuel cell stack within a period of time, and can avoid the interference of transient changes (such as water logging, hydrogen shortage and oxygen shortage) of different operation conditions of the fuel cell stack and the like on the evaluation of the health degree of the stack.
Specifically, the steps S102 to S108 are all real-time tests after the fuel cell is loaded, and the health of the stack can be evaluated without disassembling the fuel cell. According to the invention, through evaluating the volt-ampere characteristic curve of the galvanic pile, the health degree of the battery can be evaluated in real time without performing bench test on a system before loading the battery to obtain initial data, and the method is convenient and fast in practical application.
Specifically, all the data, such as the volt-ampere parameters, the preset time interval, the preset threshold, and the health value, are stored in the FCU memory Fan Coil Unit) in real time for being called at any time.
The present embodiment is a method for evaluating the health of a fuel cell stack, the method including: collecting real-time volt-ampere parameters of a fuel cell stack based on a preset first time interval; determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state; determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types; and if the ratio of the number of the single health degrees changing to the number of the working condition types is larger than a preset calculation threshold, updating the comprehensive health degree according to the single health degree. The method and the device can comprehensively evaluate the change condition of the volt-ampere data of the fuel cell stack within a period of time, and can avoid the interference of transient changes (such as water logging, hydrogen shortage and oxygen shortage) of different operation conditions of the fuel cell stack and the like on the evaluation of the health degree of the stack.
Example two
Another method for evaluating the health of a fuel cell stack is provided in an embodiment of the present invention, as shown in fig. 2, the method includes:
step S202, judging whether the fuel cell stack is in initial operation after delivery.
And step S204, if the fuel cell stack is operated for the first time after leaving the factory, acquiring the initial volt-ampere parameter of the fuel cell stack in a preset second time interval.
In particular, the second time interval is greater than the first time interval.
And S206, correcting the pre-collected factory volt-ampere parameters according to the initial volt-ampere parameters to obtain corrected volt-ampere parameters and corrected health degree.
Specifically, although a description of a galvanic pile is attached to a fuel cell when the fuel cell is shipped, the description may record a voltammetry parameter when the fuel cell is shipped (the fuel cell is activated and has a performance reaching the standard), but the fuel cell is generally placed in a warehouse for several months or even several years from shipping to loading, and the health degree of the fuel cell is necessarily reduced in this period of time, so that it is necessary to collect a real-time voltage and current parameter (i.e., an initial voltammetry parameter) within a second time interval (e.g., 20 hours) after loading, and modify the shipping voltammetry parameter on the shipping specification according to the parameter, to obtain a corrected voltammetry parameter and a corrected health degree, and to obtain a subsequent health degree evaluation basis after the corrected voltammetry parameter and the corrected health degree are left. This operation can reduce the error of the health assessment.
Specifically, as shown in fig. 3, which is a schematic diagram of a factory voltammogram and a calibration voltammogram, it can be seen that the voltammogram of the fuel cell after being left for a certain period of time is shifted.
And step S208, collecting real-time volt-ampere parameters of the fuel cell stack based on a preset first time interval.
And step S210, determining the output power of the fuel cell stack according to the real-time volt-ampere parameters or the preset working condition state.
Specifically, the output power may be obtained by multiplying the real-time output current and the output voltage in the real-time voltammetry parameters. Alternatively, the output power may be obtained according to the operating state of the vehicle. There are many ways to determine the real-time output power, and the method is not limited herein.
And S212, determining the working condition types, the number of the working condition types and the sampling times according to the output power, wherein the states of the fuel cell stacks with the same output power are the same type of working conditions.
Step S214, determining the continuous sampling time of the single working condition according to the sampling times and the first time interval.
Specifically, the continuous sampling time refers to the sum of intermittent sampling times under a certain working condition, and the continuous sampling time is less than the total testing time. For example, the vehicle runs for 40 hours (i.e., the total test time is 40 hours), and the sampling times in the states of 10 kw, 50 kw, 80 kw, 100 kw, and 200 kw are 5 hours, 10 hours, 20 hours, 4 hours, and 1 hour, respectively. And multiplying the sampling times under a certain working condition by the first time interval to obtain the continuous sampling time of any single working condition. Under each working condition, the operation data can be respectively counted, and fig. 4 is a 220A current output accumulated operation data statistical graph of the fuel cell stack; FIG. 5 is a graph of 370A current output cumulative operating data statistics; FIG. 6 is a statistical graph of the 310A current output cumulative operating data.
In step S216, it is determined whether the continuous sampling time is greater than or equal to a preset third time interval.
In step S218, if the continuous sampling time is greater than or equal to the preset third time interval, the single health degree under the single working condition is calculated.
In step S220, if the continuous sampling time is less than the preset third time interval, the single health degree under the working condition is not changed.
Specifically, for example, if the preset third time interval is 5 hours, only the single health degree of the working condition under 10 kilowatts, 50 kilowatts and 80 kilowatts is calculated; because the continuous sampling time is short and has no reference value, the health degree of the working condition under 100 kilowatts and 200 kilowatts is temporarily considered to be unchanged, and the operation can reduce the calculation amount in the process of evaluating the health degree.
Specifically, the single health under a single operating condition is calculated based on the following equation:
wherein,
the health degree of the patient is a single health degree,
is a real-time voltage value in the real-time volt-ampere parameter,
is a rated voltage value under a single working condition when leaving a factory,
the sampling times under a single working condition are the sampling times,
is composed of
And summing the real-time voltage values of the sampling points.
Specifically, in the system operation process, the attenuation conditions of the stack (namely the single health degree) under different working condition points are calculated in real time, the health degree attenuation data are counted, and when the single health degree data fluctuate (possibly increase and possibly decrease), the comprehensive health degree calculation and updating of the battery are triggered.
Specifically, 3 single health degrees of the current working conditions under 10 kilowatts, 50 kilowatts and 80 kilowatts can be calculated through formula 1), for example, 99%, 98% and 97% respectively (the corresponding previous health degree or corrected health degree under the 3 working conditions is 99%, 99% and 99% respectively, and then the health degree under 2 working conditions (50 kilowatts and 80 kilowatts) is found to be attenuated, and the health degree under 1 working condition (10 kilowatts) is not changed); it can also be obtained that the health degree under 100 kw and 200 kw is not calculated, that is, the health degree value is unchanged and still is the last health degree or the corrected health degree: 99% and 99.5%.
Step S222, determining whether a ratio between the number of changes in the single health degree and the number of the working condition types is greater than a preset calculation threshold.
Specifically, the above calculation threshold is any value between 0 and 1, such as 0.3. If the number of the above-mentioned working condition types is 5 and the number of the single health degree changes is 2, the ratio between the number of the single health degree changes and the number of the working condition types is 0.4, and 0.4 is greater than 0.3, so step S224 is executed, otherwise step S226 is executed.
In step S224, if the ratio between the number of changes of the single health degree and the number of the working condition types is greater than the preset calculation threshold, the comprehensive health degree is updated according to the single health degree.
Specifically, the comprehensive health degree is determined based on the following equation:
wherein,
in order to integrate the degree of health,
the number of the working condition types.
Specifically, different weights may be set according to the importance of different working conditions, for example, the weight of the working condition with high output power is set to be larger data, so that more objective comprehensive health data can be obtained.
Specifically, when the integrated health degree is less than 90%, it indicates that the fuel cell needs to be replaced (the factory health degree is default to 100%), and fig. 7 is a schematic diagram comparing the factory voltammetry parameters with the voltammetry parameters decaying to 90%.
In step S226, if the ratio between the number of changes of the single health degree and the number of the working condition types is not greater than the preset calculation threshold, the comprehensive health degree is not updated.
The method further comprises the following steps: and determining the current correction operation corresponding to the current abnormal condition according to the historical abnormal condition of the fuel cell stack and the historical correction operation corresponding to the tester.
Specifically, the scheme can also integrate the voltage and current data of the galvanic pile under different working conditions, self-learn and record the operation mode of the driver, and subsequently provide system operation suggestions (such as suggestions for manually restarting the system by the driver, suggestions for stopping the system and purging the system by the driver and the like) which can be referred by the driver. Because the performance Of the electric pile is attenuated to be a long-term process, when the electric pile voltage drops under the same output current (lasting for a certain time), a driver can possibly determine that the electric pile is flooded and the like under the condition, so the driver can manually control the fuel cell system to purge and restart, an SOH (Stack Of Health) system can record the operation process Of the driver manual control system under different current voltages and automatically conduct the training Of the SOH system, after the process lasts for a period Of time, the SOH system can repeatedly generate the state, and the driver is warned to manually operate and protect the fuel cell electric pile when the driver does not manually perform the operation.
The self-learning training part of the SOH system is characterized in that various problems of voltage drop of the cell stack can be met in the testing stage, testers can manually intervene in the operation (shutdown purging, activation and the like) of the fuel cell system according to the problems, the manual intervention process of the testers is also used for training the SOH algorithm, and after the training is mature, the SOH algorithm can give different suggestions according to different current volt-ampere characteristic curves of the cell stack.
In addition, the present embodiment also provides a schematic diagram of a third method for evaluating the health of a fuel cell stack, as shown in fig. 8.
For the process of fig. 8, when the fuel cell system is in use, the fuel cell system will switch back and forth between different operating conditions (from idle to peak power operating conditions), the system control software will sample the stack voltage and current data at fixed time intervals, and the stack voltage data at different times of the same stack output current will be compared in the software, and the stack performance degradation will be determined only when 70% (data is estimated data, the specific value needs to be trained by a large amount of data, and the percentage can be set arbitrarily) of data has an error with the initial data.
The fuel cell SOH evaluation system recognizes that stack performance decay requires a period of time (20 hours of estimated run time and not subsequently resumed, where 20 hours is the third time interval) to detect a decay in stack current-voltage characteristic from the initial stack current-voltage characteristic before it can be recognized as stack performance decay. If the SOH system detects a 20 hour stack current-voltage characteristic decay, but then the system state recovers during operation and the decay disappears, then it is assumed that no decay has occurred in the fuel cell stack.
According to the technical scheme in the embodiment, additional testing on the fuel cell is not needed, real-time health evaluation of the galvanic pile can be carried out in real time in the operation process of the fuel cell, and the user is warned when the service life of the galvanic pile is reduced to the limit. The method and the device can comprehensively evaluate the change condition of the volt-ampere data of the fuel cell stack within a period of time, and can avoid the interference of transient changes (such as water logging, hydrogen shortage and oxygen shortage) of different operation conditions of the fuel cell stack and the like on the evaluation of the health degree of the stack.
EXAMPLE III
The present invention provides an apparatus for evaluating the health of a fuel cell stack, as shown in fig. 9, the apparatus comprising:
and the real-time acquisition module 91 is configured to acquire real-time volt-ampere parameters of the fuel cell stack based on a preset first time interval.
And the working condition determining module 92 is configured to determine the working condition types, the number of the working condition types, and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameter or the preset working condition state.
And the single health degree determining module 93 is used for determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types.
And the comprehensive health degree determining module 94 is configured to update the comprehensive health degree according to the single health degree if a ratio of the number of changes of the single health degree to the number of the working condition types is greater than a preset calculation threshold.
The implementation principle and the technical effects of the device for evaluating the health of the fuel cell stack provided by the embodiment of the invention are the same as those of the embodiment of the method for evaluating the health of the fuel cell stack, and for the sake of brief description, corresponding contents in the embodiment of the method can be referred to where the embodiment of the device is not mentioned.
Example four
The present invention provides a fuel cell stack health assessment system for performing the fuel cell stack health assessment method according to any one of the preceding embodiments.
The above-described evaluation system of the fuel cell stack health includes a vehicle 1, a fuel cell stack 2, and a stack health sub-system 3, as shown in fig. 10.
Specifically, before the whole process of the application is started, the fuel cell stack is required to be installed at a corresponding position of a vehicle, then the vehicle and the stack health subsystem are started, the stack health subsystem is used for collecting volt-ampere parameters of the vehicle under different working conditions so as to automatically update and predict the health degree of the fuel cell stack, and when the health degree is lower than a preset health threshold value, a user is reminded to replace the fuel cell.
The implementation principle and the generated technical effect of the system for evaluating the health of the fuel cell stack provided by the embodiment of the invention are the same as those of the embodiment of the method for evaluating the health of the fuel cell stack, and for the sake of brief description, corresponding contents in the embodiment of the method can be referred to where the embodiment of the system is not mentioned.
EXAMPLE five
An embodiment of the present invention provides an electronic device, which includes a processor and a memory, where the memory stores machine executable instructions capable of being executed by the processor, and the processor executes the machine executable instructions to implement the method for evaluating the health of a fuel cell stack according to any one of the foregoing embodiments.
An embodiment of the present invention further provides an electronic device, which is shown in fig. 11 and includes a processor 101 and a memory 100, where the memory 100 stores machine executable instructions capable of being executed by the processor 101, and the processor executes the machine executable instructions to implement the above-mentioned method for evaluating the health of a fuel cell stack.
Further, the electronic device shown in fig. 5 further includes a bus 102 and a communication interface 103, and the processor 101, the communication interface 103, and the memory 100 are connected through the bus 102.
The Memory 100 may include a high-speed Random Access Memory (RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 103 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used. The bus 102 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 5, but this does not indicate only one bus or one type of bus.
The processor 101 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 101. The Processor 101 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 100, and the processor 101 reads the information in the memory 100, and completes the steps of the method of the foregoing embodiment in combination with the hardware thereof.
Embodiments of the present invention further provide a machine-readable storage medium, where the machine-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the above method for evaluating the health of a fuel cell stack.
The method, the apparatus, the system and the computer program product for evaluating the health of a fuel cell stack provided in the embodiments of the present invention include a computer readable storage medium storing program codes, where instructions included in the program codes may be used to execute the methods described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and will not be described herein again.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of assessing the health of a fuel cell stack, the method comprising:
collecting real-time volt-ampere parameters of a fuel cell stack based on a preset first time interval;
determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state;
determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types;
and if the ratio of the number of the single health degrees which change to the number of the working condition types is larger than a preset calculation threshold, updating the comprehensive health degree according to the single health degree.
2. The method of claim 1, wherein prior to the step of collecting real-time voltammetric parameters of the fuel cell stack based on a preset first time interval, the method further comprises:
if the fuel cell stack is in initial operation after leaving a factory, acquiring initial volt-ampere parameters of the fuel cell stack within a preset second time interval; wherein the second time interval is greater than the first time interval;
and correcting the pre-collected factory volt-ampere parameters according to the initial volt-ampere parameters to obtain corrected volt-ampere parameters and corrected health degree.
3. The method according to claim 1, wherein the step of determining the operating condition types, the number of the operating condition types and the sampling times of each operating condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset operating condition states comprises the following steps:
determining the output power of the fuel cell stack according to the real-time volt-ampere parameter or the preset working condition state;
and determining the working condition types, the number of the working condition types and the sampling times according to the output power, wherein the states of the fuel cell stacks with the same output power are the same type of working conditions.
4. The method of claim 2, wherein the step of determining the single health of the fuel cell stack from the real-time voltammetric parameters, the number of samplings, the operating condition type, and the number of operating condition types comprises:
determining the continuous sampling time of a single working condition according to the sampling times and the first time interval;
and if the continuous sampling time is greater than or equal to a preset third time interval, calculating the single health degree under the single working condition.
5. The method of claim 4, wherein the single health at the single operating condition is calculated based on the following equation:
wherein,
in order for the single degree of health to be said,
is a real-time voltage value in the real-time volt-ampere parameter,
the rated voltage value under the single working condition when the device is delivered from a factory,
the sampling times under the single working condition are obtained.
6. The method of claim 5, wherein the overall health is determined based on the following equation:
wherein,
in order to obtain the overall degree of health,
the number of the working condition types is shown.
7. The method of claim 1, further comprising:
and determining the current correction operation corresponding to the current abnormal condition according to the historical abnormal condition of the fuel cell stack and the historical correction operation corresponding to the tester.
8. An apparatus for evaluating the health of a fuel cell stack, the apparatus comprising:
the real-time acquisition module is used for acquiring real-time volt-ampere parameters of the fuel cell stack based on a preset first time interval;
the working condition determining module is used for determining the working condition types, the number of the working condition types and the sampling times of each working condition type of the fuel cell stack in the working process according to the real-time volt-ampere parameters or the preset working condition state;
the single health degree determination module is used for determining the single health degree of the fuel cell stack according to the real-time volt-ampere parameters, the sampling times, the working condition types and the number of the working condition types;
and the comprehensive health degree determining module is used for updating the comprehensive health degree according to the single health degree if the ratio of the number of the single health degree changes to the number of the working condition types is greater than a preset calculation threshold.
9. A fuel cell stack health assessment system for performing the fuel cell stack health assessment method according to any one of claims 1 to 7;
the system includes a vehicle, a fuel cell stack, and a stack health subsystem.
10. An electronic device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor, the processor executing the machine executable instructions to implement the fuel cell stack health assessment method of any one of claims 1 to 7.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114843558A (en) * | 2022-05-20 | 2022-08-02 | 上海捷氢科技股份有限公司 | Method and device for determining operating characteristics of fuel cell |
| CN114976130A (en) * | 2022-06-08 | 2022-08-30 | 中国第一汽车股份有限公司 | Vehicle fuel cell system health state evaluation method and system, electronic device and storage medium |
| CN115663242A (en) * | 2022-11-11 | 2023-01-31 | 苏州氢辀新能源科技有限公司 | Fuel cell detection method and system |
| US20230216074A1 (en) * | 2022-01-04 | 2023-07-06 | Hyundai Motor Company | System and method for determining performance of fuel cell stack |
| CN117665684A (en) * | 2023-12-05 | 2024-03-08 | 广东天汇储能科技有限公司 | Method and device for testing lithium battery state estimation algorithm |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002151125A (en) * | 2000-11-14 | 2002-05-24 | Mitsubishi Heavy Ind Ltd | Abnormality detecting method for fuel cell and abnormality detecting device for fuel cell |
| US20110115491A1 (en) * | 2009-11-16 | 2011-05-19 | Hyundai Motor Company | Method for detecting ice blocking of fuel cell stack and controlling fuel cell vehicle using the same |
| CN104297691A (en) * | 2014-09-29 | 2015-01-21 | 上海吉能电源系统有限公司 | Battery pack health status diagnostic system and method |
| CN107957562A (en) * | 2018-01-05 | 2018-04-24 | 广西大学 | A kind of lithium ion battery residual life on-line prediction method |
| CN109143099A (en) * | 2018-11-12 | 2019-01-04 | 潍柴动力股份有限公司 | A kind of method and device of preestimating battery system health |
| CN109747482A (en) * | 2019-02-02 | 2019-05-14 | 北京长城华冠汽车科技股份有限公司 | A kind of operation method and running gear of Vehicular dynamic battery group |
| CN110077282A (en) * | 2019-05-16 | 2019-08-02 | 上海楞次新能源汽车科技有限公司 | The online life detecting method of the fuel cell of new-energy automobile, system and device |
| CN110658462A (en) * | 2019-10-25 | 2020-01-07 | 北京航空航天大学 | Lithium battery online service life prediction method based on data fusion and ARIMA model |
| CN111144021A (en) * | 2019-12-30 | 2020-05-12 | 新源动力股份有限公司 | Fuel cell service life prediction method and system |
| CN111443294A (en) * | 2020-04-10 | 2020-07-24 | 华东理工大学 | Method and device for indirectly predicting remaining life of lithium ion battery |
| CN112257984A (en) * | 2020-09-24 | 2021-01-22 | 南方电网调峰调频发电有限公司 | State monitoring method based on health degree evaluation of power equipment |
| CN112784216A (en) * | 2021-01-26 | 2021-05-11 | 武汉船用电力推进装置研究所（中国船舶重工集团公司第七一二研究所） | Health degree evaluation method and system of proton exchange membrane fuel cell system |
| CN113281671A (en) * | 2021-06-28 | 2021-08-20 | 长安大学 | Lithium ion battery remaining service life prediction method and system based on IGS-SVM |
| CN215065121U (en) * | 2021-07-21 | 2021-12-07 | 深圳市雄韬电源科技股份有限公司 | Device for testing waterway seal life of hydrogen fuel cell |
-
2022
- 2022-03-31 CN CN202210327748.7A patent/CN114420983B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002151125A (en) * | 2000-11-14 | 2002-05-24 | Mitsubishi Heavy Ind Ltd | Abnormality detecting method for fuel cell and abnormality detecting device for fuel cell |
| US20110115491A1 (en) * | 2009-11-16 | 2011-05-19 | Hyundai Motor Company | Method for detecting ice blocking of fuel cell stack and controlling fuel cell vehicle using the same |
| CN104297691A (en) * | 2014-09-29 | 2015-01-21 | 上海吉能电源系统有限公司 | Battery pack health status diagnostic system and method |
| CN107957562A (en) * | 2018-01-05 | 2018-04-24 | 广西大学 | A kind of lithium ion battery residual life on-line prediction method |
| CN109143099A (en) * | 2018-11-12 | 2019-01-04 | 潍柴动力股份有限公司 | A kind of method and device of preestimating battery system health |
| CN109747482A (en) * | 2019-02-02 | 2019-05-14 | 北京长城华冠汽车科技股份有限公司 | A kind of operation method and running gear of Vehicular dynamic battery group |
| CN110077282A (en) * | 2019-05-16 | 2019-08-02 | 上海楞次新能源汽车科技有限公司 | The online life detecting method of the fuel cell of new-energy automobile, system and device |
| CN110658462A (en) * | 2019-10-25 | 2020-01-07 | 北京航空航天大学 | Lithium battery online service life prediction method based on data fusion and ARIMA model |
| CN111144021A (en) * | 2019-12-30 | 2020-05-12 | 新源动力股份有限公司 | Fuel cell service life prediction method and system |
| CN111443294A (en) * | 2020-04-10 | 2020-07-24 | 华东理工大学 | Method and device for indirectly predicting remaining life of lithium ion battery |
| CN112257984A (en) * | 2020-09-24 | 2021-01-22 | 南方电网调峰调频发电有限公司 | State monitoring method based on health degree evaluation of power equipment |
| CN112784216A (en) * | 2021-01-26 | 2021-05-11 | 武汉船用电力推进装置研究所（中国船舶重工集团公司第七一二研究所） | Health degree evaluation method and system of proton exchange membrane fuel cell system |
| CN113281671A (en) * | 2021-06-28 | 2021-08-20 | 长安大学 | Lithium ion battery remaining service life prediction method and system based on IGS-SVM |
| CN215065121U (en) * | 2021-07-21 | 2021-12-07 | 深圳市雄韬电源科技股份有限公司 | Device for testing waterway seal life of hydrogen fuel cell |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20230216074A1 (en) * | 2022-01-04 | 2023-07-06 | Hyundai Motor Company | System and method for determining performance of fuel cell stack |
| CN114843558A (en) * | 2022-05-20 | 2022-08-02 | 上海捷氢科技股份有限公司 | Method and device for determining operating characteristics of fuel cell |
| CN114976130A (en) * | 2022-06-08 | 2022-08-30 | 中国第一汽车股份有限公司 | Vehicle fuel cell system health state evaluation method and system, electronic device and storage medium |
| CN115663242A (en) * | 2022-11-11 | 2023-01-31 | 苏州氢辀新能源科技有限公司 | Fuel cell detection method and system |
| CN115663242B (en) * | 2022-11-11 | 2023-12-19 | 苏州氢辀新能源科技有限公司 | Fuel cell detection method and system |
| CN117665684A (en) * | 2023-12-05 | 2024-03-08 | 广东天汇储能科技有限公司 | Method and device for testing lithium battery state estimation algorithm |
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