Validation and correction of gen 2 anode H2 concentration estimation

A system and method for determining whether a concentration estimation value of hydrogen gas in an anode sub-system of a fuel cell system is within a predetermined threshold of a valid hydrogen gas concentration, and if not, correcting the estimation value. The method includes providing a hydrogen gas concentration sensor value from a virtual sensor and calculating the hydrogen gas concentration estimation value using a gas concentration estimation model. The method also includes determining if a difference between the estimation value and the sensor value is greater than at least one threshold, and if so, causing an extended bleed event to occur that bleeds an anode exhaust gas to force the estimation value to be closer to the sensor value. The method also includes setting a diagnostic if multiple extended bleeds do not cause the estimation value and the sensor value to converge.

BACKGROUND OF THE INVENTION

Field of the Invention

This invention relates generally to a system and method for validating an estimation of hydrogen gas in an anode of a fuel stack and, more particularly, to a system and method for validating an estimation of hydrogen gas in an anode of a fuel cell stack and correcting the estimation if an error is identified, where the method includes comparing a measurement from a hydrogen gas virtual sensor to the estimation of the hydrogen gas that is determined using a gas concentration estimation model.

Discussion of the Related Art

A hydrogen fuel cell is an electro-chemical device that includes an anode and a cathode with an electrolyte therebetween. The anode receives hydrogen gas and the cathode receives oxygen or air. The hydrogen gas is dissociated in the anode to generate free hydrogen protons and electrons. The hydrogen protons pass through the electrolyte to the cathode. The electrons from the anode cannot pass through the electrolyte, and thus are directed through a load to perform work before being sent to the cathode. Proton exchange membrane fuel cells (PEMFC) are a popular fuel cell type for vehicles, and generally includes a solid polymer electrolyte proton conducting membrane, such as a perfluorosulfonic acid membrane. The anode and cathode typically include finely divided catalytic particles, usually platinum (Pt), supported on carbon particles and mixed with an ionomer, where the catalytic mixture is deposited on opposing sides of the membrane. The combination of the anode catalytic mixture, the cathode catalytic mixture and the membrane define a membrane electrode assembly (MEA).

Several fuel cells are typically combined in a fuel cell stack to generate the desired power. A fuel cell stack typically includes a series of flow field or bipolar plates positioned between the several MEAs in the stack, where the bipolar plates and the MEAs are positioned between two end plates. The bipolar plates include an anode side and a cathode side for adjacent fuel cells in the stack. Anode gas flow channels are provided on the anode side of the bipolar plates that allow the anode reactant gas to flow to the respective MEA. Cathode gas flow channels are provided on the cathode side of the bipolar plates that allow the cathode reactant gas to flow to the respective MEA. One end plate includes anode gas flow channels, and the other end plate includes cathode gas flow channels. The bipolar plates and end plates are made of a conductive material, such as stainless steel or a conductive composite. The end plates conduct the electricity generated by the fuel cells out of the stack. The bipolar plates also include flow channels through which a cooling fluid flows.

Many fuel cell system control algorithms require knowing the concentration of hydrogen gas in the anode sub-system of the fuel cell system for various purposes, such as maintaining fuel cell stack stability, promoting a healthy start-up/shutdown sequence of the system, and initiating a hydrogen gas injection event to maintain hydrogen in the anode side during system off-time. It is possible to provide a gas concentration sensor at a strategic location in the fuel cell system, such as the output of the anode, to measure the concentration of the particular gas, such as hydrogen. However, in order for these types of sensors to provide an accurate estimation of the gas in the hot and wet environment of a fuel cell system, the sensors are very expensive, and still are not fully reliable, thus rendering them ineffective for automotive fuel cell system applications.

The MEAs in the fuel cells are permeable and thus allow nitrogen in the air from the cathode side of the stack to permeate through and collect in the anode side of the stack, often referred to as nitrogen cross-over. Even though the anode side pressure may be slightly higher than the cathode side pressure, cathode side partial pressures will cause air to permeate through the membrane. Nitrogen in the anode side of the fuel cell stack dilutes the hydrogen such that if the nitrogen concentration increases above a certain percentage, such as 50%, fuel cells in the stack may become starved of hydrogen. If a fuel cell becomes hydrogen starved, the fuel cell stack will fail to produce adequate electrical power and may suffer damage to the electrodes in the fuel cell stack. Thus, it is known in the art to provide a bleed valve in the anode exhaust gas output line of the fuel cell stack to remove nitrogen from the anode side of the stack. The fuel cell system control algorithms will identify a desirable minimum hydrogen gas concentration in the anode, and cause the bleed valve to open when the gas concentration falls below that threshold, where the threshold is based on stack stability.

It is known in the art to estimate the molar fraction of nitrogen and other gases in the anode side of a fuel cell stack using a model to determine when to perform the bleed of the anode side or anode sub-system. For example, gas concentration estimation (GCE) models are known for estimating hydrogen, nitrogen, oxygen, water vapor, etc. in various volumes of a fuel cell system, such as the anode flow-field, anode plumbing, cathode flow-field, cathode header and plumbing, etc. U.S. Pat. No. 8,195,407 issued Jun. 5, 2012 to Salvador et al., assigned to the assignee of this invention and herein incorporated by reference, describes one exemplary GCE model for this purpose.

It has been shown that these types of GCE models are susceptible to a number of operating conditions of the fuel cell system that can cause the GCE model to provide a relatively inaccurate estimation of the particular gas. Additionally, component failures and degradation of the components in the fuel cell system, such as the fuel cell membrane, may also cause errors in the model estimation. If the anode nitrogen molar fraction estimation is significantly higher than the actual nitrogen molar fraction, the fuel cell system will vent or bleed more anode gas than is necessary, i.e., will waste hydrogen fuel. If the anode nitrogen molar fraction estimation is significantly lower than the actual nitrogen molar fraction, the system will not vent enough anode gas and may starve the fuel cells of reactants, which may damage the electrodes in the fuel cell stack. In addition, current fuel cell system processes do not allow for correction of the hydrogen gas estimation if it is determined to be inaccurate.

SUMMARY OF THE INVENTION

The present invention discloses and describes a system and method for determining whether a concentration estimation value of hydrogen gas in an anode sub-system of a fuel cell system is within a predetermined threshold of a valid hydrogen gas concentration, and if not, correcting the estimation value. The method includes providing a hydrogen gas concentration sensor value from a virtual sensor and calculating a hydrogen gas concentration estimation value using a gas concentration estimation model. The method also includes determining if a difference between the estimation value and the sensor value is greater than at least one threshold, and if so, causing an extended bleed event to occur that bleeds an anode exhaust gas to force the estimation value to be closer to the sensor value. The method also includes setting a diagnostic if multiple extended bleeds do not cause the estimation value and the sensor value to converge.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The following discussion of the embodiments of the invention directed to a system and method for determining whether an estimation of hydrogen gas in an anode sub-system of a fuel cell stack is accurate is merely exemplary in nature, and is in no way intended to limit the invention or its applications or uses.

FIG. 1is a schematic block diagram of a fuel cell system10including a fuel cell stack12. A compressor14provides an airflow to the cathode side of the fuel cell stack12on a cathode input line16through a water vapor transfer (WVT) unit18that humidifies the cathode input air. A cathode exhaust gas is output from the stack12on a cathode exhaust gas line20that directs the cathode exhaust gas to the WVT unit18to provide the water vapor to humidify the cathode input air. The fuel cell system10also includes a source24of hydrogen fuel, typically a high pressure tank, that provides hydrogen gas to an injector26that injects a controlled amount of the hydrogen gas to the anode side of the fuel cell stack12on an anode input line28. Although not specifically shown, one skilled in the art would understand that various pressure regulators, control valves, shut-off valves, etc. would be provided to supply the high pressure hydrogen gas from the source24at a pressure suitable for the injector26. The injector26can be any injector suitable for the purposes discussed herein. One example is an injector/ejector as described in U.S. Pat. No. 7,320,840, titled, Combination of Injector/Ejector for Fuel Cell Systems, issued Jan. 22, 2008, assigned to the assignee of this application and herein incorporated by reference.

An anode effluent output gas is output from the anode side of the fuel cell stack12on an anode output line30, which is provided to a bleed valve32. As discussed above, nitrogen cross-over from the cathode side of the fuel cell stack12dilutes the hydrogen gas in the anode side of the stack12, thereby affecting fuel cell stack performance. Therefore, it is necessary to periodically bleed the anode effluent gas from the anode sub-system to reduce the amount of nitrogen in the anode sub-system. When the system10is operating in a normal non-bleed mode, the bleed valve32is in a position where the anode effluent gas is provided to a recirculation line36that recirculates the anode gas to the injector26to operate it as an ejector and provide recirculated hydrogen gas back to the anode input of the stack12. When a bleed is commanded to reduce the nitrogen in the anode side of the stack12, the bleed valve32is positioned to direct the anode effluent gas to a by-pass line34that combines the anode effluent gas with the cathode exhaust gas on the line20, where the hydrogen gas is diluted to a level suitable for the environment.

The system10also includes a virtual hydrogen gas sensor40that measures the hydrogen gas concentration in the anode sub-system of the fuel cell system10. The measured hydrogen gas concentration is provided to a controller38that performs the gas concentration comparison and estimations discussed herein. As will be discussed in detail below, the present invention proposes a system and method for determining whether a gas concentration estimation (GCE) model is providing an accurate estimation of the hydrogen gas concentration in the anode sub-system of the fuel cell system10by comparing the estimation to a measurement value from the virtual hydrogen gas sensor40, and if the estimation and the measurement value deviate beyond a predetermined threshold, then the system and method command a bleed to correct the hydrogen gas estimation. The system and method also set a counter and generate a diagnostic trouble code if the number of deviation events exceeds a predetermined threshold.

The know GCE model determines the hydrogen gas concentration within the anode and cathode sub-systems during all possible fuel cell system states. To accomplish this, the model needs to change its functionality based on the fuel cell system operating mode. The GCE model adjusts the anode hydrogen gas concentration based on the estimated flow of the anode exhaust that is leaving the anode sub-system through an output valve. The model also accounts for the electro-chemical hydrogen consumption and gas permeation through the fuel cell membranes that can change due to the age of the fuel cell stack materials. The GCE model converts the hydrogen gas concentration to a mole fraction of each individual gas within the anode and cathode flow streams and can be used to analyze the model estimation accuracy verses measurement information from a hydrogen concentration sensor. The gas concentration estimation is completely model based and does not include direct or indirect feedback information making it an open loop model with an integrating error potential.

FIG. 2is a flow chart diagram60showing a process performed by algorithms in the controller38for determining whether a gas concentration estimation value that identifies an estimation of hydrogen gas in the anode sub-system of the fuel cell system10using a GCE model is accurate, and if not, correcting the estimation value. The algorithm begins at box62and obtains a hydrogen gas measurement value from a hydrogen gas concentration sensor at box64. As discussed above, hydrogen gas concentration sensors are generally not provided in fuel cell systems on a vehicle because the sensors are typically costly and unreliable as a result of the wet environment that the fuel cell system operates in. The hydrogen concentration sensor referred to herein may be the virtual sensor40that obtains a hydrogen gas concentration measurement value by other known processes or algorithms separate from the GCE model, and can be an actual hydrogen gas concentration sensor online or offline.

In one embodiment, the virtual sensor40measures the hydrogen gas concentration based on voltage measurements of the fuel cell stack12and is provided at each bleed event. Thus, the measurement provided by the virtual sensor40may not always be available as a valid measurement. Therefore, the algorithm determines, based on the operating conditions of the fuel cell system10, whether the virtual sensor40is providing a valid measurement at decision diamond66, and if it is not a valid measurement, the algorithm determines whether the time that has elapsed from a previous hydrogen gas concentration estimation correction is greater than a predetermined threshold, such as three seconds, at decision diamond68. As mentioned, the algorithm performs a comparison between the available virtual sensor measurement value and the hydrogen gas concentration estimation value calculated by the GCE model, and if those values are different beyond a predetermined threshold, then the algorithm corrects the concentration estimation value provide by the model. Thus, the time elapsed at the decision diamond68is the time from the last time that the estimation value was corrected. If the time elapsed is not greater than the threshold at the decision diamond68, then the algorithm takes no action at box70.

If the virtual sensor measurement value is valid at the decision diamond66, then the algorithm compares the virtual sensor measurement value with the hydrogen gas concentration estimation value calculated by the GCE model at box72, and determines whether the difference between the measurement value and the estimation value is greater than a first threshold or the difference between the estimation value and the measurement value is greater than a second threshold at decision diamond74, where the first second thresholds can be different. It is important for the algorithm to know whether the estimation of the hydrogen gas concentration is greater than or less than the measured concentration, which gives a determination of whether there is too much hydrogen gas or too little hydrogen gas in the anode sub-system so as to adjust the bleed event accordingly.

If the sensor measurement value is not greater than the GCE model estimation value by the first threshold or the GCE model estimation value is not greater than the sensor measurement value by the second threshold at the decision diamond74, then the algorithm takes no action at the box70. If the time elapsed from the last correction at the decision diamond68, or the sensor measurement value is greater than the estimation value by the first threshold at the decision diamond74, or the estimation value is greater than the sensor measurement value by the second threshold at the decision diamond74, then the algorithm commands an extended reactive bleed by the bleed valve32to force the model estimation value to merge with the sensor measurement value at box76. At the end of the extended bleed at the box76, the algorithm will then again determine the difference between the sensor value and the estimation value the same as it did above at decision diamond74, and if either of these differences is below the respective threshold, the algorithm will return to the box62to begin again. If the difference between the measurement value and the model estimation value are outside of the thresholds at the decision diamond78, then a fault counter is incremented by one at box80. This part of the algorithm is determining whether there is a more serious problem with the fuel cell system10, such as a hydrogen leak, where the reactive bleed does not cause the model estimation value to become more accurate.

Once the counter is incremented by one at the box80, the algorithm determines whether the total count value is greater than a predetermined count threshold, such as four, at decision diamond82, and if not, returns to the box76to perform another extended bleed to again attempt to correct the GCE model estimation value. If the count value has reached the count threshold at the decision diamond82, meaning there is some other issue causing the model to indicate an improper hydrogen estimation, the algorithm will report a diagnostic trouble code and clear the counter at box84, and then return to the beginning of the algorithm.

FIG. 3shows a graphical representation of the process discussed above, where time is on the horizontal axis. Graph line50represents the hydrogen gas concentration estimation value as determined by the GCE model and graph line52represents the hydrogen gas concentration measurement value as provided by the virtual sensor40. The bleeds of the bleed valve32are initiated each time the hydrogen gas concentration estimation value falls below 75% in this non-limiting embodiment. This is represented by line54that illustrates when the bleed events occur by pulses56, where each pulse56represents the bleed valve32being opened. Thus, as shown, each time the model indicates that the hydrogen gas concentration has fallen to 75%, the bleed algorithm will open the bleed valve32, where the concentration of the hydrogen gas in the anode increases as a result of the bleed. However, the actual hydrogen gas concentration is shown by the line52, where the bleed events are actually occurring when the hydrogen concentration is above 75%, thus wasting fuel. Once the difference between the model estimation value and the virtual sensor measurement increases above a certain error, represented here at time58, the algorithm discussed above will cause an extended remedial bleed to occur as represented by pulse48so that the model estimation value will move to the virtual sensor measurement value during the bleed event.

As will be well understood by those skilled in the art, the several and various steps and processes discussed herein to describe the invention may be referring to operations performed by a computer, a processor or other electronic calculating device that manipulate and/or transform data using electrical phenomenon. Those computers and electronic devices may employ various volatile and/or non-volatile memories including non-transitory computer-readable medium with an executable program stored thereon including various code or executable instructions able to be performed by the computer or processor, where the memory and/or computer-readable medium may include all forms and types of memory and other computer-readable media.