Gas quality identification and compensation method and device, storage medium and electronic equipment

Abstract

The application provides a gas quality identification and compensation method and device, a storage medium and an electronic device. The method comprises the following steps: obtaining a gas air-fuel ratio closed loop coefficient of a vehicle; determining a current gas quality of the vehicle according to a numerical relationship between the gas air-fuel ratio closed loop coefficient and a gas air-fuel ratio threshold value, wherein the current gas quality comprises a first type of quality and a second type of quality; in the case that a change of the current gas quality is detected, calculating a quality deviation of the vehicle, wherein the quality deviation represents an air-fuel ratio closed loop coefficient deviation between the second type of quality and the first type of quality; and updating a gas self-learning table of the vehicle by using the quality deviation to obtain an updated gas self-learning table of a current driving cycle, wherein the updated gas self-learning table of the current driving cycle is used to correct the gas air-fuel ratio of the vehicle. The application solves the problem that the existing gas closed loop control scheme cannot solve the poor engine performance caused by the change of the gas quality.

Description

Technical Field

[0001] This application relates to the field of gas quality identification and compensation technology, and more specifically, to a gas quality identification and compensation method, apparatus, storage medium and electronic device. Background Technology

[0002] Due to regional differences, the composition of fuel gas varies. When the fuel gas quality is poor, i.e., low-quality gas, if the vehicle cannot quickly learn this significant difference in quality, the required fuel volume will still be based on the fuel gas composition of the previous cycle, resulting in insufficient fuel volume and negatively impacting the vehicle's power performance and emissions.

[0003] Most current electronically controlled natural gas engines use closed-loop control systems to correct the gas injection pulse width in order to achieve ideal engine performance. This is achieved by installing a wide-range oxygen sensor on the engine exhaust pipe to measure oxygen concentration and provide feedback on the measured excess air coefficient. The ECU receives this feedback and compares the measured value with the target value to compensate for the injection quantity (increasing or decreasing it). However, this existing technology relies on a calibrated, constant target excess air coefficient as the guide for the closed-loop feedback. Changes in gas composition can cause changes in the target excess air coefficient. When the gas composition changes significantly, engine performance deteriorates severely, affecting user experience. Therefore, this closed-loop gas control scheme cannot solve the problem of poor engine performance caused by changes in gas composition. Summary of the Invention

[0004] The main objective of this application is to provide a method, device, storage medium, and electronic device for identifying and compensating for gas quality, so as to at least solve the problem that existing gas closed-loop control schemes cannot solve the problem of poor engine performance caused by changes in gas quality.

[0005] To achieve the above objectives, according to one aspect of this application, a method for identifying and compensating for fuel gas quality is provided, comprising: obtaining a closed-loop coefficient of the fuel gas air-fuel ratio of a vehicle; determining the current fuel gas quality of the vehicle based on a numerical relationship between the closed-loop coefficient of the fuel gas air-fuel ratio and a fuel gas air-fuel ratio threshold, wherein the current fuel gas quality includes a first type of quality and a second type of quality; calculating a quality deviation of the vehicle when a change in the current fuel gas quality is detected, wherein the quality deviation represents the deviation of the closed-loop coefficient of the air-fuel ratio between the second type of quality and the first type of quality; updating the vehicle's fuel gas self-learning table using the quality deviation to obtain an updated fuel gas self-learning table for the current driving cycle, wherein the updated fuel gas self-learning table for the current driving cycle is used to correct the fuel gas air-fuel ratio of the vehicle.

[0006] Optionally, when the current gas quality change is detected, the gas quality deviation of the vehicle is calculated, including: when the current gas quality changes from the first type of gas quality to the second type of gas quality, obtaining the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the first type of gas quality, and determining the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality as the gas quality deviation of the vehicle.

[0007] Optionally, when the current gas quality change is detected, the gas quality deviation of the vehicle is calculated, including: when the current gas quality changes from the second type of gas quality to the first type of gas quality, obtaining the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the first type of gas quality, and determining the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality as the gas quality deviation of the vehicle.

[0008] Optionally, obtaining the closed-loop coefficient of the vehicle's gas-air ratio includes: after the natural gas engine of the vehicle has closed-loop combustion, determining the ratio of the difference between the excess air coefficient and a preset coefficient to the excess air coefficient as the closed-loop coefficient of the vehicle's gas-air ratio.

[0009] Optionally, updating the vehicle's gas self-learning table using the gas quality deviation to obtain an updated gas self-learning table for the current driving cycle includes: obtaining the vehicle's gas quality self-learning coefficient table, wherein the gas quality self-learning coefficient table is a self-learning coefficient table pre-stored in the vehicle, and the gas quality self-learning coefficient table includes coefficients corresponding to various speeds of the natural gas engine and manifold pressures; calculating the sum of each coefficient in the gas quality self-learning coefficient table and the gas quality deviation to obtain the gas self-learning table for the current driving cycle.

[0010] Optionally, before determining the numerical relationship between the gas air-fuel ratio closed-loop coefficient and the gas air-fuel ratio threshold, the method further includes: the method further includes: conducting performance tests on the natural gas engine of the vehicle using different inferior gas and normal gas respectively, obtaining the test gas air-fuel ratio closed-loop coefficients corresponding to each of the inferior gas and the normal gas; and determining the gas air-fuel ratio threshold based on the test gas air-fuel ratio closed-loop coefficients.

[0011] Optionally, after obtaining the gas self-learning table for the current driving cycle, the method further includes: storing the gas self-learning table for the current driving cycle in a non-volatile memory in the vehicle's ECU.

[0012] According to another aspect of this application, a fuel gas quality identification and compensation device is provided, comprising: an acquisition unit, configured to acquire a closed-loop coefficient of the fuel gas air-fuel ratio of a vehicle, and determine the current fuel gas quality of the vehicle based on the numerical relationship between the closed-loop coefficient of the fuel gas air-fuel ratio and a fuel gas air-fuel ratio threshold, wherein the current fuel gas quality includes a first type of quality and a second type of quality; a calculation unit, configured to calculate a quality deviation of the vehicle when a change in the current fuel gas quality is detected, wherein the quality deviation represents the deviation of the closed-loop coefficient of the air-fuel ratio between the second type of quality and the first type of quality; and an update unit, configured to update the fuel gas self-learning table of the vehicle using the quality deviation to obtain an updated fuel gas self-learning table for the current driving cycle, wherein the updated fuel gas self-learning table for the current driving cycle is used to correct the fuel gas air-fuel ratio of the vehicle.

[0013] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform any of the described gas quality identification and compensation methods.

[0014] According to another aspect of this application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any of the described gas quality identification and compensation methods.

[0015] By applying the technical solution of this application, and determining the relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, drastic changes in gas quality can be effectively identified, and insufficient or excessive gas injection caused by differences in gas quality can be quickly compensated for, significantly improving the engine's response speed and adaptability. This application not only reduces the time required to relearn gas quantity deviations but also improves the engine's operating efficiency under different operating conditions, reduces emissions, and enhances the user's driving experience. It solves the problem that existing gas closed-loop control schemes cannot address the issue of poor engine performance caused by changes in gas quality. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for performing a gas quality identification and compensation method according to an embodiment of this application is shown.

[0018] Figure 2 A schematic flowchart of a gas quality identification and compensation method according to an embodiment of this application is shown;

[0019] Figure 3 A flowchart illustrating a specific gas quality identification and compensation method according to an embodiment of this application is shown.

[0020] Figure 4 A schematic diagram of the current driving cycle self-learning table update provided according to an embodiment of this application is shown;

[0021] Figure 5 A structural diagram of a gas quality identification and compensation system provided according to an embodiment of this application is shown;

[0022] Figure 6 A structural block diagram of a gas quality identification and compensation device according to an embodiment of this application is shown. Detailed Implementation

[0023] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] As described in the background section, existing gas closed-loop control schemes cannot solve the problem of poor engine performance caused by changes in gas quality. To address this issue, embodiments of this application provide a gas quality identification and compensation method, apparatus, storage medium, and electronic device.

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0028] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a gas quality identification and compensation method according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0029] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the gas quality identification and compensation method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one instance, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0030] This embodiment provides a method for identifying and compensating for gas quality that runs on a mobile terminal, computer terminal, or similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] Figure 2 This is a flowchart of a gas quality identification and compensation method according to an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0032] Step S201: Obtain the closed-loop coefficient of the gas air-fuel ratio of the vehicle. Based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, determine the current gas quality of the vehicle. The current gas quality includes a first type of gas quality and a second type of gas quality.

[0033] The air-fuel ratio closed-loop deviation is the deviation between the calibrated theoretical air-fuel ratio and the air-fuel ratio measured by the oxygen sensor. The ECU monitors the oxygen sensor data in real time and calculates the gas air-fuel ratio closed-loop coefficient to identify the current gas quality. The air-fuel ratio closed-loop deviation is compared with a preset threshold to determine whether the gas is of poor quality or normal.

[0034] Specifically, when the aforementioned closed-loop coefficient of the gas air-fuel ratio is less than or equal to the gas air-fuel ratio threshold, the current gas quality of the vehicle is considered to be of type I (gas quality). Type I gas quality represents normal gas quality and is consistent with the gas quality required for normal use of the vehicle's natural gas engine. When the aforementioned closed-loop coefficient of the gas air-fuel ratio is greater than the gas air-fuel ratio threshold, the current gas quality of the vehicle is considered to be of type II (gas quality). Type II gas quality represents poor gas quality and is inconsistent with the normal use of the vehicle's natural gas engine.

[0035] Step S202: When the above-mentioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality.

[0036] Step S203: The gas self-learning table of the vehicle is updated using the gas quality deviation mentioned above to obtain the updated gas self-learning table for the current driving cycle. The updated gas self-learning table for the current driving cycle is used to correct the gas air-fuel ratio of the vehicle.

[0037] Specifically, it can quickly respond to changes in gas quality, calculate gas quality deviations and update the self-learning table to ensure that the engine can adjust the gas injection quantity in a timely manner to maintain stable combustion when facing different gas qualities.

[0038] By applying steps S201, S202, and S203 in this embodiment, and determining the relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, drastic changes in gas quality can be effectively identified, and insufficient gas quantity or over-injection caused by differences in gas quality can be quickly compensated, significantly improving the engine's response speed and adaptability. This application not only reduces the time required to relearn gas quantity deviations but also improves the engine's operating efficiency under different operating conditions, reduces emissions, and enhances the user's driving experience. It solves the problem that existing gas closed-loop control schemes cannot address the issue of poor engine performance caused by changes in gas quality.

[0039] In the specific implementation process, when the above-mentioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, including: when the above-mentioned change in the current gas quality from the first type of gas quality to the second type of gas quality is detected, the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the first type of gas quality is obtained, and the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality is determined as the gas quality deviation of the vehicle.

[0040] This method accurately calculates the gas mixture deviation by comparing the closed-loop air-fuel ratio coefficients under two different gas mixture characteristics. Based on mathematical calculations of the closed-loop air-fuel ratio coefficients, the impact of gas mixture changes on engine performance is quantified. This calculation method can accurately reflect the air-fuel ratio deviation caused by changes in gas mixture characteristics, providing a crucial basis for subsequent self-learning table updates.

[0041] Specifically, when the aforementioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, including: when the current gas quality is detected to change from the second type of gas quality to the first type of gas quality, obtaining the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the first type of gas quality, and determining the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality as the gas quality deviation of the vehicle.

[0042] This method covers all possible gas quality switching scenarios, ensuring the comprehensiveness of gas quality deviation calculation. By comparing the closed-loop air-fuel ratio coefficients during different gas quality transitions, dynamic monitoring of gas quality changes is achieved. Whether switching from normal gas to inferior gas or vice versa, this embodiment can quickly identify and calculate the gas quality deviation, providing a guarantee for rapid engine performance recovery.

[0043] More specifically, obtaining the closed-loop coefficient of the gas-air ratio of a vehicle includes: after the gas-air ratio of the natural gas engine of the vehicle is closed, determining the ratio of the difference between the excess air coefficient and a preset coefficient to the excess air coefficient as the closed-loop coefficient of the gas-air ratio of the vehicle.

[0044] This method uses a closed-loop control mechanism to adjust the gas injection quantity in real time to match actual combustion conditions. In principle, it calculates the air-fuel ratio closed-loop coefficient by comparing the measured excess air coefficient with the calibrated ideal value. In terms of effect, closed-loop control improves engine stability and efficiency, and reduces performance fluctuations caused by changes in gas composition.

[0045] Further, updating the vehicle's gas self-learning table using the gas quality deviation to obtain the updated gas self-learning table for the current driving cycle includes: obtaining the vehicle's gas quality self-learning coefficient table, wherein the gas quality self-learning coefficient table is a self-learning coefficient table pre-stored in the vehicle, and the gas quality self-learning coefficient table includes coefficients corresponding to the speeds of the natural gas engine and the manifold pressure; calculating the sum of each coefficient in the gas quality self-learning coefficient table and the gas quality deviation to obtain the updated gas self-learning table for the current driving cycle.

[0046] By calculating the gas quality deviation caused by the gas quality changes in common operating conditions (e.g., speed 1100-1300 rpm), this gas quality deviation value is updated to other operating conditions in the gas quality self-learning coefficient table, resulting in an updated gas self-learning table. This extends the gas quantity deviation learned from individual operating points (common operating conditions) to other operating points, reducing the time required for other operating conditions to relearn the gas quantity deviation, and achieving rapid compensation for insufficient or excessive gas injection due to gas quality differences.

[0047] This method utilizes a self-learning table to store past gas injection experience, enabling rapid adaptation to new gas atmosphere environments. By adding the gas atmosphere deviation to the self-learning coefficient, the self-learning table is updated in real time. This update strategy significantly shortens the engine's adaptation time to new gas atmospheres and improves overall performance.

[0048] Furthermore, before determining the numerical relationship between the gas air-fuel ratio closed-loop coefficient and the gas air-fuel ratio threshold, the method further includes: conducting performance tests on the natural gas engine of the vehicle using different inferior and normal gas to obtain the test gas air-fuel ratio closed-loop coefficients corresponding to each of the inferior and normal gas; and determining the gas air-fuel ratio threshold based on the test gas air-fuel ratio closed-loop coefficients.

[0049] The air-fuel ratio thresholds for inferior gas and normal gas are preset and are obtained by conducting performance tests using different inferior gas and normal gas, and calibrating the total closed-loop deviation of the air-fuel ratio at these tests.

[0050] This method, through experimental calibration, determines the threshold for distinguishing between inferior and normal fuel gas. In principle, based on extensive experimental data, statistical analysis reveals the distribution characteristics of the air-fuel ratio closed-loop coefficient under different fuel qualities, thereby setting a reasonable threshold. The established threshold enables the ECU to accurately determine the fuel gas quality, avoiding misjudgment and overcompensation.

[0051] Specifically, after obtaining the gas self-learning table for the current driving cycle, the method further includes storing the gas self-learning table for the current driving cycle into a non-volatile memory in the ECU of the vehicle.

[0052] This method ensures the persistent storage of the self-learning table, preventing data loss even during power outages. Non-volatile memory retains data after power is turned off, allowing the self-learning table to continue operating upon next startup. Effectively, this storage strategy guarantees the continuity of the self-learning process and data security. Furthermore, cloud storage technology can be employed to upload the self-learning table to the cloud, enabling data sharing and remote upgrades.

[0053] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the gas quality identification and compensation method of this application will be described in detail below with reference to specific embodiments.

[0054] Due to regional differences, the composition of fuel gas varies. When the fuel gas quality is poor, i.e., low-quality gas, if the vehicle cannot quickly learn this significant difference in quality, the required fuel volume will still be based on the fuel gas composition of the previous cycle, resulting in insufficient fuel volume and negatively impacting the vehicle's power performance and emissions.

[0055] This embodiment relates to a specific method for identifying and compensating for changes in fuel gas composition. By identifying drastic changes in fuel gas composition, it quickly compensates for insufficient or excessive fuel injection due to differences in gas composition through a fuel gas composition learning and determination method, thereby reducing the impact on vehicle power, economy, and emissions. Figure 3 As shown, the current gas quality (normal or inferior gas) is determined based on the numerical relationship between the closed-loop total coefficient of the air-fuel ratio in the current cycle and the limit. When a change in the current gas quality is detected, the vehicle's gas quality deviation is calculated to update the current driving cycle self-learning table. The specific gas quality identification and compensation methods include the following:

[0056] 1. Identifying inferior gas from normal gas:

[0057] Total closed-loop air-fuel ratio coefficient: This coefficient, along with the self-learning coefficient, is used to correct the target air-fuel ratio in a natural gas engine. This parameter characterizes the gas quality. It is calculated within the commonly used operating range (1100-1300 rpm).

[0058] The closed-loop coefficient and self-learning coefficient of the air-fuel ratio are both parameters that characterize whether the gas is too rich or too poor. They are used to adjust the gas injection quantity in real time to ensure that the air-fuel ratio is maintained at the ideal value (equivalent combustion), thereby improving combustion efficiency and reducing gas consumption and emissions.

[0059] The closed-loop coefficient and self-learning coefficient of the gas air-fuel ratio are obtained by (excess air coefficient - standard coefficient) / excess air coefficient after the gas air-fuel ratio is closed.

[0060] When the closed-loop coefficient of the gas air-fuel ratio exceeds the limit (calibrated by the emission boundary of the performance test), it is stored in the self-learning table as the gas quantity correction feedforward, i.e., the gas air-fuel ratio self-learning coefficient.

[0061] Normal gas: Gas air-fuel ratio closed-loop coefficient ≤ limit;

[0062] Inferior gas: The closed-loop coefficient of the gas-air-fuel ratio exceeds the limit;

[0063] Among them, the limits for inferior gas and normal gas are preset and are obtained by conducting performance tests using different inferior gas and normal gas, and calibrating the total deviation of the gas air-fuel ratio closed loop at that time.

[0064] 2. Store the normal air-fuel ratio self-learning coefficient table (backup table) and the corresponding gas air-fuel ratio closed-loop total coefficient, which is used to calculate and update the current driving cycle self-learning table after the change in gas quality.

[0065] The current driving cycle self-learning table is used to calculate the self-learning coefficient of the ignition gas-fuel ratio under different operating conditions in the current driving cycle.

[0066] 3. Calculation method for the current driving cycle self-learning table:

[0067] When a switch from normal gas to inferior gas or vice versa is detected, the calculation and update of the current driving cycle self-learning table is achieved by adding the deviation between the inferior gas and the normal gas air-fuel ratio closed-loop total coefficient stored in the backup table to the normal gas self-learning coefficient table stored in the backup table, thereby extending the gas quantity coefficient learned from the commonly used operating conditions to other operating points.

[0068] The deviation of the closed-loop coefficient of the air-fuel ratio between inferior gas and normal gas, a = total closed-loop coefficient of air-fuel ratio of inferior gas - total closed-loop coefficient of air-fuel ratio of normal gas stored in the spare table; coefficient a is calculated in the commonly used operating range.

[0069] The current driving cycle self-learning table = deviation 'a' of the air-fuel ratio closed-loop coefficient between inferior and normal air + the normal air self-learning coefficient table stored in the spare table. The normal air self-learning coefficient table stored in the spare table is updated by adding coefficient 'a' to each operating point to obtain the updated current driving cycle self-learning table.

[0070] like Figure 4 As shown, assuming the closed-loop coefficient of the air-fuel ratio is 0.5, the updated current driving cycle self-learning table = deviation of the closed-loop coefficient of the air-fuel ratio between inferior gas and normal gas, a + the normal gas self-learning coefficient table stored in the spare table. The deviation of the closed-loop coefficient of the air-fuel ratio between inferior gas and normal gas, a = (6 + 0.5) - (3 + 0.5) = 3.

[0071] 4. After the self-learning table is completed, the current driving cycle continues to calculate to ensure sufficient learning of the fuel quantity deviation caused by the air-fuel ratio composition. After the current driving cycle is powered off, the self-learning table for the current air-fuel ratio deviation is updated. The air-fuel ratio deviation self-learning table stores the closed-loop deviation of the air-fuel ratio at different operating conditions as feedforward.

[0072] 5. When a switch from normal air to normal air or from inferior air to inferior air is detected, the air-fuel ratio self-learning table of the current driving cycle is updated to the stored normal air air-fuel ratio self-learning coefficient table.

[0073] This embodiment also relates to a gas quality identification and compensation system, such as... Figure 5 As shown, the system includes: a signal acquisition module, a gas rapid self-learning module, and an execution module.

[0074] The signal acquisition module consists of an oxygen sensor and an ECU. The ECU acquires and processes the oxygen sensor signal and transmits it to the gas rapid self-learning module.

[0075] The gas rapid self-learning module identifies and calculates the components of inferior gas, and extends the gas quantity deviation learned from individual operating points to other operating points.

[0076] The actuation module consists of a nozzle assembly, which receives signals from the ECU and injects fuel gas.

[0077] The gas rapid self-learning module identifies differences in gas composition and quickly compensates for insufficient gas volume due to these differences by learning and determining the gas composition. The gas composition difference identification and rapid compensation function works when the ECU detects a drastic change in gas composition during vehicle refueling—specifically, when switching between normal and inferior gas. It extends the gas volume deviation learned from individual operating points to other operating points, reducing the time required for relearning gas volume deviations under different conditions and thus quickly compensating for insufficient or excessive gas injection due to gas composition differences.

[0078] This application's embodiments extend the gas quantity deviation learned from individual operating points to other operating points, reducing the time required for other operating points to relearn the gas quantity deviation and achieving rapid compensation for under- or over-injection of gas due to gas quality differences. Furthermore, the calculation and updating of the self-learning table involves adding the deviation between the air-fuel ratio closed-loop total coefficient of inferior gas and the normal gas stored in the backup table to the normal gas self-learning coefficient table stored in the backup table. This method preserves the air-fuel ratio difference trend at different operating points, making gas control more precise.

[0079] This application also provides a gas quality identification and compensation device. It should be noted that the gas quality identification and compensation device of this application can be used to execute the gas quality identification and compensation method provided in this application. This device is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0080] The following describes the gas quality identification and compensation device provided in the embodiments of this application.

[0081] Figure 6 This is a schematic diagram of a gas quality identification and compensation device according to an embodiment of this application. Figure 6 As shown, the device includes:

[0082] The acquisition unit 61 is used to acquire the closed-loop coefficient of the gas air-fuel ratio of the vehicle, and determine the current gas quality of the vehicle based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold. The current gas quality includes a first type of gas quality and a second type of gas quality.

[0083] The calculation unit 62 is used to calculate the gas quality deviation of the vehicle when the above-mentioned current gas quality change is detected, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality.

[0084] The updating unit 63 is used to update the fuel self-learning table of the vehicle using the aforementioned gas quality deviation, to obtain the updated fuel self-learning table for the current driving cycle. The updated fuel self-learning table for the current driving cycle is used to correct the fuel-air ratio of the vehicle.

[0085] In this embodiment, an acquisition unit is used to acquire the closed-loop coefficient of the vehicle's fuel-air ratio and determine the current fuel quality of the vehicle based on the numerical relationship between the closed-loop coefficient and the fuel-air ratio threshold. The current fuel quality includes a first type of fuel quality and a second type of fuel quality. A calculation unit is used to calculate the fuel quality deviation of the vehicle when a change in the current fuel quality is detected. The fuel quality deviation represents the deviation of the closed-loop coefficient of the fuel-air ratio between the second type of fuel quality and the first type of fuel quality. An update unit is used to update the vehicle's fuel self-learning table using the fuel quality deviation to obtain an updated fuel self-learning table for the current driving cycle. The updated fuel self-learning table for the current driving cycle is used to correct the fuel-air ratio of the vehicle. By determining the relationship between the closed-loop coefficient and the fuel-air ratio threshold, drastic changes in fuel quality can be effectively identified, and insufficient fuel quantity or over-injection caused by fuel quality differences can be quickly compensated, significantly improving the engine's response speed and adaptability. This application not only reduces the time required to relearn the fuel quantity deviation but also improves the engine's operating efficiency under different operating conditions, reduces emissions, and enhances the user's driving experience. This solves the problem that existing gas closed-loop control schemes cannot address, which leads to poor engine performance due to changes in gas composition.

[0086] As an optional solution, the calculation unit includes a first determining module, which is used to obtain the gas air-fuel ratio closed-loop coefficient of the second type of gas and the first type of gas when the current gas quality is detected to change from the first type of gas quality to the second type of gas quality, and to determine the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality as the gas quality deviation of the vehicle.

[0087] Specifically, by comparing the closed-loop air-fuel ratio coefficients under two different gas qualities, the gas quality deviation is accurately calculated. Based on the mathematical calculations of the closed-loop air-fuel ratio coefficients, the impact of gas quality changes on engine performance is quantified. This calculation method accurately reflects the air-fuel ratio deviation caused by changes in gas quality, providing a crucial basis for subsequent self-learning table updates.

[0088] In one optional scheme, the calculation unit further includes a second determining module, which is used to obtain the gas air-fuel ratio closed-loop coefficient of the second type of gas and the first type of gas when the current gas quality is detected to change from the second type of gas quality to the first type of gas quality, and to determine the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality as the gas quality deviation of the vehicle.

[0089] Specifically, this embodiment covers all possible gas quality switching scenarios, ensuring the comprehensiveness of gas quality deviation calculation. By comparing the closed-loop air-fuel ratio coefficients during different gas quality transitions, dynamic monitoring of gas quality changes is achieved. Whether switching from normal gas to inferior gas or vice versa, this embodiment can quickly identify and calculate the gas quality deviation, providing a guarantee for rapid engine performance recovery.

[0090] In one optional scheme, the acquisition unit includes a third determining module, which is used to determine the ratio of the difference between the excess air coefficient and a preset coefficient to the excess air coefficient as the gas-fuel ratio closed-loop coefficient of the vehicle after the natural gas engine gas closed loop.

[0091] Specifically, a closed-loop control mechanism is used to adjust the gas injection quantity in real time to match actual combustion conditions. In principle, the air-fuel ratio closed-loop coefficient is calculated by comparing the measured excess air coefficient with the calibrated ideal value using the closed-loop control principle. In terms of effect, closed-loop control improves the stability and efficiency of engine operation and reduces performance fluctuations caused by changes in gas quality.

[0092] In one optional scheme, the updating unit includes an acquisition module and a calculation module; the acquisition module is used to acquire the gas quality self-learning coefficient table of the vehicle, wherein the gas quality self-learning coefficient table is a self-learning coefficient table pre-stored in the vehicle, and the gas quality self-learning coefficient table includes coefficients corresponding to the speed of each natural gas engine and the manifold pressure; the calculation module is used to calculate the sum of each coefficient in the gas quality self-learning coefficient table and the gas quality deviation to obtain the gas quality self-learning table of the current driving cycle.

[0093] Specifically, a self-learning table stores past gas injection experience, enabling rapid adaptation to new gas atmosphere environments. By adding the gas atmosphere deviation to the self-learning coefficient, the self-learning table is updated in real time. This update strategy significantly shortens the engine's adaptation time to new gas atmospheres and improves overall performance.

[0094] In one optional embodiment, the apparatus further includes a performance testing unit and a determination unit; the performance testing unit is used to conduct performance tests on the natural gas engine of the vehicle using different inferior and normal fuels before determining the numerical relationship between the aforementioned fuel-air ratio closed-loop coefficient and the fuel-air ratio threshold, thereby obtaining the test fuel-air ratio closed-loop coefficients corresponding to each of the aforementioned inferior and normal fuels; the determination unit is used to determine the aforementioned fuel-air ratio threshold based on the aforementioned test fuel-air ratio closed-loop coefficients.

[0095] Specifically, through experimental calibration, a threshold for distinguishing between inferior and normal fuel gas was determined. In principle, based on extensive experimental data, statistical analysis revealed the distribution characteristics of the air-fuel ratio closed-loop coefficient under different fuel qualities, thereby setting a reasonable threshold. This threshold setting enables the ECU to accurately determine the fuel gas quality, avoiding misjudgment and overcompensation.

[0096] In one alternative embodiment, the apparatus further includes a storage unit for storing the gas self-learning table for the current driving cycle into a non-volatile memory in the vehicle's ECU after obtaining the gas self-learning table for the current driving cycle.

[0097] Specifically, this embodiment ensures the persistent storage of the self-learning table, preventing data loss even in the event of a power outage. Non-volatile memory retains data even after power is off, allowing the self-learning table to continue operating upon next startup. Effectively, this storage strategy guarantees the continuity of the self-learning process and the security of the data. Furthermore, cloud storage technology can be employed to upload the self-learning table to the cloud, enabling data sharing and remote upgrades.

[0098] The aforementioned gas quality identification and compensation device includes a processor and a memory. The acquisition unit, calculation unit, and update unit are all stored as program units in the memory, and the processor executes these program units to achieve the corresponding functions. All of the above modules are located in the same processor; alternatively, the modules may be located in different processors in any combination.

[0099] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured; adjusting kernel parameters can address issues that existing gas-gas closed-loop control schemes cannot resolve, such as poor engine performance due to gas quality variations.

[0100] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0101] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the gas quality identification and compensation method.

[0102] Specifically, the gas quality identification and compensation methods include:

[0103] Step S201: Obtain the closed-loop coefficient of the gas air-fuel ratio of the vehicle. Based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, determine the current gas quality of the vehicle. The current gas quality includes a first type of gas quality and a second type of gas quality.

[0104] Step S202: When the above-mentioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality.

[0105] Step S203: The gas self-learning table of the vehicle is updated using the gas quality deviation mentioned above to obtain the updated gas self-learning table for the current driving cycle. The updated gas self-learning table for the current driving cycle is used to correct the gas air-fuel ratio of the vehicle.

[0106] This invention provides a processor for running a program, wherein the program executes the gas quality identification and compensation method.

[0107] Specifically, the gas quality identification and compensation methods include:

[0108] Step S201: Obtain the closed-loop coefficient of the gas air-fuel ratio of the vehicle. Based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, determine the current gas quality of the vehicle. The current gas quality includes a first type of gas quality and a second type of gas quality.

[0109] Step S202: When the above-mentioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality.

[0110] Step S203: The gas self-learning table of the vehicle is updated using the gas quality deviation mentioned above to obtain the updated gas self-learning table for the current driving cycle. The updated gas self-learning table for the current driving cycle is used to correct the gas air-fuel ratio of the vehicle.

[0111] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0112] Step S201: Obtain the closed-loop coefficient of the gas air-fuel ratio of the vehicle. Based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, determine the current gas quality of the vehicle. The current gas quality includes a first type of gas quality and a second type of gas quality.

[0113] Step S202: When the above-mentioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality.

[0114] Step S203: The gas self-learning table of the vehicle is updated using the gas quality deviation mentioned above to obtain the updated gas self-learning table for the current driving cycle. The updated gas self-learning table for the current driving cycle is used to correct the gas air-fuel ratio of the vehicle.

[0115] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0116] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0117] Step S201: Obtain the closed-loop coefficient of the gas air-fuel ratio of the vehicle. Based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold, determine the current gas quality of the vehicle. The current gas quality includes a first type of gas quality and a second type of gas quality.

[0118] Step S202: When the above-mentioned change in the current gas quality is detected, the gas quality deviation of the vehicle is calculated, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality.

[0119] Step S203: The gas self-learning table of the vehicle is updated using the gas quality deviation mentioned above to obtain the updated gas self-learning table for the current driving cycle. The updated gas self-learning table for the current driving cycle is used to correct the gas air-fuel ratio of the vehicle.

[0120] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0121] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0122] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0123] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0124] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0125] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0126] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0127] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0128] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0129] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0130] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for identifying and compensating for gas quality, characterized in that, include: The closed-loop coefficient of the vehicle's fuel-air ratio is obtained. Based on the numerical relationship between the closed-loop coefficient and the fuel-air ratio threshold, the current fuel quality of the vehicle is determined. The current fuel quality includes a first type of quality and a second type of quality. Upon detecting the current change in fuel quality, the vehicle's quality deviation is calculated, wherein the quality deviation characterizes the deviation of the air-fuel ratio closed-loop coefficient between the second type of fuel quality and the first type of fuel quality. The gas quality deviation is used to update the vehicle's gas self-learning table to obtain the updated gas self-learning table for the current driving cycle. The updated gas self-learning table for the current driving cycle is used to correct the vehicle's gas-air ratio. Obtaining the closed-loop coefficient of the gas-air ratio of a vehicle includes: after the gas-air ratio of the natural gas engine of the vehicle is closed, determining the ratio of the difference between the excess air coefficient and a preset coefficient to the excess air coefficient as the closed-loop coefficient of the gas-air ratio of the vehicle. The process of updating the vehicle's gas self-learning table using the gas quality deviation to obtain the updated gas self-learning table for the current driving cycle includes: obtaining the vehicle's gas quality self-learning coefficient table, wherein the gas quality self-learning coefficient table is a self-learning coefficient table pre-stored in the vehicle, and the gas quality self-learning coefficient table includes coefficients corresponding to various speeds and manifold pressures of the natural gas engine; and calculating the sum of each coefficient in the gas quality self-learning coefficient table and the gas quality deviation to obtain the updated gas self-learning table for the current driving cycle.

2. The method according to claim 1, characterized in that, Upon detecting the current change in fuel quality, the vehicle's fuel quality deviation is calculated, including: When the current gas quality is detected to change from the first type of gas quality to the second type of gas quality, the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the first type of gas quality is obtained, and the difference between the gas air-fuel ratio closed-loop coefficient of the second type of gas quality and the gas air-fuel ratio closed-loop coefficient of the first type of gas quality is determined as the gas quality deviation of the vehicle.

3. The method according to claim 1, characterized in that, Upon detecting the current change in fuel quality, the vehicle's fuel quality deviation is calculated, including: When the current gas quality is detected to change from the second type to the first type, the gas air-fuel ratio closed-loop coefficient of the second type and the first type are obtained, and the difference between the gas air-fuel ratio closed-loop coefficient of the second type and the gas air-fuel ratio closed-loop coefficient of the first type is determined as the gas quality deviation of the vehicle.

4. The method according to claim 1, characterized in that, Before basing the method on the numerical relationship between the gas air-fuel ratio closed-loop coefficient and the gas air-fuel ratio threshold, the method further includes: The performance of the vehicle's natural gas engine was tested using different types of inferior and normal fuel gas, and the closed-loop coefficient of the air-fuel ratio of each type of inferior and normal fuel gas was obtained. The air-fuel ratio threshold is determined based on the closed-loop coefficient of the test gas air-fuel ratio.

5. The method according to claim 1, characterized in that, After obtaining the fuel self-learning table for the current driving cycle, the method further includes: The gas self-learning table for the current driving cycle is stored in the non-volatile memory of the vehicle's ECU.

6. A gas quality identification and compensation device, characterized in that, The gas quality identification and compensation device is used to execute the gas quality identification and compensation method according to any one of claims 1 to 5, wherein the gas quality identification and compensation device comprises: The acquisition unit is used to acquire the closed-loop coefficient of the gas air-fuel ratio of the vehicle, and determine the current gas quality of the vehicle based on the numerical relationship between the closed-loop coefficient of the gas air-fuel ratio and the gas air-fuel ratio threshold. The current gas quality includes a first type of gas quality and a second type of gas quality. The calculation unit is used to calculate the gas quality deviation of the vehicle when the current gas quality change is detected, wherein the gas quality deviation represents the deviation of the air-fuel ratio closed-loop coefficient between the second type of gas quality and the first type of gas quality. An update unit is used to update the vehicle's fuel self-learning table using the gas quality deviation, to obtain an updated fuel self-learning table for the current driving cycle. The updated fuel self-learning table for the current driving cycle is used to correct the vehicle's fuel-air ratio.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the gas quality identification and compensation method according to any one of claims 1 to 5.

8. An electronic device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing the gas quality identification and compensation method according to any one of claims 1 to 5.

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