Computer-implemented method for detecting engine misfire events for an engine of a vehicle and a vehicle with an internal combustion engine operating according to the method.

Abstract

The examples described here provide a method that includes calculating an engine speed, at least partially, based on a crankshaft angle sensor signal received by the engine's crankshaft angle sensor at periodic intervals defined by a crankshaft rotation. The method further includes calculating an engine acceleration, at least partially, based on the engine speed. The method also includes generating, using a filter, a filtered engine acceleration for the periodic intervals, at least partially based on the engine acceleration. Finally, the method includes calculating an RMS engine acceleration, at least partially, based on the filtered engine acceleration for the periodic intervals.The method further comprises detecting an engine misfire event, at least partially, based on the RMS engine acceleration. The method further comprises implementing a corrective action for the vehicle in response to the detection of the engine misfire event.

Description

BACKGROUND

[0001] The present invention relates to vehicles and in particular to a computer-implemented method for detecting engine misfire events for an engine of a vehicle and to a vehicle with an engine operating according to the method.

[0002] Conventional methods and systems for detecting misfires in an internal combustion engine are described in documents DE 11 2014 007 308 B3 and DE 10 2016 117 342 B4.

[0003] Modern vehicles (e.g., a passenger car, a motorcycle, a boat, or any other type of automobile) can be equipped with a power engine such as an internal combustion engine (ICE). During operation, an ICE ignites on a regular, periodic basis. However, misfires can occur in certain situations.

[0004] An engine misfire occurs when one or more cylinders in an internal combustion engine fail to ignite the air-fuel mixture at the correct time. This can lead to a variety of problems, including reduced engine performance, increased emissions, and potential damage to engine components. Misfires can be caused by a range of factors, such as faulty spark plugs, fuel delivery problems, or issues with the engine's ignition system. Accurate and prompt detection of engine misfires is highly desirable to maintain engine health and performance.

[0005] The invention is therefore based on the objective of fulfilling this wish. SUMMARY

[0006] According to the invention, this problem is solved by a computer-implemented method for detecting engine misfire events in vehicles using a filter, characterized by the features of claim 1. Advantageous embodiments of the method are described in dependent claims 2 to 8.

[0007] The method comprises calculating a motor speed at least partially based on a crankshaft angle sensor signal received by a crankshaft angle sensor of the motor at periodic intervals defined by a crankshaft rotation. The method further comprises calculating a motor acceleration at least partially based on the motor speed. The method further comprises generating, using a filter, a filtered motor acceleration for the periodic intervals, at least partially based on the motor acceleration. The method further comprises calculating an RMS motor acceleration value, at least partially based on the filtered motor acceleration for the periodic intervals.The method further includes detecting an engine misfire event, at least partially, based on the RMS engine acceleration. The method further includes implementing a corrective action for the vehicle in response to the detection of the engine misfire event.

[0008] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include the filter being a high-pass filter.

[0009] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include the filter being a Butterworth filter.

[0010] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include the detection of the engine misfire event comprising a comparison of the RMS engine acceleration with a normal ignition value.

[0011] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include the detection of the engine misfire event in response to the RMS engine acceleration deviating by more than four standard deviations from the normal ignition value.

[0012] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include the generation of the filtered power machine acceleration being carried out using a folding process.

[0013] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include the folding being defined by the following equation: yx=B0+B1z−1+B2z−2+⋯+BNz−NA0+A1z−1+A2z−2+⋯+AMz−M where A0... A M and B0... B N The coefficients are pre-calculated for the filter, M and N are integers, and y and x refer to a filtered and an unfiltered acceleration, respectively.

[0014] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include calculating the RMS engine acceleration using the following equation: mod(B0ak+B1ak−1+B2ak−2+B3ak−3+A1a'k−1+A2a'k−2+A3a'k−3a0, crankshaft rotation) where A0... A M and B0... B NThe coefficients are pre-calculated for the filter, M and N are integers, a k , a k-1 , a k-2 , a k-3 the unfiltered acceleration for a current sample and three previous samples are, a' k , a' k-1 , a' k-2' a' k-3 The filtered acceleration for the current sample and the three previous samples is, and k represents an amount of crankshaft rotation in degrees.

[0015] The problem underlying the invention is further solved by a vehicle characterized by the features of claim 9. An advantageous embodiment of the vehicle is also found in claim 10.

[0016] The vehicle includes an internal combustion engine, a crankshaft associated with the engine, and a processing system. The processing system includes a memory containing computer-readable instructions. The processing system also includes a processing device for executing the computer-readable instructions, which control the processing system to perform operations for detecting engine misfire events for the internal combustion engine. These operations include calculating the engine speed of the internal combustion engine, at least partially, based on a crankshaft angle sensor signal received from the crankshaft angle sensor at periodic intervals defined by a crankshaft rotation. The operations further include calculating the engine acceleration of the internal combustion engine, at least partially, based on the engine speed.The operations further include generating, using a filter, a filtered engine acceleration value for the internal combustion engine for the periodic intervals, at least partially based on the engine acceleration. The operations further include calculating an RMS engine acceleration value for the internal combustion engine, at least partially based on the filtered engine acceleration for the periodic intervals. The operations further include detecting an engine misfire event of the internal combustion engine, at least partially based on the RMS engine acceleration. The operations further include implementing a corrective action for the vehicle in response to the detection of the engine misfire event.

[0017] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include the filter being a high-pass filter.

[0018] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the filter being a Butterworth filter.

[0019] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the detection of the engine misfire event comprising a comparison of the RMS engine acceleration with a normal ignition value.

[0020] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the detection of the engine misfire event in response to the RMS engine acceleration deviating by more than four standard deviations from the normal ignition value.

[0021] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the generation of the filtered engine acceleration being carried out using a folding process.

[0022] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include the folding being defined by the following equation: yx=B0+B1z−1+B2z−2+⋯+BNz−NA0+A1z−1+A2z−2+⋯+AMz−M where A0... A M and B0... BN The coefficients are pre-calculated for the filter, M and N are integers, and y and x refer to a filtered and an unfiltered acceleration, respectively.

[0023] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the RMS engine acceleration being calculated using the following equation: mod(B0ak+B1ak−1+B2ak−2+B3ak−3+A1a'k−1+A2a'k−2+A3a'k−3a0, crankshaft rotation) where A0... A M and B0... B N The coefficients are pre-calculated for the filter, M and N are integers, a k , a k-1 , a k-2 , a k-3 the unfiltered acceleration for a current sample and three previous samples are, a' k , a' k-1 , a' k-2 , a' k-3The filtered acceleration for the current sample and the three previous samples is, and k represents an amount of crankshaft rotation in degrees.

[0024] Furthermore, a computer program product is described. The computer program product includes a computer-readable storage medium containing program instructions embodied therein, wherein the program instructions are executable by at least one processor to cause the at least one processor to perform operations for detecting engine misfire events for an engine of a vehicle. The operations include calculating an engine speed at least partially based on a crankshaft angle sensor signal received from a crankshaft angle sensor of the engine at periodic intervals defined by a crankshaft rotation. The operations further include calculating an engine acceleration at least partially based on the engine speed.The operations further include generating a filtered engine acceleration for the periodic intervals, at least partially based on the engine acceleration, using a filter. The operations further include calculating an RMS engine acceleration value, at least partially based on the filtered engine acceleration for the periodic intervals. The operations further include detecting an engine misfire event, at least partially based on the RMS engine acceleration. The operations further include implementing a corrective action for the vehicle in response to the detection of the engine misfire event.

[0025] In addition to one or more of the features described herein, or as an alternative, further embodiments of the computer program product may include that the detection of the engine misfire event comprises a comparison of the RMS engine acceleration with a normal ignition value, wherein the engine misfire event is detected in response to the RMS engine acceleration deviating from the normal ignition value by more than four standard deviations.

[0026] In addition to one or more of the features described herein, or as an alternative, further embodiments of the computer program product may include the generation of the filtered force machine acceleration being performed using a convolution defined by the following equation: yx=B0+B1z−1+B2z−2+⋯+BNz−NA0+A1z−1+A2z−2+⋯+AMz−M where A0... A M and B0... B NThe coefficients are pre-calculated for the filter, M and N are integers, and y and x refer to a filtered and an unfiltered acceleration, respectively.

[0027] In addition to one or more of the features described herein, or as an alternative, further embodiments of the computer program product may include calculating the RMS force machine acceleration using the following equation: mod(B0ak+B1ak−1+B2ak−2+B3ak−3+A1a'k−1+A2a'k−2+A3a'k−3a0, crankshaft rotation) where A0... A M and B0... B N The coefficients are pre-calculated for the filter, M and N are integers, a k , a k-1 , a k-2 , a k-3 the unfiltered acceleration for a current sample and three previous samples are, a' k , a' k-1 , a' k-2 , a' k-3The filtered acceleration for the current sample and the three previous samples is, and k represents an amount of crankshaft rotation in degrees.

[0028] The features and advantages described above, and further features and advantages of the invention, will become apparent from the following detailed description when taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Further features, advantages and details appear only as examples in the following detailed description, which refers to the drawings; they show: Fig. 1 an illustration of a vehicle comprising a processing system and an internal combustion engine according to one or more embodiments; Fig. 2 a block diagram of the processing system of Fig. 1 according to one or more embodiments; Fig. 3 a flowchart of a method for detecting engine misfire events for vehicles using a filter according to one or more embodiments; Fig. 4 a graph of actual acceleration signals for ignition and misfire events according to one or more embodiments; Fig. 5 a graph of filtered acceleration signals for ignition and misfire events according to one or more embodiments; and Fig. 6 a block diagram of a processing system for implementing one or more embodiments described herein. DETAILED DESCRIPTION

[0030] The following description is for illustrative purposes only. It should be understood that throughout the drawings, corresponding reference numerals denote similar or corresponding sections and features. As used here, the term "module" refers to a processing circuit arrangement that may include an application-specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or grouped) with memory executing one or more software or firmware programs, a combinational logic circuit, and / or other suitable components that provide the described functionality.

[0031] One or more embodiments described here relate to the detection of engine misfire events for vehicles using a filter.

[0032] Accurate and immediate detection of engine misfires is essential for maintaining engine health and performance. Some misfire detection methods rely on monitoring engine speed and acceleration. However, these methods may be less effective at certain engine speeds and loads, particularly in the presence of resonance effects caused by the engine's damping system. These resonance effects can mask true engine behavior, making it difficult to distinguish between normal operation and misfires.

[0033] Some vehicles, such as plug-in hybrid electric vehicles (PHEVs), do not have torque converters or implement locked torque converter clutches. In such configurations, existing solutions for detecting misfires struggle to effectively detect misfires under these conditions, which can lead to potential performance and reliability issues.

[0034] Conventional detection solutions often fail to account for the damper torque effect on the operating torque at resonance.

[0035] This limitation results in inaccurate detection of engine misfires, especially in scenarios involving low-order resonance and high operating variability. There is a need for a more effective method to detect operational anomalies that can operate reliably across varying engine speeds and conditions, and that does not use torque converters or employs locked torque converter clutches, thus ensuring accurate detection and improved vehicle performance.

[0036] Accurate and immediate detection of engine misfire events is essential for maintaining engine health and performance. To address these challenges, advanced detection solutions are desired that can filter out noise caused by resonance and other factors, providing a clearer and more accurate indication of engine misfire events. Such solutions improve the reliability of misfire detection, leading to improved engine performance, reduced emissions, and lower maintenance costs.

[0037] One or more embodiments described here address these challenges by introducing a novel approach to detecting engine misfire events. For example, one or more embodiments employ a high-pass filter applied to the engine acceleration to attenuate resonance and combustion randomness effects. The high-pass filter uses a discrete-order filter that remains invariant with engine speeds. The engine acceleration RMS value for combustion-to-combustion events is calculated using the filtered acceleration.This solution provides a more effective approach to detecting misfire events, especially in conditions involving low-order resonance and high combustion variations and / or where torque converters are not present or locked torque converter clutches are used.

[0038] Fig. Figure 1 shows a vehicle 100 with a processing system 102 and an internal combustion engine (ICE) 104 according to one or more embodiments.

[0039] Vehicle 100 can be a passenger car, a truck, a van, a bus, a motorcycle, a boat, or any other type of motor vehicle. According to one embodiment, Vehicle 100 contains the ICE 104, which is powered by gasoline, diesel, or the like. According to another embodiment, Vehicle 100 is a hybrid electric vehicle, such as a plug-in hybrid electric vehicle (PHEV), which is powered partially or entirely by electric power in conjunction with an internal combustion engine. According to one or more embodiments, Vehicle 100 is an autonomous or a semi-autonomous vehicle. An autonomous vehicle is a vehicle that has self-driving capabilities. A semi-autonomous vehicle is a vehicle that has certain autonomous features (e.g., self-parking, lane keeping, etc.) but does not have fully autonomous control.

[0040] The processing system 102 communicates with the ICE 104 to monitor and control various engine parameters. According to one or more embodiments, the processing system 102 is an engine control unit (ECU). The processing system 102 is responsible for executing various control algorithms and processing data received from various sensors, such as a crankshaft angle sensor (see Fig. 2) According to one or more embodiments, the processing system 102 is integrated into the architecture of the vehicle 100 to provide seamless communication with other components.

[0041] The ICE 104 (also simply referred to as the "power engine") is a component of the Vehicle 100 responsible for generating power through fuel combustion. The ICE 104 works in conjunction with the Processing System 102 to ensure optimal performance and efficiency. The ICE 104 contains various subsystems and sensors that provide real-time signals / data to the Processing System 102 for analysis and control.

[0042] Further features of the processing system 102 will now be described with reference to Fig. 2- Fig. 5 described.

[0043] In particular, Fig. 2 a block diagram of the processing system 102 of Fig. 1 according to one or more embodiments. According to one or more embodiments, the processing system 102 comprises a processing device 202, a memory 204, and a misfire detection machine 210. It is to be acknowledged that the processing system 102 can be any device suitable for detecting an engine misfire. For example, the processing system 102 can be a device implemented in or otherwise associated with the vehicle 100. As another example, the processing system 102 can be a smartphone, a tablet computer, a laptop computer, a desktop computer, a portable computing device, and / or the like, including combinations and / or multiples thereof. As yet another example, the processing system 102 can be the processing system 600 of Fig. 6 and / or may be one or more components of the processing system 600 of Fig. 6 included.

[0044] The processing device 202 in the processing system 102 handles the computational tasks for engine control and misfire detection. The processing device 202 processes data from various sensors, such as a crankshaft angle sensor 212, and executes algorithms to monitor the engine performance of the ICE 104. The processing device 202 is any suitable processing circuit arrangement for processing and / or commands. The processing device 202 is an example of one or more of the processing devices 621 of Fig. 6, as described in more detail here.

[0045] Memory 204 stores the data and algorithms for operating the processing system 102. Memory 204 provides storage for real-time data processing and analysis of historical data. Memory 204 is any suitable device for storing data and / or instructions. Memory 204 is an example of system memory 622 and / or read / write memory 623 and / or read-only memory 624. Fig. 6, as described in more detail here.

[0046] The misfire detection machine 210 is a specialized component in the processing system 102, designed to detect engine misfire events. The misfire detection machine 210 analyzes signals and / or data from the crankshaft angle sensor 212 and other engine parameters to detect misfire events. Features and functionality of the misfire detection machine 210 are now described with reference to Fig. 3- Fig. 5 described in more detail.

[0047] As described here, the ICE 104 generates power through fuel combustion and works in conjunction with the processing system 102 to provide optimal performance and efficiency. The ICE 104 incorporates various subsystems and sensors, such as the crankshaft angle sensor 212, which provide real-time signals / data to the processing system 102 for analysis and control.

[0048] The crankshaft angle sensor 212 is a component of the ICE 104 that provides real-time information (e.g., signals or data) about the position and speed of the ICE 104's crankshaft. For example, the crankshaft angle sensor 212 sends signals to the processing system 102, which are used by the misfire detection machine 210 to detect misfire events.

[0049] Fig. Figure 3 is a flowchart of a method 300 for detecting engine misfire events for engines (e.g., the ICE 104) of vehicles (e.g., the vehicle 100) according to one or more embodiments. For example, the method 300 detects engine misfire events for the ICE 104 using a filtered engine acceleration and an RMS engine acceleration. The method 300 includes several components and steps that work together to achieve accurate misfire detection. The method 300 can be implemented using any suitable system or device. For example, the method 300 can be implemented using the processing system 102 of Fig. 1 and Fig. 2, through the processing system 600 of Fig. 6 and / or the like, which contains combinations and / or several thereof, must be implemented. Procedure 300 is now implemented with reference to Fig. 1, Fig. 2, Fig. 4 and / or Fig. 5 described.

[0050] Procedure 300 begins in block 302, where the misfire detection machine 210 calculates an engine speed at least partially based on a crankshaft angle sensor signal received from the crankshaft angle sensor 212 of the ICE 104 at periodic intervals defined by a crankshaft rotation. This step involves using the crankshaft angle sensor signal to determine the engine speed. The crankshaft angle sensor provides real-time data on the position and speed of the crankshaft, which are used to accurately calculate the engine speed. The processing system 102 receives the crankshaft angle sensor signal from the crankshaft angle sensor 212 at periodic intervals defined by the crankshaft rotation, ensuring accurate timing for the speed calculation.For example, the crankshaft rotation can be 6 degrees, in which case the crankshaft angle sensor signal is received every 6 degrees (e.g., 60 times per crankshaft rotation). According to one or more embodiments, a crankshaft angle sensor implements a 58x sensing design, meaning it has 58 teeth every 6 degrees with a gap of two teeth. A crankshaft sensing design with a gap of "X" teeth can be implemented in various embodiments. It should be noted that further values ​​for crankshaft rotation may be implemented in other embodiments.

[0051] In block 304, the misfire detection machine 210 calculates an engine acceleration at least partially based on the engine speed from block 302. This step involves using the previously calculated engine speed to determine the engine acceleration. The misfire detection machine 210 calculates the engine acceleration by analyzing the changes in engine speed over time for the periodic interval defined by the crankshaft rotation. According to one or more embodiments, the misfire detection machine 210 calculates the engine acceleration using the following equation: Engine acceleration = ωn−ωn−1 periodic interval where ω n The engine speed for a given time n is ω. n-1The engine speed for a preceding time n - 1 is defined by the crankshaft rotation. According to one or more embodiments, the generation of the filtered engine acceleration is carried out using a convolution defined by the following equation: yx=B0+B1z−1+B2z−2+⋯+BNz−NA0+A1z−1+A2z−2+⋯+AMz−M where A0... A M and B0... B N The coefficients are pre-calculated for the filter, M and N are integers, and y and x refer to a filtered and an unfiltered acceleration, respectively. This calculation is useful for understanding the dynamic behavior of a power engine and identifying any irregularities that might indicate a misfire event.

[0052] In Block 306, the misfire detection machine 210 generates a filtered engine acceleration for the periodic intervals, at least partially based on the engine acceleration from Block 304, using a filter. This step involves applying a filter (e.g., a high-pass filter, a Butterworth filter, a low-pass filter, a bandwidth filter, and / or the like, including combinations and / or multiple filters) to the calculated engine acceleration to remove noise and other unwanted signals. According to one or more embodiments, the filter is either a high-pass filter or a Butterworth filter. The high-pass filter is designed to filter out low-frequency components, while the Butterworth filter provides a smooth frequency response. According to one or more embodiments, the filter can be optimized to maximize a signal-to-noise ratio.The filtered force machine acceleration is generated by performing a convolution using the unfiltered force machine acceleration with the filter, which ensures that the resulting signal is free from resonance effects and other distortions.

[0053] In block 308, the misfire detection machine 210 calculates an engine-engine-residual-measurement (RMS) engine-engine-residual-measurement acceleration value, at least partially, based on the filtered engine-engine-residual-measurement acceleration for the periodic intervals from block 306. This step includes calculating the RMS value of the filtered engine-engine-residual-measurement acceleration, which provides a measure of the overall acceleration behavior of an engine. According to one or more embodiments, the RMS engine-engine-residual-measurement acceleration is calculated using the following equation: mod(B0ak+B1ak−1+B2ak−2+B3ak−3+A1a'k−1+A2a'k−2+A3a'k−3a0, crankshaft rotation) where A0... A M and B0... B N The coefficients are pre-calculated for the filter, M and N are integers, a k , a k-1 , a k-2 , a k-3 the unfiltered acceleration for a current sample and three previous samples are, a' k , a' k-1 , a' k-2 , a' k-3 The filtered acceleration for the current sample and the three preceding samples is given by , and k represents the amount of crankshaft rotation in degrees. This calculation helps identify any significant deviations from engine operation that could indicate a misfire event.

[0054] In block 310, the misfire detection machine 210 detects whether an engine misfire event has occurred, at least partially based on the RMS engine acceleration from block 308. This step involves comparing the RMS engine acceleration with a normal ignition value to determine whether a misfire event has occurred. If the RMS engine acceleration differs from the normal ignition value by a threshold amount (e.g., a certain percentage, a certain value, and / or the like, including combinations and / or several thereof), a misfire event is presumed to have occurred. According to one or more embodiments, the engine misfire event is detected in response to the RMS engine acceleration deviating from the ignition value by more than four standard deviations.This comparison helps to differentiate between normal engine operation and misfire events, ensuring accurate detection.

[0055] In Block 312, in response to the detection of an engine misfire event (Block 310 "Yes"), the misfire detection machine 210 causes a corrective action to be implemented for the vehicle 100. Following the detection of an engine misfire event, several corrective actions can be taken to mitigate the impact and ensure the vehicle continues to operate safely and efficiently. These corrective actions may include one or more of the following: Adjusting the fuel injection timing: The processing system 102 (e.g., an engine control unit) can modify the timing of a fuel injection to ensure that the air-fuel mixture is ignited at the optimal moment. This adjustment can aid in restoring normal combustion and prevent further misfires.

[0056] Ignition system adjustment: The Processing System 102 can adjust the ignition timing or increase the spark energy to ensure the spark plug effectively ignites the air-fuel mixture. This can help resolve problems related to weak or delayed ignition.

[0057] Cylinder deactivation: In cases where a particular cylinder consistently misfires, the processing system 102 can temporarily deactivate that cylinder to prevent further damage to the engine. This allows the vehicle 100 to continue operating at reduced power until the problem can be addressed.

[0058] Fuel System Inspection: Processing System 102 can initiate a diagnostic routine to examine the fuel delivery system for problems such as clogged fuel injectors or low fuel pressure. If a problem is detected, Processing System 102 can attempt to correct it by adjusting fuel delivery parameters.

[0059] Engine Load Reduction: Processing System 102 can reduce engine load by limiting throttle opening or adjusting transmission shift points. This can help minimize engine stress and prevent further misfires while allowing the vehicle to continue operating.

[0060] Diagnostic Data Logging: The Processing System 102 can log detailed diagnostic data related to the misfire event, including engine speed, acceleration, and sensor readings. This data can be used by technicians to more effectively diagnose and repair the root cause of the misfire.

[0061] Adaptive Learning: The Processing System 102 can use adaptive learning algorithms to adjust engine parameters based on the detected misfire event. Over time, adaptive learning can help the engine adapt to changing conditions and prevent future misfires.

[0062] According to one or more embodiments, in addition to or instead of carrying out the corrective action, the processing system 102 can warn an operator of the vehicle 100, for example, by activating a warning light on the dashboard of a vehicle or by emitting an audible tone and / or an audible message regarding the misfire event. This warning can prompt the driver to seek maintenance or repair services to address the underlying problem causing the engine misfire event.

[0063] By implementing one or more of these corrective measures, the processing system 102 can manage engine misfire events more effectively and efficiently, ensuring continued desirable and efficient vehicle operation while minimizing the risk of damage to engine components.

[0064] If no misfire event is detected (Block 310 “No”), procedure 300 can return to Block 302 and repeat.

[0065] Additional processes may also be included, and it should be understood that the processes that are in Fig. The processes shown in Figure 3 are for illustrative purposes only and demonstrate that further processes can be added, or existing processes can be removed, modified, or rearranged. It should also be understood that the processes shown in Figure 3 are not intended to be interpreted in this way. Fig. 3 are shown, can be implemented as programming instructions stored in a non-transient, computer-readable storage medium and then, when executed by a processor (e.g., the processing device 202 of Fig. 2, the one or more processors 621 of Fig. 6 and / or the like, which includes combinations and / or several thereof) of a computing system (e.g., of the processing system 102 of Fig. 1 and Fig. 2, of the processing system 1100 of Fig. 6 and / or the like, which includes combinations and / or several thereof) are executed, causing the processor to perform the processes described herein.

[0066] Fig. Figure 4 shows a graph 400 of actual acceleration signals for normal ignition and single-cylinder misfire events. Graph 400 contains an actual acceleration signal 402 for a normal ignition event and an actual acceleration signal 404 for a single-cylinder misfire event, which are expressed in terms of acceleration (meters / second). 2 The values ​​are graphically represented on the vertical axis over time (seconds) and on the horizontal axis. Graph 400 illustrates the differences in acceleration signals between normal ignition and misfire events, highlighting the fluctuations in engine behavior during these conditions.

[0067] The actual acceleration signal 402 represents the acceleration of the engine during a normal ignition event. This signal serves as a reference for comparing the performance of an engine under normal (non-misfire) operating conditions. The actual acceleration signal 402 is characterized by a substantially consistent pattern that reflects the regular combustion cycles of the engine.

[0068] The actual acceleration signal 404 represents the acceleration of the engine during a single-cylinder misfire event. This signal shows deviations from the pattern observed in the actual acceleration signal 402. The fluctuations in the actual acceleration signal 404 indicate irregularities in the combustion process of the engine, which suggest a misfire event 406.

[0069] Fig. Figure 5 shows a graph of 500 filtered acceleration signals for normal ignition and single-cylinder misfire events. Graph 500 contains a filtered acceleration signal 502 for a normal ignition event and a filtered acceleration signal 504 for a single-cylinder misfire event, expressed in terms of acceleration (meters / second). 2 The graphs (vertical axis) and (horizontal axis) are graphically represented over time (seconds). Graph 500 shows the effectiveness of the filtering process in isolating the relevant acceleration signals for accurate misfire detection.

[0070] The filtered acceleration signal 502 represents the acceleration of the engine during a normal ignition event after applying the filter, as described here. The filtered acceleration signal 502 provides a clearer and more consistent representation of the engine's performance compared to the actual acceleration signal 402. Fig. 4. A filtered signal is available, free from noise and other distortions. This filtered signal serves as a reference for identifying deviations in the power machine's behavior.

[0071] The filtered acceleration signal 504 represents the acceleration of the engine during a single-cylinder misfire event after the filter has been applied, as described here. This signal highlights the differences between engine operation and misfire events more pronouncedly than the actual acceleration signals, as can be observed by comparing graphs 400 and 500. The filtered acceleration signal 504 shows significant deviations from the filtered acceleration signal 502, indicating the presence of a misfire event 506.

[0072] It is understood that one or more of the embodiments described here can be implemented in conjunction with any other type of computing environment, whether known now or developed later. For example, Fig.Figure 6 shows a block diagram of a processing system 600 for implementing the techniques described herein. According to one or more embodiments described herein, the processing system 600 is an example of a cloud computing node in a cloud computing environment. In examples, the processing system 600 has one or more central processing units (also referred to as "processors" or "processing equipment" or "processing devices") 621a, 621b, 621c, etc. (collectively or generically referred to as one or more processors 621 and / or one or more processing devices). In aspects of the present invention, each processor 621 may contain a microprocessor as a reduced instruction set computer (RISC microprocessor). The processors 621 are coupled to a system memory 622 and / or various other components by means of a system bus 633.The system memory 622 can contain one or more temporary and / or persistent storage devices, such as a read / write memory (RAM) 623, a read-only memory (ROM) 624, and / or the like, including combinations and / or multiples thereof. The system bus 633 can contain a basic input / output system (BIOS) that controls certain basic functions of the processing system 600.

[0073] Furthermore, an input / output adapter (I / O adapter) 627 and a network adapter 626 are shown, which are connected to the system bus 633. The input / output adapter 627 can be a small computer systems interface (SCSI) adapter, which communicates with a hard disk 635 and / or a storage device 636 or another similar component. The input / output adapter 627, the hard disk 635, and the storage device 636 are collectively referred to here as mass storage 634. An operating system 640 for execution in the processing system 600 can be stored in the mass storage 634. The network adapter 626 connects the system bus 633 to an external network 638, which enables the processing system 600 to communicate with other such systems.

[0074] A display device (e.g., a display monitor) 639 is connected to the system bus 633 via the display adapter 632, which may include a graphics adapter to improve the performance of graphics-intensive applications and a video controller. In one aspect of the present invention, the adapters 626, 627, and / or 632 may be connected to one or more input / output buses, which are connected to the system bus 633 by means of an intermediate bus bridge (not shown). Suitable input / output buses for connecting peripheral devices such as hard disk controllers, network adapters, and graphics adapters typically include common protocols such as the Peripheral Component Connection (PCI). Additional input / output devices are shown as being connected to the system bus 633 by means of a user interface adapter 628 and a display adapter 632.A keyboard 629, a mouse 630 and a loudspeaker 631 can be connected to the system bus 633 by means of a user interface adapter 628, which may contain, for example, a super input / output chip that integrates several device adapters into a single integrated circuit.

[0075] In certain aspects of the present invention, a processing system 600 includes a graphics processing unit (GPU) 637. The graphics processing unit 637 is a specialized electronic circuit designed to manipulate and modify memory to accelerate the generation of images in a frame buffer intended for output to a display device. In general, the graphics processing unit 637 is very efficient in manipulating computer graphics and in image processing and has a highly parallel structure, which makes it more effective than generally applicable CPUs for algorithms, with the parallel processing of large blocks of data.

[0076] Thus, as configured here, the processing system 600 includes a processing capability in the form of processors 621, a storage capacity comprising the system memory 622 and the mass storage device 634, input means such as the keyboard 629 and the mouse 630, and an output capability comprising the loudspeaker 631 and the display device 639. In certain aspects of the present invention, a section of the system memory 622 and a section of the mass storage device 634 jointly store the operating system 640 in order to coordinate the functions of the various components shown in the processing system 600. legend

[0077] In the drawing figures, N stands for no and Y for yes.

Claims

[1] Computer-implemented method for detecting engine misfire events for an engine (104) of a vehicle (100), the method comprising: Calculating a motor speed at least partially on the basis of a crankshaft angle sensor signal received by a crankshaft angle sensor (212) of the motor (104) at periodic intervals defined by a crankshaft rotation; Calculating the acceleration of a power engine, at least partially, based on the engine speed; Generating, using a filter, a filtered engine acceleration for the periodic intervals, at least partially based on the engine acceleration; Calculating an effective value of the engine acceleration (RMS engine acceleration) at least partially based on the filtered engine acceleration for the periodic intervals; Detecting an engine misfire event at least partially based on RMS engine acceleration, and Implementing a corrective action for the vehicle (100) in response to a detection of the engine misfire event. [2] Computer-implemented method according to claim 1, wherein the filter is a high-pass filter. [3] Computer-implemented method according to claim 1, wherein the filter is a Butterworth filter. [4] Computer-implemented method according to claim 1, wherein the detection of the engine misfire event comprises comparing the RMS engine acceleration with a normal ignition value. [5] Computer-implemented method according to claim 4, wherein the engine misfire event is detected in response to the RMS engine acceleration deviating from the normal ignition value by more than four standard deviations. [6] Computer-implemented method according to claim 1, wherein the generation of the filtered force machine acceleration is carried out using a convolution. [7] Computer-implemented method according to claim 6, wherein the convolution is defined by the following equation: yx=B0+B1z−1+B2z−2+⋯+BNz−NA0+A1z−1+A2z−2+⋯+AMz−M where A0... A M and B0... B N The coefficients are pre-calculated for the filter, M and N are integers, and y and x refer to a filtered and an unfiltered acceleration, respectively. [8] Computer-implemented method according to claim 1, wherein the RMS force machine acceleration is calculated using the following equation: mod(B0ak+B1ak−1+B2ak−2+B3ak−3+A1a'k−1+A2a'k−2+A3a'k−3a0, crankshaft rotation) where A0... A M and B0 ... B N The coefficients are pre-calculated for the filter, M and N are integers, a k , a k-1 , a k-2 , a k-3 the unfiltered acceleration for a current sample and three previous samples are, a' k , a' k-1 , a' k-2 , a' k-3 The filtered acceleration for the current sample and the three previous samples is, and k represents an amount of crankshaft rotation in degrees. [9] Vehicle (100) comprising: an internal combustion engine (104); a crankshaft angle sensor (212) assigned to the internal combustion engine (104); and a processing system (102, 600) that includes: a memory (204, 622, 634) containing computer-readable instructions; and a processing device (202) for executing the computer-readable instructions, wherein the computer-readable instructions control the processing system (102, 600) to perform operations for detecting engine misfire events for the internal combustion engine (104), and the operations include: Calculating an engine speed of the internal combustion engine (104) at least partially on the basis of a crankshaft angle sensor signal received by the crankshaft angle sensor (212) at periodic intervals defined by a crankshaft rotation; Calculating the acceleration of the internal combustion engine (104) at least partially on the basis of the engine speed; Generating, using a filter, a filtered engine acceleration of the internal combustion engine (104) for the periodic intervals at least partially based on the engine acceleration; Calculating an effective value of the engine acceleration (RMS engine acceleration) of the internal combustion engine (104) at least partially on the basis of the filtered engine acceleration for the periodic intervals; Detecting an engine misfire event of the internal combustion engine (104) at least partially based on the RMS engine acceleration, and Implementing a corrective action for the vehicle (100) in response to a detection of the engine misfire event. [10] Vehicle (100) according to claim 9, wherein the detection of the engine misfire event comprises comparing the RMS engine acceleration with a normal ignition value, wherein the engine misfire event is detected in response to the RMS engine acceleration deviating from the normal ignition value by more than four standard deviations.

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