Centroid Shift Deviation Method for Obtaining Engine Cycle-Level Combustion Parameters Based on Multi-Sensor Signals

Abstract

The present invention discloses a centroid shift deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals, which relates to the technical field of engines and their combustion control. The method provided by the present invention includes: taking the prior values of combustion characteristic parameters under various operating conditions as a reference, reconstructing the values of combustion characteristic parameters based on the signal characteristics obtained by engine sensors, and calculating the deviation and its weight between the values of combustion characteristic parameters and the prior values; obtaining the fusion deviation of the combustion characteristic parameters as the transient fluctuation amount of the combustion characteristic parameters; according to the obtained transient fluctuation amount, using the centroid shift deviation method to correct the prior values to obtain the actual values of the combustion characteristic parameters of the engine in the current cycle; and updating the combustion heat release rate curve using the Weber equation to obtain the information of each transient combustion parameter under the current operating condition. Therefore, by adopting the above method, the problem of missing combustion information caused by the lack of direct sensing technology can be solved, providing a powerful means for analyzing the working state of the engine and improving its performance.

Description

Technical Field

[0001] The invention relates to the technical field of engines and combustion control thereof, and in particular to a decentered deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals. Background Art

[0002] With the increasing intelligence and electrification of vehicles, new technologies that improve engine performance, reduce emissions and increase fuel economy are developing rapidly. Further optimizing engine combustion control technology has become an important issue that needs to be addressed urgently.

[0003] Real-time state monitoring of the engine is an essential requirement for the development of new engine combustion control technologies, and the lack of combustion parameters is an unavoidable key issue in the development of engine combustion control technologies. Since combustion state parameters cannot be measured directly, they are generally obtained by constructing an engine combustion model and checking the combustion parameter prior calibration map. However, the engine combustion model is computationally complex and cannot meet the real-time requirements of engine combustion control; the combustion parameter prior calibration map reflects the multi-cycle average value of all cylinders of the engine under the calibration conditions, and cannot reflect the changes in combustion information between cycles and between different cylinders, so it cannot accurately reflect the changes in combustion parameters in all cycles of all conditions under real conditions.

[0004] In order to improve the accuracy of combustion parameters and achieve cycle-level engine control optimization, the most feasible technical route is to extract key combustion information from existing sensor signals, and the method of reconstructing combustion parameters through cylinder pressure sensor signals, crankshaft position sensor signals, and knock sensor vibration signals (hereinafter referred to as knock signals) has been developed. However, the cost of installing cylinder pressure sensors is still very high, and the harsh combustion environment in the cylinder will greatly shorten the service life of the sensor. These problems make cylinder pressure sensors unable to be widely used. In order to avoid the use of cylinder pressure sensors, technical methods for extracting combustion information based on sensor signals widely equipped with modern engines have received widespread attention. However, the accuracy of reconstructing combustion parameters using only sensor signals is heavily dependent on the working state of the sensor and is easily affected by noise. These problems are particularly prominent when only a single sensor signal is used to reconstruct combustion parameters.

[0005] In addition, some studies use neural network models to predict combustion parameters. Although this method has good real-time performance, its calculation accuracy is closely related to the data quality of the training set and the degree of coverage of operating conditions. For engines, it is unrealistic to build a training set that includes all operating conditions. Therefore, it is urgent to develop a new cycle-level combustion parameter acquisition method that takes into account the requirements of real-time performance and accuracy, and provide a reference for further optimization of engine combustion control technology. Summary of the invention

[0006] The object of the present invention is to provide a centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals, which can accurately obtain cycle-level combustion parameters in real time.

[0007] To achieve the above object, the present invention provides a centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals, including the following steps:

[0008] S1. Obtain the average value of the engine combustion characteristic parameters under different working conditions as the prior value, and store it in the form of a mathematical model or a MAP table; at the same time, establish a shape basic model of the key shape parameters of the Weber equation for the combustion heat release rate curve under different working conditions; establish a shape relationship model of the correction relationship between the combustion characteristic parameter deviation value and the key shape parameters under each specific working condition;

[0009] S2. Check the mathematical model or MAP table storing the prior value of the combustion characteristic parameters according to the current working condition information, obtain the prior value of the combustion characteristic parameters under the current working condition, and obtain the key shape parameters a base and m base ;

[0010] S3. Reconstruct the combustion characteristic parameter values based on the signal characteristics obtained by multiple sensors of the engine, calculate the deviation between the reconstructed value of the combustion characteristic parameter and the prior value respectively, and determine the weight corresponding to each deviation through the probability distribution of the deviation;

[0011] S4. Based on the determined deviation weights, perform weighted summation on each deviation to obtain the fusion deviation of the combustion characteristic parameters as the real-time deviation amount of the combustion characteristic parameters;

[0012] S5. According to the obtained real-time deviation value, correct the prior value to obtain the actual characteristic value;

[0013] S6. According to the actual deviation value obtained in step S3 and the shape relationship model, correct the key shape parameters a base and m base obtained through the shape basic model, update the mathematical expression of the combustion heat release rate curve, and then obtain the combustion parameter values under the current cycle.

[0014] Preferably, in step S1, the prior value of the combustion characteristic parameter, the basic shape parameter of the heat release rate, and the shape parameter correction relationship are the empirical values of the engine combustion characteristic parameters with respect to the working condition information, and are obtained through engine bench tests or simulation calculations.

[0015] Preferably, in step S2, the process of reconstructing the combustion characteristic parameter values includes preprocessing each sensing signal, then comparing and analyzing the preprocessed sensing signal curve with the cylinder pressure curve and the heat release rate curve, extracting the characteristic information related to the engine combustion state, and establishing a mapping model or function of the relationship between the sensing signal characteristic information and the combustion characteristic parameter according to the correlation between the sensing signal characteristic information and the combustion characteristic parameter.

[0016] Preferably, the determination of the deviation weight includes:

[0017] First, based on the deviation method, establish the relationship between the experimental value and the prior value of the combustion characteristic parameter:

[0018]

[0019] In the formula, Y is the experimental value of the combustion characteristic parameter; X i is the reconstructed value of the i-th combustion characteristic parameter, which are independent of each other; K i is the deviation weight corresponding to X i ; is the prior value of the combustion characteristic parameter;

[0020] Then, use the method of minimum variance of the experimental value of the combustion characteristic parameter to determine the deviation weight corresponding to each reconstructed value of the combustion characteristic parameter respectively.

[0021] Preferably, in step S3, the calculation method of the fusion deviation is as follows:

[0022] First, calculate the deviation between the reconstructed value and the prior value of each combustion characteristic parameter; secondly, calculate the deviation weight corresponding to each reconstructed value of the combustion characteristic parameter; finally, perform weighted summation on all deviation values to obtain the fusion deviation, and the specific expression is as follows:

[0023]

[0024] In the formula, ΔX is the fusion deviation, n is the number of types of sensor signals, f i (δ i ) represents the reconstructed value of the combustion characteristic parameter corresponding to the i-th sensing signal characteristic information.

[0025] Preferably, the centroid deviation method refers to moving the combustion characteristic parameter value on the combustion heat release rate curve based on the fusion deviation, where centroid shifting means moving the representative combustion characteristic parameter value on the combustion heat release rate curve, and the specific expression is as follows:

[0026]

[0027] In the formula, Z core is the combustion characteristic parameter value obtained after centroid shifting.

[0028] Preferably, the specific steps for updating the combustion heat release rate curve are as follows:

[0029] First, according to the shape relationship model of the correction relationship between the combustion characteristic parameter deviation value and the shape parameter of the Weber equation under specific working conditions, update a base and m base obtained from the shape-based model to obtain the updated key shape parameters a and m of the Weber equation;

[0030] Secondly, substitute the updated combustion characteristic parameters, a, and m into the Weber function to obtain the combustion heat release rate curve of the current working condition cycle, and then obtain the values of each combustion parameter, specifically as follows:

[0031]

[0032] In the formula, Q(θ) is the cumulative heat release rate at the crankshaft angle of θ; θ0 is the crankshaft angle corresponding to the start time of combustion; Δθ is the combustion duration; a and m are shape parameters, depending on the working condition state.

[0033] Preferably, the calculation of the combustion parameters is completed within a single engine cycle, and the cycle-level combustion parameters are obtained.

[0034] Therefore, the present invention adopts the above-mentioned centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals, and has the following technical effects:

[0035] (1) Through the centroid deviation method, the combustion characteristic parameters are divided into steady-state and transient parts, with the prior value as the steady-state reflection quantity and the fusion deviation of each sensor as the transient fluctuation quantity, reflecting the transient changes of the combustion characteristic parameters, and realizing the real-time and accurate acquisition of cycle-level combustion parameters;

[0036] (2) Using the characteristics of multiple sensing signals to calculate the fusion deviation can not only improve the calculation accuracy of the combustion parameters, but also reduce the dependence of the calculated values of the combustion parameters on the working state of the sensors.

[0037] Next, through the drawings and embodiments, the technical solutions of the present invention will be further described in detail. Description of the Drawings

[0038] Figure 1 is a schematic diagram of the experimental test platform in the embodiment of the centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals;

[0039] Figure 2 is a schematic diagram of the principle of the centroid deviation method in the embodiment of the centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals;

[0040] Figure 3It is a comparison chart of the minimum value feature of the crankshaft transient angular velocity and the combustion characteristic parameters in the centroid deviation method embodiment for obtaining engine cycle-level combustion parameters based on multi-sensor signals. Among them, Figure 3 In (a), it is the comparison chart with CA10. Figure 3 In (b), it is the comparison chart with CA50. Figure 3 In (c), it is the comparison chart with CA90.

[0041] Figure 4 It is a comparison chart of the peak value feature of the knock signal and the combustion characteristic parameters in the centroid deviation method embodiment for obtaining engine cycle-level combustion parameters based on multi-sensor signals.

[0042] Figure 5 It is a comparison chart of the calculated value and the experimental value of the combustion characteristic parameters in the third embodiment of the centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals. Among them, Figure 5 In (a), it is the comparison chart of CA10. Figure 5 In (b), it is the comparison chart of CA50. Figure 5 In (c), it is the comparison chart of CA90. Specific implementation manner

[0043] The present invention can be more detailedly explained through the following embodiments. The purpose of disclosing the present invention is to protect all changes and improvements within the scope of the present invention. The present invention is not limited to the following embodiments.

[0044] As Figure 1 shown, in this embodiment, the centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals is all carried out on an experimental test platform. Among them, the experimental test platform includes an engine bench, a time synchronization unit, a controller unit, a combustion analyzer, and an in-vehicle computing unit. The functions of each component are specifically as follows:

[0045] (1) The engine bench runs under the command of the controller unit. The controller unit acquires sensing signals through sensors deployed on the engine.

[0046] (2) The time synchronization unit has two main functions. One is to collect the crankshaft position signal and calculate the crankshaft transient angular velocity, and the other is to determine the time reference to achieve signal synchronization.

[0047] On the one hand, this unit collects the crankshaft position signal and records the sampling point time at the same time. By identifying the rising edge of the crankshaft position square wave signal and the time interval between adjacent rising edges, the crankshaft transient angular velocity is calculated. On the other hand, the time synchronization unit determines the missing tooth position according to the crankshaft position square wave signal, takes it as the starting point for determining the tooth position, obtains the time clock during the engine operation process, and then determines the time reference for the transmission of sensing signals to achieve signal synchronization.

[0048] (3) The combustion analyzer is used to collect, record, and analyze the engine combustion information, providing a reference for the calculation results of the centroid deviation method.

[0049] (4) The vehicle-mounted computing unit is a high-performance computing unit for deploying the centroid deviation method, capable of meeting the analysis and calculation of sensing signals, the calculation of the combustion characteristic parameter reconstruction model, and the calculation of the centroid deviation method.

[0050] As Figure 2 shown, the centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals provided by the present invention is further illustrated by the following embodiments.

[0051] Embodiment 1

[0052] First, for the case of n = 0, the combustion parameters are obtained through prior information, and the specific steps are as follows:

[0053] According to the current operating condition parameters, the prior values of the engine combustion characteristic parameters are obtained by means of look-up tables, neural network models, etc., which can reflect the multi-cycle average values of all cylinders under steady state. For non-calibrated operating conditions, they are obtained by interpolation or neural network fitting.

[0054] Embodiment 2

[0055] For the case of n = 1, at this time the sensor signals only include the crankshaft position signal, and the combustion parameters are obtained based on the prior information of the combustion characteristic parameters and the crankshaft position signal, specifically as follows:

[0056] The prior values of the combustion characteristic parameters are obtained by looking up the prior calibration map and the combustion characteristic parameters are constructed based on the characteristics of the crankshaft position signal to obtain the reconstructed value X1 of the combustion characteristic parameters;

[0057] According to the deviation between the reconstructed value and the prior value, the prior value is adjusted to obtain the combustion characteristic parameter value under the current operating condition and the current cycle, and the process can be summarized as:

[0058]

[0059] In the formula, Z core is the value of the combustion characteristic parameter after centroid shift, c is the deviation weight coefficient, which can be determined based on the operating condition identification, and the value range is (0, 1].

[0060] Among them, the method for reconstructing the combustion characteristic parameters based on the characteristics of the crankshaft position signal is as follows:

[0061] (1) Signal preprocessing

[0062] The original square wave signal collected by the crankshaft position sensor is used to calculate the transient angular velocity of the crankshaft. The main steps include: The time synchronization unit determines the specific moments of the rising edges of the square wave signal according to the collected crankshaft position square wave signal and the corresponding sampling time, and calculates the time interval T between two adjacent rising edges. k,k+1 :

[0063] T k,k+1 = T k+1 - T k

[0064] In the formula, T represents the moment corresponding to the rising edge, and k represents the number of teeth.

[0065] According to the above time interval, calculate the transient angular velocity v of the crankshaft. k,k+1 :

[0066]

[0067] Among them, v represents the transient angular velocity of the crankshaft. Since the recognition of the rising and falling edges of the crankshaft is affected by the sampling frequency, the transient angular velocity of the crankshaft calculated by the above method is extremely uneven, and the signal characteristics are not easy to observe and extract. Therefore, it is necessary to filter and smooth the transient angular velocity curve of the crankshaft; in this embodiment, a Gaussian filter is selected to filter and smooth the transient angular velocity of the crankshaft.

[0068] (2) Extract signal features

[0069] By comparing and analyzing the transient angular velocity curve of the crankshaft and the cylinder pressure curve, the maximum cylinder pressure peak appears after the minimum value of the transient angular velocity of the crankshaft; therefore, the minimum value of the transient angular velocity of the crankshaft is taken as the signal feature of the crankshaft position.

[0070] (3) Reconstruct the combustion characteristic parameter X1

[0071] As Figure 3 shown, according to the results of the correlation analysis, there is an obvious inverse relationship between the minimum value of the transient angular velocity of the crankshaft and each combustion characteristic parameter. Therefore, a parameter identification model from the minimum value of the transient angular velocity of the crankshaft to each combustion characteristic parameter is established to reconstruct the combustion characteristic parameter X1.

[0072] Example three

[0073] For the case of n = 2, at this time the sensor signals include the crankshaft position signal and the knock signal, and the combustion characteristic parameters obtained by the centroid deviation method are expressed as:

[0074]

[0075] In the formula, K1 and K2 are deviation weight coefficients, and f1(δ1) and f2(δ2) are the combustion characteristic parameter values reconstructed based on the crankshaft position signal and the knock signal characteristics respectively.

[0076] (1) According to the current operating condition parameters, look up the prior calibration map to obtain the prior values of the combustion characteristic parameters As the core of the combustion heat release rate curve;

[0077] (2) Preprocess each sensing signal

[0078] The preprocessing method of the crankshaft position signal is the same as that in the second embodiment.

[0079] The vibration signal obtained by the knock sensor includes not only the vibration signal related to combustion, but also the cylinder block vibration signal caused by other engine components. In order to extract the effective information strongly related to the combustion process, it is necessary to first perform filtering and noise reduction processing on the original signal collected by the knock sensor.

[0080] First, perform Fourier transform on the knock original signal to obtain its distribution in different frequency domains, and sample the frequency to obtain the discrete Fourier transform (DFT) X(k):

[0081]

[0082] In the formula, x(n) is the knock discrete signal, and N is the sampling number of discrete data.

[0083] After the above Fourier transform, determine the frequency domain of the signal distribution strongly related to combustion in the knock original signal; within this frequency domain, perform coherence estimation on the in-cylinder pressure and knock signals to analyze the correlation degree between the two signals:

[0084]

[0085] In the formula, C xy (f) represents the amplitude squared coherence estimate, which is a function of frequency and has a value between 0 and 1, indicating the corresponding degree with y at each frequency; P xx (f) and P yy (f) are the power spectral densities of x and y respectively; P xy (f) is the cross-power spectral density of x and y.

[0086] Calculate the coherence coefficient between the knock signal and the cylinder pressure signal through the above method, and it is found that the knock signal and the cylinder pressure signal have a high coherence at low frequencies, especially in the frequency domain of 0-400 Hz; in order to filter out high-frequency noise, a Chebyshev low-pass filter is selected to filter the knock signal:

[0087]

[0088] In the formula, H n (ω) is the transfer function of the filter, ε is the passband ripple, T nis the Chebyshev polynomial, ω is the expected cut-off frequency, and ω0 is the passband cut-off frequency.

[0089] According to the frequency domain range obtained from the above coherence analysis, the passband cut-off frequency of the Chebyshev low-pass filter is set to 200 Hz, the stopband cut-off frequency is set to 800 Hz, the attenuation BD number in the sideband region is set to 1, and the attenuation DB number in the stopband region is set to 30; further extract the effective signal segments related to combustion in the knock signal.

[0090] (3) Extract the characteristics of each sensing signal

[0091] The method for extracting the signal characteristics of the crankshaft position signal is the same as that in Embodiment 2, and the minimum value of the crankshaft transient angular velocity is used as the signal characteristic of the crankshaft position signal.

[0092] Compare and analyze the preprocessed knock signal segment with the cylinder pressure signal, and it is found that the peak phase of the knock signal is slightly ahead of the maximum cylinder pressure phase, and there is an obvious positive correlation between the maximum cylinder pressure and the peak value of the knock signal; therefore, extract the peak value of the knock signal as the knock signal characteristic.

[0093] (4) Reconstruct the combustion characteristic parameters based on the characteristics of each sensing signal

[0094] The method for reconstructing the combustion characteristic parameters based on the crankshaft position signal is consistent with that in Embodiment 2, and the combustion characteristic parameters reconstructed based on the crankshaft position signal are denoted as X1.

[0095] Analyze the relationship between the peak characteristics of the knock signal and the combustion characteristic parameters, and it is found that the change trends of the peak value of the knock signal and the combustion characteristic parameters are significantly consistent, as Figure 4 shown. Therefore, with the peak value of the knock signal as the input and the combustion characteristic parameters as the output, a combustion characteristic parameter reconstruction model is constructed by the parameter identification method to reconstruct the combustion characteristic parameters X2.

[0096] (5) Calculation of the fusion weight

[0097] Calculate the deviation between the combustion characteristic parameter values reconstructed based on the characteristics of each sensing signal and the prior value; and calculate the fusion weight of each characteristic deviation according to the reconstructed value of the combustion characteristic parameter and the actual value calculated by the combustion analyzer. The specific steps are as follows:

[0098] Assume that the reconstructed values X1 and X2 of the combustion characteristic parameters are two independent variables, Y is the actual value of the combustion characteristic parameter calculated by the combustion analyzer, and K i represents the fusion weight of the deviation corresponding to X i , and the relationship between the prior value and the reconstructed value satisfies:

[0099]

[0100] Minimize the variance of Y to determine the fusion weight K i 。

[0101] Weighted sum of the deviations corresponding to each reconstructed value and the fusion weight to obtain the fusion deviation, that is

[0102]

[0103] (6) Adjust the prior value according to the fusion deviation Obtain the values of each combustion characteristic parameter under the current cycle of the engine, and use the Weber function to obtain the information of each transient combustion parameter.

[0104] Example 4

[0105] For the case of n = 3, at this time the sensing signals include the crankshaft position signal, the knock signal, and the rail pressure signal. The principle of the centroid deviation method is as follows:

[0106]

[0107] In the formula, f i (δ i ) is the value of the combustion characteristic parameter reconstructed based on the signal obtained by sensor i.

[0108] Among them, the signal preprocessing methods of the crankshaft position signal and the knock signal are the same as those in Example 2 and Example 3. The values of the combustion characteristic parameters reconstructed based on these two signals are respectively denoted as X1 and X2, and the corresponding weights are K1 and K2.

[0109] For the rail pressure signal, filtering processing should be carried out first, and then the filtered signal is compared and analyzed with the cylinder pressure signal to extract the signal characteristics and reconstruct the combustion characteristic parameter X3. The determination method of K3 is the same as that of K1 and K2.

[0110] In the actual operation process, the methods for extracting the sensing signal characteristics and reconstructing the combustion characteristic parameters have been completed before the application of the centroid deviation method; in other words, the sensing signal characteristics are pre-selected. During actual use, the corresponding signal characteristic values are directly extracted from the preprocessed signal to reconstruct the combustion characteristic parameters. In addition, through the above method, data transmission and combustion parameter calculation can be completed within a single cycle of the engine, and the acquisition of engine cycle-level combustion parameters can be realized.

[0111] Therefore, the present invention adopts the above-mentioned centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals, using the fusion deviation as the transient fluctuation amount, which can reflect the transient changes of the combustion characteristic parameters and realize the real-time and accurate acquisition of cycle-level combustion parameters.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions of the present invention or make equivalent replacements, and these modifications or equivalent replacements do not enable the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. The centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals, characterized in that It includes the following steps: S1. Through engine bench tests or simulation calculations, obtain the average values of engine combustion characteristic parameters under different working conditions as prior values, and store them in the form of mathematical models or map tables. At the same time, establish a shape-based model for the key shape parameters of the Wiebe equation of the combustion heat release rate curve under different working conditions; establish a shape relationship model for the correction relationship between the deviation values of combustion characteristic parameters and key shape parameters under each specific working condition; S2. According to the current working condition information, query the mathematical model or map table storing the prior values of combustion characteristic parameters, obtain the prior values of combustion characteristic parameters under the current working condition, and obtain the key shape parameters a of the Weibull equation of the combustion heat release rate curve under the current working condition from the shape basic model base and m base ; S3. Reconstruct the combustion characteristic parameter values based on the signal characteristics obtained by multiple engine sensors, calculate the deviations between the reconstructed values of combustion characteristic parameters and the prior values respectively, and determine the weights corresponding to each deviation through the probability distribution of the deviations; Among them, the determination of the deviation weights includes: First, based on the deviation method, establish the relationship between the experimental values and prior values of combustion characteristic parameters: where Y is the experimental value of the combustion characteristic parameter; X i is the reconstructed value of the i-th combustion characteristic parameter, which are independent of each other; K i is the deviation weight corresponding to X i ; is the prior value of the combustion characteristic parameter; Then, use the method of the minimum variance of the experimental values of combustion characteristic parameters to determine the deviation weights corresponding to the reconstructed values of each combustion characteristic parameter respectively; S4. Based on the determined deviation weights, perform weighted summation on each deviation to obtain the fusion deviation of combustion characteristic parameters as the real-time deviation amount of combustion characteristic parameters; The calculation method of the fusion deviation is as follows: First, calculate the deviations between the reconstructed values and prior values of each combustion characteristic parameter; secondly, calculate the deviation weights corresponding to the reconstructed values of each combustion characteristic parameter; finally, perform weighted summation on all deviation values to obtain the fusion deviation, and the specific expression is as follows: Where, ΔX is the fusion deviation, n is the number of types of sensor signals, f i (δ i ) represents the reconstructed value of the combustion characteristic parameter corresponding to the characteristic information of the i-th sensing signal; S5. According to the obtained real-time deviation values, correct the prior values to obtain the actual characteristic values; S6. According to the actual deviation value obtained in step S3 and the shape relationship model, correct the key shape parameters a base and m base of the Wiebe equation obtained through the shape basic model, update the mathematical expression of the combustion heat release rate curve, and then obtain the values of various combustion parameters in the current cycle.

2. The centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals according to claim 1, characterized in that In step S3, the process of reconstructing the combustion characteristic parameter values includes preprocessing each sensing signal, then comparing and analyzing the preprocessed sensing signal curve with the cylinder pressure curve and the heat release rate curve, extracting the characteristic information related to the engine combustion state, and establishing a mapping model or function for the relationship between the sensing signal characteristic information and the combustion characteristic parameters according to the correlation between the sensing signal characteristic information and the combustion characteristic parameters.

3. The centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals according to claim 1, characterized in that The centroid shift deviation method refers to moving the combustion characteristic parameter values on the combustion heat release rate curve based on the fusion deviation, and the specific expression is as follows: where Z core is the value of the combustion characteristic parameter obtained after decentering.

4. The centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensing signals according to claim 1, characterized in that The specific steps for updating the combustion heat release rate curve are as follows: First, according to the shape relationship model of the correction relationship between the combustion characteristic parameter deviation value and the Weber equation shape parameter under specific working conditions, update a obtained from the shape basic model base and m base , and obtain the updated key shape parameters a and m of the Weber equation; Secondly, substitute the updated combustion characteristic parameters, a and m into the Wiebe function to obtain the combustion heat release rate curve of the current working condition cycle, and then obtain each combustion parameter value, specifically as follows: In the formula, Q(θ) is the cumulative heat release rate at the crankshaft angle of θ; θ0 is the crankshaft angle corresponding to the start time of combustion; Δθ is the combustion duration; a and m are shape parameters depending on the working condition state.

5. The centroid deviation method for obtaining engine cycle-level combustion parameters based on multi-sensor signals according to any one of claims 1 to 4, characterized in that The calculation of combustion parameters is completed within a single engine cycle, and cycle-level combustion parameters are obtained.

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