Power management system based on internal combustion engine operating data analysis

Abstract

The present invention provides a power management system based on the analysis of the working condition data of an internal combustion engine, which belongs to the field of power management technology and includes: a feature extraction module, which is used to split the working condition data of the internal combustion engine according to the working condition parameters and extract the first feature of each split data set, and extract the second feature of the separate working condition set of different working condition parameters at the same historical moment; a mapping processing module, which is used to map all the first extracted features, and determine the factors to be optimized and the attributes to be optimized of the factors to be optimized corresponding to the second extracted features in combination with the standard operating conditions of the internal combustion engine; a strategy generation module, which is used to generate a power management strategy according to the factors and attributes to be optimized at each historical moment; a management and early warning module, which is used to manage and warn the current power situation of the internal combustion engine based on the power management strategy. It ensures that the abnormality of the internal combustion engine is solved in time and improves its working efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and in particular to a power management system based on internal combustion engine operating condition data analysis. Background Art

[0002] Internal combustion engines are the power source of automobiles. They can be divided into gasoline engines and diesel engines. They differ in fuel, thermal efficiency, emissions, etc., and as their application scenarios become more and more extensive, such as marine and power generation, internal combustion engines are still irreplaceable in these application scenarios. In order to ensure the reliable operation of internal combustion engines, it is particularly important to analyze the operating data of internal combustion engines.

[0003] The common analysis method now is to measure the parameters of the internal combustion engine based on various existing sensors, and determine the abnormal conditions of the internal combustion engine through human judgment. A series of data in this process will not be retained, resulting in each judgment being an independent and restarted process, that is, it will not rely on historical data for comprehensive analysis, resulting in reduced reliability of power analysis, which is not conducive to the power management of the internal combustion engine.

[0004] Therefore, the present invention proposes a power management system based on analysis of internal combustion engine operating condition data. Summary of the invention

[0005] The present invention provides a power management system based on the analysis of the operating condition data of an internal combustion engine, which is used to obtain the operating condition data at historical moments to perform feature extraction from two aspects, a single historical moment and a single parameter, to ensure the reliability of the analysis basis, and subsequently obtain the optimization factors and attributes through feature mapping to generate a management strategy, so as to facilitate timely power management and early warning of the current operating conditions, ensure the timely resolution of internal combustion engine abnormalities, and improve its working efficiency.

[0006] The present invention provides a power management system based on internal combustion engine operating condition data analysis, comprising:

[0007] A feature extraction module is used to split the internal combustion engine operating condition data according to the operating condition parameters and perform a first feature extraction on each split data set, and at the same time, perform a second feature extraction on a separate operating condition set with different operating condition parameters at the same historical moment;

[0008] A mapping processing module, used for mapping all the first extracted features, and determining the factors to be optimized corresponding to the second extracted features and the properties to be optimized of the factors to be optimized in combination with the standard operating conditions of the internal combustion engine;

[0009] A strategy generation module, used to generate a power management strategy of the internal combustion engine according to the factors to be optimized and the attributes to be optimized at each historical moment;

[0010] A management and warning module is used to manage and warn the current power situation of the internal combustion engine based on the power management strategy.

[0011] Preferably, the feature extraction module comprises:

[0012] A curve drawing unit, used to respectively obtain the setting mode of the internal combustion engine at each historical moment, obtain a standard data set based on each operating condition parameter, and draw a corresponding standard parameter curve, and at the same time, draw a curve for the corresponding split data set to obtain a historical actual parameter curve;

[0013] An alignment processing unit, used to align the standard parameter curve and the historical actual parameter curve under the same working condition parameters at the same time, and display the alignment processing curve prominently at the corresponding time point based on the mode label of the set mode;

[0014] A first determination unit is used for screening the relatively stable segments of the corresponding historical actual parameters based on the standard parameter curve if the significance display result is one, and determining a first relative characteristic quantity based on each relatively stable segment;

[0015] ;

[0016] in, Represents the first relative characteristic quantity of the i1th relatively stable segment; It represents the standard setting range of the i1th relatively stable segment; represents the parameter value at the j1th historical moment in the i1th relatively stable segment; represents the total number of historical moments that appear in the i1th relatively stable segment; Indicates the characteristic setting coefficient of the i1th relatively stable segment matching the corresponding setting mode; To set a constant; Indicates that based on all The variance of

[0017] ;

[0018] in, Indicates the working mode-coefficient comparison table; Indicates that from the working mode-coefficient comparison table Obtain the characteristic setting coefficients matching the i1th relatively stable segment and the corresponding setting mode ;

[0019] A second determination unit is used for, if there are multiple significant display results, intercepting the historical actual parameter curve according to the continuous appearance time of each mode label to obtain an intercepted segment, and relying on the standard segment under the corresponding mode label and the conversion transition condition under the label that is adjacent to the corresponding mode label, performing a smooth measurement on the intercepted segment to obtain a second relative feature value;

[0020] The sequence sorting unit is used to sort the corresponding relative feature quantities according to the sequence of appearance of the pattern labels, construct an analysis vector, and input it into the first operating condition analysis model corresponding to the corresponding operating condition parameters to obtain the first extracted feature of the corresponding split data set.

[0021] Preferably, the second determining unit includes:

[0022] A fine-tuning function determination subunit, used for constructing a fine-tuning function for the intercepted segment;

[0023] ;

[0024] A calculation subunit, used for calculating a second relative characteristic quantity for the intercepted segment;

[0025] ;

[0026] in, represents the second relative characteristic value of the i2-th segment; represents the standard value of the standard segment corresponding to the i2th intercepted segment; represents the parameter value at the j2th historical moment in the i2th interception segment; represents the number of historical moments existing in the i2th interception segment; A1 represents the judgment function; Indicates the transition condition based on the conversion , corresponding mode label , labels of neighbor relations The fine-tuning function of Indicates that the i2th interception segment satisfies The number of moments; Indicates that the i2th interception segment satisfies The number of moments; Indicates the transition condition based on the conversion The number of transition moments; Indicates the corresponding mode label , labels of neighbor relations The setting constant.

[0027] Preferably, the feature extraction module further includes:

[0028] A retrieving unit, used to retrieve a second operating condition analysis model consistent with a set mode at a corresponding historical moment from a mode-model database;

[0029] The model analysis unit is used to input the individual operating condition set at the corresponding historical moment into the second operating condition analysis model to obtain the second extracted features.

[0030] Preferably, the mapping processing module includes:

[0031] A coordinate mapping unit, for mapping all first extracted features into a corresponding mode coordinate system according to a set mode corresponding to a historical moment;

[0032] The feature acquisition unit is used to obtain comprehensive extraction features based on the mapping results.

[0033] Preferably, the mapping processing module further includes:

[0034] A feature fusion unit, used for fusing the comprehensive extracted feature with the corresponding second extracted feature to obtain a fused feature;

[0035] A feature matching unit, used to obtain the standard operating condition of the internal combustion engine in the set mode, and match the standard feature from the condition-feature comparison table;

[0036] A feature registration unit, used to register the standard feature with the comprehensive extraction feature, the second extraction feature, and the fusion feature, respectively, to obtain the corresponding first difference feature, the second difference feature, and the third difference feature;

[0037] a feature analysis unit, configured to determine a high difference feature based on the first difference feature, the second difference feature, and the third difference feature;

[0038] The re-matching unit is used to obtain the factor to be optimized that matches the high-difference feature from the feature-factor comparison table, and at the same time, obtain the attribute to be optimized that matches the factor to be optimized from the factor-operating condition-attribute comparison table.

[0039] Preferably, the strategy generation module includes:

[0040] A matrix construction unit is used to construct a vector to be optimized based on the factors to be optimized and the attributes to be optimized at each historical moment, and to construct a matrix to be optimized according to the order of the historical moments;

[0041] A maintenance analysis unit, used for acquiring each column vector in the matrix to be optimized and inputting it into a single optimization model matching the corresponding factor to be optimized, so as to obtain comprehensive maintenance information of the corresponding factor to be optimized;

[0042] The weight allocation unit is used to solve the optimal vector group of the matrix to be optimized, and allocate a maintenance weight to each comprehensive maintenance information to generate a power management strategy.

[0043] Preferably, the management and early warning module includes:

[0044] A comparison and analysis unit, used for comparing and analyzing the current power situation with the expected power situation at the current moment;

[0045] A management unit, used to determine the operating condition parameters to be managed and the management level in the comparative analysis results based on the power management strategy;

[0046] The output unit is used to generate an early warning report output according to the operating condition parameters to be managed and the management level.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0049] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0051] Figure 1 This is a structural diagram of a power management system based on internal combustion engine operating condition data analysis in an embodiment of the present invention;

[0052] Figure 2 FIG. 4 is a diagram showing the configuration of saliency display in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0054] The present invention provides a power management system based on internal combustion engine operating condition data analysis, such as Figure 1 As shown, including:

[0055] A feature extraction module is used to split the internal combustion engine operating condition data according to the operating condition parameters and perform a first feature extraction on each split data set, and at the same time, perform a second feature extraction on a separate operating condition set with different operating condition parameters at the same historical moment;

[0056] A mapping processing module, used for mapping all the first extracted features, and determining the factors to be optimized corresponding to the second extracted features and the properties to be optimized of the factors to be optimized in combination with the standard operating conditions of the internal combustion engine;

[0057] A strategy generation module, used to generate a power management strategy of the internal combustion engine according to the factors to be optimized and the attributes to be optimized at each historical moment;

[0058] A management and warning module is used to manage and warn the current power situation of the internal combustion engine based on the power management strategy.

[0059] In this embodiment, the internal combustion engine operating condition data includes but is not limited to the internal combustion engine's speed, torque, power, fuel consumption point, air consumption, ignition advance angle, fuel supply advance angle, etc., and the relevant data at different historical moments are obtained.

[0060] In this embodiment, the rotation speed can be achieved by using a magnetoelectric sensor, a Hall sensor, etc., and the torque measurement can be achieved by using a flange torque sensor, etc., that is, the relevant working condition data involved can be measured by corresponding equipment.

[0061] In this embodiment, data splitting is to split the internal combustion engine operating condition data according to parameter type, retaining the speed type and torque type, so as to obtain a split data set under each parameter type, and the data set contains measurement values ​​of the same parameter type at different historical moments.

[0062] In this embodiment, the first feature extraction is to determine how the data under the parameter type changes.

[0063] In this embodiment, the separate operating condition set at the same historical moment refers to a numerical combination of different parameter types at the same historical moment, and the second feature extraction is to determine the operating condition of the internal combustion engine at that moment.

[0064] In this embodiment, the mapping process is to map the first extracted features to obtain a result including all parameters, so as to facilitate subsequent comparative analysis with the second extracted features.

[0065] In this embodiment, the standard operating conditions are set in advance, such as the operating standards of the speed, torque, power, etc. corresponding to the operating conditions of the internal combustion engine.

[0066] In this embodiment, the factor to be optimized refers to a value that needs to be adjusted and improved on the internal combustion engine, and the attribute to be optimized refers to a direction in which the internal combustion engine is to be improved.

[0067] In this embodiment, the power management strategy is generated based on the comprehensive generation of factors and attributes, and serves as a logical judgment basis for the subsequent analysis of the internal combustion engine, thereby achieving the management and early warning of the power of the internal combustion engine.

[0068] It should be noted that management is to promptly identify any abnormal operating conditions of the internal combustion engine and to further optimize the power management strategy, and early warning is to promptly handle abnormalities of the internal combustion engine and improve operating efficiency.

[0069] The beneficial effects of the above technical solution are: obtaining operating data at historical moments to extract features from a single historical moment and a single parameter to ensure the reliability of the analysis basis, and subsequently obtaining optimization factors and attributes through feature mapping to generate management strategies, so as to facilitate timely power management and early warning of current operating conditions, ensure timely resolution of internal combustion engine abnormalities, and improve its work efficiency.

[0070] The present invention provides a power management system based on internal combustion engine operating condition data analysis, wherein the feature extraction module comprises:

[0071] A curve drawing unit, used to respectively obtain the setting mode of the internal combustion engine at each historical moment, obtain a standard data set based on each operating condition parameter, and draw a corresponding standard parameter curve, and at the same time, draw a curve for the corresponding split data set to obtain a historical actual parameter curve;

[0072] An alignment processing unit, used to align the standard parameter curve and the historical actual parameter curve under the same working condition parameters at the same time, and display the alignment processing curve prominently at the corresponding time point based on the mode label of the set mode;

[0073] A first determination unit is used for screening the relatively stable segments of the corresponding historical actual parameters based on the standard parameter curve if the significance display result is one, and determining a first relative characteristic quantity based on each relatively stable segment;

[0074] ;

[0075] in, Represents the first relative characteristic quantity of the i1th relatively stable segment; It represents the standard setting range of the i1th relatively stable segment; represents the parameter value at the j1th historical moment in the i1th relatively stable segment; represents the total number of historical moments that appear in the i1th relatively stable segment; Indicates the characteristic setting coefficient of the i1th relatively stable segment matching the corresponding setting mode; To set a constant; Indicates that based on all The variance of

[0076] ;

[0077] in, Indicates the working mode-coefficient comparison table; Indicates that from the working mode-coefficient comparison table Obtain the characteristic setting coefficients matching the i1th relatively stable segment and the corresponding setting mode ;

[0078] A second determination unit is used for, if there are multiple significant display results, intercepting the historical actual parameter curve according to the continuous appearance time of each mode label to obtain an intercepted segment, and relying on the standard segment under the corresponding mode label and the conversion transition condition under the label that is adjacent to the corresponding mode label, performing a smooth measurement on the intercepted segment to obtain a second relative feature value;

[0079] The sequence sorting unit is used to sort the corresponding relative feature quantities according to the sequence of appearance of the pattern labels, construct an analysis vector, and input it into the first operating condition analysis model corresponding to the corresponding operating condition parameters to obtain the first extracted feature of the corresponding split data set.

[0080] Preferably, the second determining unit includes:

[0081] A fine-tuning function determination subunit, used for constructing a fine-tuning function for the intercepted segment;

[0082] ;

[0083] A calculation subunit, used for calculating a second relative characteristic quantity for the intercepted segment;

[0084] ;

[0085] in, represents the second relative characteristic value of the i2-th segment; represents the standard value of the standard segment corresponding to the i2th intercepted segment; represents the parameter value at the j2th historical moment in the i2th interception segment; represents the number of historical moments existing in the i2th interception segment; A1 represents the judgment function; Indicates the transition condition based on the conversion , corresponding mode label , labels of neighbor relations The fine-tuning function of Indicates that the i2th interception segment satisfies The number of moments; Indicates that the i2th interception segment satisfies The number of moments; Indicates the transition condition based on the conversion The number of transition moments; Indicates the corresponding mode label , labels of neighbor relations The setting constant.

[0086] In this embodiment, the setting mode refers to the working mode of the internal combustion engine. Different working modes correspond to different rotation speeds, such as a stable operation mode, an acceleration operation mode, a deceleration operation mode, and the like.

[0087] In this embodiment, the standard data set refers to the standard value of the same operating parameter in different setting modes.

[0088] In this embodiment, the horizontal axis of the standard parameter curve is different historical moments, and the vertical axis is the standard value of the corresponding operating condition parameter at the corresponding historical moment.

[0089] In this embodiment, the horizontal coordinate of the historical actual parameter curve is different historical moments, and the vertical coordinate is the measured value of the corresponding operating condition parameter at the corresponding historical moment.

[0090] In this embodiment, the significant display refers to the part where the historical actual parameters after alignment processing change abnormally based on the standard parameter curve, such as Figure 2 As shown, the standard parameter curve is E1, and the historical actual parameter curve is E2, wherein the segment from b2 to b3 in E2 is too deviated from E1. At this time, a mode label is set at b2 and a significant display is performed, wherein the significant display is implemented by color marking.

[0091] In this embodiment, a relatively stable segment refers to a situation where the difference between the standard parameter curve and the historical actual parameter curve at each moment in a certain historical moment is within a certain fixed range, such as within the fixed range of a1 to a2. At this time, it is considered to be relatively stable, where a1 and a2 are variables.

[0092] In this embodiment, the operating mode-coefficient comparison table includes different setting modes and characteristic setting coefficients based on the setting modes, which are pre-set and can be used directly.

[0093] In this embodiment, the order in which the mode tags appear is determined according to the order of historical moments.

[0094] In this embodiment, analysis vector={relative feature quantities that appear successively}.

[0095] In this embodiment, the first operating condition analysis model is obtained from a parameter database, which contains the same parameters under several different setting mode combinations and the internal combustion engine operation analysis results under the mode combinations as samples. The first operating condition analysis model is obtained by training the neural network model, and then the first extracted features for the split data set can be directly obtained.

[0096] In this embodiment, the transition conversion conditions are pre-set because the internal combustion engine will have a certain conversion process during the mode switching process. The information involved in the process is the transition conversion condition, such as the stable increase in speed, the stable decrease in speed, etc.

[0097] In this embodiment, the value range of the fine-tuning function is 0 to 0.2.

[0098] The beneficial effect of the above technical solution is: by drawing the standard parameter curve and the historical actual parameter curve for the same parameter to set the label for significance processing, it is convenient for subsequent reasonable analysis of the actual operation situation, and further by classifying and discussing the number of significance display results to further determine the mutual construction analysis vector of the feature quantity, to ensure the accuracy and reliability of the acquisition of the first extracted feature, and to lay a solid foundation for improving the construction strategy.

[0099] The present invention provides a power management system based on internal combustion engine operating condition data analysis, wherein the feature extraction module further includes:

[0100] A retrieving unit, used to retrieve a second operating condition analysis model consistent with a set mode at a corresponding historical moment from a mode-model database;

[0101] The model analysis unit is used to input the individual operating condition set at the corresponding historical moment into the second operating condition analysis model to obtain the second extracted features.

[0102] In this embodiment, the mode-model database includes the second operating condition analysis models corresponding to different modes, and the second operating condition analysis models are obtained by training the neural network model based on the operating condition parameters under different modes and the operation analysis results of the internal combustion engine under the mode as samples.

[0103] In this embodiment, the second extracted feature refers to the operation condition of the corresponding internal combustion engine in the corresponding mode.

[0104] The beneficial effect of the above technical solution is: the model related to the mode is retrieved from the database, which facilitates the analysis of the individual working condition set to obtain the second extracted features, and provides convenience for the subsequent acquisition of factors and attributes.

[0105] The present invention provides a power management system based on internal combustion engine operating condition data analysis, wherein the mapping processing module comprises:

[0106] A coordinate mapping unit, for mapping all first extracted features into a corresponding mode coordinate system according to a set mode corresponding to a historical moment;

[0107] The feature acquisition unit is used to obtain comprehensive extraction features based on the mapping results.

[0108] In this embodiment, the mode coordinate system is obtained from the mode-coordinate system comparison table, and the corresponding mode coordinate systems are different under different setting modes, mainly because the conversion standards between modes and features are different. Therefore, all the first extracted features obtained are mapped to the mode coordinate systems under different setting modes respectively to analyze the fit between the feature and the corresponding setting mode to obtain the comprehensive extraction features under the corresponding mode.

[0109] In this embodiment, features matching the mapping results are obtained from a result-feature comparison table, and the comparison table includes mapping results in different modes and features matching the results, and can be directly obtained.

[0110] The beneficial effect of the above technical solution is that by mapping the first extracted features into different pattern coordinate systems, it is convenient to directly obtain the comprehensive extracted features.

[0111] The present invention provides a power management system based on internal combustion engine operating condition data analysis, wherein the mapping processing module further includes:

[0112] A feature fusion unit, used for fusing the comprehensive extracted feature with the corresponding second extracted feature to obtain a fused feature;

[0113] A feature matching unit, used to obtain the standard operating condition of the internal combustion engine in the set mode, and match the standard feature from the condition-feature comparison table;

[0114] A feature registration unit, used to register the standard feature with the comprehensive extraction feature, the second extraction feature, and the fusion feature, respectively, to obtain the corresponding first difference feature, the second difference feature, and the third difference feature;

[0115] a feature analysis unit, configured to determine a high difference feature based on the first difference feature, the second difference feature, and the third difference feature;

[0116] The re-matching unit is used to obtain the factor to be optimized that matches the high-difference feature from the feature-factor comparison table, and at the same time, obtain the attribute to be optimized that matches the factor to be optimized from the factor-operating condition-attribute comparison table.

[0117] In this embodiment, the comprehensive extracted features exist at every historical moment, so they are fused with the second extracted features at the corresponding historical moment to obtain fused features, and the fused features are implemented based on a feature fusion model, which is obtained by training a neural network model with different feature combinations and fusion results based on the combinations as samples, thereby directly obtaining fused features.

[0118] In this embodiment, the standard operating conditions are pre-set, and the standard values ​​of various parameters in different setting modes are known.

[0119] In this embodiment, the condition-feature comparison table includes different standard operating conditions and standard features matching the conditions, and is pre-planned.

[0120] In this embodiment, the first difference feature is the difference between the standard feature and the comprehensive extraction feature;

[0121] The second difference feature is the difference between the standard feature and the second extracted feature;

[0122] The third difference feature is the difference between the standard feature and the fusion feature.

[0123] In this embodiment, the high difference feature refers to the feature obtained by performing intersection processing on the first difference feature, the second difference feature, and the third difference feature.

[0124] For example, the first difference feature is: feature 1, feature 2, the second difference feature is: feature 1, feature 3, and the third difference feature is: feature 1, feature 4. At this time, the feature after intersection processing is feature 1, and is regarded as a high-difference feature.

[0125] In this embodiment, the feature-factor comparison table contains different difference features and the factors to be optimized that match the features, that is, the parameter factor information adjusted for the internal combustion engine, which can be a numerical value containing a unit symbol. It should be noted that the purpose of including the unit symbol is to determine the parameter type to be adjusted.

[0126] In this embodiment, the factor-operating condition-attribute comparison table includes different factors to be optimized, setting modes (operating conditions) and matching attributes to be optimized, wherein the attribute to be optimized refers to the adjustment direction, which matches the parameter type. For example, supercharging technology is used to increase the air density of the intake pipe to ensure the working efficiency of the internal combustion engine.

[0127] The beneficial effect of the above technical solution is: by comparing the standard features with the features in three cases, the integrity of the subsequent analysis is guaranteed, and then by extracting high-difference features through comparative analysis of the three differences, factors and attributes are obtained to ensure the reasonable repair of the differences.

[0128] The present invention provides a power management system based on internal combustion engine operating condition data analysis, wherein the strategy generation module comprises:

[0129] A matrix construction unit is used to construct a vector to be optimized based on the factors to be optimized and the attributes to be optimized at each historical moment, and to construct a matrix to be optimized according to the order of the historical moments;

[0130] A maintenance analysis unit, used for acquiring each column vector in the matrix to be optimized and inputting it into a single optimization model matching the corresponding factor to be optimized, so as to obtain comprehensive maintenance information of the corresponding factor to be optimized;

[0131] The weight allocation unit is used to solve the optimal vector group of the matrix to be optimized, and allocate a maintenance weight to each comprehensive maintenance information to generate a power management strategy.

[0132] In this embodiment, the vector to be optimized={all factors to be optimized involved in the corresponding historical moment+attributes to be optimized}.

[0133] , where the behavior is all factors and attributes to be optimized at the same historical moment, and each column in the matrix contains blank information of all factors. It can be obtained by replacing the blank information with the relevant element information in the vector to be optimized.

[0134] In this embodiment, each column of the matrix represents the same factor to be optimized and attribute variable to be optimized at different historical moments, and the specific values ​​involved may be different.

[0135] In this embodiment, a single optimization model is obtained by training a neural network model based on various possible optimization reasons under different optimization factors and maintenance information as samples. For example, the sample is: factor to be optimized 1--set maintenance information 01, etc.

[0136] In this embodiment, the optimal vector group is obtained by calculating AX=0 for the optimization matrix, which belongs to the prior art. Then, the corresponding weight can be set according to the necessity of existence of each factor in the vector group, and the sum of the weights of all factors is 1.

[0137] In this embodiment, the power management strategy is composed of comprehensive maintenance information of all corresponding factors to be optimized and maintenance weights of the corresponding factors to be optimized.

[0138] The beneficial effect of the above technical solution is: by constructing the matrix to be optimized and then analyzing each column in the matrix to obtain the comprehensive maintenance information under the corresponding factors, and combining the optimal vector group obtained by solving the matrix, it is convenient to generate the power management strategy, which provides a basis for subsequent analysis and early warning.

[0139] The present invention provides a power management system based on internal combustion engine operating condition data analysis, wherein the management and early warning module comprises:

[0140] A comparison and analysis unit, used for comparing and analyzing the current power situation with the expected power situation at the current moment;

[0141] A management unit, used to determine the operating condition parameters to be managed and the management level in the comparative analysis results based on the power management strategy;

[0142] The output unit is used to generate an early warning report output according to the operating condition parameters to be managed and the management level.

[0143] In this embodiment, the expected power condition refers to the standard power condition of the setting mode at the current moment, which is preset.

[0144] In this embodiment, by comparing and analyzing the actual current power situation with the expected power situation, the existing operating parameters to be managed (certain parameters such as torque and speed) can be directly determined. The management level refers to the corresponding difference between the actual and expected situations, and the comprehensive maintenance information and comprehensive maintenance level based on the difference are determined based on the power management strategy to generate a report.

[0145] Among them, the comprehensive maintenance level is achieved based on the difference situation, and the management level of the corresponding parameter = the difference of the corresponding parameter × maintenance weight.

[0146] The early warning includes different operating condition parameters to be managed and the matching management levels, as well as maintenance suggestions based on the information of both.

[0147] The beneficial effect of the above technical solution is: analyzing the power situation based on the power management strategy not only realizes power management but also facilitates the generation of early warning output.

[0148] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A power management system based on internal combustion engine operating condition data analysis, characterized in that: include: A feature extraction module is used to split the internal combustion engine operating condition data according to the operating condition parameters and perform a first feature extraction on each split data set, and at the same time, perform a second feature extraction on a separate operating condition set with different operating condition parameters at the same historical moment, wherein the internal combustion engine operating condition data is data at different historical moments, and each split data set contains measurement values ​​at different historical moments under the same operating condition parameters; a mapping processing module, used for mapping all the first features, and determining the factors to be optimized corresponding to the second features and the attributes to be optimized of the factors to be optimized in combination with the standard operating conditions of the internal combustion engine, wherein the factors to be optimized refer to the values ​​that need to be adjusted and improved for the internal combustion engine, and the attributes to be optimized refer to the directions for improving the internal combustion engine; A strategy generation module, used to generate a power management strategy of the internal combustion engine according to the factors to be optimized and the attributes to be optimized at each historical moment; A management and warning module, used for managing and warning the current power situation of the internal combustion engine based on the power management strategy; Wherein, the mapping processing module includes: A coordinate mapping unit, for mapping all first features into a corresponding mode coordinate system according to a set mode corresponding to a historical moment; A feature acquisition unit, used for obtaining comprehensive extraction features based on the mapping results; Wherein, the mapping processing module further includes: A feature fusion unit, used for fusing the comprehensive extracted feature with the corresponding second feature to obtain a fused feature; A feature matching unit, used to obtain the standard operating condition of the internal combustion engine in the set mode, and match the standard feature from the condition-feature comparison table; A feature registration unit, used to register the standard feature with the comprehensive extraction feature, the second feature, and the fusion feature, respectively, to obtain the corresponding first difference feature, the second difference feature, and the third difference feature; a feature analysis unit, configured to determine a high difference feature based on the first difference feature, the second difference feature, and the third difference feature; The re-matching unit is used to obtain the factor to be optimized that matches the high-difference feature from the feature-factor comparison table, and at the same time, obtain the attribute to be optimized that matches the factor to be optimized from the factor-operating condition-attribute comparison table.

2. The power management system based on internal combustion engine operating condition data analysis according to claim 1, characterized in that: The feature extraction module comprises: A curve drawing unit, used to respectively obtain the setting mode of the internal combustion engine at each historical moment, obtain a standard data set based on each operating condition parameter, and draw a corresponding standard parameter curve, and at the same time, draw a curve for the corresponding split data set to obtain a historical actual parameter curve; An alignment processing unit, used to align the standard parameter curve and the historical actual parameter curve under the same working condition parameters at the same time, and display the alignment processing curve prominently at the corresponding time point based on the mode label of the set mode; A first determination unit is used for screening the relatively stable segments of the corresponding historical actual parameters based on the standard parameter curve if the significance display result is one, and determining a first relative characteristic quantity based on each relatively stable segment; ; in, Represents the first relative characteristic quantity of the i1th relatively stable segment; It represents the standard setting range of the i1th relatively stable segment; represents the parameter value at the j1th historical moment in the i1th relatively stable segment; represents the total number of historical moments that appear in the i1th relatively stable segment; Indicates the characteristic setting coefficient of the i1th relatively stable segment matching the corresponding setting mode; To set a constant; Indicates that based on all The variance of ; in, Indicates the working mode-coefficient comparison table; Indicates that from the working mode-coefficient comparison table Obtain the characteristic setting coefficient matching the i1th relatively stable segment with the corresponding setting mode ; A second determination unit is used for, if there are multiple significant display results, intercepting the historical actual parameter curve according to the continuous appearance time of each mode label to obtain an intercepted segment, and relying on the standard segment under the corresponding mode label and the conversion transition condition under the label that is adjacent to the corresponding mode label, performing a smooth measurement on the intercepted segment to obtain a second relative feature value; The sequence sorting unit is used to sort the corresponding relative feature quantities according to the sequence of appearance of the pattern labels, construct an analysis vector, and input it into the first operating condition analysis model corresponding to the corresponding operating condition parameters to obtain the first feature of the corresponding split data set.

3. The power management system based on internal combustion engine operating condition data analysis according to claim 2, characterized in that: The second determining unit includes: A fine-tuning function determination subunit, used for constructing a fine-tuning function for the intercepted segment; ; A calculation subunit, used for calculating a second relative characteristic quantity for the intercepted segment; ; in, represents the second relative characteristic value of the i2-th segment; represents the standard value of the standard segment corresponding to the i2th intercepted segment; represents the parameter value at the j2th historical moment in the i2th interception segment; represents the number of historical moments existing in the i2th interception segment; A1 represents the judgment function; Indicates the transition condition based on the conversion , corresponding mode label , labels of neighbor relations The fine-tuning function of Indicates that the i2th interception segment satisfies The number of moments; Indicates that the i2th interception segment satisfies The number of moments; Indicates the transition condition based on the conversion The number of transition moments; Indicates the corresponding mode label , labels of neighbor relations The setting constant.

4. The power management system based on internal combustion engine operating condition data analysis according to claim 2, characterized in that: The feature extraction module further includes: A retrieving unit, used to retrieve a second operating condition analysis model consistent with a set mode at a corresponding historical moment from a mode-model database; The model analysis unit is used to input the individual operating condition set at the corresponding historical moment into the second operating condition analysis model to obtain the second feature.

5. The power management system based on internal combustion engine operating condition data analysis according to claim 1, characterized in that: The strategy generation module comprises: A matrix construction unit is used to construct a vector to be optimized based on the factors to be optimized and the attributes to be optimized at each historical moment, and to construct a matrix to be optimized according to the order of the historical moments; A maintenance analysis unit, used for acquiring each column vector in the matrix to be optimized and inputting it into a single optimization model matching the corresponding factor to be optimized, so as to obtain comprehensive maintenance information of the corresponding factor to be optimized; The weight allocation unit is used to solve the optimal vector group of the matrix to be optimized, and allocate a maintenance weight to each comprehensive maintenance information to generate a power management strategy.

6. The power management system based on internal combustion engine operating condition data analysis according to claim 1, characterized in that: The management and early warning module includes: A comparison and analysis unit, used for comparing and analyzing the current power situation with the expected power situation at the current moment; A management unit, used to determine the operating condition parameters to be managed and the management level in the comparative analysis results based on the power management strategy; The output unit is used to generate an early warning report output according to the operating condition parameters to be managed and the management level.

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