Ammonia storage correction method and system based on kalman filtering

Abstract

The present disclosure provides a Kalman filter-based ammonia storage correction method and system, which comprises: obtaining relevant state quantities of a diesel engine aftertreatment system at a previous time; obtaining an ammonia storage change rate state equation based on a reaction kinetics equation and an ammonia storage conservation calculation equation involved in an SCR model; constructing an observation equation of a NOx sensor downstream of the SCR system based on a concentration state prediction equation of NOx and ammonia and a calculation formula of a model value of the NOx sensor downstream of the SCR system; discretizing and linearizing the ammonia storage change rate state equation and the observation equation of the NOx sensor downstream of the SCR system, respectively, and obtaining a state quantity expression corrected based on Kalman filtering based on the linearization result; and obtaining a corrected ammonia storage value at the current time by inputting the relevant state quantities at the previous time into the state quantity expression.

Description

TECHNICAL FIELD

[0001] The present disclosure belongs to the technical field of engine aftertreatment, and particularly relates to an ammonia storage correction method and system based on Kalman filtering. BACKGROUND

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] Selective catalytic reduction (SCR) systems are widely used in the emission systems of diesel engines to treat the exhaust gas of such engines. By improving the conversion efficiency of the SCR system, it is beneficial to meet the demand for higher conversion efficiency and to improve the NOx level of the engine to reduce fuel consumption.

[0004] In order to improve the control accuracy of the SCR system, model-based SCR control becomes a necessary means. However, the inventors have found that in actual environment, the operation of the SCR model is affected by factors such as sensor accuracy and injection system accuracy, which can cause the calculation results of the SCR model to deviate. At the same time, due to the cross-sensitivity of the NOx sensor, it is not easy to distinguish whether the leakage is NOx or NH3. However, the determination of the closed-loop control direction requires the advance judgment of NH3 leakage. The current main judgment method is to judge according to special working conditions (for example: reverse drag or sharp temperature change, etc.), which cannot achieve real-time judgment and affects the closed-loop control effect. SUMMARY

[0005] The present disclosure provides an ammonia storage correction method and system based on Kalman filtering to solve the above problems. The scheme provides an ammonia storage correction method and system based on Kalman filtering. The scheme designs an ammonia storage recursive equation based on an SCR model, simplifies the observation model of NOx value, and at the same time, calibrates the ammonia storage value of the SCR model through nonlinear Kalman filtering, effectively guarantees the injection control accuracy and emission consistency, and improves the control robustness.

[0006] According to a first aspect of an embodiment of the present disclosure, there is provided an ammonia storage correction method based on Kalman filtering, comprising:

[0007] Obtaining relevant state quantities at a previous time of a diesel engine aftertreatment system; wherein the state quantities include ammonia storage value, state equation error value and observation equation error value;

[0008] Based on the reaction kinetics equation and the ammonia storage conservation calculation equation involved in the SCR model, an ammonia storage change rate state equation is obtained; based on the concentration state prediction equation of NOx and ammonia and the NOx sensor model value calculation formula downstream of the SCR system, an observation equation of the NOx sensor downstream of the SCR system is constructed;

[0009] The ammonia storage rate of change state equation and the observation equation of the NOx sensor downstream of the SCR system are discretized and linearized respectively, and based on the linearization results, a state quantity expression after Kalman filter correction is obtained;

[0010] The relevant state quantity at the previous time is brought into the state quantity expression to obtain the corrected ammonia storage value at the current time.

[0011] Further, the ammonia storage conservation calculation equation is obtained based on the reaction kinetics equation involved in the SCR model by applying mass conservation to the adsorption reaction.

[0012] Further, the NOx and ammonia concentration state prediction equation is obtained based on the mass conservation of the substance concentration, and the SCR system downstream NOx sensor model value calculation formula is specifically represented as:

[0013]

[0014] Wherein, C NO is the concentration of nitrogen monoxide, is the concentration of nitrogen dioxide, is the concentration of ammonia, α is the cross-sensitivity coefficient of the NOx sensor for NH2 measurement, β is the cross-sensitivity coefficient of the NOx sensor for NH3 measurement, P is the gas pressure, R is the universal gas constant, and T is the gas temperature.

[0015] Further, the ammonia storage rate of change state equation is discretized and linearized, specifically: the ammonia storage rate of change state equation is discretized and a recursive equation is established, based on the recursive equation, the reaction kinetics equation involved in the SCR model and the ammonia storage conservation calculation equation, an ammonia storage state prediction equation is obtained, and the ammonia storage state prediction equation is linearized.

[0016] Further, the observation equation of the NOx sensor downstream of the SCR system is discretized and linearized, specifically: taking the change of gas concentration with time as 0 as a premise, based on the simplified equation of the NOx and ammonia concentration state prediction equation, an SCR downstream NOx sensor model concentration expression is obtained, and the SCR downstream NOx sensor model concentration expression is linearized.

[0017] Further, the state quantity expression after Kalman filter correction is obtained based on the linearization results, specifically:

[0018]

[0019] Wherein, θ k|k is the ammonia storage value after Kalman correction at the current time; θ k|k-1is a state quantity of a current moment estimated according to a state quantity of a previous moment, k k is a Kalman gain calculated, NOx snr is a real SCR downstream NOx sensor measurement value, is a SCR downstream NOx sensor model value.

[0020] Further, the reaction kinetics equation involved in the SCR model includes an adsorption reaction kinetics equation, a desorption reaction kinetics equation, a fast reaction kinetics equation, a NOx standard reaction kinetics equation, a slow reaction kinetics equation, and an oxidation reaction kinetics equation.

[0021] According to a second aspect of the embodiments of the present disclosure, an ammonia storage correction system based on Kalman filtering is provided, and the system includes:

[0022] a data acquisition unit configured to acquire relevant state quantities of a previous moment of a diesel engine aftertreatment system;

[0023] a Kalman filtering processing unit configured to obtain an ammonia storage change rate state equation based on a reaction kinetics equation involved in the SCR model and an ammonia storage conservation equation, and to construct an observation equation of a SCR system downstream NOx sensor based on a NOx and ammonia concentration state prediction equation and a SCR system downstream NOx sensor model value calculation formula; the ammonia storage change rate state equation and the observation equation of the SCR system downstream NOx sensor are respectively discretized and linearized, and based on a linearization processing result, a state quantity expression after Kalman filtering correction is obtained;

[0024] a state quantity correction unit configured to input the relevant state quantities of the previous moment into the state quantity expression to obtain an ammonia storage value after correction of a current moment.

[0025] According to a third aspect of the embodiments of the present disclosure, an electronic device is provided, which includes a memory, a processor, and a computer program stored on the memory and running on the memory, and the processor implements the ammonia storage correction method based on Kalman filtering when executing the program.

[0026] According to a fourth aspect of the embodiments of the present disclosure, a non-transitory computer readable storage medium is provided, which stores a computer program, and the program is executed by a processor to implement the ammonia storage correction method based on Kalman filtering.

[0027] Compared with the prior art, the present disclosure has the following beneficial effects:

[0028] The present disclosure provides an ammonia storage correction method and system based on Kalman filtering. The scheme designs the ammonia storage recursive equation based on the SCR model, which simplifies the NOx value observation model. At the same time, the ammonia storage value of the SCR model is calibrated by nonlinear Kalman filtering, which effectively ensures the injection control accuracy and emission consistency and improves the control robustness.

[0029] Advantages of this disclosure in additional aspects will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0030] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0031] Figure 1 This is a flowchart of the ammonia storage correction method based on Kalman filtering as described in the embodiments of this disclosure;

[0032] Figure 2 This is a schematic diagram of the control logic of an existing model-based SCR system as described in the embodiments of this disclosure;

[0033] Figure 3 This is a schematic diagram of the overall structure of the SCR system described in the embodiments of this disclosure;

[0034] The components include: 1. Selective catalytic reduction system; 2. First nitrogen oxide sensor; 3. Urea nozzle; 4. Second nitrogen oxide sensor; 5. Temperature sensor; and 6. Mixer. Detailed Implementation

[0035] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0036] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0037] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0038] Where there is no conflict, the embodiments and features described herein can be combined with each other.

[0039] Terminology Explanation:

[0040] SCR system: Selective Catalytic Reduction system. This system can reduce NOx in diesel vehicle exhaust to N2 and H2O by injecting a reducing agent such as ammonia or urea under the action of a catalyst.

[0041] SCR model: A mathematical model based on the principles of chemical reaction kinetics, used for urea injection control and diagnosis.

[0042] Example 1:

[0043] The purpose of this embodiment is to provide an ammonia storage correction method based on Kalman filtering.

[0044] like Figure 1 As shown, an ammonia storage correction method based on Kalman filtering includes:

[0045] Obtain the relevant state quantities of the diesel engine aftertreatment system at the previous moment; wherein, the state quantities include ammonia storage value, state equation error value, and observation equation error value;

[0046] Based on the reaction kinetic equations and ammonia storage conservation calculation equations involved in the SCR model, the ammonia storage change rate state equation is obtained; based on the NOx and ammonia concentration state prediction equations and the calculation formula of the NOx sensor model value in the downstream of the SCR system, the observation equation of the NOx sensor in the downstream of the SCR system is constructed.

[0047] The ammonia storage change rate state equation and the observation equation of the downstream NOx sensor of the SCR system are discretized and linearized respectively. Based on the linearization result, the state expression after Kalman filtering correction is obtained.

[0048] Substitute the relevant state variables from the previous time step into the state variable expression to obtain the corrected ammonia storage value at the current time step.

[0049] In specific implementation, the ammonia storage conservation calculation equation is obtained based on the reaction kinetic equations involved in the SCR model, by applying mass conservation to the adsorption reaction. The NOx and ammonia concentration state prediction equations are obtained based on the mass conservation of substance concentration. The specific formula for calculating the NOx sensor model value downstream of the SCR system is as follows:

[0050]

[0051] Among them, C NO The concentration of nitric oxide. The concentration of nitrogen dioxide. denoted as ammonia concentration, α as the cross-sensitivity coefficient of the NOx sensor for NH2 measurement, β as the cross-sensitivity coefficient of the NOx sensor for NH3 measurement, P as gas pressure, R as the universal gas constant, and T as gas temperature.

[0052] In specific implementation, the discretization and linearization of the ammonia storage change rate state equation specifically involves: discretizing the ammonia storage change rate state equation and establishing a recursive equation; based on the recursive equation, the reaction kinetic equation involved in the SCR model, and the ammonia storage conservation calculation equation, obtaining the ammonia storage state prediction equation; and linearizing the parameters of the ammonia storage state prediction equation. The discretization and linearization of the observation equation of the downstream NOx sensor in the SCR system specifically involves: assuming that the gas concentration changes by 0 over time, obtaining the concentration expression of the downstream NOx sensor model based on the simplified equation of the NOx and ammonia concentration state prediction equation; and linearizing the concentration expression of the downstream NOx sensor model.

[0053] In specific implementation, the state expression after Kalman filtering correction is obtained based on the linearization processing result, specifically as follows:

[0054]

[0055] Where, θ k|k θ represents the ammonia storage value at the current moment after Kalman correction; k|k-1 k is the state quantity at the current time that is estimated in advance based on the state quantity at the previous time step. k To calculate the Kalman gain, NOX SNR These are actual NOx sensor measurements downstream of the SCR system. These are the model values ​​for the NOx sensor downstream of the SCR.

[0056] In specific implementation, the reaction kinetic equations involved in the SCR model include adsorption reaction kinetic equations, desorption reaction kinetic equations, fast reaction kinetic equations, NOx standard reaction kinetic equations, slow reaction kinetic equations, and oxidation reaction kinetic equations.

[0057] Specifically, for ease of understanding, the following detailed description of the solution in this embodiment is provided in conjunction with the accompanying drawings from a practical implementation perspective:

[0058] like Figure 2The diagram illustrates the control logic of an existing model-based SCR system. Currently, model-based SCR control uses a set ammonia storage level as the target and the model ammonia storage level as the feedback value for forward feedback control of the injection quantity. Closed-loop control is then implemented using the downstream NOx sensor and model values. Specifically, the existing control mainly consists of the following five modules: SCR pre-control calculates the feedforward NH3 injection quantity NH3_Pre based on upstream NOx emissions, current temperature, model ammonia storage, and set efficiency. Ammonia storage correction calculates the ammonia injection correction quantity NH3_Cor based on the set ammonia storage and model ammonia storage. The SCR model calculates the internal ammonia storage and downstream NOx based on upstream NOx and temperature. The closed-loop controller performs closed-loop PI control based on the downstream NOx in the model SCR and the actual sensor NOx to obtain the injection correction factor Fac_CL. The adaptive function generally uses a fixed time or low SCR efficiency triggering, and obtains the over-injection or under-injection state and the correction factor FacAdap through three processes: injection stop, fixed injection, and efficiency detection.

[0059] like Figure 3 The diagram shows the hardware structure of the SCR system. Before the selective catalytic reduction system 1 are the urea nozzle 3 and the temperature sensor 5. The first nitrogen oxide sensor 2 is located before the selective catalytic reduction system 1, and the second nitrogen oxide sensor 4 is located after the selective catalytic reduction system 1. As shown... Figure 3 As shown, a mixer 6 is also provided before the selective catalytic reduction system 1.

[0060] The following is a derivation of the specific formulas involved in the solution described in this embodiment:

[0061] The reaction kinetic equations involved in the SCR model:

[0062] Adsorption reaction:

[0063] Desorption reaction:

[0064] Rapid response:

[0065] NOx standard reaction:

[0066] Slow reaction:

[0067] Oxidation reaction:

[0068] Where r: reaction rate, mol / (m 3 s), NOx gas reactant concentration, mol / m³ 3 , Ammonia reactant concentration, mol / m 3 k Std : Frequency factor of the standard NOx reaction, 1 / s; k Ads : Frequency factor of adsorption reaction, 1 / s; k Des Frequency factor of desorption reaction, mol / m 3 / s;k Ox : Frequency factor of oxidation reaction, 1 / s; k Fst : Frequency factor of fast reaction, 1 / s; E: Activation energy divided by universal gas constant; T: Temperature; θ: Ammonia coverage of SCR catalyst; ε: Desorption-ammonia storage correlation parameter; θ C NO x The ammonia storage adjustment parameter for the reaction, k Slw This is the slow response frequency factor.

[0069] Ammonia storage conservation calculation:

[0070]

[0071] Where Ω represents the maximum ammonia reserve in mol / m³ 3 ; This represents the actual mass of NH3 in the catalyst. This represents the maximum mass of NH3 that can be stored in the catalyst. V represents the volume of the catalyst, and 17 represents the molar mass of NH3.

[0072] Based on the law of conservation of mass for substance concentration, the state prediction equations for NOx and NH3 are as follows:

[0073]

[0074]

[0075]

[0076] in, The concentration of NH3 at the SCR inlet is in mol / m³. 3 C NO,in NO concentration at SCR inlet, mol / m 3 ; NO2 concentration at SCR inlet, mol / m 3 volFlow represents the volumetric flow rate of exhaust gas, in m³ / s. 3 / s; V is the volume of the SCR catalyst, m 3 OpFrt is the ratio of the flow volume to the total volume of the SCR catalyst.

[0077] For ease of description, let

[0078] SCR downstream NOx sensor model values:

[0079]

[0080] Where P: gas pressure; R: universal gas constant; T: gas temperature; α = 0.8, representing the NOx sensor's response to NO2.

[0081] The measured cross-sensitivity coefficient; β=1, is the cross-sensitivity coefficient of the NOx sensor for NH3 measurement. For the SCR system, the following state equation is established according to formula (7):

[0082]

[0083] in, denoted as the ammonia storage change rate; f(θ) is the reaction rate function related to ammonia storage; w is the process noise of the state equation, which conforms to a Gaussian normal distribution with variance Q.

[0084] Based on formula (11), the observation equation of the NOx sensor downstream of the SCR is established:

[0085] NOx Ds = g(θ) + v (13)

[0086] Among them, NOx Ds θ represents the NOx sensor model value downstream of SCR; g(θ) is the NOx-ammonia storage correlation function, v is the noise of the observation equation, which conforms to a Gaussian normal distribution with variance R;

[0087] For formulas (11) and (13), after discretization, the recursive equations are established as follows:

[0088] θ k =f(θ) k-1 )+w k (14)

[0089]

[0090] According to formulas (1)-(7) and (14): the ammonia storage status is estimated as follows:

[0091]

[0092] Since the state equations are nonlinear, the parameters of the state equations are linearized:

[0093]

[0094] Based on the simplified equations of formulas (8)-(10), assuming that the gas concentration changes by 0 with time, the outlet volume concentrations of NO, NO2, and NH3 are calculated as follows:

[0095]

[0096]

[0097]

[0098] The NOx concentration downstream of the SCR sensor model is calculated according to formula (11):

[0099] Since the NOx concentration observation equation is nonlinear, the parameters of the observation equation are linearized:

[0100]

[0101] in:

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108] k|k-1: The state quantity at the current time, estimated in advance based on the state quantity at the previous time step.

[0109] k-1|k-1: The state variable after Kalman correction at the previous time step.

[0110] k|k: The state variable after Kalman correction at the current moment.

[0111] Specifically, the entire Kalman filtering process includes the following steps:

[0112] Step 1) Calculate the pre-estimated ammonia storage θ using the ammonia storage recursive formula derived from the conservation equation. k|k-1 Specifically, it is expressed as follows:

[0113] θ k|k-1 =f(θ) k-1|k-1 (16)

[0114] Step 2) Use the covariance matrix P from the previous time step k-1|k-1 To calculate θ k|k-1 Estimated covariance P k|k-1 Specifically, it is expressed as follows:

[0115]

[0116] The ammonia storage, state equation error value, and observation equation error value are all stored in the covariance matrix.

[0117] At the same time, for Since the ammonia storage at the current moment is not linearly related to the ammonia storage at the previous moment (i.e., not in a first-order form), θ is expanded by applying the Taylor formula. k =(θ k-1 We obtain its first-order form, linearize the equation, and obtain the updated covariance matrix coefficients.

[0118] Step 3) Based on θ k|k-1 The value is used to calculate the model value of the NOx sensor downstream of the SCR, as shown below:

[0119]

[0120] Step 4) Calculate the Kalman gain k k Specifically, it is expressed as follows:

[0121]

[0122] Step 5) Correct the ammonia storage value according to the Kalman gain to obtain the corrected ammonia storage value, as shown below:

[0123]

[0124] Among them, NOx snr These are actual NOx sensor measurements downstream of the SCR system.

[0125] Step 6) Update the covariance matrix based on the Kalman gain for the calculation of the next time step, as shown below:

[0126]

[0127] Among them, for The calculation, and The calculations are consistent and will not be repeated here.

[0128] By repeating steps 1) to 6), the ammonia storage value can be obtained at different times.

[0129] Example 2:

[0130] The purpose of this embodiment is to provide an ammonia storage correction system based on Kalman filtering.

[0131] A Kalman filter-based ammonia storage correction system includes:

[0132] The data acquisition unit is used to acquire the relevant state quantities of the diesel engine aftertreatment system at the previous moment.

[0133] The Kalman filter processing unit is used to obtain the ammonia storage change rate state equation based on the reaction kinetic equations and ammonia storage conservation calculation equations involved in the SCR model; and to construct the observation equation of the downstream NOx sensor of the SCR system based on the concentration state prediction equations of NOx and ammonia and the calculation formula of the model value of the downstream NOx sensor of the SCR system. The ammonia storage change rate state equation and the observation equation of the downstream NOx sensor of the SCR system are discretized and linearized respectively. Based on the linearization result, the state expression after Kalman filtering correction is obtained.

[0134] The state quantity correction unit is used to input the relevant state quantities from the previous moment into the state quantity expression to obtain the corrected ammonia storage value at the current moment.

[0135] Furthermore, the system described in this embodiment corresponds to the method described in Embodiment 1, and its technical details have been described in detail in Embodiment 1, so they will not be repeated here.

[0136] In further embodiments, the following is also provided:

[0137] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When executed by the processor, the computer instructions perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0138] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0139] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0140] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0141] The method in Embodiment 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0142] Those skilled in the art will recognize that the units, i.e., algorithm steps, of the various examples described in connection with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0143] The ammonia storage correction method and system based on Kalman filtering provided in the above embodiments can be implemented and has broad application prospects.

[0144] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for correcting ammonia storage based on Kalman filtering, characterized in that, include: Obtain the relevant state quantities of the diesel engine aftertreatment system at the previous moment; wherein, the state quantities include ammonia storage value, state equation error value, and observation equation error value; Based on the reaction kinetic equations and ammonia storage conservation calculation equations involved in the SCR model, the ammonia storage change rate state equation is obtained; based on the NOx and ammonia concentration state prediction equations and the calculation formula for the NOx sensor model value downstream of the SCR system, the observation equation for the NOx sensor downstream of the SCR system is constructed; the NOx and ammonia concentration state prediction equations are obtained based on the mass conservation of substance concentration, and the calculation formula for the NOx sensor model value downstream of the SCR system is specifically expressed as follows: in, The concentration of nitric oxide. The concentration of nitrogen dioxide. Let be the concentration of ammonia, α be the cross-sensitivity coefficient of the NOx sensor for NO2 measurement, and β be the cross-sensitivity coefficient of the NOx sensor for NH3 measurement. P For gas pressure, R This is the universal gas constant. T The gas temperature; The ammonia storage rate of change state equation and the observation equation of the downstream NOx sensor of the SCR system are discretized and linearized respectively. Based on the linearization result, the state expression after Kalman filtering correction is obtained. Specifically, the ammonia storage rate of change state equation is discretized and a recursive equation is established. Based on the recursive equation, the reaction kinetic equation involved in the SCR model, and the ammonia storage conservation calculation equation, the ammonia storage state prediction equation is obtained, and the ammonia storage state prediction equation is parameter linearized. The observation equations of the downstream NOx sensor of the SCR system are discretized and linearized respectively. Specifically, the following steps are taken: taking the gas concentration change with time as zero as a premise, the simplified equations of the NOx and ammonia concentration state prediction equations are used to obtain the concentration expression of the downstream NOx sensor of the SCR system, and the concentration expression of the downstream NOx sensor of the SCR system is linearized. The state expression after Kalman filtering correction is obtained based on the linearization result, specifically as follows: in, This is the ammonia storage value at the current moment after Kalman correction; The state quantity at the current time is estimated in advance based on the state quantity at the previous time step. To calculate the Kalman gain, These are actual NOx sensor measurements downstream of the SCR system. The NOx sensor model value is for the downstream of the SCR. Substitute the relevant state variables from the previous time step into the state variable expression to obtain the corrected ammonia storage value at the current time step.

2. The ammonia storage correction method based on Kalman filtering as described in claim 1, characterized in that, The ammonia storage conservation equation is obtained by applying mass conservation to the adsorption reaction based on the reaction kinetic equations involved in the SCR model.

3. The ammonia storage correction method based on Kalman filtering as described in claim 1, characterized in that, The reaction kinetic equations involved in the SCR model include adsorption reaction kinetic equations, desorption reaction kinetic equations, fast reaction kinetic equations, NOx standard reaction kinetic equations, slow reaction kinetic equations, and oxidation reaction kinetic equations.

4. An ammonia storage correction system based on Kalman filtering, characterized in that, The system comprises: (1) Correcting the ammonia storage value of an SCR model using the method described in any one of claims 1-3; The data acquisition unit is used to acquire the relevant state quantities of the diesel engine aftertreatment system at the previous moment. The Kalman filter processing unit is used to obtain the ammonia storage change rate state equation based on the reaction kinetic equations and ammonia storage conservation calculation equations involved in the SCR model; and to construct the observation equation of the downstream NOx sensor of the SCR system based on the concentration state prediction equations of NOx and ammonia and the calculation formula of the model value of the downstream NOx sensor of the SCR system. The ammonia storage change rate state equation and the observation equation of the downstream NOx sensor of the SCR system are discretized and linearized respectively. Based on the linearization result, the state expression after Kalman filtering correction is obtained. The state quantity correction unit is used to input the relevant state quantities from the previous moment into the state quantity expression to obtain the corrected ammonia storage value at the current moment.

5. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and running thereon, characterized in that, When the processor executes the program, it implements an ammonia storage correction method based on Kalman filtering as described in any one of claims 1-3.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements an ammonia storage correction method based on Kalman filtering as described in any one of claims 1-3.

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