Optimization control method and device for SCR target ammonia storage amount and engine controller

Abstract

The present invention relates to the technical field of engine tail gas purification, and provides an optimization control method and device for an SCR target ammonia storage amount and an engine controller. The method comprises: acquiring a control sequence at a current moment, the control sequence being used for controlling an ammonia storage amount of an SCR system; on the basis of the control sequence at the current moment, a preset SCR dynamics model and a corresponding objective function, determining a state variable and a control target of the SCR system in a prediction time domain; on the basis of the state variable and the control target, determining a gradient of the control target to the control sequence at the current moment; and on the basis of the gradient in combination with a gradient descent iteration method and an iteration step size, determining an optimal control sequence of the prediction time domain, and controlling a target ammonia storage amount of the SCR system on the basis of the optimal control sequence. The present invention enables determination of the optimal control sequence of the prediction time domain by means of the gradient descent iteration method, realizes a model-based closed-loop optimization control strategy, and solves the technical problem of improving the SCR ammonia storage control accuracy.

Description

Optimized control methods, devices, and engine controllers for SCR target ammonia storage capacity Technical Field

[0001] This invention relates to the field of engine exhaust gas purification technology, specifically to an optimized control method, device, and engine controller for SCR target ammonia storage capacity. Background Technology

[0002] Currently, to meet the China VI emission standards, the market widely adopts SCR (Selective Catalytic Reduction) ammonia storage control + NO post-processing. X The revised SCR closed-loop control scheme uses PID control to adjust and compensate for the urea injection rate in real time based on the deviation between the set target ammonia storage amount and the actual NH3 storage amount, according to the feedforward NH3 demand, so that the SCR catalyst NH3 storage amount reaches the set target NH3 storage amount. The aforementioned China VI control algorithms all use a MAP-based control strategy for the target ammonia storage amount, requiring extensive experimental calibration. This results in poor transient control performance and the inability to optimize and upgrade the control function based on changes in actual operating conditions. Therefore, the accuracy of SCR ammonia storage control needs improvement. Summary of the Invention

[0003] In view of this, it is necessary to provide an optimized control method, device and engine controller for the target ammonia storage capacity of SCR, so as to solve the problem of improving the ammonia storage control accuracy of SCR.

[0004] To address the aforementioned problems, this invention provides, on the one hand, an optimized control method for the target ammonia storage capacity in SCR, comprising:

[0005] Obtain the control sequence at the current moment; the control sequence is used to control the ammonia storage capacity of the SCR system.

[0006] Based on the control sequence at the current moment, and the preset SCR dynamics model and corresponding objective function, the state variables and control objectives of the SCR system in the prediction time domain are determined.

[0007] Based on the state variables and the control objective, determine the gradient of the control objective with respect to the control sequence at the current moment;

[0008] Based on the gradient and combined with the gradient descent iterative method and iteration step size, the optimal control sequence in the prediction time domain is determined, and the target ammonia storage capacity of the SCR system is controlled based on the optimal control sequence.

[0009] In one possible implementation, the iteration step size is inversely correlated with the number of iterations of the gradient descent iteration method, and the iteration step size remains unchanged when the number of iterations is greater than a preset threshold.

[0010] In one possible implementation, the state variables of the SCR system include: the NOx concentration and NH3 concentration at the SCR system outlet; the SCR kinetic model includes: a NOx kinetic model and an NH3 kinetic model.

[0011] The NOx kinetic model is used to characterize the relationship between the NOx concentration at the outlet of the SCR system at the current moment and the NOx concentration at the outlet of the SCR system at the previous moment.

[0012] The NH3 kinetic model is used to characterize the relationship between the NH3 concentration at the SCR system outlet at the current moment and the NH3 concentration at the SCR system outlet at the previous moment.

[0013] In one possible implementation, the relationship represented by the NOx kinetic model is:

[0014] The NOx concentration at the SCR system outlet at the current moment is determined based on the NOx concentration at the SCR system outlet at the previous moment, as well as the control cycle, space velocity, the NOx concentration at the SCR system inlet at the current moment, the NOx catalytic reduction reaction rate constant, the NOx catalytic reduction reaction activation energy, the SCR catalyst temperature, the ammonia coverage of the SCR system at the previous moment, and the maximum ammonia coverage of the SCR system.

[0015] In one possible implementation, the relationship represented by the NH3 kinetic model is as follows:

[0016] The NH3 concentration at the SCR system outlet at the current moment is determined based on the NH3 concentration at the SCR system outlet at the previous moment, as well as the control cycle, space velocity, urea injection rate at the SCR system inlet at the current moment, ammonia desorption reaction rate constant, ammonia adsorption reaction rate constant, NH3 desorption reaction activation energy, ammonia coverage of the SCR system at the previous moment, NH3 desorption reaction characteristic parameters, maximum ammonia coverage of the SCR system, and SCR catalyst temperature.

[0017] In one possible implementation, the objective function is determined based on the NOx concentration at the SCR system outlet, the NH3 leakage, and the rate of change of the control sequence during the control period.

[0018] In one possible implementation, the objective function aims to minimize the weighted sum of the NOx concentration at the SCR system outlet, the NH3 leakage, and the rate of change of the control sequence within the control period.

[0019] On the other hand, the present invention also provides an optimized control device for SCR target ammonia storage capacity, comprising:

[0020] The acquisition module is used to acquire the control sequence at the current moment; the control sequence is used to control the ammonia storage capacity of the SCR system.

[0021] The prediction module is used to determine the state variables and control objectives of the SCR system in the prediction time domain based on the control sequence at the current moment, the preset SCR dynamics model and the corresponding objective function.

[0022] The gradient calculation module is used to determine the gradient of the cost with respect to the control sequence at the current time based on the state variables and the cost.

[0023] The control module is used to determine the optimal control sequence in the prediction time domain based on the gradient and in combination with the gradient descent iterative method and the iteration step size, and to control the target ammonia storage capacity of the SCR system based on the optimal control sequence.

[0024] On the other hand, the present invention also provides an engine controller, including a memory and a processor, wherein,

[0025] The memory is used to store programs;

[0026] The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps of the optimized control method for the target ammonia storage capacity of SCR as described in any of the above.

[0027] On the other hand, the present invention also provides an automobile including the above-described engine controller.

[0028] The beneficial effects of the above implementation are as follows: The optimization control method, device, and engine controller for the target ammonia storage capacity of SCR provided by this invention determine the state variables and control objectives of the SCR system in the prediction time domain by using the control sequence of the SCR system at the current moment, and the preset SCR dynamics model and corresponding objective function. Based on the state variables and the control objectives, the gradient of the control objectives with respect to the control sequence at the current moment is determined. Based on the gradient and combined with the gradient descent iteration method and iteration step size, the optimal control sequence in the prediction time domain is determined, realizing a model-based closed-loop optimization control strategy. Based on the SCR dynamics model, the future state variables of the SCR system can be predicted. Based on the gradient and combined with the gradient descent iteration method and iteration step size, the control action and model error feedback correction are repeatedly optimized, calculated, and implemented online. By predicting the future output of the controlled object through a model and evaluating the system behavior using relevant objective functions, the optimal control sequence for a future period is solved through online rolling optimization. The online rolling optimization model predictive control provided by this invention has the advantages of good control effect and strong robustness. It can effectively overcome process uncertainty, nonlinearity and parallelism, improve transient control effect, and optimize and upgrade the control function according to changes in actual operating conditions, thereby improving the accuracy of SCR ammonia storage control. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 is a flowchart of an embodiment of the optimized control method for SCR target ammonia storage capacity provided by the present invention;

[0031] Figure 2 is a logical schematic diagram of the optimized control method for SCR target ammonia storage provided by the present invention;

[0032] Figure 3 is a flowchart of another embodiment of the optimized control method for SCR target ammonia storage provided by the present invention;

[0033] Figure 4 is a schematic diagram of the optimized control device for SCR target ammonia storage capacity provided by the present invention.

[0034] Figure 5 is a schematic diagram of an embodiment of the engine controller provided by the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0036] In the description of the embodiments of this application, unless otherwise stated, "a plurality of" means two or more.

[0037] In this embodiment of the invention, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, apparatus, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such process, method, product or device.

[0038] The naming or numbering of steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed in the time / logical order indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effect can be achieved.

[0039] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0040] This invention provides an optimized control method, device, and engine controller for the target ammonia storage capacity of an SCR system, which will be described below.

[0041] As shown in Figure 1, this invention provides an optimized control method for the target ammonia storage capacity in SCR, comprising:

[0042] S101. Obtain the control sequence at the current moment; the control sequence is used to control the ammonia storage capacity of the SCR system.

[0043] S102. Based on the control sequence at the current moment, and the preset SCR dynamics model and corresponding objective function, determine the state variables and control objectives of the SCR system in the prediction time domain.

[0044] S103. Based on the state variables and the control objective, determine the gradient of the control objective with respect to the control sequence at the current moment;

[0045] S104. Based on the gradient and combined with the gradient descent iterative method and iteration step size, determine the optimal control sequence in the prediction time domain, and control the target ammonia storage capacity of the SCR system based on the optimal control sequence.

[0046] It is understood that the control sequence in this invention is also called the control parameter or control variable; SCR, or Selective Catalytic Reduction, is a treatment process for NOx in diesel vehicle exhaust emissions. Under the action of a catalyst, ammonia or urea is injected as a reducing agent to reduce NOx in the exhaust gas to N2 and H2O. The logic for optimizing the control of the target ammonia storage amount in SCR can be seen in Figure 2. The target NH3 storage amount is the control target for the closed-loop control of NH3 storage. To ensure a high NOx conversion efficiency in the SCR system, the NH3 storage amount needs to be maintained at a high level. However, if the NH3 storage amount is too high, the risk of NH3 escape will greatly increase. Therefore, setting the target NH3 storage amount at a reasonable level is crucial for the NH3 storage control function. To achieve high-precision ammonia storage control, it is necessary to obtain real-time calculations of the target ammonia storage amount, thereby improving the accuracy of the final urea injection control.

[0047] The technical problem this invention aims to solve is to provide a more accurate method for calculating the target ammonia storage capacity for SCR ammonia storage control in the China VI emission standard aftertreatment control strategy. Model predictive control (MDI) is a model-based control algorithm and a model-based closed-loop optimization control strategy. Its core algorithm is: a predictable dynamic model, online iterative optimization calculation and rolling implementation of control actions, and feedback correction of model errors.

[0048] Model predictive control (MRC) predicts the future output of the controlled object by using a SCR kinetic model (i.e., an SCR chemical reaction kinetic model), evaluates the system behavior using correlation functions, and solves for the optimal control sequence over a future period through online rolling optimization. MRC has advantages such as good control performance and strong robustness, and can effectively overcome process uncertainties, nonlinearities, and parallelism. It can also easily handle various constraints in the controlled and manipulated variables of the process.

[0049] Optimization solution for the SCR dynamics model:

[0050] To address this optimization problem, this invention employs the gradient descent method. Gradient descent is a first-order optimization algorithm that finds a local minimum of a function, thereby improving real-time computation. This invention utilizes the SCR chemical reaction kinetic model, combined with system input, to determine the system state at each stage, and then selects gradient descent to obtain the optimal local control performance.

[0051] In some embodiments, the iteration step size is inversely correlated with the number of iterations of the gradient descent iteration method, and the iteration step size remains unchanged when the number of iterations is greater than a preset threshold.

[0052] Understandably, to accelerate the convergence process, a relatively large initial step size is set, which gradually decreases during iteration, stabilizing after N iterations, where N is a preset threshold. In some embodiments, the state variables of the SCR system include: the NOx concentration and NH3 concentration at the SCR system outlet; the SCR kinetic model includes: a NOx kinetic model and an NH3 kinetic model.

[0053] The NOx kinetic model is used to characterize the relationship between the NOx concentration at the outlet of the SCR system at the current moment and the NOx concentration at the outlet of the SCR system at the previous moment.

[0054] The NH3 kinetic model is used to characterize the relationship between the NH3 concentration at the SCR system outlet at the current moment and the NH3 concentration at the SCR system outlet at the previous moment.

[0055] In some embodiments, the relationship represented by the NOx kinetic model is as follows:

[0056] The NOx concentration at the SCR system outlet at the current moment is determined based on the NOx concentration at the SCR system outlet at the previous moment, as well as the control cycle, space velocity, the NOx concentration at the SCR system inlet at the current moment, the NOx catalytic reduction reaction rate constant, the NOx catalytic reduction reaction activation energy, the SCR catalyst temperature, the ammonia coverage of the SCR system at the previous moment, and the maximum ammonia coverage of the SCR system.

[0057] In some embodiments, the relationship represented by the NH3 kinetic model is as follows:

[0058] The NH3 concentration at the SCR system outlet at the current moment is determined based on the NH3 concentration at the SCR system outlet at the previous moment, as well as the control cycle, space velocity, urea injection rate at the SCR system inlet at the current moment, ammonia desorption reaction rate constant, ammonia adsorption reaction rate constant, NH3 desorption reaction activation energy, ammonia coverage of the SCR system at the previous moment, NH3 desorption reaction characteristic parameters, maximum ammonia coverage of the SCR system, and SCR catalyst temperature.

[0059] It is understood that this invention calculates the basic control parameter inputs based on the SCR chemical reaction kinetic model, takes the minimum NOx concentration and minimum NH3 leakage at the SCR outlet as control objectives, selects the target ammonia storage as the control variable, and constructs an optimization control function for the target ammonia storage of the SCR. The specific implementation steps include the following parts:

[0060] Constructing a chemical reaction kinetic model for SCR:

[0061] The SCR outlet NOx and NH3 kinetic model calculations are as follows:

[0062] Where: state variables The control variable is u = θ.

[0063] k is the sampling sequence, k = 1, 2, 3, 4, 5.........;

[0064] C NOx (k) represents the NOx concentration at the SCR outlet at time k;

[0065] C NH3 (k) represents the NH3 concentration at the SCR outlet at time k;

[0066] C NOX,in (k) represents the NOx concentration at the SCR inlet at time k;

[0067] C NH3，in (k) represents the urea injection rate at the SCR inlet at time k; θ is the ammonia coverage ratio of the SCR system, θ max This represents the maximum ammonia coverage of the SCR system.

[0068] Ts is the sampling time or the control period;

[0069] For airspeed, EF V =EF m R·T represents exhaust flow rate, and V represents catalyst volume;

[0070] k1 is the rate constant for ammonia adsorption reaction; k2 is the rate constant for ammonia desorption reaction; k3 is the rate constant for NOx catalytic reduction reaction; E1 is the activation energy for NH3 adsorption reaction;

[0071] E2 is the activation energy for the desorption reaction of NH3;

[0072] E3 is the activation energy for the catalytic reduction reaction of NOx.

[0073] m is a characteristic parameter of the NH3 desorption reaction;

[0074] T represents the SCR catalyst temperature, which is typically the average of the SCR inlet and outlet temperatures.

[0075] In some embodiments, the objective function is determined based on the NOx concentration at the SCR system outlet, the NH3 leakage, and the rate of change of the control sequence during the control period.

[0076] In some embodiments, the objective function aims to minimize the weighted sum of the NOx concentration, NH3 leakage, and control sequence change rate at the SCR system outlet during the control period.

[0077] Understandably, the objective function is constructed with the goals of minimizing the NOx and NH3 concentrations at the SCR outlet and minimizing the rate of change of the control variable θ, as follows:

[0078] in:

[0079] In the formula, x1 represents the NOx concentration at the SCR outlet, and x2 represents the NH3 concentration at the SCR outlet. The first term of the objective function indicates that the reference value for the NOx concentration at the SCR outlet is 0. By controlling the target ammonia storage quantity, the control variable of the SCR system, the NOx concentration at the SCR outlet is made as close to 0 as possible. The second term of the objective function indicates that the NH3 leakage at the SCR outlet is also infinitely close to 0. L1, L2, and L3 are the weights of the objective function, representing the magnitude of each term's influence in the objective function. N p For the control time domain and prediction time domain of model predictive control, N p ≥1, generally taken as 20.

[0080] The first term of the objective function represents the reference value of NOx concentration at the SCR outlet as 0. By controlling the target ammonia storage amount of the SCR system control variable, the NOx concentration at the SCR outlet is made as close to 0 as possible. The second term of the objective function represents the amount of NH3 leakage at the SCR outlet as close to 0 as possible.

[0081] L1 is the weight of NOx in the objective function, a calibration value, which also corresponds to the numerical value P1;

[0082] L2 is the weight of NH3 in the objective function, a calibration value, which also corresponds to the numerical value P2;

[0083] L3 is the weight of ammonia coverage in the objective function, a calibration value, which also corresponds to the numerical value P3;

[0084] Ts is the sampling time or control period, typically set to 50ms.

[0085] U(k) is the SCR ammonia coverage at time k, U min U is 0 max =1;

[0086] θ represents the ammonia coverage of the actual SCR catalyst; θ max This represents the maximum ammonia coverage of the SCR system.

[0087] k1 is the rate constant for the ammonia adsorption reaction;

[0088] k2 is the rate constant for the ammonia desorption reaction;

[0089] k3 is the rate constant for the catalytic reduction of NOx;

[0090] For airspeed, EF V =EF m R·T represents exhaust flow rate, and V represents catalyst volume;

[0091] E1 is the activation energy of the NH3 adsorption reaction, which is a calibration value;

[0092] T represents the SCR catalyst temperature, which is typically the average of the SCR inlet and outlet temperatures.

[0093] In addition to considering the emission requirements of the SCR system, relevant constraints of the SCR system also need to be considered, mainly including the maximum injection capacity of the actuator urea pump and the limits of various state variables of the SCR system. min U max The minimum and maximum limits for ammonia storage capacity of SCR catalysts. min The operating conditions are determined to ensure that the SCR system always maintains a certain amount of ammonia storage, thus avoiding a surge in NOx at the SCR outlet when NOx concentration changes rapidly.

[0094] In summary, the model predictive control algorithm provided by this invention mainly consists of the following three steps:

[0095] 1) At each sampling time, based on the current measurement information (control sequence), the model of the controlled object is used to predict the future dynamics of the system;

[0096] 2) Solve a numerical solution to a finite-time open-loop optimization problem online;

[0097] 3) Apply the first element of the obtained control sequence to the controlled object.

[0098] The above three steps are repeated, which constitutes the "rolling optimization" mechanism of model predictive control. In the initialization procedure of the control sequence, it is assumed that the control quantity remains constant in the prediction time domain. Within the constraint range, the control quantity is taken at equal intervals of N values, and the corresponding objective function values ​​are calculated according to the above optimization problem.

[0099] In other embodiments, the optimized control method for the SCR target ammonia storage capacity provided by the present invention can be referred to Figure 3, and specifically includes:

[0100] a) Determine the adaptive iteration step size:

[0101] To accelerate the convergence process, a relatively large initial step size is set, which is gradually reduced during the iteration process and stabilizes at the set step size after N iterations.

[0102] b) State prediction:

[0103] Based on the current control sequence and the SCR system dynamics model, the state variables and objective function values ​​in the predicted time domain are obtained.

[0104] c) Solve the calculation:

[0105] Calculate the gradient of the constraint function, and use gradient descent iterative optimization to obtain the optimal sequence of control variables at time k0 [u_k0, u_(k0+1), ..., u_(k0+Nc)]. Only the first control variable u_k is applied to the system. At the next time k0+1, repeat the above solution steps to obtain the optimal sequence of control variables at time k0+1 [u_(k0+1), ..., u_(k0+Nc+1)].

[0106] Control parameter design and optimization:

[0107] The three parameters L1, L2, and L3 of the model predictive control objective function have different physical meanings. L1 is the constraint weight for NOx emissions. Increasing L1 will make the constraint on NOx more stringent, resulting in a reduction in NOx emissions and an increase in urea injection. Similarly, increasing L2 will lead to a reduction in NH3 escape and an increase in NOx emissions. L3 is the constraint term for the target ammonia storage, which is a soft constraint on the target ammonia storage.

[0108] Currently, the control parameter calibration method is based on coordinated control of simulation test and bench calibration results, and the final engine emissions and urea consumption are evaluated as a whole.

[0109] In summary, the optimization control method for the target ammonia storage capacity of an SCR system provided by this invention includes: acquiring a control sequence at the current moment; using the control sequence to control the ammonia storage capacity of the SCR system; determining the state variables and control objective of the SCR system in the prediction time domain based on the control sequence at the current moment, a preset SCR dynamics model, and the corresponding objective function; determining the gradient of the control objective with respect to the control sequence at the current moment based on the state variables and the control objective; determining the optimal control sequence in the prediction time domain based on the gradient and in combination with a gradient descent iteration method and an iteration step size; and controlling the target ammonia storage capacity of the SCR system based on the optimal control sequence.

[0110] The optimized control method for the target ammonia storage capacity of a SCR system provided by this invention determines the state variables and control objective of the SCR system in the prediction time domain by using the control sequence of the SCR system at the current moment, a preset SCR dynamics model, and the corresponding objective function. Based on the state variables and the control objective, the gradient of the control objective with respect to the control sequence at the current moment is determined. Based on the gradient and combined with the gradient descent iterative method and the iteration step size, the optimal control sequence in the prediction time domain is determined, realizing a model-based closed-loop optimization control strategy. The future state variables of the SCR system can be predicted based on the SCR dynamics model. Based on the gradient and combined with the gradient descent iterative method and the iteration step size, the control action and model error feedback correction are repeatedly calculated and implemented online. By predicting the future output of the controlled object through the model and evaluating the system behavior using the relevant objective function, the optimal control sequence for a future period is solved online through rolling optimization. The model predictive control method provided by this invention, which solves the optimal control sequence online through rolling optimization, has the advantages of good control effect and strong robustness. It can effectively overcome process uncertainty, nonlinearity, and parallelism, improve transient control effect, and optimize and upgrade the control function according to changes in actual operating conditions, thereby improving the accuracy of SCR ammonia storage control.

[0111] As shown in Figure 4, the present invention also provides an optimized control device 400 for SCR target ammonia storage capacity, comprising:

[0112] The acquisition module 401 is used to acquire the control sequence at the current moment; the control sequence is used to control the ammonia storage amount of the SCR system.

[0113] The prediction module 402 is used to determine the state variables and control objectives of the SCR system in the prediction time domain based on the control sequence at the current moment, the preset SCR dynamics model and the corresponding objective function.

[0114] The gradient solving module 403 is used to determine the gradient of the cost with respect to the control sequence at the current time based on the state variables and the control objective.

[0115] The control module 404 is used to determine the optimal control sequence in the prediction time domain based on the gradient and in combination with the gradient descent iterative method and the iteration step size, and to control the target ammonia storage capacity of the SCR system based on the optimal control sequence.

[0116] In some embodiments, the iteration step size is inversely correlated with the number of iterations of the gradient descent iteration method, and the iteration step size remains unchanged when the number of iterations is greater than a preset threshold.

[0117] Understandably, in order to accelerate the convergence process, the initial step size is set to be relatively large. As the iteration process progresses, the step size gradually decreases and stabilizes at the set step size after N iterations (i.e., the preset threshold).

[0118] In some embodiments, the state variables of the SCR system include: the NOx concentration and NH3 concentration at the SCR system outlet; the SCR kinetic model includes: the NOx kinetic model and the NH3 kinetic model;

[0119] The NOx kinetic model is used to characterize the relationship between the NOx concentration at the outlet of the SCR system at the current moment and the NOx concentration at the outlet of the SCR system at the previous moment.

[0120] The NH3 kinetic model is used to characterize the relationship between the NH3 concentration at the SCR system outlet at the current moment and the NH3 concentration at the SCR system outlet at the previous moment.

[0121] In some embodiments, the relationship represented by the NOx kinetic model is as follows:

[0122] The NOx concentration at the SCR system outlet at the current moment is determined based on the NOx concentration at the SCR system outlet at the previous moment, as well as the control cycle, space velocity, the NOx concentration at the SCR system inlet at the current moment, the NOx catalytic reduction reaction rate constant, the NOx catalytic reduction reaction activation energy, the SCR catalyst temperature, the ammonia coverage of the SCR system at the previous moment, and the maximum ammonia coverage of the SCR system.

[0123] In some embodiments, the relationship represented by the NH3 kinetic model is as follows:

[0124] The NH3 concentration at the SCR system outlet at the current moment is determined based on the NH3 concentration at the SCR system outlet at the previous moment, as well as the control cycle, space velocity, urea injection rate at the SCR system inlet at the current moment, ammonia desorption reaction rate constant, ammonia adsorption reaction rate constant, NH3 desorption reaction activation energy, ammonia coverage of the SCR system at the previous moment, NH3 desorption reaction characteristic parameters, maximum ammonia coverage of the SCR system, and SCR catalyst temperature.

[0125] In some embodiments, the objective function is determined based on the NOx concentration at the SCR system outlet, the NH3 leakage, and the rate of change of the control sequence during the control period.

[0126] In some embodiments, the objective function aims to minimize the weighted sum of the NOx concentration, NH3 leakage, and control sequence change rate at the SCR system outlet during the control period.

[0127] It is understood that the SCR target ammonia storage optimization control device provided by this invention predicts the future output of the controlled object through an SCR kinetic model (i.e., an SCR chemical reaction kinetic model), evaluates the system behavior using correlation functions, and solves the optimal control sequence for a future period through online rolling optimization. Model predictive control has advantages such as good control effect and strong robustness, and can effectively overcome process uncertainties, nonlinearities, and parallelism, and can conveniently handle various constraints in the controlled and manipulated variables of the process.

[0128] Specifically, the optimized control device for SCR target ammonia storage capacity provided by this invention determines the state variables and control objective of the SCR system in the prediction time domain by using the control sequence of the SCR system at the current moment, and the preset SCR dynamics model and corresponding objective function. Based on the state variables and the control objective, the gradient of the control objective with respect to the control sequence at the current moment is determined. Based on the gradient and combined with the gradient descent iteration method and iteration step size, the optimal control sequence in the prediction time domain is determined, realizing a model-based closed-loop optimization control strategy. The future state variables of the SCR system can be predicted based on the SCR dynamics model. Based on the gradient and combined with the gradient descent iteration method and iteration step size, the control action and model error feedback correction are repeatedly optimized and implemented online. By predicting the future output of the controlled object through the model and evaluating the behavior of the system using the relevant objective function, the optimal control sequence for a future period is solved online through rolling optimization. The model predictive control method provided by this invention, which solves the optimal control sequence online through rolling optimization, has advantages such as good control effect and strong robustness. It can effectively overcome process uncertainty, nonlinearity and parallelism, improve transient control effect, and optimize and upgrade the control function according to changes in actual operating conditions, thereby improving the accuracy of SCR ammonia storage control.

[0129] The optimized control device for the target ammonia storage capacity of SCR provided in the above embodiments can realize the technical solutions described in the above embodiments of the optimized control method for the target ammonia storage capacity of SCR. The specific implementation principles of each module or unit can be found in the corresponding content in the above embodiments of the optimized control method for the target ammonia storage capacity of SCR, and will not be repeated here.

[0130] As shown in Figure 5, the present invention also provides an engine controller 500. The engine controller 500 includes a processor 501 and a memory 502. Figure 5 only shows some components of the engine controller 500; however, it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented alternatively.

[0131] In some embodiments, memory 502 may be an internal storage unit of engine controller 500.

[0132] In some embodiments, processor 501 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 502 or process data, such as the optimized control method for SCR target ammonia storage in this invention.

[0133] In some embodiments of the present invention, when the optimized control program for the SCR target ammonia storage capacity in the engine controller is executed, the following steps can be achieved:

[0134] Obtain the control sequence at the current moment; the control sequence is used to control the ammonia storage capacity of the SCR system.

[0135] Based on the control sequence at the current moment, and the preset SCR dynamics model and corresponding objective function, the state variables and control objectives of the SCR system in the prediction time domain are determined.

[0136] Based on the state variables and the control objective, determine the gradient of the control objective with respect to the control sequence at the current moment;

[0137] Based on the gradient and combined with the gradient descent iterative method and iteration step size, the optimal control sequence in the prediction time domain is determined, and the target ammonia storage capacity of the SCR system is controlled based on the optimal control sequence.

[0138] It should be understood that, in addition to the functions mentioned above, the SCR target ammonia storage optimization control program in the engine controller can also implement other functions, as detailed in the description of the corresponding method embodiments above.

[0139] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an optimized control method for the SCR target ammonia storage capacity provided by the methods described above, the method comprising:

[0140] Obtain the control sequence at the current moment; the control sequence is used to control the ammonia storage capacity of the SCR system.

[0141] Based on the control sequence at the current moment, and the preset SCR dynamics model and corresponding objective function, the state variables and control objectives of the SCR system in the prediction time domain are determined.

[0142] Based on the state variables and the control objective, determine the gradient of the control objective with respect to the control sequence at the current moment;

[0143] Based on the gradient and combined with the gradient descent iterative method and iteration step size, the optimal control sequence in the prediction time domain is determined, and the target ammonia storage capacity of the SCR system is controlled based on the optimal control sequence.

[0144] The present invention also provides an automobile that includes the vehicle controller 500 described above.

[0145] The above provides a detailed description of the optimized control method, device, and engine controller for SCR target ammonia storage provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. An optimization control method for an SCR target ammonia storage amount, characterized by, The method comprises the following steps: obtaining a control sequence at a current time; the control sequence is used to control the ammonia storage amount of the SCR system; based on the control sequence at the current time, and a preset SCR dynamic model and a corresponding target function, determining the state quantity and control target of the SCR system in a prediction time domain; based on the state quantity and the control target, determining the gradient of the control target on the control sequence at the current time; based on the gradient and combined with the gradient descent iteration method and the iteration step, determining the optimal control sequence of the prediction time domain, and controlling the target ammonia storage amount of the SCR system based on the optimal control sequence.

2. The method of claim 1, wherein The iteration step is inversely related to the number of iterations of the gradient descent iteration method, and the iteration step remains unchanged when the number of iterations is greater than a preset threshold.

3. The method of claim 1, wherein The state quantity of the SCR system comprises the NOx concentration and the NH3 concentration at the outlet of the SCR system; the SCR dynamic model comprises a NOx dynamic model and an NH3 dynamic model; The NOx dynamic model is used to represent the relationship between the NOx concentration at the outlet of the SCR system at the current time and the NOx concentration at the outlet of the SCR system at the previous time; The NH3 dynamic model is used to represent the relationship between the NH3 concentration at the outlet of the SCR system at the current time and the NH3 concentration at the outlet of the SCR system at the previous time.

4. The method of claim 3, wherein The relationship represented by the NOx dynamic model is: The NOx concentration at the outlet of the SCR system at the current time is determined based on the NOx concentration at the outlet of the SCR system at the previous time, the control period, the space velocity, the NOx concentration at the inlet of the SCR system at the current time, the NOx catalytic reduction reaction rate constant, the NOx catalytic reduction reaction activation energy, the SCR catalyst temperature, the ammonia coverage rate of the SCR system at the previous time, and the maximum ammonia coverage rate of the SCR system.

5. The method of claim 4, wherein The relationship represented by the NH3 dynamic model is: The NH3 concentration at the outlet of the SCR system at the current time is determined based on the NH3 concentration at the outlet of the SCR system at the previous time, the control period, the space velocity, the urea injection amount at the inlet of the SCR system at the current time, the ammonia desorption reaction rate constant, the ammonia adsorption reaction rate constant, the NH3 desorption reaction activation energy, the ammonia coverage rate of the SCR system at the previous time, the NH3 desorption reaction characteristic parameter, the maximum ammonia coverage rate of the SCR system, and the SCR catalyst temperature.

6. The optimal control method for the SCR target ammonia storage amount according to claim 5, wherein: the target function is determined based on the NOx concentration at the outlet of the SCR system, the NH3 leakage amount, and the control sequence change rate in the control period.

7. The method of claim 6, wherein the target ammonia storage amount of the SCR catalyst is optimized based on the ammonia slip amount. The target function takes the minimum weighted sum value of the NOx concentration at the outlet of the SCR system, the NH3 leakage amount, and the control sequence change rate in the control period as the control target.

8. An optimized control device for SCR target ammonia storage capacity, characterized in that, The method comprises the following steps: an obtaining module is configured to obtain a control sequence at a current time; the control sequence is used to control the ammonia storage amount of the SCR system; a prediction module is configured to determine the state quantity and control target of the SCR system in a prediction time domain based on the control sequence at the current time, and a preset SCR dynamic model and a corresponding target function. a gradient solving module configured to determine a gradient of the control target to a control sequence at a current time based on the state variable and the control target; a control module configured to determine an optimal control sequence of a prediction time domain based on the gradient in combination with a gradient descent iteration method and an iteration step, and control a target ammonia storage amount of the SCR system based on the optimal control sequence.

9. An engine controller characterized by, comprising a memory and a processor, the memory is configured to store a program; the processor, coupled with the memory, is configured to execute the program stored in the memory to implement the steps of the SCR target ammonia storage amount optimization control method according to any one of claims 1 to 7.

10. An automobile characterized by comprising: an engine controller according to claim 9.

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