A control method and system for a diesel-methanol blended fuel engine

Abstract

The application provides a diesel-methanol mixed fuel engine control method and system, comprising: acquiring real-time working condition data including engine speed, load and temperature parameters, determining the optimal supply ratio of diesel and methanol under the current working condition according to the real-time working condition data and combining a preset fuel characteristic difference model; calculating the mixed gas concentration of methanol and diesel according to the optimal supply ratio; if the mixed gas concentration exceeds a preset threshold, adjusting the injection pressure of methanol to make the mixed gas concentration return to the target range. If the combustion rate is lower than the preset lower limit value after increasing the methanol injection frequency, the injection direction of the methanol injector is adjusted to improve the mixing uniformity; if the combustion rate is still lower than the preset lower limit value, the methanol injection timing is adjusted to make the methanol injection and the diesel injection form the best cooperation in time, so as to ensure the stable engine output power and meet the high-efficiency and clean operation target.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular to a diesel-methanol mixed fuel engine control method and system. BACKGROUND

[0002] When diesel engines use methanol as a substitute fuel, the injection amount of methanol needs to be accurately controlled to achieve the optimal mixing ratio with diesel. However, there are significant differences in physical and chemical properties such as viscosity, surface tension, and vapor pressure between methanol and diesel, making it difficult to calibrate the given injection control. In addition, the combustion rate of methanol-air mixture is also different from that of diesel, and too high or too low mixture concentration will lead to unstable combustion, increased fuel consumption, and other problems. At the same time, due to the low heat value of methanol fuel, the engine will face the problem of reduced output power when using methanol. Therefore, it is necessary to design an injection system and combustion control algorithm that takes into account the characteristics of methanol, to coordinate the supply ratio and injection timing of diesel and methanol, to ensure smooth operation of the engine while improving the efficiency of the engine to compensate for the power loss caused by the low heat value of methanol. This requires the injection system to adjust the injection pressure, injection frequency, and injection direction of methanol in real time according to the engine operating conditions and fuel characteristics, to improve the combustion process and maximize the substitution potential of methanol, and to achieve efficient and clean operation of the diesel-methanol dual-fuel engine. SUMMARY

[0003] The present application provides a diesel-methanol mixed fuel engine control method, mainly comprising:

[0004] Obtain real-time operating condition data including engine speed, load, and temperature parameters, and determine the optimal supply ratio of diesel and methanol under the current operating conditions based on the real-time operating condition data and a pre-set fuel characteristic difference model;

[0005] Calculate the mixture concentration of methanol and diesel based on the optimal supply ratio, and adjust the injection pressure of methanol if the mixture concentration exceeds the pre-set threshold to return the mixture concentration to the target range;

[0006] After adjusting the injection pressure of methanol, determine whether the current mixture combustion rate meets the stable operation requirements of the engine through a pre-set combustion rate difference model, and increase the injection frequency of methanol to improve the mixture combustion rate if the combustion rate is below the pre-set lower limit;

[0007] After increasing the injection frequency of methanol, adjust the injection direction of the methanol injector to improve the mixing uniformity if the combustion rate is still below the pre-set lower limit;

[0008] If the combustion rate is still lower than the preset lower limit value, the methanol injection timing is adjusted to make the methanol injection and the diesel injection form the best cooperation in time, so as to ensure the stability of the engine output power and meet the high-efficiency and clean operation target.

[0009] The application provides a diesel-methanol mixed fuel engine control system, which mainly comprises:

[0010] A real-time working condition data acquisition module is configured to acquire real-time working condition data including engine speed, load and temperature parameters;

[0011] A fuel supply ratio calculation module is configured to determine the optimal supply ratio of diesel and methanol under the current working condition according to the real-time working condition data and in combination with a preset fuel characteristic difference model;

[0012] A mixed gas concentration adjustment module is configured to calculate the mixed gas concentration of methanol and diesel according to the optimal supply ratio, and adjust the injection pressure of methanol to make the mixed gas concentration return to the target range if the mixed gas concentration exceeds a preset threshold value;

[0013] A combustion rate judgment module is configured to judge whether the current mixed gas combustion rate meets the stable operation requirement of the engine through a preset combustion rate difference model after the injection pressure of methanol is adjusted, and increase the injection frequency of methanol to improve the mixed gas combustion rate if the combustion rate is lower than a preset lower limit value;

[0014] An injection parameter optimization module is configured to adjust the injection direction of the methanol injector to improve the mixing uniformity if the combustion rate is lower than the preset lower limit value after the injection frequency of methanol is increased, and adjust the injection timing of methanol to make the methanol injection and the diesel injection form the best cooperation in time if the combustion rate is still lower than the preset lower limit value, so as to ensure the stability of the engine output power and meet the high-efficiency and clean operation target.

[0015] The technical scheme provided by the application embodiment can have the following beneficial effects:

[0016] The application discloses a diesel-methanol mixed fuel engine control method. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A flow chart of a diesel-methanol mixed fuel engine control method of the present application.

[0018] Figure 2 A schematic diagram of a diesel-methanol mixed fuel engine control method and system of the present application.

[0019] Figure 3 Another schematic diagram of a diesel-methanol mixed fuel engine control method and system of the present application.

[0020] Figure 4 A structural schematic diagram of a diesel-methanol mixed fuel engine control method and system of the present application. DETAILED DESCRIPTION

[0021] In order to make the person skilled in the art better understand the technical solutions in the specification, the technical solutions in the specification will be described clearly and completely in the following with reference to the drawings in the specification. Obviously, the described embodiments are only part of the embodiments of the specification, not all. Based on the embodiments in the specification, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the specification.

[0022] As Figures 1-4 , the diesel-methanol mixed fuel engine control method and system of the present embodiment can specifically include:

[0023] S101, real-time working condition data including engine speed, load and temperature parameters are acquired, and according to the real-time working condition data, the optimal supply ratio of diesel and methanol under the current working condition is determined in combination with a preset fuel characteristic difference model.

[0024] A database containing the differences of combustion characteristic parameters of diesel and methanol fuel under different working conditions is obtained as the training data of the BP neural network model. At the same time, the real-time working condition parameters of the engine, including the speed, load and intake volume, are obtained as the input of the model. By using the trained BP neural network model, a nonlinear mapping relationship between the real-time working condition parameters, fuel characteristic parameters and combustion efficiency is established, and a comprehensive index representing the combustion efficiency is output. The K-means clustering algorithm is used to divide the real-time working condition data points at different times into several typical working condition categories, and each typical working condition corresponds to a cluster center. The feature parameters of each cluster center are input into the BP neural network model to obtain the corresponding combustion efficiency comprehensive index. For each typical working condition, the fuel mixing ratio is taken as the optimization variable, and the genetic algorithm is used to search for the optimal mixing ratio that maximizes the combustion efficiency comprehensive index. The fitness function of the genetic algorithm is the comprehensive index output by the BP neural network model, and the constraint condition is the value range of the mixing ratio. According to the optimal mixing ratio under each typical working condition searched by the genetic algorithm, a mapping relationship between the real-time working condition parameters and the optimal mixing ratio is established. In actual operation, according to the real-time working condition parameters of the engine, the corresponding optimal mixing ratio of diesel and methanol is determined, and the fuel mixing control command is output.

[0025] For example, the ignition delay period, flame propagation speed, and heat value of diesel and methanol under different working conditions can be obtained through bench tests. These data reflect the differences in the combustion behavior of the two fuels under different conditions and provide a basis for subsequent modeling. Engine speed, load, and other parameters can be obtained through the engine control unit (ECU), and the intake air quantity can be measured by a mass flow meter. These parameters collectively reflect the instantaneous operating state of the engine and are key inputs to the model. During the establishment of the BP neural network model, the working condition parameters and fuel characteristic parameters can be used as input layer neurons, and the combustion efficiency index can be used as an output layer neuron. The network weights are continuously adjusted through the backpropagation algorithm, and a nonlinear mapping relationship is ultimately established. This method can effectively capture the characteristics of the complex combustion process. The application of the K-means clustering algorithm helps to simplify the optimization process. Assuming that the real-time working condition data is clustered into five categories, each representing a typical working condition, such as idle speed, low load at medium speed, high load at medium speed, low load at high speed, and high load at high speed. This method can discretize the continuous working condition space, making it easier to optimize later. Genetic algorithms have an advantage in finding the optimal mixing ratio. The mixing ratio can be encoded as a chromosome, and the efficiency index output by the BP neural network can be used as the fitness function. Through selection, crossover, and mutation operations, the optimal solution is evolved generation by generation. This method can quickly find the global optimal solution in a complex solution space. Finally, establishing a mapping relationship between the working condition parameters and the optimal mixing ratio is crucial for real-time control. The lookup table method or fitting polynomial equation method can be used to achieve fast mapping. In actual operation, the optimal mixing ratio is obtained by querying or calculating based on the current working condition parameters, thereby achieving precise fuel ratio control. The technical effects of this method are mainly as follows: First, an accurate model of the combustion process is established through data-driven methods, overcoming the limitations of traditional theoretical models in accurately describing complex combustion processes. Second, machine learning algorithms are used to achieve intelligent optimization of fuel ratio, which can better adapt to different working conditions compared to traditional fixed ratio methods. Finally, real-time control strategies are used to ensure that the engine always operates in the best combustion state, which is beneficial to improving fuel economy and reducing emissions.

[0026] S102、According to the optimal supply ratio, the concentration of the methanol and diesel mixture is calculated; if the concentration of the mixture exceeds the preset threshold, the injection pressure of the methanol is adjusted to return the concentration of the mixture to the target range.

[0027] According to the stoichiometric equation, the optimal mass ratio of diesel and methanol is calculated, and the theoretical air-fuel ratio of the mixed fuel is determined accordingly. After the actual supply of diesel and methanol, the actual concentration value of the mixed fuel is calculated according to the mass of the two. Through system integration test, the concentration range required for safe and stable combustion under different working conditions is obtained, which is set as the threshold range of concentration control. The actual concentration value of the mixed fuel is monitored in real time, and it is compared with the preset threshold. If the concentration exceeds the threshold range, the adjustment mechanism of methanol injection pressure is triggered. For different degrees of concentration overrun, the response relationship curve of methanol injection pressure and fuel concentration is established in advance through test. According to the actual concentration overrun, the corresponding target pressure value is obtained by looking up the table, which is used as the set value of PID control algorithm. The PID controller takes the target pressure value as the set value and the actual pressure value as the feedback value, and adjusts the proportional, integral and differential parameters to control the working of the methanol injection device, realizes the automatic adjustment of the injection pressure, and then controls the mixed fuel concentration within the threshold range. In the process of pressure regulation, the actual concentration value of the mixed fuel is continuously collected, which is compared with the target concentration value to calculate the concentration error. The concentration error is introduced into the PID controller to adaptively correct the control parameters, improve the regulation accuracy and dynamic response speed. The concentration of the mixed fuel is continuously monitored for a long time, and the concentration change trend is predicted by time series analysis method. When the predicted concentration value has the risk of exceeding the threshold range, the fine adjustment of methanol injection pressure is started in advance to avoid the instability caused by sharp change of concentration.

[0028] For example, the optimal mass ratio of diesel to methanol in a dual-fuel engine system is calculated based on stoichiometric equations. For a specific diesel and methanol blend, theoretical calculations may yield an optimal mass ratio of 7:3. This ratio takes into account the chemical composition and combustion characteristics of both fuels, aiming to achieve optimal combustion efficiency and emission performance. Based on this optimal mass ratio, a weighted average method is used to multiply the air-fuel ratios of diesel and methanol by their respective ratio values, resulting in a calculated air-fuel ratio for the blended fuel. Assuming a theoretical air-fuel ratio of 14.5:1 for pure diesel and 6.45:1 for pure methanol, a 7:3 diesel-methanol blend would have a theoretical air-fuel ratio of approximately 12.3:1. This value provides an important reference for subsequent fuel supply and air flow control. In actual operation, the system continuously monitors the mass of diesel and methanol supplied, calculating the actual concentration of the blended fuel. For example, if the actual mass ratio of diesel to methanol supplied is 6.8:3.2, slightly deviating from the ideal ratio, the system feeds this information back to the control unit, preparing for subsequent adjustments. Through extensive system integration tests, the concentration range required for safe and stable combustion under different operating conditions can be obtained. For example, in low-speed light-load operating conditions, the safe concentration range of the blended fuel may be 28%-32% (expressed as the mass percentage of methanol); while in high-speed heavy-load operating conditions, this range may narrow to 29%-31%. These data are set as the threshold range for concentration control, providing a basis for real-time control. The real-time monitoring system continuously tracks the actual concentration of the blended fuel and compares it with the pre-set threshold. When the detected concentration exceeds the threshold range, the system triggers the adjustment mechanism for methanol injection pressure. For example, if the concentration of the blended fuel mixture rises to 33% in medium-speed medium-load operating conditions, exceeding the pre-set upper limit of 32%, the system will initiate the adjustment process. To accurately control the methanol injection pressure, a response relationship curve between methanol injection pressure and fuel concentration can be established through extensive tests. This curve may show that, under certain operating conditions, reducing the methanol injection pressure from 8 MPa to 7.5 MPa can reduce the mass percentage of methanol in the blended fuel from 33% to 31%. The system will obtain the corresponding target pressure value by looking up the table according to the actual concentration overrun. The PID controller takes this target pressure value as the set value and the actual pressure value as the feedback value, adjusting the proportional, integral, and derivative parameters to control the operation of the methanol injection device. For example, if the initial P, I, and D parameters are 0.5, 0.3, and 0.1, respectively, the controller may dynamically adjust these parameters based on the size and trend of the pressure error to achieve faster response speed and smaller steady-state error. During the pressure adjustment process, the system continuously collects the actual concentration of the blended fuel and compares it with the target concentration value to calculate the concentration error. This error information is fed back to the PID controller for adaptive correction of the control parameters.For example, if the concentration adjustment speed is found to be too slow, the system can increase the proportional coefficient; if the concentration oscillates, the differential coefficient can be reduced. By continuously monitoring the mixed fuel concentration for a long time, the system can predict the concentration trend using time series analysis methods. For example, if it is observed that the concentration has been rising slowly for the past 15 seconds and is predicted to exceed the upper threshold in 30 seconds, the system will pre-activate the methanol injection pressure fine-tuning and reduce the pressure by 0.1 MPa to prevent combustion instability caused by rapid changes in concentration.

[0029] S103、After adjusting the methanol injection pressure, determine whether the current mixed gas combustion rate meets the engine stable operation requirement through the preset combustion rate difference model. If the combustion rate is lower than the preset lower limit value, increase the methanol injection frequency to improve the mixed gas combustion rate.

[0030] According to the ANSYS Fluent numerical simulation software, a fuel combustion model under different methanol injection pressure and injection frequency conditions is established, and a series of theoretical combustion rate data is calculated. Using multivariate linear regression analysis method, taking injection pressure and frequency as independent variables and combustion rate as dependent variable, the quantitative relationship expression between them is fitted to form the mapping relationship between injection parameters and combustion rate. Install the methanol injection device on the engine test bench, design different engine speed and load conditions, and gradually reduce the methanol injection frequency by adjusting the injection device until the engine shows obvious unstable operation, and record the combustion rate at this time as the lower limit value of the engine stable operation combustion rate under this condition. Test multiple working conditions to obtain an engine combustion rate lower limit value lookup table. During engine operation, the ECU collects engine speed, torque, intake volume and other working condition parameters in real time. According to the current speed and load, two-dimensional interpolation is performed in the combustion rate lower limit value lookup table to obtain the lower limit value of the engine stable operation combustion rate under the current working condition. The oxygen sensor monitors the actual combustion rate of the mixed fuel in real time, compares it with the combustion rate lower limit value obtained by lookup table, and calculates the difference between the actual value and the lower limit value. If the difference is negative, it means that the actual combustion rate is lower than the lower limit value, and the methanol injection frequency adjustment mechanism needs to be triggered. According to the size of the combustion rate difference, the injection parameter and combustion rate mapping relationship table is queried by interpolation to obtain the methanol injection frequency correction amount that needs to be adjusted. For example, if the difference is -10%, the lookup table shows that the frequency needs to be increased by 2 Hz. Add the frequency correction amount to the current injection frequency to obtain the corrected target injection frequency. Then, according to the flow characteristic curve of the electronic control injector, calculate the opening and closing time parameters of the injector under the target frequency. Generate PWM pulse width modulation control instructions and send them to the control unit of the methanol injection device through the CAN bus to adjust the opening and closing time of the injector, realize the dynamic adjustment of the methanol injection frequency, make the actual combustion rate meet the engine stable operation requirement, and ensure the high efficiency of the mixed fuel combustion.

[0031] For example, numerical simulation is an important means of optimizing the performance of dual-fuel engines. Using ANSYS Fluent software, the fuel combustion process under different methanol injection parameters can be simulated. For instance, one study simulated combustion when the injection pressure varied from 5 MPa to 10 MPa and the injection frequency from 10 Hz to 50 Hz. These simulations obtained a series of theoretical combustion rate data, laying the foundation for subsequent analysis. Multiple linear regression analysis was used to establish the relationship between injection parameters and combustion rate. Taking a certain study as an example, with injection pressure and frequency as independent variables and combustion rate as the dependent variable, the following relationship was fitted: Combustion rate = 0.5 × injection pressure + 0.3 × injection frequency + 2.1. This expression intuitively reflects the degree of influence of injection parameters on combustion rate, providing a theoretical basis for actual control. Engine bench testing is a key step in verifying the theoretical model. In one test, researchers gradually reduced the methanol injection frequency at 1500 rpm and 50% load. When the frequency dropped to 15 Hz, the engine exhibited operational instability with a 20% decrease in torque, corresponding to a combustion rate of 25 g / s. This value is recorded as the lower limit of the combustion rate under that operating condition. Through similar tests at multiple operating points, a comprehensive lookup table of lower limit combustion rates was ultimately created. The core of the real-time control system lies in accurately determining the current operating condition and making corresponding adjustments. For example, when the engine is running at 2000 rpm and 75% load, the ECU, by looking up the table, finds that the lower limit of the combustion rate under this condition is 30 g / s. Simultaneously, the oxygen sensor detects an actual combustion rate of 27 g / s, which is 3 g / s lower than the lower limit. The system then triggers an adjustment mechanism, determining, based on the mapping relationship between injection parameters and combustion rate, that the methanol injection frequency needs to be increased by 2 Hz. Precise control of the electronically controlled injector is key to achieving combustion optimization. Assuming the current injection frequency is 20 Hz, according to the aforementioned calculation, it needs to be increased to 22 Hz. Consulting the injector flow characteristic curve, it is determined that at a frequency of 22 Hz, the injector's on-time in each injection cycle should be 2.5 ms. The control system then generates corresponding PWM control commands, which are sent to the injection unit via the CAN bus to achieve precise adjustment of the methanol injection frequency. This control strategy, based on model prediction and real-time feedback, can effectively ensure the combustion efficiency of mixed fuels, improve the overall performance of the engine, reduce fuel consumption, and reduce harmful emissions.

[0032] S104. If the combustion rate is lower than the preset lower limit after increasing the methanol injection frequency, adjust the injection direction of the methanol injector to improve the mixing uniformity.

[0033] The ANSYS Fluent software was used to establish a three-dimensional model of the engine combustion chamber under different injection directions, and the structured grid was divided. On the basis of the grid, the finite volume method was used to discretize the control equation, and the realizable k-ε turbulence model was used to calculate the turbulent kinetic energy k and turbulent dissipation rate ε transport equation, and the velocity, pressure and temperature distribution of the mixture in the combustion chamber were solved. The mixture uniformity index UI was introduced, which was defined as the standard deviation of the equivalence ratio of each grid element, where the equivalence ratio represented the ratio of the actual air-fuel ratio to the stoichiometric ratio. The quadratic polynomial was selected as the regression model, and the quantitative relationship expression was established with the injection direction as the independent variable and UI as the dependent variable, and the "injection direction-UI" quadratic polynomial regression model was obtained; The goodness of fit was judged by the root mean square error and the determination coefficient R². A fast-response flame ionization current sensor was installed on the engine test bench, and its basic working principle is that charged particles will be produced in high-temperature flames, which can form a weak ionization current between the electrodes, and the current signal can represent the change process of the flame. The ignition process of the mixture under different injection directions was collected by the oscilloscope; The ignition delay period was defined as the time interval from the start of fuel injection to the detection of flame signal by the ionization current sensor. The maximum ignition delay period was tested when the engine was running stably, and a two-dimensional query table of "injection direction-critical ignition delay period" was established. The ECU collects real-time working condition parameters such as engine speed, torque, and intake volume through the CAN bus, and uses a simplified engine mean value model as the state space model of Kalman filtering, where the state equation is the first-order inertia link of engine speed and torque, and the observation equation is the linear combination of speed and torque. The speed and torque signals are filtered. Combined with the "injection direction-critical ignition delay period" query table established by pre-calibration, the theoretical optimal injection direction is determined under the current working condition. The wide-range oxygen sensor installed on the exhaust pipe monitors the exhaust oxygen concentration in real time, and through the concentration-equivalence ratio conversion formula obtained by pre-calibration, the actual equivalence ratio of the mixture is calculated. Compare the deviation of the actual equivalence ratio and the target value, if the deviation exceeds the preset threshold, it is considered that the mixture uniformity does not meet the standard. Query the "injection direction-UI" quadratic polynomial regression model fitted in front, and calculate the correction amount of the injection direction. The injector angle adjustment command is generated and sent to the injector drive control unit through the CAN bus. Ensure that the mixture reaches the ideal uniformity, improve the combustion process, and improve the engine combustion efficiency.

[0034] For example, the optimization of dual-fuel engines involves multiple aspects, among which mixture uniformity and combustion efficiency are key factors. ANSYS Fluent software plays a crucial role in this process, simulating the internal combustion chamber conditions under different injection directions by building 3D models and meshing. For instance, one study simulated the mixture distribution as the injection angle varied from 0° to 60°. By calculating the velocity, pressure, and temperature distributions, a series of theoretical data were obtained, laying the foundation for subsequent analysis. The introduction of the mixture uniformity index (UI) enables quantitative analysis. In practical applications, it may be found that the UI value reaches its minimum when the injection angle is 30°, indicating the most uniform mixture distribution at this point. By establishing a quadratic polynomial regression model, an expression similar to UI = 0.02θ² - 1.2θ + 18 can be obtained, where θ represents the injection angle. This model not only intuitively reflects the relationship between injection direction and mixture uniformity but also provides a theoretical basis for real-time control. In a bench test, researchers might observe that when the injection angle increases from 15° to 45°, the ignition delay period decreases from 2.5 ms to 1.8 ms. This relationship is recorded as a lookup table, providing a reference for subsequent real-time control. For example, under operating conditions of 2000 rpm and 75% load, the system might look up the table to find that the optimal injection angle is 35°, corresponding to a critical ignition delay of 2.0 ms. The application of a Kalman filter in signal processing demonstrates the advanced nature of the control system. Suppose that in a certain test, the original speed signal fluctuates around 1800 rpm, and the filtered signal stabilizes at 1805 rpm. This smoothing process helps improve the accuracy of operating condition judgment, laying the foundation for subsequent injection control. The use of a wide-range oxygen sensor demonstrates the importance of closed-loop control. For example, the system might detect an oxygen concentration of 5% in the exhaust, which translates to an equivalence ratio of 0.9, a 10% deviation from the target value of 1.0. In this case, the control system will calculate, based on the "injection direction-UI" model, that the injection angle needs to be adjusted by 2° to improve the mixing uniformity. Finally, the correction command is sent to the injector drive unit via the CAN bus to achieve precise control. This fine adjustment ensures ideal uniformity of the air-fuel mixture, thereby improving combustion efficiency and reducing emissions.

[0035] S105. If the combustion rate is still lower than the preset lower limit, adjust the methanol injection timing to achieve the best timing coordination between methanol injection and diesel injection, ensuring stable engine output power while meeting the goal of efficient and clean operation.

[0036] Real-time acquisition of engine speed and torque signals, using the least squares method for curve fitting of the collected data, to get smooth speed and torque curve. According to the curve fitting, through the query engine performance map, get the current working condition of the theoretical combustion rate. Using pressure sensor to measure the in-cylinder pressure, the pressure signal is fast Fourier transform, extract the frequency domain characteristics of the pressure signal. According to the fundamental component amplitude A in the frequency domain characteristics and the in-cylinder pressure peak P_max, according to the formula r_actual=k·A / P_max, the actual combustion rate r_actual is calculated, wherein k is the calibration coefficient. The actual combustion rate and the theoretical value are compared, if the actual value is lower than 90% of the theoretical value, it is judged that the combustion rate is low. For the case of low combustion rate, read the pre-calibration of "methanol injection time-combustion rate" two-dimensional query table from ECU memory, take the current speed and torque as the index, calculate the optimal methanol injection time t_opt to improve the combustion rate to the theoretical value by bilinear interpolation method. According to the engine crankshaft position sensor signal, determine the crank angle θ_opt corresponding to the optimal methanol injection time t_opt. The crank angle is used as the pulse center of the injector driving signal, adjust the pulse width w and the duty cycle d, so that the starting time t_start and the duration t_dur of the methanol injection meet: t_start=θ_opt-w·d / 2, t_dur=w·d. Through the CAN bus, the control command (t_start, t_dur) is sent to the injector driving module to accurately control the methanol injection process. A feedforward neural network-based diesel-methanol injection time coordination model is established, with engine speed n, torque T, and combustion rate r as input, and two fuel injection time interval Δt as output. The hidden layer is set to 2 layers, and the number of nodes is 10 and 5 respectively. Select (n, T, r, Δt) sample pairs from the historical working condition database, and use Levenberg-Marquardt algorithm to train network parameters. Online call trained neural network model, dynamically adjust Δt, make the mixed fuel form the best mixing distribution in the combustion chamber, ensure the smooth and rapid combustion rate.

[0037] For example, the raw engine speed data fluctuates around 2000 rpm, while the fitted curve shows a stable 2005 rpm, providing a reliable basis for subsequent analysis. Engine performance maps are an important reference tool. By consulting the map, the theoretical combustion rate under a specific operating condition can be obtained. For example, under the condition of 2005 rpm and 200 Nm, the map shows that the theoretical combustion rate is 15 m / s. This benchmark value provides a reference for subsequent judgment. The pressure sensor measures the in-cylinder pressure, and the fast Fourier transform reveals the frequency domain characteristics of the pressure signal. The amplitude A of the fundamental component reflects the intensity of combustion, while the in-cylinder pressure peak P_max represents the limit of the combustion process. By the formula r_actual = k·A / P_max, the actual combustion rate can be estimated. Assuming that A = 500 kPa, P_max = 8000 kPa, and the calibration coefficient k = 0.2, then r_actual = 12.5 m / s is calculated. Comparing the actual combustion rate with the theoretical value can judge the combustion condition. In this example, the actual value 12.5 m / s is 90% lower than the theoretical value 15 m / s, indicating that the combustion rate is too low and needs to be adjusted. This comparison method can timely detect combustion abnormalities and provide a basis for adjusting the control strategy. The two-dimensional lookup table of "methanol injection time - combustion rate" established by pre-calibration is an efficient optimization tool. Through bilinear interpolation, the optimal injection time can be quickly found. For example, under the current operating condition, the lookup table gives the optimal injection time t_opt as -15° CA ATDC (i.e. 15° crank angle before top dead center). The choice of this time directly affects the combustion efficiency and emission performance. The crank position sensor signal is used to accurately position the injection time. Convert t_opt to crank angle θ_opt, and then adjust the pulse center, width and duty cycle of the injector drive signal accordingly to achieve precise fuel injection control. For example, if the pulse width w = 30° CA and the duty cycle d = 0.6, then the injection start time t_start = -24° CA ATDC and the duration t_dur = 18° CA can be calculated. The introduction of the neural network model embodies the intelligence of the control strategy. Taking engine speed, torque and combustion rate as input, and outputting the injection time interval of two fuels, more precise fuel collaborative control can be achieved. For example, the model may output that under the condition of 2005 rpm, 200 Nm and 12.5 m / s, the optimal injection time interval Δt is 2.5 ms. This dynamic adjustment ensures the optimal distribution of mixed fuel in the combustion chamber, which helps to improve combustion efficiency and reduce emissions.

[0038] The present application provides a diesel-methanol mixed fuel engine control system, mainly comprising:

[0039] A real-time working condition data acquisition module is configured to acquire real-time working condition data including engine speed, load and temperature parameters;

[0040] A fuel supply ratio calculation module is configured to determine the optimal supply ratio of diesel and methanol under the current working condition according to the real-time working condition data and in combination with a preset fuel characteristic difference model;

[0041] A mixture concentration adjustment module is configured to calculate the mixture concentration of methanol and diesel according to the optimal supply ratio, and adjust the injection pressure of methanol to return the mixture concentration to the target range if the mixture concentration exceeds the preset threshold.

[0042] A combustion rate judgment module is configured to judge whether the current mixture combustion rate meets the engine stable operation requirement through a preset combustion rate difference model after the adjustment of the methanol injection pressure, and increase the methanol injection frequency to improve the mixture combustion rate if the combustion rate is lower than the preset lower limit value.

[0043] An injection parameter optimization module is configured to adjust the injection direction of the methanol injector to improve the mixture uniformity if the combustion rate is lower than the preset lower limit value after the increase of the methanol injection frequency, and adjust the methanol injection timing to form the optimal cooperation between the methanol injection and the diesel injection in time to ensure the stable engine output power and meet the target of high-efficiency and clean operation.

[0044] Although the present application has been described in detail with general description and specific embodiments above, some modifications or improvements can be made on the basis of the present application, which is obvious to those skilled in the art. Therefore, these modifications or improvements made on the basis of not deviating from the spirit of the present application shall fall within the scope of the present application.

Claims

1. A control method for a diesel-methanol blended fuel engine, characterized in that, The method includes: Acquire real-time operating condition data including engine speed, load, and temperature parameters. Based on the real-time operating condition data and a preset fuel characteristic difference model, determine the optimal supply ratio of diesel and methanol under the current operating conditions. Calculate the concentration of the methanol-diesel mixture based on the optimal supply ratio; if the mixture concentration exceeds the preset threshold, adjust the methanol injection pressure to bring the mixture concentration back to the target range. After adjusting the methanol injection pressure, the current air-fuel mixture combustion rate is determined to meet the requirements for stable engine operation by using a preset combustion rate difference model. If the combustion rate is lower than the preset lower limit, the methanol injection frequency is increased to improve the air-fuel mixture combustion rate. If the combustion rate is lower than the preset lower limit after increasing the methanol injection frequency, the injection direction of the methanol injector will be adjusted to improve the mixing uniformity. If the combustion rate is still lower than the preset lower limit, adjust the methanol injection timing to achieve the best timing coordination between methanol injection and diesel injection, ensuring stable engine output power while meeting the goal of efficient and clean operation.

2. The method according to claim 1, characterized in that, The acquisition of real-time operating condition data, including engine speed, load, and temperature parameters, and the determination of the optimal diesel to methanol supply ratio under the current operating conditions based on the real-time operating condition data and a preset fuel characteristic difference model, includes: A difference database containing combustion characteristic parameters of diesel and methanol fuels under different operating conditions was obtained, and the difference database was used as training data for the BP neural network model. The engine's real-time operating parameters, including speed, load, and intake air volume, are obtained and used as input to the BP neural network model. Using a pre-trained BP neural network model, a nonlinear mapping relationship between real-time operating parameters, fuel characteristic parameters and combustion efficiency is established, and a comprehensive index characterizing combustion efficiency is output. The K-means clustering algorithm is used to divide the real-time operating condition data points at different times into several typical operating condition categories, with each typical operating condition corresponding to a cluster center; The characteristic parameters of each cluster center are input into the BP neural network model to obtain the corresponding comprehensive combustion efficiency index. For each typical operating condition, the fuel mixing ratio is used as the optimization variable. The genetic algorithm is used to search for the optimal mixing ratio that maximizes the comprehensive combustion efficiency index. The fitness function of the genetic algorithm is the comprehensive index output by the BP neural network model, and the constraint condition is the range of values ​​for the mixing ratio. Based on the optimal mixing ratio obtained from the genetic algorithm search under each typical working condition, a mapping relationship between real-time working condition parameters and the optimal mixing ratio is established. In actual operation, the optimal mixing ratio of diesel and methanol is determined based on the engine's real-time operating parameters, and fuel mixing control commands are output.

3. The method according to claim 1, characterized in that, The process involves calculating the concentration of the methanol-diesel mixture based on the optimal supply ratio; if the mixture concentration exceeds a preset threshold, adjusting the methanol injection pressure to bring the mixture concentration back to the target range, including: Obtain the stoichiometric equations for diesel and methanol, calculate the optimal mass ratio of diesel to methanol based on the stoichiometric equations, and determine the theoretical air-fuel ratio of the mixed fuel based on the optimal mass ratio. Real-time monitoring of the actual supply quality of diesel and methanol, and calculation of the actual concentration value of the mixed fuel based on the actual supply quality; Obtain the concentration range required for safe and stable combustion under different operating conditions, which is obtained in advance through system integration tests, and set the concentration range as the threshold range for concentration control; Determine if the actual concentration value exceeds the threshold range; if so, trigger the methanol injection pressure adjustment mechanism. Obtain the response curve between methanol injection pressure and fuel concentration established in advance through experiments, and obtain the corresponding target pressure value by looking up the table based on the actual excess of the concentration value; The target pressure value is used as the set value of the PID control algorithm, and the actual pressure value is used as the feedback value. The operation of the methanol injection device is controlled by adjusting the proportional, integral and derivative parameters of the PID controller, so as to realize the automatic adjustment of the injection pressure. During the pressure regulation process, the actual concentration value of the mixed fuel is continuously collected, the concentration error between the actual concentration value and the target concentration value is calculated, and the concentration error is introduced into the PID controller for adaptive correction of the control parameters. Long-term continuous monitoring of the mixed fuel concentration is conducted, and the concentration change trend is predicted through time series analysis. When the predicted concentration value is at risk of exceeding the threshold range, the methanol injection pressure is fine-tuned in advance to avoid instability caused by drastic concentration changes.

4. The method according to claim 1, characterized in that, After adjusting the methanol injection pressure, a preset combustion rate difference model is used to determine whether the current air-fuel mixture combustion rate meets the requirements for stable engine operation. If the combustion rate is lower than a preset lower limit, the methanol injection frequency is increased to improve the air-fuel mixture combustion rate, including: Obtain a pre-established mapping table between fuel injection parameters and combustion rate. The mapping table contains multiple sets of fuel injection pressure, injection frequency and corresponding theoretical combustion rate data. Obtain a lookup table of engine combustion rate lower limits obtained from pre-tests. The lookup table contains combustion rate lower limit data for multiple engine speeds and load conditions. Obtain the current engine speed and load parameters, perform two-dimensional interpolation in the lookup table, and obtain the lower limit of the combustion rate required for stable engine operation under the current working conditions; Obtain the actual combustion rate of the mixed fuel, compare the actual combustion rate with the lower limit value, and calculate the difference between the actual value and the lower limit value; If the difference is less than zero, an interpolation query is performed in the mapping table to obtain the fuel injection frequency correction amount that needs to be adjusted. Based on the frequency correction amount and the current injection frequency, determine the corrected target injection frequency; Based on the target injection frequency, the corresponding injector opening and closing time parameters are determined, PWM control commands are generated, and sent to the fuel injection device via the CAN bus to adjust the injector opening and closing time, thereby achieving dynamic adjustment of the fuel injection frequency and ensuring that the actual combustion rate meets the requirements for stable engine operation.

5. The method according to claim 1, characterized in that, If, after increasing the methanol injection frequency, the combustion rate is lower than a preset lower limit, the injection direction of the methanol injector is adjusted to improve mixing uniformity, including: The engine speed and torque signals under the current operating conditions are obtained, and a simplified engine mean model is used as the state space model of the Kalman filter to filter and estimate the speed and torque signals. Based on the estimated engine speed and torque under the current operating conditions, the theoretically optimal injection direction under the current operating conditions is determined by querying the pre-calibrated two-dimensional lookup table of "injection direction - critical ignition delay period". The system acquires the exhaust oxygen concentration signal monitored in real time by a wide-range oxygen sensor installed on the exhaust pipe, and calculates the actual equivalent ratio of the current air-fuel mixture according to a pre-calibrated concentration-equivalent ratio conversion formula. If the deviation between the actual equivalence ratio and the target equivalence ratio exceeds a preset threshold, the correction amount of the injection direction is calculated in the pre-fitted quadratic polynomial regression model of "injection direction-mixture uniformity". Based on the injection direction correction amount, an injector angle adjustment command is generated and sent to the injector drive control unit via the CAN bus to adjust the injection direction of the injector to ensure that the air-fuel mixture achieves ideal uniformity.

6. The method according to claim 1, characterized in that, If the combustion rate is still lower than the preset lower limit, the methanol injection timing will be adjusted to achieve optimal timing coordination between methanol and diesel injection, ensuring stable engine output power while meeting the goal of efficient and clean operation, including: The engine speed and torque signals are acquired, and the least squares method is used to perform curve fitting on the speed and torque signals to obtain smooth speed and torque curves. Based on the smooth speed and torque curves, the theoretical combustion rate under the current operating conditions is obtained by querying a pre-established engine performance map. Acquire the in-cylinder pressure signal, perform a fast Fourier transform on the in-cylinder pressure signal, and extract the frequency domain features of the in-cylinder pressure signal. The actual combustion rate is calculated according to a preset formula based on the amplitude of the fundamental component in the frequency domain characteristics and the peak pressure in the cylinder. Determine whether the actual combustion rate is lower than the preset percentage threshold of the theoretical combustion rate. If so, determine that the combustion rate is too low. When the combustion rate is determined to be too low, the optimal methanol injection time required to increase the combustion rate to the theoretical value is calculated from the pre-calibrated two-dimensional lookup table of "methanol injection time-combustion rate" using the current speed and torque as indexes and bilinear interpolation. Acquire the engine crankshaft position sensor signal to determine the target crankshaft angle corresponding to the optimal methanol injection time; Based on the target crankshaft angle, adjust the pulse parameters of the injector drive signal to control the start time and duration of methanol injection; The methanol injection control command is sent to the injector drive module via the bus to precisely control the methanol injection process. Historical operating condition data samples were obtained, and a diesel-methanol injection time coordination model based on a feedforward neural network was established using machine learning algorithms. The online collaborative model is invoked, and the injection time interval of the two fuels is dynamically adjusted with engine speed, torque and combustion rate as inputs to form the optimal blending distribution of the mixed fuel and ensure a stable and rapid combustion rate.

7. A diesel-methanol blended fuel engine control system, characterized in that, The system includes: The real-time operating condition data acquisition module is used to acquire real-time operating condition data, including engine speed, load, and temperature parameters. The fuel supply ratio calculation module is used to determine the optimal supply ratio of diesel and methanol under the current operating conditions based on real-time operating data and a preset fuel characteristic difference model. The mixture concentration adjustment module is used to calculate the mixture concentration of methanol and diesel according to the optimal supply ratio; if the mixture concentration exceeds the preset threshold, the injection pressure of methanol is adjusted to bring the mixture concentration back to the target range. The combustion rate judgment module is used to determine whether the current air-fuel mixture combustion rate meets the requirements for stable engine operation after the methanol injection pressure is adjusted, based on a preset combustion rate difference model. If the combustion rate is lower than the preset lower limit, the methanol injection frequency is increased to improve the air-fuel mixture combustion rate. The injection parameter optimization module is used to adjust the injection direction of the methanol injector to improve the mixing uniformity if the combustion rate is lower than the preset lower limit after increasing the methanol injection frequency; if the combustion rate is still lower than the preset lower limit, the methanol injection timing is adjusted to make the methanol injection and diesel injection optimally matched in time, ensuring stable engine output power and meeting the goal of efficient and clean operation.

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