Fuel consumption optimization method and system, storage medium and electronic equipment

Abstract

The invention provides a fuel consumption optimization method and system, a storage medium and electronic equipment, and relates to the technical field of diesel generator fuel consumption control, and the method comprises the steps: collecting and processing environment information and working condition information through preset sensing equipment; fitting a preset function corresponding to a preset combustion model according to the working condition information, and adjusting parameters of the preset function according to fitting data and the environment information so as to determine a target function; and determining a target control parameter through an optimization algorithm according to the working condition information and the environment information by taking the target function as a constraint, so as to control the real-time fuel consumption of the diesel generating set according to the target control parameter. The problem that in the prior art, a diesel generating set fuel oil consumption optimization method for dynamically optimizing the fuel oil utilization and combustion state based on the complex working condition lacks is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of diesel generator fuel consumption control, and in particular relates to a fuel consumption optimization method and system, a storage medium and an electronic device. BACKGROUND

[0002] The diesel generator set is an industrial power supply device formed by integrating a diesel engine as the core power source, a generator, and a control screen and other key components. Its working principle is to convert heat energy into mechanical energy through diesel combustion, and then further convert the mechanical energy into electrical energy to realize power output.

[0003] Such devices have a wide range of applications, not only for emergency power supply during power grid failures, but also as a standby power source in industrial production, and at the same time, they bear the core power supply task in polar scientific exploration, remote field, and other scenarios without power grid coverage. The existing fuel consumption control of diesel generator sets mostly adopts a fixed "load-speed" mode and a simple fuel injection adjustment strategy, that is, according to the power generation demand, the gear is controlled, and by monitoring the basic load, engine speed, fuel pressure and other parameters, the fuel injection amount and air intake amount are adjusted to adapt to the operation requirements of different gears.

[0004] However, in remote areas without power grid coverage or in harsh environments such as low temperature and high temperature, the device often needs to be powered for a long time, which puts higher requirements on the precise control of fuel consumption and the effective guarantee of combustion efficiency, that is, it needs to dynamically optimize the fuel utilization and combustion state based on complex working conditions. However, the existing control method lacks targeted adaptation to the characteristics of the device in extreme environments, making it difficult to achieve precise regulation and control of fuel consumption, and only meets the basic power supply demand in conventional scenarios such as power grid failure, and cannot adapt to the operation requirements of long time, high efficiency and low emission in extreme environments. SUMMARY

[0005] Therefore, the present application aims to provide a fuel consumption optimization method and system, a storage medium and an electronic device, which aims to solve the problem of lacking a diesel generator set fuel consumption optimization method based on dynamic optimization of fuel utilization and combustion state under complex working conditions in the prior art.

[0006] According to the fuel consumption optimization method of the present application, the method comprises: acquiring and processing environmental information and working condition information through a preset sensing device; fitting a preset function corresponding to a preset combustion model according to the working condition information, to adjust the parameters of the preset function according to the fitting data and the environmental information, and then determine a target function; Determine a target control parameter according to the working condition information and the environment information by an optimization algorithm with the target function as a constraint, so as to control real-time fuel consumption of the diesel generating set according to the target control parameter.

[0007] In addition, the fuel consumption optimization method according to the above-mentioned embodiment of the application can further have the following additional technical features: Further, the step of fitting a preset function corresponding to the preset combustion model according to the working condition information, adjusting parameters of the preset function according to fitting data and the environment information, and determining a target function further includes: Determine an actual mass combustion fraction curve and corresponding real-time combustion start angle and real-time combustion duration according to the working condition information; Correct the real-time combustion start angle and the real-time combustion duration according to the environment information to determine a target combustion start angle and a target combustion duration; Substitute the target combustion start angle and the target combustion duration into the preset function, and fit a theoretical mass combustion fraction curve predicted by the preset combustion model and the actual mass combustion fraction curve to determine a target combustion efficiency coefficient and a target combustion shape index; Substitute the target combustion efficiency coefficient, the target combustion shape index, the target combustion start angle and the target combustion duration into the preset function to determine the target function; The preset function is:

[0008] wherein, is a burned fuel mass fraction, is a combustion efficiency coefficient, is a current crank angle, is a combustion start angle, is a combustion duration, is a combustion shape index.

[0009] Further, the step of correcting the real-time combustion start angle and the real-time combustion duration according to the environment information to determine a target combustion start angle and a target combustion duration further includes: Correct the real-time combustion start angle and the real-time combustion duration according to the environment information by a combustion start angle correction equation and a combustion duration correction equation to determine a target combustion start angle and a target combustion duration; The combustion start angle correction equation is:

[0010] wherein, is a target combustion start angle, a real-time combustion start angle, a temperature compensation amount, a viscosity compensation amount, a drift compensation amount; The combustion duration correction equation is:

[0011] wherein, a target combustion duration, a real-time combustion duration, a temperature compensation factor, a viscosity compensation factor, a combustion state factor.

[0012] Further, the step of determining the target control parameter according to the working condition information and the environment information by the optimization algorithm with the target function as a constraint comprises: constructing a multi-objective optimization function, and determining a current working condition state according to the working condition information; determining a target optimization algorithm according to the working condition state, and determining the target control parameter according to the multi-objective optimization function, the working condition information and the environment information by the target optimization algorithm.

[0013] Further, the step of determining the target control parameter according to the multi-objective optimization function, the working condition information and the environment information by the target optimization algorithm comprises: predicting a theoretical fuel index according to the target control parameter, the working condition information and the environment information on a fuel consumption index of a preset time period; acquiring an actual fuel index of the preset time period and comparing the actual fuel index with the theoretical fuel index to determine difference data, and adjusting the multi-objective optimization function and the target optimization algorithm according to the difference data.

[0014] Further, the step of collecting and processing the environment information and the working condition information by the preset sensing device comprises: determining a change rate of the environment information and the working condition information, and judging whether the change rate of the environment information or the working condition information exceeds a preset change threshold; if yes, producing a temporary control parameter by a preset fast convergence optimization model within a preset time based on the current working condition information, the environment information and a historical optimal control parameter, and controlling a real-time fuel consumption of the diesel generator set according to the temporary control parameter; if no, performing the step of fitting a preset function corresponding to the preset combustion model according to the working condition information, adjusting parameters of the preset function according to fitting data and the environment information, and determining a target function.

[0015] Further, the step of collecting and processing the environment information and the working condition information by the preset sensing device comprises: synchronously acquiring multi-source information collected by multiple sensors and time stamp aligning the multi-source information, and filtering and determining multi-source correction information by corresponding methods according to information types; standardizing the multi-source correction information and classifying to determine the working condition information and the environment information.

[0016] Another object of the present application is to provide a fuel consumption optimization system, which comprises: a data acquisition module for collecting and processing the environment information and the working condition information by the preset sensing device; a function adjustment module for fitting a preset function corresponding to a preset combustion model according to the working condition information, adjusting parameters of the preset function according to fitting data and the environment information, and determining a target function; a parameter determination module for determining a target control parameter by an optimization algorithm with the target function as a constraint according to the working condition information and the environment information, and controlling real-time fuel consumption of the diesel generator set according to the target control parameter.

[0017] The present application collects real-time environment information and working condition information, fits and adjusts a preset function corresponding to a preset combustion model according to real-time information, obtains a corresponding target function under current environment and working condition, determines a real-time fuel combustion model by the target function, adjusts each control parameter according to an optimization algorithm under the constraint of the target function, determines fuel utilization, combustion condition and combustion emission parameters under different control parameters, current environment and working condition, and thus can determine optimal control parameters according to complex working conditions and environment. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 a flow chart of the fuel consumption optimization method in the first embodiment of the present application; Figure 2 a result schematic diagram of the fuel consumption optimization system in the second embodiment of the present application; Figure 3 a structure schematic diagram of the electronic device in the third embodiment of the present application; The following specific embodiments will further illustrate the present application in combination with the above drawings. DETAILED DESCRIPTION

[0019] For the purpose of promoting the understanding of the present application, a more complete description of the application will be rendered by reference to specific embodiments thereof which are depicted in the accompanying drawings. These embodiments are non-limiting examples of the present application and are intended to provide further support for the disclosure of the application. The application may, of course, be carried out in many different ways, and is therefore not limited to these embodiments. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0021] Embodiment one Please refer to Figure 1 , which shows the fuel consumption optimization method in the first embodiment of the present application, which specifically includes steps S01-S03.

[0022] S01, collecting and processing environmental information and working condition information through a pre-set sensing device.

[0023] Specifically, multi-source information collected by multiple sensors is synchronously acquired and time-stamped, and the multi-source correction information is determined by filtering through corresponding methods according to information types; the multi-source correction information is standardized and classified to determine the working condition information and the environmental information. Specifically, through the spatio-temporal alignment technology of multi-source sensing information, combined with signal classification processing mechanism, i.e. differential filtering of cylinder pressure, speed and temperature, the effectiveness of environmental information and working condition information is guaranteed from the data source, and high signal-to-noise ratio input is provided for upper-level decision-making.

[0024] In addition, after step S01, the fuel consumption optimization method in the present application further includes determining the change rate of the environmental information and the working condition information, and determining whether the change rate of the environmental information or the working condition information exceeds a pre-set change threshold; if yes, temporary control parameters are generated within a pre-set time through a pre-set fast convergence optimization model based on the current working condition information, the environmental information and the historical optimal control parameters, so as to control the real-time fuel consumption of the diesel generator set according to the temporary control parameters; if not, step S02 is executed. Specifically, for dramatic changes in environmental or working condition parameters, a multi-level response chain of change rate detection, historical parameter calling, simplified optimization, etc. is constructed. Through the fast convergence model, feasible control parameters are generated in a short time, avoiding the risk of flameout caused by calculation delay in traditional methods, and providing safety redundancy for extreme working conditions.

[0025] S02, fitting a preset function corresponding to a preset combustion model according to the working condition information, adjusting parameters of the preset function according to fitting data and the environment information, and determining a target function.

[0026] Specifically, an actual mass combustion fraction curve and corresponding real-time combustion start angle and real-time combustion duration are determined according to the working condition information; a target combustion start angle and a target combustion duration are determined by correcting the real-time combustion start angle and the real-time combustion duration according to the environment information; the target combustion start angle and the target combustion duration are substituted into the preset function, and a target combustion efficiency coefficient and a target combustion mode index are determined by fitting a theoretical mass combustion fraction curve predicted by the preset combustion model and the actual mass combustion fraction curve; the target combustion efficiency coefficient, the target combustion mode index, the target combustion start angle and the target combustion duration are substituted into the preset function to determine the target function; the preset function is:

[0027] wherein, is a burned fuel mass fraction, is a combustion efficiency coefficient, is a current crank angle, is a combustion start angle, is a combustion duration, is a combustion mode index. Specifically, the actual combustion curve is dynamically matched with the theoretical model by a fitting technique of a function. The combustion phase parameters (start angle / duration) corrected by the environment compensation are implanted into the model, which significantly improves the prediction accuracy of the combustion state under extreme conditions and lays a mathematical model foundation for the implementation of the optimization algorithm.

[0028] Further, the step of correcting the real-time combustion start angle and the real-time combustion duration according to the environment information to determine the target combustion start angle and the target combustion duration includes: correcting the real-time combustion start angle and the real-time combustion duration according to the environment information by a combustion start angle correction equation and a combustion duration correction equation to determine the target combustion start angle and the target combustion duration. The combustion start angle correction equation is:

[0029] wherein, is a target combustion start angle, is a real-time combustion start angle, is a temperature compensation amount, is a viscosity compensation amount, is a drift compensation amount; The combustion duration correction equation is:

[0030] wherein, is a target combustion duration, is a real-time combustion duration, is a temperature compensation factor, is a viscosity compensation factor, is a combustion state factor. By multi-physical field coupling, the influence of the environment on the target parameter is determined, and correction is made to realize environmental compensation. The timing control problems such as low-temperature ignition delay and abnormal fuel atomization are solved, so that the ignition phase still maintains sufficient precision in extreme environments. And according to the environmental conditions, the length of the combustion window is dynamically adjusted to ensure the accuracy of the combustion duration. Further, through the double compensation mechanism, the combustion integrity under complex environment is ensured.

[0031] S03. According to the working condition information and the environmental information, a target control parameter is determined by an optimization algorithm with the target function as a constraint, so as to control the real-time fuel consumption of the diesel generator set according to the target control parameter.

[0032] Specifically, a multi-objective optimization function is constructed, and the current working condition state is determined according to the working condition information; a target optimization algorithm is determined according to the working condition state, and a target control parameter is determined by the target optimization algorithm according to the multi-objective optimization function, the working condition information and the environmental information. In specific implementation, according to the specific scene and working condition, the adaptability of different optimization algorithms is different, and the corresponding target optimization algorithm needs to be selected according to the actual situation. More specifically, the optimization algorithm can include a particle swarm algorithm, which is suitable for the stage of dramatic change of system state, such as cold start process, load mutation working condition or first running without historical data. The optimization algorithm can include a gradient descent method, which is suitable for the stage of stable operation of the system, such as the working condition of small speed fluctuation and load change. The optimization algorithm can include a case reasoning method, which is suitable for the emergency state of the system, such as sudden straight line of sensor, transient process control overshoot and other sudden conditions, and historical cases are used to quickly respond to emergencies.

[0033] Further, after step S03, the fuel consumption optimization method in the application further comprises predicting and determining a theoretical fuel index of a preset time period according to the target control parameter, the working condition information and the environment information; acquiring an actual fuel index of the preset time period and comparing the actual fuel index with the theoretical fuel index to determine difference data, so as to adjust the multi-target optimization function and the target optimization algorithm according to the difference data. Specifically, by analyzing the difference between the theoretical fuel index prediction and the actual operation data, a reverse calibration channel of the model parameter is established. When the environment deteriorates or the equipment ages, causing the combustion model to deviate, this mechanism drives the system to update the key parameters such as the combustion efficiency coefficient and the shape index autonomously, so that the optimization capability continuously enhances over time, effectively resisting system performance degradation.

[0034] In summary, the fuel consumption optimization method in the above-mentioned embodiments of the application collects real-time environment information and working condition information, adjusts a preset function corresponding to a preset combustion model according to real-time information, to obtain a target function corresponding to the current environment and working state, that is, to determine a real-time fuel combustion model through the target function, so that under the constraint of the target function, each control parameter is adjusted according to the optimization algorithm, to determine the fuel utilization rate, combustion condition and combustion emission under different control parameters, the current environment and working state, so that the optimal control parameter can be determined according to complex working conditions and environment. Therefore, the application solves the problem of lacking a fuel consumption optimization method for diesel generator sets based on dynamic optimization of fuel utilization and combustion state under complex working conditions in the prior art.

[0035] Embodiment two Please refer to Figure 2 , which is a structural block diagram of the fuel consumption optimization system in the second embodiment of the application. The fuel consumption optimization system 200 comprises a data acquisition module 21, a function adjustment module 22 and a parameter determination module 23, wherein: The data acquisition module 21 is configured to collect and process environment information and working condition information through a preset sensing device. The function adjustment module 22 is configured to fit a preset function corresponding to a preset combustion model according to the working condition information, to adjust the parameters of the preset function according to the fitting data and the environment information, and to determine a target function. The parameter determination module 23 is configured to determine a target control parameter through an optimization algorithm according to the working condition information and the environment information under the constraint of the target function, and to control the real-time fuel consumption of the diesel generator set according to the target control parameter.

[0036] The functions or operation steps realized when the above-mentioned modules are executed are generally the same as those of the above-mentioned method embodiments, and will not be described here again.

[0037] Embodiment Three Another aspect of the present application provides an electronic device, referring to Figure 3 , which is a schematic diagram of an electronic device in the third embodiment of the present application, comprising a memory 20, a processor 10, and a computer program 30 stored in the memory and capable of running on the processor, wherein the processor 10 implements the fuel consumption optimization method as described above when executing the computer program 30.

[0038] In some embodiments, the processor 10 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip, for running program codes or processing data stored in the memory 20, such as executing access restriction programs.

[0039] In some embodiments, the memory 20 can be an internal storage unit of the electronic device, such as a hard disk of the electronic device. In other embodiments, the memory 20 can also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 20 can include both an internal storage unit and an external storage device. The memory 20 can be used not only for storing application software and various data of the electronic device, but also for temporarily storing data that has been output or will be output.

[0040] It should be noted that Figure 3 The structure shown does not constitute a limitation on the electronic device, and in other embodiments, the electronic device can include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0041] The embodiments of the present application also provide a computer readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the fuel consumption optimization method as described above.

[0042] Those skilled in the art can appreciate that the logic and / or steps represented in the flow diagrams, or otherwise described herein, can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device, such as a computer-based system, processor- containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions, or in conjunction with which the instructions can be executed. In the context of this specification, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.

[0043] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can also be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that can be later executed by a computer. In some embodiments, the computer-readable medium can be a transmission medium that can contain, store, or carry the program for use by or in connection with an instruction execution system, apparatus, or device.

[0044] It should be understood that aspects of the application can be implemented in hardware, software, firmware, or combinations thereof. In the embodiments described above, various steps or methods can be implemented, for example, by software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following techniques, which are well known in the art, can be used to implement the various techniques and technologies described herein: a discrete logic circuit(s) having logic gates for implementing logic functions upon data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), and / or the like.

[0045] In the description of the specification, reference to "one embodiment" "some embodiments" "an example" "a specific example" or "some examples" etc. means that a particular feature, structure, material, or characteristic being described in connection with the embodiment or example is included in at least one embodiment or example of the application. The appearances of the above-described terms in various places in the specification are not necessarily referring to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0046] The above embodiments only express several implementation manners of the present application, the description is more specific and detailed, but it cannot be understood as the limitation of the patent scope of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for optimizing fuel consumption, characterized in that, The method for controlling fuel consumption of a diesel generator set includes: Environmental and operating condition information is collected and processed through pre-set sensing devices; The preset function corresponding to the preset combustion model is fitted according to the operating condition information, and the parameters of the preset function are adjusted according to the fitted data and the environmental information to determine the target function. Using the objective function as a constraint, the target control parameters are determined through an optimization algorithm based on the operating condition information and the environmental information, so as to control the real-time fuel consumption of the diesel generator set according to the target control parameters.

2. The fuel consumption optimization method according to claim 1, characterized in that, The steps of fitting a preset function corresponding to a preset combustion model based on the operating condition information, and adjusting the parameters of the preset function based on the fitted data and the environmental information to determine the target function include: Based on the aforementioned operating condition information, determine the actual mass combustion fraction curve and the corresponding real-time combustion initiation angle and real-time combustion duration; Based on the environmental information, the real-time combustion initiation angle and the real-time combustion duration are corrected to determine the target combustion initiation angle and the target combustion duration. Substitute the target combustion initiation angle and the target combustion duration into the preset function, and fit the theoretical mass combustion fraction curve predicted by the preset combustion model with the actual mass combustion fraction curve to determine the target combustion efficiency coefficient and the target combustion morphology index. The target combustion efficiency coefficient, the target combustion morphology index, the target combustion initiation angle, and the target combustion duration are substituted into the preset function to determine the target function; The preset function is: in, The mass fraction of the fuel already burned. The combustion efficiency coefficient, This is the current crankshaft angle. The combustion initiation angle, The duration of combustion, This is the combustion state index.

3. The fuel consumption optimization method according to claim 2, characterized in that, The steps for determining the target combustion initiation angle and target combustion duration by correcting the real-time combustion initiation angle and the real-time combustion duration based on the environmental information include: Based on the environmental information, the real-time combustion initiation angle and the real-time combustion duration are corrected using the combustion initiation angle correction equation and the combustion duration correction equation to determine the target combustion initiation angle and the target combustion duration. The combustion initiation angle correction equation is: in, The starting angle for the target combustion. For real-time combustion initiation angle, This is the temperature compensation amount. For viscosity compensation, This is the drift compensation amount; The corrected equation for the combustion duration is: in, For the target combustion duration, For real-time combustion duration, For temperature compensation factor, It is the viscosity compensation factor. This is the combustion state factor.

4. The fuel consumption optimization method according to claim 3, characterized in that, The steps of determining the target control parameters using the objective function as a constraint and based on the operating condition information and the environmental information through an optimization algorithm include: Construct a multi-objective optimization function and determine the current working condition state based on the working condition information; The target optimization algorithm is determined based on the operating conditions, and the target control parameters are determined by the target optimization algorithm based on the multi-objective optimization function, the operating conditions information, and the environmental information.

5. The fuel consumption optimization method according to claim 4, characterized in that, After the step of determining the target control parameters using the target optimization algorithm based on the multi-objective optimization function, the operating condition information, and the environmental information, the following steps are included: Based on the target control parameters, the operating condition information, and the environmental information, the fuel consumption index for a preset time period is predicted to determine the theoretical fuel index. The actual fuel index for a preset time period is obtained and compared with the theoretical fuel index to determine the difference data, so as to adjust the multi-objective optimization function and the objective optimization algorithm according to the difference data.

6. The fuel consumption optimization method according to claim 1, characterized in that, Following the steps of collecting and processing environmental and operational information through preset sensing devices, the following is included: Determine the rate of change of the environmental information and the operating condition information, and determine whether the rate of change of the environmental information or the operating condition information exceeds a preset change threshold; If so, based on the current operating condition information, the environmental information, and the historical optimal control parameters, temporary control parameters are generated within a preset time using a preset fast convergence optimization model, so as to control the real-time fuel consumption of the diesel generator set according to the temporary control parameters; If not, perform the step of fitting a preset function corresponding to a preset combustion model based on the operating condition information, and adjusting the parameters of the preset function based on the fitted data and the environmental information to determine the target function.

7. The fuel consumption optimization method according to claim 1, characterized in that, The steps for collecting and processing environmental and operational information using preset sensing devices include: Simultaneously acquire multi-source information collected by multiple sensors and align the multi-source information with timestamps, and filter and determine multi-source correction information by using corresponding methods according to information type; The multi-source correction information is standardized and classified to determine operating condition information and environmental information.

8. A fuel consumption optimization system, characterized in that, The system for implementing the fuel consumption optimization method as described in any one of claims 1 to 7 includes: The data acquisition module is used to collect and process environmental and operating condition information through preset sensing devices; The function adjustment module is used to fit a preset function corresponding to a preset combustion model based on the operating condition information, and to adjust the parameters of the preset function based on the fitted data and the environmental information to determine the target function. The parameter determination module is used to determine target control parameters based on the operating condition information and the environmental information using an optimization algorithm, with the objective function as a constraint, so as to control the real-time fuel consumption of the diesel generator set according to the target control parameters.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the fuel consumption optimization method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the fuel consumption optimization method as described in any one of claims 1-7.

Images