Enhanced minimum mass limit for direct injection engines

Abstract

According to example embodiments, methods and systems for controlling fuel injection of a fuel injector of a direct injection engine are provided. In one embodiment, a method includes storing a first table of values in a first data storage device, storing a second table of values in a second data storage device, and adjusting a minimum mass value for controlling fuel injection based on an injector learning value, the first table, and the second table via instructions provided by a processor of a vehicle, wherein the injector learning value is set based on an amount of injector learning completed.

Description

TECHNICAL FIELD

[0001] The technical field relates generally to the field of vehicles, and more particularly, to control of fuel injection in a vehicle engine. BACKGROUND

[0002] Many vehicles today have a drive system comprising an engine, such as a combustion engine. A direct injection combustion engine (hereinafter also referred to as a direct injection engine) comprises a fuel injector for each cylinder. Fuel, such as gasoline, is injected directly into the combustion chamber via the fuel injector and mixed with intake air introduced into the combustion chamber from an inlet to form a mixture which can be ignited by a spark plug. Direct injection engines have low fuel consumption, low emissions and high power output.

[0003] Fuel is injected according to a defined mass. The amount of fuel injected by a fuel injector is typically limited by a minimum mass, which is typically static in the engine system. Fuel priming errors can occur, which affect fuel injection near the minimum mass limit. It is therefore desirable to provide an improved system and method for controlling fuel injection in a direct injection engine of a vehicle. Further, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and this background of the invention. SUMMARY

[0004] According to an exemplary embodiment, a method for controlling fuel injection of a fuel injector of a direct injection engine is provided, the method comprising: storing a first table of values in a first data storage device; storing a second table of values in a second data storage device; and adjusting, via instructions provided by a processor of a vehicle, a minimum mass value for controlling fuel injection based on an injector learning value, the first table and the second table. The injector learning value is set based on an amount of injector learning completed.

[0005] In various embodiments, the first table is defined by a plurality of injector learning values and a plurality of mass values.

[0006] In various embodiments, the second table is defined by a plurality of injector learning values and a plurality of mass values.

[0007] In various embodiments, adjusting the minimum mass value is based on a blend of a mass value from the first table and a mass value from the second table according to the injector learning value.

[0008] In various embodiments, the injector learning value is a value ranging from zero to one, and when the injector learning value is zero, the amount of injector learning completed is zero, and when the injector learning value is one, the amount of injector learning is full.

[0009] In various embodiments, the minimum quality value is set to a highest quality value of the plurality of quality values when the injector learning value is zero.

[0010] In various embodiments, the minimum quality value is set to a lowest quality value of the plurality of quality values when the injector learning value is one.

[0011] In another embodiment, a system for controlling fuel injection by fuel injectors of a direct injection engine is provided. The system includes a data storage device configured to store a first table of values and a second table of values, and a processor configured to facilitate, at least, adjustment of a minimum quality value for controlling fuel injection based on an injector learning value, the first table, and the second table. The injector learning value is set based on an amount of injector learning that is complete.

[0012] In various embodiments, the first table is defined by a plurality of injector learning values and a plurality of quality values.

[0013] In various embodiments, the second table is defined by a plurality of injector learning values and a plurality of quality values.

[0014] In various embodiments, adjustment of the minimum quality value is based on a blend of a quality value from the first table and a quality value from the second table according to the injector learning value.

[0015] In various embodiments, the injector learning value is a value ranging from zero to one, and the amount of injector learning that is complete is zero when the injector learning value is zero, and the amount of injector learning is full when the injector learning value is one.

[0016] In various embodiments, the minimum quality value is set to a highest quality value of the plurality of quality values when the injector learning value is zero.

[0017] In various embodiments, the minimum quality value is set to a lowest quality value of the plurality of quality values when the injector learning value is one.

[0018] In another embodiment, a vehicle is provided. The vehicle includes an engine having a plurality of fuel injectors, one or more sensors of the vehicle configured to sense an observable condition of the plurality of fuel injectors, and a processor coupled to the one or more sensors and configured to facilitate, at least, storage of a first table of values in a first data storage device, storage of a second table of values in a second data storage device, and adjustment of a minimum quality value for controlling the fuel injection based on an injector learning value, the first table, and the second table via instructions provided by the processor of the vehicle. The injector learning value is set based on an amount of injector learning that is complete.

[0019] In various embodiments, the first table is defined by a plurality of injector learning values and a plurality of quality values, and the second table is defined by a plurality of injector learning values and a plurality of quality values.

[0020] In various embodiments, adjusting the minimum quality value is based on a blend of the quality value from the first table and the quality value from the second table according to the injector learning value.

[0021] In various embodiments, the injector learning value is a value ranging from zero to one, and when the injector learning value is zero, the amount of injector learning completed is zero, and when the injector learning value is one, the amount of injector learning is full.

[0022] In various embodiments, when the injector learning value is zero, the minimum quality value is set to the highest quality value of the plurality of quality values.

[0023] In various embodiments, when the injector learning value is 1, the minimum quality value is set to the lowest quality value of the plurality of quality values. BRIEF DESCRIPTION OF DRAWINGS

[0024] The present disclosure will be described hereinafter with reference to the following drawings, in which like numerals denote like elements, and in which:

[0025] Figure 1 is a functional block diagram of a vehicle according to an exemplary embodiment, the vehicle including a drive system having an engine with direct fuel injectors and a control system for controlling the engine direct fuel injectors; and

[0026] Figure 2 is a flowchart of a process for controlling fuel injection based on dynamic minimum quality according to an exemplary embodiment, and the process can be implemented in conjunction with Figure 1 the vehicle and control system of DETAILED DESCRIPTION

[0027] The following detailed description is merely exemplary in nature and is not intended to limit the application and use. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description. As used herein, the term module refers to any hardware, software, firmware, electronic control components, processing logic, and / or processor devices, individually or in any combination, alone or in any combination, including but not limited to: application specific integrated circuits (ASICs), electronic circuits, processors (shared, dedicated or group) and memories that execute one or more software or firmware programs, combinational logic circuits, and / or other suitable components that provide the described functionality.

[0028] Embodiments of the present disclosure can be described herein in terms of functional and / or logical block components and various processing steps. It should be appreciated that such block components can be realized by any number of hardware, software, and / or firmware components configured to perform the specified functions. For example, an embodiment of the present disclosure can employ various integrated circuit components, e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, which can carry out a variety of functions under the control of one or more microprocessors or other control devices. In addition, those skilled in the art will appreciate that embodiments of the present disclosure can be practiced with any number of systems including systems not specifically depicted herein, including systems employing any number of hardware components, software components, and / or firmware components.

[0029] For the sake of brevity, conventional techniques related to signal processing, data transmission, signaling, control, and other functionality of the systems (and various operational components of the systems) can or can not be described in detail herein. Furthermore, the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and / or physical couplings between the various elements. It should be noted that many alternatives or additional functional relationships or physical connections can be present in an embodiment of the present disclosure.

[0030] Figure 1 A vehicle 100 according to an example embodiment is shown. As described in further detail below, the vehicle 100 includes a drive system 104 having an engine 150 with at least one direct fuel injector 158. As also described in further detail below and depicted in FIG. 1, the vehicle 100 further includes a control system 102 that controls fuel injection by the direct fuel injection 158 of the engine 150 based on a dynamically adjusted minimum mass limit. Figure 1

[0031] In certain embodiments, the vehicle 100 includes an automobile. In various embodiments, the vehicle 100 can be any of a number of different types of automobiles, such as a sedan, a four-door vehicle, a truck, or a sport utility vehicle (SUV), and can be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD), or all-wheel drive (AWD) and / or various other types of vehicles in certain embodiments. In certain embodiments, the vehicle 100 can also include a motorcycle and / or one or more other types of vehicles. Additionally, in various embodiments, it should be appreciated that the vehicle 100 can include any number of other types of mobile platforms.

[0032] ​In the depicted embodiment, vehicle 100 includes a body 110 that substantially encloses other components of vehicle 100. Also in the depicted embodiment, vehicle 100 includes a plurality of axles 112 and wheels 114. Wheels 114 are each rotatably coupled to one or more axles 112 near a respective corner of body 110 to facilitate movement of vehicle 100. In one embodiment, vehicle 100 includes four wheels 114, although this can vary in other embodiments (e.g., for trucks and certain other vehicles).

[0033] Drive system 104 drives wheels 114. In the depicted embodiment, drive system 104 includes a propulsion system and includes engine 150 described above. In various embodiments, engine 150 includes an internal combustion engine, such as a gasoline or diesel fuel internal combustion engine.

[0034] In various embodiments, engine 150 includes combustion chambers 152 and intake valves 154, as well as direct fuel injectors 158 described above. In various embodiments, direct fuel injectors 158 are directly coupled to combustion chambers 152 and provide fuel directly to combustion chambers 152. It will be appreciated that, in various embodiments, combustion chambers 152 are implemented as a plurality of combustion chambers, each having a direct fuel injector 158 and an intake valve based on the number of cylinders (not shown) implemented in engine 150. Each direct fuel injector is individually controlled based on a minimum mass limit.

[0035] In various embodiments, control system 102 provides instructions for controlling drive system 104, including instructions for controlling engine 150. In various embodiments, control system 102 includes an engine control unit (ECU) for engine 150. Also in various embodiments, control system 102 selectively controls operation of direct fuel injectors 158, including respective rates of fuel provided therefrom to combustion chambers 152, to control power output of the engine, among other functions. In various embodiments, control system 102 controls operation of direct fuel injectors 158 in accordance with the process 200 described further below. Figure 2 The steps of process 200 described further below provide these functions.

[0036] As Figure 1 depicted in FIG. 1, in various embodiments, control system 102 incorporates sensor array 120 as well as controller 130. In various embodiments, sensor array 120 includes sensors for measuring sensor data. As shown in FIG. 1, in various embodiments, sensor array 120 includes one or more engine sensors 122. In various embodiments, engine sensors 122 are attached to, disposed within, or otherwise disposed proximate to combustion chambers 152. Figure 1

[0037] ​In certain embodiments, the sensor array 120 can also include one or more other sensors 124, such as for operation of the engine. For example, in certain embodiments, the other sensors 124 can include one or more ignition sensors for detecting when the engine 150 is turned on and / or running, etc.

[0038] In various embodiments, the controller 130 is coupled to the sensor array 120 and provides instructions for controlling the engine 150, including controlling fuel injection, based on the sensor data. As Figure 1 shown, the controller 130 includes a computer system. In certain embodiments, the controller 130 can also include the sensor array 120 and / or one or more other vehicle components. Additionally, it should be understood that the controller 130 can be different in other ways from the embodiment depicted in Figure 1 FIG. 1. For example, the controller 130 can be coupled to or can otherwise utilize one or more remote computer systems and / or other control systems, such as as part of one or more of the vehicle devices and systems described above.

[0039] In the depicted embodiment, the computer system of the controller 130 includes a processor 132, a memory 134, an interface 136, a storage device 138, and a bus 140. The processor 132 performs the computational and control functions of the controller 130 and can comprise any type of processor or multiple processors, a single integrated circuit (such as a microprocessor), or any suitable number of integrated circuit devices and / or circuit boards working in cooperation to perform the functions of a processing unit. During operation, the processor 132 executes one or more programs 142 contained in the memory 134 and, as such, controls the general operation of the controller 130 and the general operation of the computer system of the controller 130, typically in accordance with the programs 142 stored in the memory 134. For example, the processor 132, in conjunction with the programs 142 and the other components of the controller 130, directs the general operation of the controller 130 and the computer system of the controller 130, including the processes described herein, such as the process 200 discussed below in connection with FIG. 2. Figure 2

[0040] The memory 134 can be any suitable type of memory. For example, the memory 134 can include various types of dynamic random access memory (DRAM) such as SDRAM, various types of static RAM (SRAM), and various types of non-volatile memory (PROM, EPROM, and flash memory). In certain examples, the memory 134 is located entirely or in part on the same computer chip as the processor 132. In the depicted embodiment, the memory 134 stores the programs 142 described above, as well as one or more stored values 144 (e.g., including predetermined threshold values for controlling emissions of the drive system, in various embodiments).

[0041] ​Bus 140 is used to transmit program, data, status, and other information or signals between various components of the computer system of controller 130. Interface 136 allows communication, for example, from a system drive and / or another computer system to the computer system of controller 130, and can be implemented using any suitable method and means. In one embodiment, interface 136 obtains various data from sensor array 120, drive system 104, one or more other components and / or systems of vehicle 100, and / or drive system 104. Interface 136 can include one or more network interfaces to communicate with other systems or components. Interface 136 can also include one or more network interfaces to communicate with a technician, and / or one or more storage interfaces to connect to storage devices, such as storage device 138.

[0042] Storage device 138 can be any suitable type of storage device, including various different types of direct access storage and / or other memory devices. In one example embodiment, storage device 138 includes a program product from which memory 134 can receive program 142 that performs one or more embodiments of one or more processes of the present disclosure, such as the steps of process 200 and the tables (Table T and Table L) discussed further below. In another example embodiment, the program product can be stored directly in and / or otherwise accessed by memory 134 and / or one or more other disks 146 and / or other memory devices. Figure 2 Further discussed tables (Table T and Table L). In another example embodiment, the program product can be stored directly in and / or otherwise accessed by memory 134 and / or one or more other disks 146 and / or other memory devices.

[0043] Bus 140 can be any suitable physical or logical means of connecting computer systems and components. This includes, but is not limited to, direct hard-wired connections, fiber optics, infrared, and wireless bus technology. During operation, program 142 is stored in memory 134 and executed by processor 132.

[0044] It should be understood that although this exemplary embodiment has been described in the context of a full-featured computer system, those skilled in the art will recognize that the mechanisms of this disclosure are capable of being distributed as a program product in which one or more types of non-transitory computer-readable signal-bearing media are used to store the program and its instructions and to perform its distribution, such as a non-transitory computer-readable medium carrying the program and containing computer instructions stored therein for causing a computer processor (such as processor 132) to execute and run the program. Such program products can take various forms, and this disclosure applies equally to any particular type of computer-readable signal-bearing medium used to perform the distribution. Examples of signal-bearing media include recordable media such as floppy disks, hard disks, memory cards, and optical disks, and transmission media such as digital and analog communication links. It should be understood that cloud-based storage and / or other technologies may also be utilized in some embodiments. It will be similarly understood that the computer system of controller 130 may also differ from other systems. Figure 1 The embodiments depicted herein, for example, involve a computer system in controller 130 that may be coupled to or may additionally utilize one or more remote computer systems and / or other control systems.

[0045] Now for reference Figure 2 The flowchart illustrates a method for controlling according to an exemplary embodiment. Figure 1 The process 200 involves fuel injection into the engine system. In various embodiments, process 200 can be combined with... Figure 1 The vehicle 100 is used to achieve this, which includes a drive system 104, an engine 150 and its control system 102.

[0046] like Figure 2 As shown, process 200 may begin at 202. In some embodiments, process 200 begins when one or more events occur to indicate that vehicle driving is taking place or is about to take place, such as a driver, operator, or passenger entering vehicle 100, the engine or motor of vehicle 100 being turned on, or the transmission of vehicle 100 being placed in "driving" mode, etc. In various embodiments, based on information from... Figure 1 Sensor data from one or more of the other sensors 124 (e.g., from the ignition sensor in some embodiments) determines the event that initiates the triggering process 200. Also in some embodiments, as part of step 202, the control system 102 is turned on or "wake up".

[0047] Thereafter, an injector learning value (IC) is obtained at 204. Injector learning compares the electrical signal of the injector to a nominal injector to learn the error in the injection process. Based on the amount of learning completed, the injector learning value (IC) is set to a value between 0 and 1. For example, when no learning is performed, IC is set to 0; when the learning is complete, the IC is set to 1; and the IC is set to a value between 0 and 1 based on the amount of learning completed.

[0048] The injector learning value is evaluated in order to dynamically determine the minimum quality value. For example, at 206, when the injector learning value indicates that injector learning has not occurred, the minimum quality value is set to the highest limit, e.g., the limit from the first table (Table T), at 208. The control system then uses the minimum quality value to control fuel injection of the direct fuel injectors 158.

[0049] Thereafter, the method 200 continues to obtain the injector learning value at 204. Once the injector learning value indicates that learning has begun, e.g., the IC is not set to zero but is not equal to 1 at 210, the minimum quality value is set to a blend between the value from the first table (Table T) and the value from the second table (Table L) as a function of the value of the injector learning at 212. The control system then uses the minimum quality value to control fuel injection of the direct fuel injectors 158.

[0050] The method 200 continues to update the minimum quality value based on the updated injector learning value until the injector is fully learned, where the injector learning value is 1, at 210.

[0051] Thereafter, the minimum quality value is set to the lower limit value from the second table (Table L). The control system then uses the minimum quality value to control fuel injection of the direct fuel injectors 158. The method can end at 216.

[0052] Accordingly, methods and systems for controlling fuel injection in a direct injection engine in a vehicle are provided. In various embodiments, the disclosed methods and systems provide a dynamically adjusted minimum quality value for controlling fuel injection. Such methods and systems allow the minimum quality to start higher on an unlearned system to optimize misfire or emissions, and to end with a much lower minimum quality once the injector compensation is fully learned, thereby improving fuel economy and particulate emissions. It should be understood that the systems, vehicles, applications, and implementations can differ from those depicted in the figures and described herein. For example, in various embodiments, the vehicle 100, control system 102, drive system 104, engine 150, components thereof, and / or other components can differ from those depicted in the figures and / or described above in connection therewith. It should also be understood that the steps of the process 200 can differ from those depicted in the figures and / or described above in connection therewith. Figure 1 Figure 2 ​different from those depicted and / or described above, and / or various steps thereof can be performed simultaneously and / or in a different order.

[0053] While at least one example embodiment has been presented in the foregoing detailed description, it should be appreciated that a wide variety of modifications exist. It should also be appreciated that the example embodiment(s) are only examples and are not intended to limit the scope, applicability, or configuration in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing an example embodiment. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope of the disclosure as set forth in the appended claims and the legal equivalents thereof.

Claims

1. A method for controlling fuel injection of a fuel injector of a direct injection engine, the method comprising: storing a first table in a first data storage device; storing a second table in a second data storage device; and adjusting, via instructions provided by a processor of a vehicle, a minimum mass value for controlling the fuel injection based on an injector learning value, the first table, and the second table, wherein the injector learning value is set based on an amount of injector learning completed; the first table is defined by a plurality of injector learning values and a plurality of mass values; the second table is defined by a plurality of injector learning values and a plurality of mass values; adjusting the minimum mass value is based on a blending of a mass value from the first table and a mass value from the second table according to the injector learning value; the injector learning value is a value ranging from zero to one, and wherein when the injector learning value is zero, the amount of injector learning completed is zero, and wherein when the injector learning value is one, the amount of injector learning is full; when the injector learning value is zero, the minimum mass value is set to a highest mass value of the plurality of mass values; when the injector learning value is 1, the minimum mass value is set to a lowest mass value of the plurality of mass values.

2. A system for controlling fuel injection of a fuel injector of a direct injection engine, the system comprising: a data storage device configured to store a first table and a second table; and a processor configured to adjust a minimum mass value for controlling the fuel injection based on an injector learning value, the first table, and the second table, wherein the injector learning value is set based on an amount of injector learning completed; the first table is defined by a plurality of injector learning values and a plurality of mass values; the second table is defined by a plurality of injector learning values and a plurality of mass values; adjusting the minimum mass value is based on a blending of a mass value from the first table and a mass value from the second table according to the injector learning value; the injector learning value is a value ranging from zero to one, and wherein when the injector learning value is zero, the amount of injector learning completed is zero, and wherein when the injector learning value is one, the amount of injector learning is full; when the injector learning value is zero, the minimum mass value is set to a highest mass value of the plurality of mass values; when the injector learning value is 1, the minimum mass value is set to a lowest mass value of the plurality of mass values.

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