System for determining the state of a filter and method for determining the state of a filter

Abstract

System for determining the state (155) of a filter that filters fuel and is connected to an engine (300), wherein the system includes a control unit configured to determine the state (155) of the filter based on an algorithm (145) that takes into account a variety of engine operating conditions, including engine running time (135), engine torque (130) and engine speed (125).

Description

CROSS-REFERENCE TO RELATED REGISTRATIONS

[0001] The present application claims priority from provisional US patent application No. 61 / 756,172, filed on January 24, 2013, the contents of which are incorporated herein by reference. TECHNICAL AREA

[0002] The present disclosure relates generally to fluid filters used in connection with various types of engine systems. In particular, the present disclosure relates to systems and methods for monitoring the condition of such fluid filters. BACKGROUND

[0003] U.S. Patent No. 7,922,914, incorporated herein in its entirety by reference, discloses methods and systems for measuring the pressure drop across a filter in the flow path and subsequently using the measured pressure drop, possibly in a normalized state and in conjunction with the time and / or other data from the system, to estimate properties of the fluid, the filter, and / or a component supplied with the filtered fluid. Such properties could include the operating condition of the filter, the remaining service life of the filter, the relative contaminant concentration in the fluid, and / or the remaining service life of a component supplied with the filtered fluid.

[0004] US patent application no. US 2011 / 0307160 A1, which is incorporated herein by reference in its entirety, discloses systems, methods, and algorithms for monitoring and displaying filter lifespan. The disclosed systems, methods, and algorithms can be used for monitoring and displaying the service life of a filter in an internal combustion engine.

[0005] Filters have a finite maintenance interval, the length of which is determined by the nature and quantity of contaminants present in the fluid, as well as by the operating conditions. Maintenance (or filter replacement) intervals are usually specified in terms of distance traveled or time before the filter should be replaced or serviced. The common practice of using distance or time to determine maintenance intervals is an approximation. In some cases, maintenance intervals can be determined based on the filter's pressure drop, but this is not usually done due to the cost of adding additional sensors.

[0006] Depending on the application, a filter may reach its final pressure drop sooner or later than the specified maintenance interval. Filters sometimes clog before the specified maintenance interval, particularly when the engine is used in extremely harsh or dirty conditions. This has been recognized through research and experimentation and is due to the fact that filter maintenance intervals are set based on expected conditions, not the conditions the filter actually experiences. SUMMARY

[0007] This summary is intended to present a selection of concepts that will be discussed in more detail in the detailed description below. This summary is not intended to identify important or essential features of the invention, nor is it meant to serve as an aid in limiting the scope of the invention.

[0008] The inventors of the present invention have recognized the advantage of utilizing existing on-board sensors in an engine system, particularly fuel and lubricating oil sensors, as condition sensors to determine the filter's condition and adapt to changes in that condition. The inventors have also recognized the advantage of providing this functionality without requiring the addition of further sensors to the system, thereby reducing costs and complexity. The condition of a filter can refer to its remaining service life and / or its status, i.e., whether the filter has a significant remaining service life, requires maintenance, or has reached or exceeded its service life.

[0009] The inventors of the present invention have recognized that, since premature filter clogging can lead to a deterioration in engine performance, accelerated wear, and / or increased service costs, it is desirable to have more accurate means of determining when a filter needs to be replaced, or at least to ensure that the filter is not used beyond its service life. This requires taking into account the effects of the duty cycle, the application, and filter- and engine-specific factors. Advance warning of when a filter is approaching the end of its service life allows the engine operator and / or service personnel to coordinate service activities and production requirements, thereby reducing costs and increasing productivity. As mentioned above, it is further desirable that this be achieved without adding additional sensors to the conventional system.

[0010] This disclosure provides a virtual sensor that determines the condition of a fuel or lubricating oil filter using engine running time, torque, and speed data. An engine speed sensor and other suitable engine sensors functionally provide an input for a control circuit, such as an engine control module (ECM). The ECM uses the data to determine the engine torque. Torque, speed, and time data are then used by an algorithm to determine the filter's condition, and the ECM provides an output to a display or control unit to inform the operator or service personnel or to initiate an appropriate response. The disclosure provides optional adjustable parameters in the algorithm, the values ​​of which depend on the operating environment, the engine, and the filter characteristics. These parameters can be changed manually or automatically to improve the accuracy of the calculation.

[0011] These and other features, along with their structure and function, will become apparent from the following detailed description when viewed together with the accompanying figures. BRIEF DESCRIPTION OF THE DRAWINGS Fig. Figure 1 is a schematic representation of a virtual filter state sensor according to various exemplary embodiments. Fig. Figure 2 is an exemplary graphical representation of a comparison of engine torque and speed, showing the engine torque versus the engine speed at both maximum load and at 70% of the maximum load. Fig. Figure 3 is a schematic representation of a system for implementing various embodiments described herein. Fig. Figure 4 is a flowchart showing an exemplary process through which various embodiments contained herein can be implemented. DETAILED DESCRIPTION

[0012] For the sake of brevity, clarity, and understanding, certain terms have been used in this description. These terms should not be interpreted as imposing any unnecessary restrictions beyond the requirements of the state of the art, as they serve only descriptive purposes and are intended to be interpreted broadly. The various devices, methods, and systems described herein can be used alone or in combination with other devices, methods, and systems. Various equivalents, alternatives, and modifications are possible.

[0013] The virtual filter condition sensor, shown schematically in the figure, assesses the condition of the engine's fuel and / or oil filters. It receives, among other things, engine runtime, engine torque, and engine speed data. Engine speed can be measured directly using onboard sensors. In modern diesel engines, engine speed is typically calculated continuously by the ECM from measured inputs, such as engine speed, intake manifold pressure, and throttle position. The sensors required for this calculation are usually already present onboard the engine. Time, torque, and speed data are either transmitted functionally or otherwise provided as inputs to the ECM or another control unit.It should be self-evident that when reference is made herein to an ECM, the associated structure, operation and characteristics may apply equally to other types of controllers or control units.

[0014] Fig. Figure 1 shows a range of functions typically found in the ECM. Data from other sensors, such as temperature, pressure, and / or fuel quality sensors, can also be provided to the ECM and used to improve the accuracy of the virtual filter condition sensor. The ECM uses an algorithm to calculate the filter condition based on time, torque, engine speed, and other optional data. Adjustable parameters can optionally be entered into the ECM to refine the algorithm and compensate for differences between engines and filters, as well as local conditions such as fuel quality and ambient conditions. These adjustable parameters can improve the accuracy of the calculation. The adjustable parameters are typically pre-programmed into the ECM of newer engines.Their values ​​can be modified or adjusted once information regarding the intended use or the final purpose of the motor is available. The adjustable parameters can also be readjusted for existing motors to fine-tune the sensor for local conditions. The result of the filter calculation is functionally transmitted to an output device, such as a visual display, colored light, fault or other informative code, digital display, or suitable data acquisition and / or processing device like a computer, ECM, or control circuit, allowing appropriate actions to be taken based on this information.

[0015] The virtual filter status sensor, Fig. 1. It functions as follows. Sensors, including those measuring engine speed 105, as well as additional sensors 110 required by the engine to calculate engine torque and as a means of monitoring engine running time 115, are provided and transmit data to the ECM. Alternatively, engine torque can be measured directly, for example, by a surface acoustic wave (SAW) sensor on the camshaft. The ECM calculates the engine torque (130), as is normally done in modern diesel engines. An algorithm 145 located in the ECM receives the engine torque data 130, engine speed data 125, and time data 135 periodically or on a near-continuous basis and uses the various data to determine the effect of current conditions on filter life. The algorithm 145 may also depend on various adjustable parameters 150 when determining the filter condition 155.Algorithm 145 can also consider the presence or absence of a filter (represented at 140) based on a suitable filter sensor 120. In summary, the results over time during a filter maintenance interval provide a continuous or periodically updated estimate of the current state of the filter (155). The ECM generates a signal corresponding to the filter's state, which is sent to an output device 160, such as a display or other device, to trigger or initiate an appropriate response. In the Fig. In the embodiment shown in Figure 1, the mechanism for calculating / determining the engine running time 115, the engine torque calculation 130, the time calculation 135, the algorithm 145 and the calculation of the filter state 155 are located on the ECM.

[0016] Onboard sensors, such as engine speed sensors, are found on modern diesel engines and can be used to control and optimize engine performance and function. Other important parameters, such as engine torque, can be calculated from these sensors. The virtual sensor receives engine torque, engine speed, and engine running time data. Therefore, all sensors required for calculating engine torque, as well as the engine speed sensors, can be used. The method for measuring or calculating torque is well-established in the field, as modern diesel engines typically possess this capability. Additional sensors or means to determine fluid flow rate, pressure, temperature, fluid quality, and other parameters can be used optionally to improve the accuracy of the calculation and the reliability of the virtual filter condition sensor.The onboard sensors provide input to the ECM to calculate engine torque and determine filter condition. Measured values ​​such as pressure and temperature are taken into account in relation to the location of the respective sensor. For example, manifold pressure and fuel return temperature can be considered.

[0017] The onboard sensors discussed herein can be located at various points on the engine. For example, fuel pressure can be measured at the accumulator (fuel rail) on various diesel engines. Fuel pressure can also be measured at other points on the engine, including, but not limited to, the fuel inlet, filter inlet, filter outlet, ECM cooler outlet, low-pressure pump inlet, low-pressure pump outlet, high-pressure fuel pump inlet, and engine fuel return line. In specific implementations, sensors may also be used to measure engine characteristics such as temperature at the fuel inlet, ECM cooler outlet, high-pressure fuel pump inlet, high-pressure fuel pump outlet, accumulator fuel return line, engine fuel return line, and injection return line. However, it should be noted that many of the above sensors may not be present in all implementations.

[0018] Sensors could also be used to measure various properties of the lubrication system. These sensors can measure, for example, the oil cooler inlet temperature, oil cooler outlet temperature, oil pan temperature, oil cooler inlet pressure, oil cooler outlet pressure, oil filter inlet pressure, oil filter outlet pressure, block inlet pressure, oil gallery temperature, and pump outlet pressure. However, it should be noted that many of the sensors mentioned above may not be present in all implementations.

[0019] Because the accuracy of the filter condition calculation depends in part on the filter's properties, the system may optionally include a sensor that determines whether a suitable filter has been installed. Examples of such sensors are described in US 6,533,926, US 6,537,444, US 6,711,524, and US 2011 / 0220560, which are incorporated herein by reference. With this option, the engine has a sensor that can detect a property, identifier, or signature, such as a memory chip, surface acoustic wave chip, electrical resistance, magnetic, or other property, that is uniquely present in suitable filters. Furthermore, the sensor can provide an output to the ECM that identifies the filter as suitable (or not). In some embodiments, the sensor can determine not only whether the filter is an original filter but also the type of installed filter.Depending on whether a suitable filter is built in or not, adjustable parameters can be selected by the algorithm that are suitable for the circumstances.

[0020] Modern engines typically have an electronic control module (ECM). The ECM is an onboard computer and / or controller (control circuit) that receives input from engine sensors and uses algorithms and lookup tables to control engine processes and functions, calculate torque, report conditions, and take other appropriate actions. The ECM may comprise a control circuit with one or more control modules or sections, each containing memory and a processor for sending and receiving control signals and for communicating with peripheral devices, such as additional control circuits, sensors, input devices, and output devices. The ECM is connected to a computer-readable medium that includes volatile and non-volatile memory containing computer-readable code.The processor accesses the computer-readable code, and the computer-readable medium, upon execution of the code, performs the functions described herein. It is also understood that, although the computer-readable medium may be separate from the processor, it may also be part of the processor or permanently connected to it. In yet other embodiments, the computer-readable medium may be implemented as a plurality of computer-readable media accessible to the processor. Various operating modes may be programmed into the control circuit, as discussed further below. The programming and control operations of the control circuit are described herein with reference to non-limiting examples and algorithms. Some of the examples / algorithms include specific sequences of steps for achieving certain system control functions.The configuration of the control circuit and all connected control circuit modules and / or areas may differ significantly from what is shown and described. The scope of this disclosure is not intended to be bound by the literal order and content of the steps described herein, and therefore non-significant differences and / or changes are not intended to fall within the scope of the disclosure. In general, the control circuit includes a programmable processor and memory for storing information. The control circuit may also be connected to the specified peripheral devices via wired and / or wireless connections for sending and receiving signals.

[0021] According to this disclosure, the ECM can have memory and programming that includes an algorithm and / or a lookup table providing the additional function of determining the condition of the fuel and / or lubricating oil filter. The algorithm can do this in a variety of ways. For example, it can have a filter lifetime mapping (described later) to determine the incremental fraction of the filter's lifetime that is consumed by the engine under current operating conditions. By summing the incremental fractions over the period the filter has been installed and comparing the sum to the expected lifetime of the filter under known conditions, the condition of the filter and its remaining service life can be estimated.In other embodiments, the time-weighted average duty cycle of the motor, based on torque and speed data over the relevant time interval, can be compared with a filter lifetime map to estimate the filter's condition and / or to compare it with the expected filter maintenance interval to determine its remaining service life. If an optional sensor is used for detecting suitable filters, the algorithm can decide to use one set of adjustable parameters for suitable filters and a different set (or provide no filter condition information at all) when an unsuitable filter is used.

[0022] Fig. Figure 3 is a schematic representation of a system for implementing various embodiments described herein. As in Fig. As shown in Figure 3, an engine 300 is communicatively connected to an engine control module 305 or a similar control unit. The engine control module 305 is also communicatively connected to a variety of sensors, each of which is used to provide data to the electronic engine control module 305 for manipulation and inclusion in an algorithm to determine the filter condition. The variety of sensors may include, among others, an engine speed sensor 310, an intake manifold pressure sensor 315, a throttle position sensor 320, an engine pressure sensor 325, a fuel quality sensor 330, a filter detection sensor 335, a filter condition sensor 340, and a "suitable filter" sensor 345. Some or all of these sensors may also be directly or indirectly connected to the engine 300.The motor control module 305 is electrically and / or communicatively connected to an output device 350, through which the detected filter status information is output.

[0023] The inventors observed that the filter lifespan for engine lubricating oil and fuel filters is a function of engine operating conditions. They found that heavy or aggressive use shortens the filter lifespan for both lubricating oil and fuel filters. Unlike lubricating oil, fuel is burned. Therefore, one would expect the fuel filter lifespan to be controlled by contaminants in the supplied fuel and, to a lesser extent, by engine operating conditions. However, the data surprisingly showed that heavy or aggressive use does indeed shorten the fuel filter lifespan. Lubricating oil, on the other hand, is recirculated indefinitely until it is replaced.The remaining engine oil life, but not the oil filter life, was determined from knowledge of the temperature, fuel delivery rate, engine speed, and load (see GB2345342B), which is incorporated herein by reference. US 6,253,601, incorporated herein by reference, describes a system and procedure for determining when the oil should be changed based on engine parameters such as engine temperature, fuel delivery rate, engine speed, and engine load. Other procedures exist for estimating the condition of the oil, but not for determining the condition of the oil (or fuel) filter. The condition of the oil filter is a function of the solid and semi-solid contaminants removed. Thus, although the condition of the filter may be related to the condition of the oil, other factors also affect filter life.

[0024] Duty cycle is a term used to describe the severity of engine operating conditions, and it can be defined in various ways using input from the engine sensors. One way to define duty cycle is as overcoming a load using a graphical representation of engine torque versus speed, as in Fig. Figure 2 illustrates this. In the figure, the shaded region is bounded by lines representing the maximum load and 70% of the load as a function of speed. This region can be defined as the heavy or high-stress duty cycle for the engine. The relationship between engine torque and speed and filter life can be mapped using engine tests under controlled conditions on an engine test bench. Using the filter life mapping, the impact of specific torque and speed conditions on filter life can be determined relative to reference conditions corresponding to the normal filter maintenance interval for the engine. This information can then be used on a continuous or periodic basis to estimate the condition of the filter.

[0025] There are other ways to create a filter lifetime map or to quantitatively model engine operating conditions and relate them to filter lifetime. For example, the duty cycle can be defined as the ratio of the time-weighted average power produced to the engine's rated power, the percentage of time the engine operates at rated power (or a fraction thereof), the percentage of time, miles, or fuel consumed at different engine speeds, torque or manifold pressures, or a combination of two or more of the above definitions. Any of these can be used to define a filter lifetime map or incorporated into an algorithm to relate engine operating conditions to filter lifetime.

[0026] The present disclosure may also utilize optional adjustable parameters to improve the accuracy of the calculation. The values ​​for the adjustable parameters are normally kept constant during a maintenance interval and depend on the type of engine and filter, the local fuel and engine oil quality, and local and environmental factors. Normally, one (1) to six (6) adjustable parameters are required; however, more may be necessary for complex algorithms and models. Adjustable parameters may be required, for example, to account for the characteristics of the engine, filter, and fluid. Normally, default values ​​for the adjustable parameters are programmed into the ECM for use by the algorithm based on the anticipated normal conditions for the engine and application.These values ​​can be changed manually, electronically, or otherwise before or after engine use if conditions are expected to differ from the default settings. For example, different values ​​for adjustable parameters may be used for engines in city bus applications in North America, as opposed to those making deliveries in Asia. If an optional suitable filter sensor is used, one set of values ​​can be used when the installation of a suitable filter is confirmed. Another set of values ​​can be used when an unsuitable filter is installed to provide a more conservative estimate of the filter condition and protect the engine. Alternatively, the algorithm can choose not to calculate and report a filter condition at all when an unsuitable filter is used.The values ​​for these parameters can also be readjusted later, for example by service personnel, based on experience and on-site observations, to improve the accuracy of the calculation. Normally, the adjustable parameters are entered manually; however, one or more can be provided automatically if suitable sensors are available, electronically or by other means.

[0027] An algorithm located in the ECM can be used to calculate the filter's state. Several types of algorithms can perform this calculation. These differ in terms of data requirements, adjustable parameters, and the accuracy of the results. All require torque, engine speed, and time data. The following equation is an example: R=E−∑0t(ABX+CY)Δt where R is the remaining service life of the filter; E is the normal maintenance interval of the filter; t is the engine running time during which the filter was actually used; A, B, and C are adjustable parameters; and X and Y are variables whose values ​​are determined from torque and speed data. The values ​​for A and C depend on the type of engine and filter. The value for B depends on the anticipated fuel quality. The values ​​for X and Y are obtained from engine torque and speed data at a specific time based on the filter lifetime mapping or mathematical modeling of the relationship between the input data and these variables.

[0028] The virtual filter condition sensor, as described, can be used for either the fuel filter or the lubricating oil filter. In a further embodiment, the system can indicate the condition and / or remaining service life of both the fuel and the lubricating oil filters. In this latter embodiment, no additional sensors would be required. Instead, only a second algorithm and means for outputting the results would be necessary.

[0029] In another embodiment, the virtual filter state sensor can also include an electronic means for detecting the presence and installation of a suitable filter on the engine to ensure the accuracy of the calculation. Values ​​for one or more of the adjustable parameters are influenced by the type of installed filter. If an electronic means for detecting suitable filters is available to provide data to the algorithm, the algorithm could confirm that the correct filter is being used before providing the filter state outputs. If an unsuitable filter is installed, the filter state would be calculated, or alternatively, adjustable parameters would be used that conservatively calculate the filter state, thus encouraging the use of suitable filters.

[0030] A virtual filter sensor is used to determine the condition of the fuel and / or lubricating oil filters based on engine torque, speed, and runtime data. This does not require a direct measurement of filter restriction (or pressure drop) or flow rate through the filter. The virtual sensor could be used in conjunction with a pressure drop measurement to further improve its reliability, but this would be considered an essentially independent and secondary measurement of filter condition. The virtual sensor uses data from typical engine sensors or values ​​calculated from these sensors by the ECM.The systems described here can provide input values ​​for adjustable parameters related to the characteristics of the engine, the filter, and the fluid being filtered, and optionally to application and local conditions to improve the accuracy of the results. Existing filter condition sensors, also known as filter life, filter clogging, and filter service indicators, typically determine filter condition based on pressure drop data or possibly based on the filtered fluid volume. Oil quality sensors are known to predict lubricating oil quality using an onboard sensor, but not the condition of the filter.Since fuel is burned rather than fully recirculated, it might seem counterintuitive that engine conditions associated with the duty cycle would affect filter life; however, this has indeed been confirmed through test cell and field trial monitoring. Furthermore, the same input parameters are used for both lubricating oil and fuel filter condition sensors, so minimal additional requirements and no additional physical sensors are needed to provide an engine with both types of virtual sensors. Finally, the system described here can optionally use a "suitable filter" sensor to ensure that appropriate adjustable parameters are used by the algorithm.

[0031] Fig. Figure 4 is a flowchart showing an exemplary process through which various embodiments contained herein can be implemented. At 400 in Fig.4. Input information from a variety of sensors in conjunction with the operation of the engine is provided to a control unit such as an ECM. At 410, at least some of the input information is used to determine a variety of input variables, where the variety of input variables represents a variety of engine operating conditions. As discussed previously, the engine operating conditions that can be represented include, among others, engine runtime, engine torque, and engine speed. For example, a variable representing engine torque can be based on input information in conjunction with at least one of the values ​​for intake manifold pressure, throttle position, and engine speed. At 420, an algorithm incorporating the variety of input variables is processed, resulting in a determination of the filter's state.As previously discussed, the algorithm can also directly or indirectly consider direct input information as well as other information, such as duty cycle, whether a suitable filter has been installed, engine operating environment, engine characteristics, filter characteristics, operator experience, engine temperature, and fuel quality. At output 430, information regarding the filter's condition is output to a user, such as a vehicle operator or service technician.

[0032] In the foregoing description, certain terms have been used for the sake of brevity, clarity, and understanding. No unnecessary limitations beyond the requirements of the prior art should be inferred from these terms, as they serve descriptive purposes and are intended to be interpreted broadly. The various configurations, systems, and process steps described herein may be used alone or in combination with other configurations, systems, and process steps. It is to be expected that various equivalents, alternatives, and modifications are possible within the scope of the appended claims. Any limitation in the appended claims shall be interpreted in accordance with 35 USC § 112, sixth section, only if the terms "means for" or "step for" are expressly listed in the corresponding limitation.

[0033] It should be noted that the term "exemplary", used here to describe various embodiments, indicates possible examples, representations and / or illustrations of possible embodiments (and that such a term should not imply that such embodiments are necessarily exceptional or outstanding examples).

[0034] It is essential to note that the construction and arrangement of the various exemplary embodiments serve only for illustration. Although only some embodiments have been described in detail in this disclosure, the person skilled in the art who studies this disclosure will readily understand that numerous modifications (e.g., in sizes, dimensions, structures, shapes and proportions of the various elements, parameter values, assembly arrangements, material use, colors, orientations, etc.) are possible without substantially departing from the new teachings and advantages of the subject matter described herein. The sequence or order of any process or procedural steps may be varied or rearranged according to alternative embodiments.Further substitutions, modifications, changes and omissions can be made to the design, operating conditions and arrangement of the various embodiments without deviating from the scope of the present invention.

Claims

[1] System for determining the state (155) of a filter that filters fuel and is connected to an engine (300), wherein the system includes a control unit configured to determine the state (155) of the filter based on an algorithm (145) that takes into account a variety of engine operating conditions, including engine running time (135), engine torque (130) and engine speed (125). [2] System according to claim 1, wherein the condition (155) of the filter comprises the remaining service life of the filter. [3] System according to claim 1, further comprising an output device (160) configured to inform an operator about the state (155) of the filter, wherein the control unit is configured to operate the output device (160). [4] System according to claim 1, further comprising a sensor configured to record the motor speed. [5] System according to claim 1, wherein the control unit is configured to calculate the engine torque (130) based on at least one input selected from the group consisting of intake manifold pressure, throttle position and engine speed. [6] System according to claim 1, further comprising a sensor configured to record at least one of the values ​​engine temperature, engine pressure and fuel quality, wherein the algorithm (145) further includes at least one of the values ​​engine temperature, engine pressure and fuel quality. [7] System according to claim 1, wherein the algorithm (145) further includes at least one variable which varies on the basis of an input selected from the group consisting of an engine operating environment, an engine property, a filter property and operator experience. [8] System according to claim 1, further comprising a sensor configured to detect whether a suitable filter has been installed in the motor (300), and wherein the algorithm (145) further takes into account whether the suitable filter has been installed in the motor (300). [9] System according to claim 1, wherein the algorithm (145) further includes the work cycle. [10] System according to claim 1, wherein the algorithm (145) is represented by the following formula R=E−∑0t(ABX+CY)Δt where R is the remaining service life of the filter; E is a normal maintenance interval of the filter; t is an input variable representing the engine running time during which the filter was actually used; X is an input variable representing the engine torque; and Y is an input variable representing the engine speed (125). [11] System according to claim 10, wherein the value A depends on the type of motor (300) used. [12] System according to claim 10, wherein the value B depends on the type of anticipated fuel quality. [13] System according to claim 10, wherein the value C depends on the type of filter used. [14] System according to claim 1, wherein the control unit comprises a motor control module (305) which includes a memory containing the algorithm (145). [15] Method for determining a state (155) of a fuel filter connected to an engine (300), the method comprising receiving, at a control unit, input information from a plurality of sensors in connection with the operation of the engine (300); Determining a plurality of input variables using at least some of the input information, wherein the plurality of input variables represent a plurality of engine operating conditions, including engine running time (135), engine torque (130) and engine speed (125); Determining the state (155) of the filter based on an algorithm (145) that takes into account the multitude of input variables; and Outputting the information related to the state (155) of the filter to a user. [16] Method according to claim 15, wherein the condition (155) of the filter comprises the remaining service life of the filter. [17] Method according to claim 15, wherein the user comprises an operator of a vehicle in which the engine (300) is located. [18] Method according to claim 15, wherein the input information obtained from the plurality of sensors includes information related to the motor speed. [19] Method according to claim 15, wherein the determination of the plurality of input variables includes the calculation of the engine torque (130) based on at least one of the values ​​intake manifold pressure, throttle valve position and engine speed. [20] The method of claim 15, wherein the input information obtained from the plurality of sensors includes information related to at least one of the values ​​of engine temperature, engine pressure and engine quality, and where the multitude of variables further includes at least one of the values ​​engine temperature, engine pressure and fuel quality. [21] Method according to claim 15, wherein at least one of the plurality of input variables varies based on one of the following factors: an engine operating environment, an engine characteristic, a filter characteristic and operator experience. [22] Method according to claim 15, further comprising detecting whether a suitable filter has been installed in the motor (300), and wherein the algorithm (145) takes into account whether the suitable filter has been installed. [23] Method according to claim 15, wherein the algorithm (145) further includes the work cycle. [24] Method according to claim 15, wherein the output of the information comprises making the information available to the user on a displayable screen. [25] Method according to claim 15, wherein the algorithm (145) is defined by the formula R=E−∑0t(ABX+CY)Δt is represented where R is the remaining service life of the filter; E is a normal maintenance interval of the filter; t is an input variable representing the engine running time (135) during which the filter was actually used; X is an input variable representing the engine torque (130); and Y is an input variable representing the engine speed (125). [26] Method according to claim 25, wherein the value of A depends on the type of motor (300) used. [27] Method according to claim 25, wherein the value of B depends on the type of anticipated fuel quality. [28] Method according to claim 25, wherein the value of C depends on the type of filter used. [29] System for determining the state (155) of a lubricating oil filter which filters oil and is connected to an engine (300), the system comprising a control unit configured to determine the state of the lubricating oil filter based on an algorithm (145) which takes into account a variety of engine operating conditions, including engine running time (135), engine torque (130) and engine speed (125). [30] System according to claim 29, wherein the condition (155) of the lubricating oil filter comprises the remaining service life of the lubricating oil filter. [31] System according to claim 29, further comprising an output device (160) configured to inform an operator about the condition (155) of the lubricating oil filter, wherein the control unit is configured to operate the output device (160). [32] System according to claim 29, further comprising a sensor configured to record the motor speed. [33] System according to claim 29, wherein the control unit is configured to calculate the engine torque (130) based on at least one input selected from the group consisting of intake manifold pressure, throttle position and engine speed. [34] System according to claim 29, further comprising a sensor configured to record at least one of the values ​​engine temperature, engine pressure and fuel quality, wherein the algorithm (145) further takes into account at least one of the values ​​engine temperature, engine pressure and fuel quality. [35] System according to claim 29, wherein the algorithm (145) further takes into account at least one variable which varies on the basis of an input selected from the group consisting of an engine operating environment, an engine property, a lubricating oil filter property and operator experience. [36] System according to claim 29, further comprising a sensor configured to detect whether a suitable lubricating oil filter has been installed in the engine (300), and wherein the algorithm (145) further takes into account whether the suitable filter has been installed in the engine (300). [37] System according to claim 29, wherein the algorithm (145) further takes into account the work cycle.

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