Vehicle fuel monitoring system and method

Abstract

Embodiments herein relate to fuel monitoring systems and related methods. In an embodiment, a fuel monitoring system for a vehicle is included, the fuel monitoring system comprising: a fuel filter sensor device configured to generate data reflecting a filter resistance value of a fuel filter; a geolocation circuit configured to generate or receive geolocation data; and a system control circuit configured to evaluate the sensor data to determine a change in the filter resistance value. The control circuit is capable of receiving fuel level data, cross-referencing the geolocation data and the fuel level data to identify a utilized refueling location, and correlating the refueling location with subsequent changes in filter resistance to identify the impact of a specific refueling location on fuel filter loading. In some embodiments, a refueling guidance system for a vehicle is included, the refueling guidance system being capable of providing route recommendations and / or refueling location recommendations based on fuel filter load rate data. Other embodiments are also included herein.

Description

[0001] This application was filed on January 29, 2021, as a PCT international patent application in the name of Donaldson Company, Inc. (a U.S. national corporation, designated applicant in all countries) and Bradly G. Hauser, a U.S. citizen, Chad M. Goltzman, a U.S. citizen, and Michael J. Wynblatt, a U.S. citizen (designated inventors in all countries), and claims priority to U.S. Provisional Patent Application No. 62 / 967,369 filed on January 29, 2020, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0002] Embodiments herein relate to fuel monitoring systems and vehicle refueling guidance systems and related methods. Background Art

[0003] Fuel filters remove impurities from fuel, preventing various adverse effects, including fuel injector clogging. However, fuel filters have a limited lifespan and must be periodically replaced or otherwise serviced. Over time, fuel filters become filled with impurities, a process known as filter loading. As filter loading increases, filter resistance increases. Therefore, filter resistance is often used as an indicator to determine when filters, such as fuel filters, need replacement or other maintenance. Summary of the Invention

[0004] Embodiments herein relate to fuel monitoring systems and vehicle refueling guidance systems and related methods. In a first aspect, the system includes a fuel monitoring system for a vehicle, the system comprising: a fuel filter sensor device configured to generate data reflecting a filter resistance value of a fuel filter; geolocation circuitry configured to generate or receive geolocation data; and system control circuitry configured to evaluate the sensor data to determine a change in the filter resistance value, receive fuel level data, cross-reference the geolocation data with the fuel level data to identify a utilized refueling location, and correlate the refueling location with subsequent changes in the filter resistance value to identify the impact of the specific utilized refueling location on fuel filter loading.

[0005] In a second aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to estimate an expected load rate associated with refueling at a particular refueling location based on previously observed fuel filter loading.

[0006] In a third aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to calculate a cost associated with a particular refueling location based on the estimated expected fuel filter loading.

[0007] In a fourth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to generate a recommendation that may include a recommended refueling location.

[0008] In a fifth aspect, additionally or in the alternative to one or more of the foregoing or following aspects, the recommendation is forwarded to a mobile communication device associated with the vehicle or the vehicle driver.

[0009] In a sixth aspect, additionally or in the alternative to one or more of the foregoing or following aspects, a recommendation is formed to include consideration of fuel system parts inventory at the refueling location.

[0010] In a seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to generate a recommendation that may include a recommended refueling time.

[0011] In an eighth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to generate a recommendation that may include a recommended refueling location and a recommended refueling time.

[0012] In a ninth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to generate a list of recommended and non-recommended fueling stations.

[0013] In a tenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to generate an alert for a vehicle driver when the vehicle enters a non-recommended fuel station location.

[0014] In an eleventh aspect, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the system control circuit is further configured to generate a report describing the frequency with which different drivers in the fleet use recommended and non-recommended fuel supply stations.

[0015] In a twelfth aspect, in addition to, or in the alternative of, one or more of the foregoing or following aspects, the fuel level data is received from a CANBus network.

[0016] In a thirteenth aspect, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the fuel filter sensor device may include an upstream pressure sensor configured to sense the pressure in the fuel line upstream of the fuel filter and a downstream pressure sensor configured to sense the pressure in the fuel line downstream of the fuel filter.

[0017] In a fourteenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the geolocation circuitry may include satellite communication circuitry.

[0018] In a fifteenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the geolocation circuit receives geolocation data from a separate device.

[0019] In a sixteenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the geolocation circuitry infers geolocation based on detection of wireless signals.

[0020] In a seventeenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the wireless signal may include at least one of a WIFI signal and a cellular communication tower signal.

[0021] In an eighteenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, an effect of a particular refueling location on fuel filter loading is determined based on an effect on a filter loading curve.

[0022] In a nineteenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuit is configured to distinguish between a normal filter load curve, an accelerated filter load curve, and a sudden blockage curve.

[0023] In a twentieth aspect, in addition to or in the alternative of one or more of the foregoing or following aspects, the system control circuit is configured to distinguish between a normal filter load curve and an abnormal filter load curve.

[0024] In a twenty-first aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is configured to identify a refueling location visited immediately before the abnormal filter loading curve began.

[0025] In a twenty-second aspect, additionally or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is configured to identify a refueling location visited immediately before the filter loading curve changes to exhibit a faster load.

[0026] In a twenty-third aspect, additionally or in the alternative to one or more of the foregoing or following aspects, the system control circuitry classifies the identified location as a contaminated fuel source and stores the classification in a refueling location database.

[0027] In a twenty-fourth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is further configured to generate fuel system parts inventory recommendations based on a refueling location database.

[0028] In a twenty-fifth aspect, in addition to one or more of the foregoing or following aspects, or in the alternative to some aspects, the fuel system parts inventory recommendation includes a recommendation to increase fuel filter inventory at a refueling location that occurs in a series of refueling locations subsequent to the identified location having contaminated fuel.

[0029] In a twenty-sixth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry classifies the identified location as a possible source of contaminated fuel and queries a database to obtain additional data about the identified location.

[0030] In a twenty-seventh aspect, additionally or in the alternative to one or more of the foregoing or following aspects, the system control circuitry is configured to determine a sequence of refueling locations visited immediately prior to the onset of the sudden jam profile.

[0031] In a twenty-eighth aspect, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the system control circuit is further configured to evaluate one or more of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and number of detected fuelings to identify the impact of a specific fueling location on fuel filter loading.

[0032] In a twenty-ninth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, cross-referencing the geolocation data and the fuel level data to identify the refueling location may include identifying the geolocation when the fuel level increases.

[0033] In a thirtieth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system may further include a water-in-fuel sensor, and the system control circuitry may be configured to evaluate data from the water-in-fuel sensor and correlate refueling locations with subsequent changes in the data from the water-in-fuel sensor to identify the impact of specific refueling locations on the water-in-fuel sensor data.

[0034] In a thirty-first aspect, in addition to or in alternative to one or more of the foregoing or following aspects, the system may further include a particle counter, and the system control circuitry may be further configured to evaluate data from the particle counter and correlate fuel refueling locations with subsequent changes in the data from the particle counter to identify the impact of specific fuel refueling locations on the particle counter data.

[0035] In a thirty-second aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry may be configured to estimate the remaining fuel filter life taking into account the refueling locations used.

[0036] In a thirty-third aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the filter resistance value may include a pressure drop across the fuel filter.

[0037] In a thirty-fourth aspect, the present invention includes a method of monitoring a fuel system, which may include measuring a filter restriction of a fuel filter, identifying a refueling location based on fuel level data and geolocation data, and calculating an impact of a specific refueling location on fuel filter loading by evaluating a filter restriction trend after refueling at the refueling location.

[0038] In a thirty-fifth aspect, in addition to one or more of the foregoing or following aspects, or in the alternative to some aspects, the method may further include estimating an expected load rate associated with refueling at a particular refueling location based on previously observed fuel filter loading.

[0039] In a thirty-sixth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include calculating a cost associated with a particular refueling location based on the estimated expected fuel filter loading rate.

[0040] In a thirty-seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include generating a recommendation that may include a recommended refueling location.

[0041] In a thirty-eighth aspect, in addition to one or more of the foregoing or following aspects, or in the alternative to some aspects, the method may further include forwarding the recommendation to a mobile communication device associated with the vehicle or the vehicle driver.

[0042] In a thirty-ninth aspect, additionally or in the alternative to one or more of the foregoing or following aspects, the recommendation is generated to include consideration of fuel system parts inventory at the refueling location.

[0043] In a fortieth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include generating a recommendation that may include a recommended refueling time.

[0044] In a forty-first aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include generating a recommendation that may include a recommended refueling location and a recommended refueling time.

[0045] In a 42nd aspect, in addition to one or more of the foregoing or following aspects, or in the alternative to some aspects, the method may further include forwarding the recommendation to a mobile communication device associated with the vehicle or the vehicle driver.

[0046] In a forty-third aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include generating a list of recommended and non-recommended fueling stations.

[0047] In a forty-fourth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include alerting a vehicle driver when the vehicle enters a non-recommended fuel station location.

[0048] In a forty-fifth aspect, in addition to one or more of the foregoing or following aspects, or in the alternative to some aspects, the method may further include generating a report describing the frequency with which different drivers in the fleet use recommended and non-recommended fuel supply stations.

[0049] In a forty-sixth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further comprise distinguishing between a normal filter load curve, an accelerated filter load curve, and a sudden blockage curve.

[0050] In a forty-seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include distinguishing between a normal filter load curve and an abnormal filter load curve.

[0051] In a forty-eighth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include identifying a refueling location visited immediately before the onset of the abnormal filter loading curve.

[0052] In a forty-ninth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include identifying a refueling location visited immediately before the filter load curve changes to exhibit a faster load.

[0053] In a fiftieth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include classifying the identified location as a contaminated fuel source and storing the classification in a refueling location database.

[0054] In a fifty-first aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include generating fuel system parts inventory recommendations based on the refueling location database.

[0055] In a fifty-second aspect, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the fuel system parts inventory recommendation includes a recommendation to increase fuel filter inventory at a refueling location that occurs in a series of refueling locations subsequent to the identified location having contaminated fuel.

[0056] In a fifty-third aspect, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the method may further include classifying the identified location as a possible source of contaminated fuel and querying a database to obtain additional data about the identified location.

[0057] In a fifty-fourth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include determining a sequence of refueling locations visited immediately before the onset of the sudden jam profile.

[0058] In aspect fifty-fifth, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the method may further include evaluating one or more of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and the number of detected fueling times to identify the impact of a specific fueling location on fuel filter loading.

[0059] In a fifty-sixth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, identifying a refueling location based on the fuel level data and the geolocation data includes identifying a geolocation when the fuel level increases.

[0060] In a fifty-seventh aspect, in addition to one or more of the foregoing or following aspects, or in the alternative to some aspects, the method may further include evaluating data from a water-in-fuel sensor and identifying the impact of a specific refueling location on the water-in-fuel sensor data.

[0061] In a fifty-eighth aspect, in addition to one or more of the foregoing or following aspects, or in the alternative of some aspects, the method may further include estimating the remaining fuel filter life taking into account the fueling locations used.

[0062] In a fifty-ninth aspect, a fuel refueling guidance system for a vehicle is provided, the fuel refueling guidance system having a system control circuit, wherein the system is configured to query a database, which may include specific fuel refueling location records and fuel filter load rate data associated with the specific fuel refueling location, wherein the system is configured to provide at least one of a route recommendation and a fuel refueling location recommendation to an output device based on the fuel filter load rate data.

[0063] In a sixtieth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system control circuitry can be further configured to evaluate sensor data to determine a change in filter resistance of a fuel filter, receive fuel level data, cross-reference geolocation data and the fuel level data to identify a refueling location, correlate the refueling location with a subsequent change in filter resistance to identify an effect of the specific refueling location on fuel filter loading, and store data regarding the effect of the specific refueling location on fuel filter loading.

[0064] In a sixty-first aspect, in addition to or in the alternative of one or more of the foregoing or following aspects, the database is stored at a location remote from the system control circuit.

[0065] In a sixty-second aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the output device may include a user output device.

[0066] In a sixty-third aspect, in addition to or in the alternative of one or more of the previous or following aspects, the user output device may comprise a smartphone.

[0067] In a sixty-fourth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the output device may include a vehicle navigation system.

[0068] In a sixty-fifth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the output device may include a fleet management system.

[0069] In aspect sixty-six, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the system is configured to calculate a remaining distance to a recommended fuel supply station, compare the remaining distance to a remaining vehicle mileage based on the remaining fuel level, and alert the vehicle driver when the vehicle driver leaves the range of the recommended fuel supply station or is within a fixed distance of the range of the recommended fuel supply station.

[0070] In aspect sixty-seven, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the system is further configured to query a database of filter providers, calculate the distance to the filter providers, calculate the remaining useful life of the current fuel filter, and alert the vehicle driver when the remaining useful life of the current fuel filter is insufficient to reach at least one of these filter providers.

[0071] In aspect sixty-eight, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the system is further configured to calculate the optimal location for a filter repair service provider to meet a vehicle requiring fuel filter repair service based on a planned route of the vehicle, minimize the repair service provider's travel time, and ensure that the filter is replaced before the end of its useful life.

[0072] In a sixty-ninth aspect, a method for providing guidance for vehicle refueling is included, the method comprising querying a database, which may include specific refueling location records and fuel filter load rate data associated with the specific refueling location, and providing at least one of a route recommendation and a refueling location recommendation to an output device based on the fuel filter load rate data.

[0073] In a seventieth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further include evaluating sensor data to determine a change in filter resistance of a fuel filter, receiving fuel level data, cross-referencing geolocation data and the fuel level data to identify a refueling location, correlating the refueling location with a subsequent change in filter resistance to identify an effect of the specific refueling location on fuel filter loading, and storing data regarding the effect of the specific refueling location on fuel filter loading.

[0074] In the seventy-first aspect, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the method may further include calculating a remaining distance to a recommended fuel supply station, comparing the remaining distance with a remaining vehicle mileage based on the remaining fuel level, and issuing an alert to the vehicle driver when the vehicle driver leaves the range of the recommended fuel supply station or is within a fixed distance of the range of the recommended fuel supply station.

[0075] In aspect seventy-two, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the system is further configured to query a database of filter providers, calculate the distance to the filter providers, calculate the remaining useful life of the current fuel filter, and issue an alert to the vehicle driver and / or fleet manager or fleet management system when the remaining useful life of the current fuel filter is insufficient to reach at least one of these filter providers.

[0076] In aspect seventy-three, in addition to one or more of the foregoing or following aspects, or in an alternative to some aspects, the method may further include calculating an optimal location for a filter repair service provider to meet a vehicle requiring fuel filter repair service based on a planned route of the vehicle, minimizing travel time for the repair service provider, and ensuring that the filter is replaced before the end of its useful life.

[0077] In a seventy-fourth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the output device may include a user output device.

[0078] In a seventy-fifth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the user output device may comprise a smartphone.

[0079] In a seventy-sixth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the output device may include a vehicle navigation system.

[0080] In a seventy-seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the output device may include a fleet management system.

[0081] In a seventy-eighth aspect, a maintenance service guidance system is included, the maintenance service guidance system having a system control circuit, wherein the system is configured to calculate an optimal location for a filter maintenance service provider to intersect a vehicle requiring fuel filter maintenance service based on a planned route of the vehicle, minimize the maintenance service provider's travel time, and ensure that the filter is replaced before the end of its useful life.

[0082] In a seventy-ninth aspect, a method for providing guidance to a filter repair service provider is included, the method comprising calculating a remaining range of a vehicle requiring fuel filter repair service, determining a planned location of the vehicle at or before a distance of the remaining range, and providing the filter repair service provider with the planned location and / or a suggested route to the planned location.

[0083] In an eightieth aspect, a system for a vehicle is provided, the system comprising: a fuel filter sensor device configured to generate data reflecting a filter resistance value of a fuel filter; a geolocation circuit configured to generate or receive geolocation data, wherein the system is configured to evaluate the fuel filter sensor data to determine a change in the filter resistance value, receive fuel level data, cross-reference the geolocation data and the fuel level data to identify a utilized refueling location, associate the refueling location with subsequent changes in the filter resistance value to identify an effect of the specific refueling location utilized on fuel filter loading, and provide at least one of a route recommendation and a refueling location recommendation to a user output device based on the fuel filter loading rate data.

[0084] In an eighty-first aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system is configured to query a database that may include records of specific refueling locations and fuel filter load rate data associated with the specific refueling locations.

[0085] In an eighty-second aspect, a maintenance service guidance system is included, the maintenance service guidance system having a system control circuit, wherein the system is configured to calculate an optimal route to a filter maintenance service provider based on a planned route of the vehicle, minimize vehicle travel time, and ensure that the filter is replaced before the end of its useful life.

[0086] In an eighty-third aspect, a vehicle guidance system is included, the vehicle guidance system having system control circuitry, wherein the system is configured to calculate an optimal route to a destination taking into account the location of a filter repair service provider, minimize vehicle travel time, and ensure that the filter is replaced before the end of its useful life.

[0087] In an eighty-fourth aspect, in addition to or in alternative to one or more of the foregoing or following aspects, the system is configured to take into account the location of the filter repair service provider to optimize the vehicle's existing planned route, minimize the vehicle's travel time, and ensure that the filter is replaced before the end of its useful life.

[0088] This summary is an overview of some of the teachings of this application and is not intended to be an exclusive or exhaustive treatment of the subject matter. Further details are found in the detailed description and the appended claims. Other aspects will be apparent to those skilled in the art upon reading and understanding the following detailed description and upon reviewing the accompanying drawings which form a part thereof, none of which should be construed as limiting. The scope of this document is defined by the appended claims and their legal equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] A more complete understanding of various aspects may be obtained with reference to the following drawings (Figures), in which:

[0090] Figure 1 is a schematic diagram of components of a fuel monitoring system according to various embodiments herein.

[0091] Figure 2 is a schematic diagram of a fuel filtering device and components of a fuel monitoring system according to various embodiments herein.

[0092] Figure 3 is a schematic diagram of a fuel filtering device and components of a fuel monitoring system according to various embodiments herein.

[0093] Figure 4 is a graph illustrating fuel level versus distance traveled for a vehicle according to various embodiments herein.

[0094] Figure 5 is a graph showing fuel filter pressure drop versus driving distance according to various embodiments herein.

[0095] Figure 6 The following is a graph of fuel filter pressure drop and fuel level versus distance traveled for a vehicle with two fuel filters replaced.

[0096] Figure 7is a schematic diagram illustrating fueling location costs according to various embodiments herein.

[0097] Figure 8 is a schematic diagram illustrating fuel supply locations in different regions according to various embodiments herein.

[0098] Figure 9 is a schematic diagram illustrating a fueling location visit sequence for multiple trips according to various embodiments herein.

[0099] Figure 10 is a schematic diagram illustrating two different routes between two geographic points and fueling locations along the routes according to various embodiments herein.

[0100] Figure 11 is a graph showing fuel filter pressure drop versus age for different types of load profiles.

[0101] Figure 12 is a block diagram of some components of a fuel monitoring system according to various embodiments herein.

[0102] Although the embodiments are susceptible to various modifications and alternative forms, details thereof have been shown by way of example and drawings and will be described in detail. However, it should be understood that the scope of this disclosure is not limited to the specific aspects described. On the contrary, the intent is to cover modifications, equivalents, and alternatives that fall within the spirit and scope of this disclosure. DETAILED DESCRIPTION

[0103] As mentioned above, fuel filters become filled with impurities / contaminants during use, a process known as filter loading. As filter loading increases, the filter resistance increases until it reaches a point where the fuel filter needs to be replaced or otherwise serviced.

[0104] However, the level of impurities / contaminants / solids in the fuel may vary based on a variety of factors, which exist to varying degrees at specific fueling locations and all of which may lead to abnormal filter loading and / or rapid clogging of the fuel filtration system. These factors include, but are not limited to, hard particle intrusion caused by weather events, dirty hoses and trucks, rusted or otherwise degraded tanks, degraded hoses or valves, sediment stirred up during tank filling, salt carried over from the refining process, salt intrusion from coastal areas, water intrusion caused by weather events, underground tank leaks, tank cleaning, degraded biodiesel, and biodiesel byproducts such as glycerol, glycerides, and sterols. In addition, the temperature, humidity, oxygen content, microorganisms, and trace metals in the tank may all lead to rapid degradation of biodiesel. Further, the level of impurities / contaminants / solids in the fuel may be affected by biofilms and the acid production associated with the microorganisms, incompatibility of fuel additives during continuous filling (such as acid additives and base additives, anionic salt additives and cationic salt additives, improperly mixed polymer fuel additives, and inappropriate summer or winter fuel mixtures).

[0105] By monitoring filter loading behavior, combined with knowledge of the refueling locations utilized, it is possible to predict the impact of refueling at a specific location on filter loading. This allows for optimization of various aspects, such as the refueling locations utilized, the routes taken, filtration system service locations and times, and fleet management. This can also serve as a basis for the system to provide information and / or make recommendations regarding various aspects, such as when to refuel, which refueling locations to use, which routes to take, where to seek filtration system service, when to seek filtration system service, and other aspects related to vehicle operation and fleet management.

[0106] Various embodiments herein include a fuel monitoring system for a vehicle. The fuel monitoring system may include a fuel filter sensor device configured to generate and / or receive data reflecting filter resistance, including but not limited to a pressure drop across a fuel filter. The system may also include geolocation circuitry configured to generate and / or receive geolocation data. The system may also be configured to evaluate pressure data to determine changes in filter resistance, generate and / or receive fuel level data, cross-reference the geolocation data and the fuel level data to identify a refueling location, and correlate the refueling location with subsequent changes in fuel filter resistance to identify the impact of a specific refueling location on fuel filter loading.

[0107] In various embodiments herein, a fuel supply guidance system for a vehicle is provided. The fuel supply guidance system may include a system control circuit and may be configured to query a database comprising a specific fuel supply location record and fuel filter load rate data associated with the specific fuel supply location. The system may also be configured to provide at least one of a route recommendation and a fuel supply location (location) recommendation based on the fuel filter load rate data. For example, the system may be configured to provide any item determined herein to an output device, and in particular at least one of a route recommendation and a fuel supply location (location) recommendation. In some embodiments, the output device includes a user output device, such as a smartphone. In some embodiments, the output device may be a vehicle navigation system. In some embodiments, the output device may be a fleet management system.

[0108] As used herein, the term "vehicle" shall mean any machine or device having an engine that moves and burns fuel and must be periodically refueled.

[0109] Now refer to Figure 1 , which shows a schematic diagram of components of a fuel monitoring system 100 according to various embodiments herein. Figure 1 A fuel monitoring system 100 is shown for a vehicle 102. The vehicle 102 includes a fuel filter system 104. Figure 1 , the vehicle 102 is shown at a refueling location 116. The refueling location 116 also includes a fuel pump 114.

[0110] In some cases, the fuel filter system 104 can be in direct wireless data communication with the cloud 122 or another data network. In some cases, the fuel filter system 104 can be in indirect wireless data communication with the cloud 122 or another data network. In some embodiments, the fuel filter system 104 can communicate with a cellular tower 120, which in turn can relay data communications to and from the cloud 122 and its components, such as a server 132 (real or virtual) and a database 134 (real or virtual).

[0111] Various protocols may be used for wireless communication. For example, wireless communication / signals exchanged between the fuel monitoring system 100 or its components and the cloud 122 (or between components of the fuel monitoring system 100) may follow many different communication protocol standards and may be accomplished via radio frequency transmission, induction, magnetism, light, or in some embodiments, even via wired connections. In some embodiments herein, IEEE 802.11 (e.g., ), (e.g., BLE, 4.2 or 5.0), Or cellular transmission protocols / platforms, such as CDMA, cdmaOne, CDMA2000, TDMA, GSM, IS-95, LTE, 5G, GPRS, EV-DO, EDGE, UMTS, HSDPA, HSUPA, HSPA+, TD-SCDMA, WiMAX, etc. In various embodiments, different standard or proprietary wireless communication protocols may also be used.

[0112] As mentioned, the cloud 122 resources may include a database 134. Such a database 134 may store various information, including, but not limited to, refueling location data (e.g., refueling location ID, refueling location geolocation data, fuel filter loading rate data associated with a specific refueling location, refueling location estimated impurity / contamination information, refueling location visit data, refueling location filter loading impact data, etc.), fleet data, vehicle data, filtration system data, etc.

[0113] It will be appreciated that the database contents may be distributed across many different physical systems, devices, and locations. Figure 1 104 itself. In various embodiments, the database 134 or portions thereof may be stored in a location remote from other components of the system, such as the fuel filter system 104. In some embodiments, the records or portions of the database may be stored across different physical locations, and in some embodiments, may be cached across different physical locations for ease of access.

[0114] In some embodiments, the refueling location 116 may include a location communication device 110. The location communication device 110 may include various components. In some embodiments, the location communication device 110 may be a wireless data gateway including components such as a router and / or other data networking hardware. In some cases, the fuel filter system 104 may wirelessly communicate with the location communication device 110 to provide communication with the cloud 122 or another data network. In some cases, the fuel filter system 104 may receive information from the location communication device 110, such as geolocation data (which may include latitude / longitude coordinates, etc.), or other location identification information, such as the nearest address, the nearest landmark, etc. As used herein, the term "geolocation data" shall include reference to all location identification data unless the context dictates otherwise.

[0115] In some cases, geolocation data may be obtained from a geolocation system based on satellites 150. Such systems may include, but are not limited to, GPS L1 / L2, GLONASS G1 / G2, BeiDou B1 / B2, Galileo E1 / E5b, SBAS, and the like. In various embodiments, the system may include geolocation circuitry (described below), which may include an appropriate signal receiver or transceiver for interfacing with satellites 150, and / or the geolocation circuitry may interface with and / or receive data from a separate device or system that provides geolocation data or obtains geolocation data from satellites 150 or other devices. However, it will be understood that geolocation data herein is not limited to data that may be received or obtained from an interface with satellites 150. Geolocation data may also be obtained from addresses, beacons, landmarks, various reference technologies, IP address evaluations, and the like.

[0116] In various embodiments, the fuel monitoring system for vehicle 102 may also include and / or communicate with a mobile communication / guidance device 130. In some cases, the mobile communication / guidance device 130 may be used to provide data communication between the fuel filter system 104 and the cloud or another data network. In various embodiments, the mobile communication / guidance device 130 may provide output to the vehicle 102 or the driver of the vehicle 102 or provide input from the vehicle or the driver of the vehicle. In some cases, the mobile communication device may be used to provide recommendations (visual, auditory, and / or tactile) to the vehicle driver. For example, in various embodiments, the system may generate a recommendation, and the recommendation may be forwarded to the mobile communication / guidance device 130 associated with the vehicle 102 or the driver of the vehicle 102.

[0117] Specific recommendations / reports generated by the system may include specific information points. However, as just one example, the fuel monitoring system 100 and / or its components may be configured to generate a report that describes different fueling locations (and / or the same pattern) and their impact on filter loading and / or recommendations regarding fueling locations based on filter loading. As another specific example, the fuel monitoring system 100 and / or its components may be configured to generate a report that describes the frequency with which different drivers in a fleet used recommended and non-recommended fueling stations.

[0118] In some embodiments, the mobile communication / guidance device 130 may be, for example, a smartphone or another type of computing device with wireless communication capabilities. In some embodiments, the mobile communication / guidance device 130 may be a vehicle navigation system.

[0119] In some embodiments, the fuel monitoring system 100 may also include and / or communicate with a fleet monitoring center 140 (real or virtual). The fleet monitoring center 140 may include a remote computing device 128 and may receive information and / or recommendations regarding specific vehicles and / or specific refueling locations. In some cases, the fuel monitoring system 100 may be configured to provide recommendations to and / or receive information or instructions from a fleet control operator at the fleet monitoring center 140.

[0120] In various embodiments, the system described herein can also function as, or be, a refueling guidance system for vehicle 102. For example, system 100 can be configured to query database 134, which can include records of specific refueling locations and fuel filter load factor data associated with the specific refueling locations. System 100 can be configured to provide at least one of a route recommendation and a refueling location recommendation to an output device based on the fuel filter load factor data. In some embodiments, the output device includes a user output device, such as a smartphone. In some embodiments, the output device can be a vehicle navigation system. In some embodiments, the output device can be a fleet management system.

[0121] Now refer to Figure 2 , a schematic diagram of various components of a fuel monitoring system according to various embodiments herein is shown. Specifically, fuel filter system 104 is shown. Fuel filter system 104 includes a filter head unit 202 or housing. Fuel filter system 104 also includes a fuel filter 208. In some cases, fuel filter 208 may be a spin-on fuel filter. However, other types of fuel filters are contemplated herein.

[0122] The fuel filter system 104 may include one or more sensor devices and / or may be configured to receive data from one or more sensor devices. For example, the fuel filter system 104 may include an upstream pressure sensor 204 and a downstream pressure sensor 206. In some embodiments, both the upstream pressure sensor 204 and the downstream pressure sensor 206 may be in fluid communication with the fuel line or may otherwise be configured to sense pressure within the fuel line. Specifically, the fuel filter sensor device may include an upstream pressure sensor 204 configured to sense pressure in the fuel line upstream of the fuel filter 208 and a downstream pressure sensor 206 configured to sense pressure in the fuel line downstream of the fuel filter 208. Based on the pressure data / signals generated by the upstream pressure sensor 204 and the downstream pressure sensor 206, a pressure drop ("ΔP") across the fuel filter 208 may be calculated. The pressure data / signals may also include or be otherwise paired with a timestamp and may be stored by various components of the system. It will be appreciated, however, that in various embodiments, other measures of filter resistance (pressure-based or otherwise) may be sensed or otherwise calculated. In some embodiments, only a single pressure sensor (located upstream or downstream of the fuel filter) is used alone or in combination with other types of sensors. In still other embodiments, a different number of pressure sensors may be used.

[0123] Fuel filter system 104 may include a fuel filter monitoring device 210. Fuel filter monitoring device 210 may receive data / signals from various sensors (fuel filter sensor devices), including but not limited to upstream pressure sensor 204 and downstream pressure sensor 206. Fuel filter monitoring device 210 may perform various functions, including but not limited to calculating filter resistance, calculating pressure drop, filtering data, processing data, compressing data, storing data, transmitting data, and performing various operations described herein. In some embodiments, fuel filter monitoring device 210 may exchange wireless and / or wired data transmissions with other devices. In some embodiments, fuel filter monitoring device 210 may communicate directly or indirectly with a cloud or another data network.

[0124] While certain types of pressure sensors are described herein as specific examples of fuel filter sensor devices that can be configured to generate data reflecting a filter resistance value of a fuel filter, it will be appreciated that various other types of sensors may also be used as fuel filter sensor devices. For example, sensors for filter resistance values ​​may include differential pressure sensors, non-differential pressure sensors, acoustic sensors, optical sensors, electromagnetic sensors, fuel efficiency sensors, engine operation sensors, fuel pump sensors (including but not limited to sensors responsive to energy consumed when operating a fuel pump, such as energy consumed by an electric motor driving the fuel pump), and the like. Furthermore, it will be appreciated that, in some instances herein, the fuel filter sensors described herein may serve as an interface for receiving data reflecting a filter resistance value from another device or system.

[0125] It will be appreciated that when data generated by other devices / systems is available, it is possible to efficiently rely on such data. For example, CANBus refers to a vehicle data bus standard designed to allow devices and electronic control units to communicate with each other. Many vehicles include a CANBus network, and communication with the CANBus network can provide many different types of data. For example, interfacing with the CANBus network can provide one or more of fuel level data, various types of engine data (including but not limited to engine RPM data, engine operating time data, odometer data, engine / vehicle temperature data), ambient temperature data, geolocation data, and the like.

[0126] Now refer to Figure 3 , which shows a schematic diagram of components of a fuel monitoring system according to various embodiments herein. Figure 3 Generally similar to Figure 2 , but it also includes additional features that may be part of various embodiments herein. As previously described, the fuel filter system 104 is shown as including a filter head unit 202 and a fuel filter 208. The fuel filter system 104 may include one or more sensor devices and / or may be configured to receive data from one or more sensor devices. For example, the fuel filter system 104 may include an upstream pressure sensor 204 and a downstream pressure sensor 206.

[0127] Fuel filter system 104 may also include fuel filter monitoring device 210. In this example, fuel filter monitoring device 210 may also interface with separate device 302. Separate device 302 may serve as a gateway and / or source or aggregator of vehicle-related data. In some embodiments, separate device 302 may generate its own data, such as geolocation data. In some cases, separate device 302 may provide communication with CANBus network 304. In various embodiments, fuel level data may be received from CANBus network 304 and transmitted to various components of the system described herein via separate device 302.

[0128] It will be appreciated that the standalone device 302 can interface with many different data sources. Specifically, the standalone device 302 can communicate with a first additional data generating or receiving device 306 and / or a second additional data generating or receiving device 308. The data may include, but is not limited to, one or more of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and the number of detected refuelings.

[0129] In some specific examples, a water-in-fuel sensor may be specifically included. For example, the first or second additional data generating and / or receiving device may include a water-in-fuel sensor or may be in communication with a water-in-fuel sensor. In various embodiments, water may be used as an example of a specific type of fuel contaminant. In various embodiments herein, the system may correlate refueling locations with subsequent changes in data from the water-in-fuel sensor to identify the impact of specific refueling locations on the water-in-fuel sensor data (and, therefore, on the water content of the fuel).

[0130] Various fuel water-in-fuel sensors can be used. In some embodiments, the fuel water-in-fuel sensor herein may include an optical fuel water-in-fuel sensor. In some embodiments, an exemplary optical fuel water-in-fuel sensor may include a light emitter (such as an LED or other emitter) and a light detector (such as a photodiode, phototransistor, photoresistor, CMOS sensor, charge-coupled device, etc.). The light emitter can be configured to emit light toward a fuel sample, and the light detector can be configured to receive light that passes through the sample. For example, the light emitter and light detector can be arranged on opposite sides of a channel through which the fuel flows. Water has a different absorbance for certain wavelengths of light (including but not limited to near-infrared light or light centered around a wavelength of approximately 1550 nanometers) than for fuel. Therefore, the signal from the light detector will vary based on the water content of the fuel. In some embodiments, the fuel to be evaluated (such as fuel flowing in a fuel line) can be at least partially diverted through a sensor channel (such as a microfluidic channel) having a light emitter that emits light toward the sensor channel and a light detector that receives light from the sensor channel. The signal from the light detector can then be evaluated to determine the water content of the fuel that has passed through the sensor channel. Similar optical sensors can also be used to identify other possible contaminants. An exemplary water-in-fuel sensor may include the sensor described in published PCT application number PCT / US2019 / 034809, entitled “DROPLET SENSORS FOR FUEL SYSTEMS,” published as WO 2019 / 232305, the contents of which are incorporated herein by reference in their entirety. It will be appreciated that data from the water-in-fuel sensor may be used alone or in combination with other types of contaminant data or resistance data discussed herein.

[0131] In some specific examples, other types of pollutant sensors may also be included. For example, the first or second additional data generation and / or receiving device may include other types of fuel pollutant sensors or may communicate with another type of fuel pollutant sensor. In various embodiments herein, the system may then associate the fuel refueling location with subsequent changes in pollutant levels identified (at least in part) by the pollutant sensor to identify the impact of a specific fuel refueling location on pollutant levels, and therefore on the fuel pollutant content. Such pollutant sensors may include, but are not limited to, on-board particle counters / monitors. In some embodiments, the pollutant sensor may include an optical-based sensor that utilizes detection of light blockage to detect particles. For example, particles may pass through an optical flow cell including a light emitter. These particles may block some light, thereby forming shadows. These shadows may be detected by a light detector. In addition to light-based optical systems, pollutant sensors may also rely on other detection methods. For example, pollutant sensors may also rely on electrical, magnetic, weight, and / or density properties to detect pollutants. In some embodiments, the pollutant sensor herein may detect particulate matter based on ISO 11171, which is data on particle counts in fluids. It will be understood that data from other types of contaminant sensors (and particularly data from particle counters / monitors) may be used alone or in combination with other types of contaminant data or resistance data discussed herein.

[0132] In various embodiments herein, the system may evaluate pressure data to determine changes in filter resistance, receive fuel level data, cross-reference geolocation data and the fuel level data to identify a refueling location, and correlate the refueling location with subsequent changes in fuel filter resistance to identify the impact of the specific refueling location on fuel filter loading behavior.

[0133] Now refer to Figure 4 , shows a graph of fuel level versus distance traveled for the vehicle 102 according to various embodiments herein. As can be seen, the graph is characterized by a set of repetitive features, including idle times 406, load operating time 408, and refueling events 404. Specifically, Figure 4 A sudden increase in fuel level volume 402 is shown, which may be interpreted as a refueling event 404 .

[0134] Now refer to Figure 5 , shows a graph of the fuel filter 208 pressure drop versus driving distance according to various embodiments herein. Figure 4 and Figure 5 The time / odometer readings are synchronized, so Figure 5 A refueling event 404 is also shown, and more specifically, in relation to Figure 4 The refueling event shown is identical to the refueling event shown in FIG. 1. Thus, the impact of a specific refueling event on subsequent filter loading can be accurately identified and assessed.

[0135] Furthermore, cross-referencing geolocation data and fuel level data can be used to identify refueling locations, specifically identifying a geolocation when the fuel level increases. Cross-referencing geolocation data and fuel level data can include a variety of possible operations. In some embodiments, both the fuel level data and the geolocation data can be timestamped or otherwise associated with time so that the two types of data can be synchronized with respect to time. Synchronous geolocation data can then be identified when a sufficiently large fuel level increase is detected.

[0136] In some cases, a specific refueling location can be identified solely by its geolocation data, such as by its longitude and latitude coordinates. However, in other embodiments, the synchronized geolocation data can then be compared with the locations of known refueling locations for various purposes, such as confirming that a refueling event has occurred and / or providing additional data to be used by the system, including generating recommendations. For example, the coordinates can be sent via a data network to a location API, such as the "Places API" commercially available as part of the Google Maps platform, to identify whether a known refueling station exists at or near a specific set of coordinates. Similarly, the synchronized geolocation data can be subjected to a reverse geocoding procedure to convert the coordinates (for example) into an address. For example, the coordinates can be sent via a data network to an API, such as the "Geocoding API" commercially available as part of the Google Maps platform. The discovered address can then be stored in a database and / or matched with the addresses of known refueling locations in the database for various purposes, such as confirming that a refueling event has occurred and / or providing additional data to be used by the system, including generating recommendations and / or alerts.

[0137] The magnitude of the fuel level increase that is sufficient to infer that a refueling event has occurred can vary. In some embodiments, if the fuel level increases by an amount that crosses a threshold, the system can infer that a refueling event has occurred. For example, a fuel level increase of at least 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% (as a percentage of the vehicle's total fuel capacity), or an amount falling within a range between any of the above, can be used as a threshold. In various embodiments, the system can require that this increase must persist for a predetermined length of time in order to infer a refueling event, thereby avoiding the adverse effects of false fuel level sensor data. In various embodiments, the system can require that this increase must represent an average of multiple fuel level data readings.

[0138] In some embodiments, the system may send a query to the vehicle driver and / or fleet manager to confirm that a refueling event has just occurred. For example, after detecting a possible refueling event, the system may send a query to the driver via the mobile communication / guidance device 130 or another device, and then receive a return input confirming the refueling event.

[0139] In some embodiments, the system may query the vehicle driver and / or receive input from the vehicle driver for purposes other than mere confirmation. For example, the vehicle driver may provide input to the system that a refueling event has occurred. The vehicle driver may provide such input in response to a query from the system and / or may simply provide such input proactively provided by the system.

[0140] It will be appreciated that fuel filter resistance (including but not limited to pressure drop) and fuel level information may be monitored over multiple fuel filter lifespans. Figure 6 , shows a graph of the fuel filter 208 pressure drop and fuel level of the vehicle 102 as a function of driving distance across two fuel filters that have been replaced. Figure 6 The refueling event 404 is shown along with the first filter life 602 and the second filter life 604 . Figure 6 A fuel filter change event 608 is shown.

[0141] A fuel filter change event 608 can be determined or inferred based on observing a sudden decrease in the pressure drop across the filter (or other measure of fuel filter resistance) and specifically a decrease to a nominal pressure drop level for a new fuel filter (or within a range of pressure drop levels for a new filter). In some embodiments, a fuel filter change event can be inferred by sensing a decrease in fuel filter resistance by at least a threshold value. For example, the threshold value can be a decrease in sensed filter resistance of at least approximately 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% to infer that a new fuel filter has been installed. Because a vehicle engine is typically shut down during fuel filter servicing, in some embodiments herein, the threshold filter resistance can be assessed based on the time between engine shutdown and the next engine start.

[0142] It will be understood that the total cost of vehicle operation includes the cost of all aspects except fuel cost. For example, the cost of maintenance service and parts replacement may be very high. Since the fuel filter must be replaced regularly, its cost and the maintenance service cost associated with replacing the fuel filter may also be included in the total cost of vehicle operation. However, since different refueling locations can cause different impacts on filter load behavior (and therefore can affect the service life of the fuel filter), different refueling locations may have different effective total costs. Therefore, except for the price per gallon of fuel, the cognition of the total cost associated with a specific refueling location can be used to form a recommendation of which refueling location to use.

[0143] Now refer to Figure 7 , shows a schematic diagram illustrating fueling location costs according to various embodiments herein. A first possible refueling location 702 has a first nominal fuel cost 704. The first possible refueling location 702 also includes a first total cost 706. A second possible refueling location 708 has a second nominal fuel cost 710. The second possible refueling location 708 also includes a second total cost 712.

[0144] The total costs 706, 712 can be calculated or estimated in various ways. In various embodiments, the system can be configured to calculate the costs associated with a particular refueling location 116 based, at least in part, on an estimated expected fuel filter 208 loading rate. This can be performed in various ways. In one approach, the effect of a particular refueling location on fuel filter loading can be used to calculate how quickly a current fuel filter, at a current filter resistance level, will be loaded sufficiently to reach an endpoint or end-of-life condition. For example, the system can calculate how quickly a current fuel filter reaches a pressure drop of 35 to 40 kPa (assuming the fuel filter is a primary fuel filter). In some embodiments, this calculation can be performed by first identifying a filter loading curve from past visits to a particular refueling location (which can be based on past visits to the particular refueling location by a particular vehicle, past visits to the particular refueling location by other vehicles in the fleet, and / or past visits to the particular refueling location by third-party vehicles) and / or averaging or other statistical processing of the particular refueling location. Using the load curve at hand and the current filter resistance value for the current filter, an estimate of the remaining distance before reaching an end-of-life or end-of-life condition can be calculated. Then, using fuel filter repair service and parts costs, the fuel filter cost associated with a particular refueling location can be derived. In some cases, the fuel filter cost associated with a particular refueling location can be compared to an average for all refueling locations, an average for all refueling locations within a specific region, or an average for all refueling locations at a specific stop or exit point along a route to generate a comparative cost and / or serve as a basis for recommendations.

[0145] In various embodiments, the system can be further configured to generate recommendations that include recommended refueling locations. In some cases, the recommendation can be derived by comparing filter load curves from a set of different refueling locations, where the refueling location with the flattest or slowest rising filter load curve is the recommended refueling location. The set of different refueling locations for consideration can be selected in various ways. For example, the set can include all or some refueling locations at a specific stop or exit along a route, all or some refueling locations along a specific route, all refueling locations approved by fleet management, all refueling locations within a certain distance of the vehicle's current location (e.g., in the same direction as the vehicle's route), etc.

[0146] In some cases, analyzing the impact of refueling location on fuel filter loading behavior can include evaluating a series of utilized refueling locations. Fuel composition and / or additives may vary slightly across geographic regions. In some cases, components within fuel from one location can interact with components within fuel from another location in a manner sufficient to affect fuel filter loading behavior. Thus, while utilizing a particular refueling location may negatively impact fuel filter loading immediately, this impact may not only be a result of the direct refueling location, but also be a function of the sequence of refueling locations utilized.

[0147] For example, now refer to Figure 8 , shows a schematic diagram illustrating fuel supply locations in different regions according to various embodiments herein. A region (which may be a state, county, etc.) may include a first region 802, a second region 804, a third region 806, and a fourth region 808. Each region may include a plurality of independent fuel supply locations (ADs) arranged therein. Now referring to Figure 9 , shows a schematic diagram illustrating a sequence of refueling location visits for multiple trips / routes according to various embodiments herein. For each refueling location visit, Figure 9 Refueling location identifiers are shown. For example, the first refueling location 902 of trip 1 is "1A." The second refueling location 904 of trip 1 is "2C." The third refueling location 906 of trip 1 is "3A," and the fourth refueling location 908 of trip 1 is "4B." Figure 9 Also shown is a fuel system status 910, which reflects the status of the vehicle's fuel filtration system at the end of a trip, for example. In this example, both Trip 1 and Trip 2 ended with a negative status, while Trip 3 ended with a positive status. In some cases, a negative status may reflect an abnormal filter loading pattern, while a positive status reflects a normal filter loading pattern.

[0148] Figure 9Explaining refueling location visit patterns can provide a better understanding of scenarios that lead to abnormal fuel filter loading conditions. For example, both Trip 1 and Trip 2 end at location "4B" and both result in a negative state. Thus, evaluating Trip 1 and Trip 2 individually might lead to the conclusion that location "4B" is the fuel source that is negatively impacting fuel filter loading. However, by also evaluating Trip 1 (which also ends at location "4B," but whose penultimate stop is not location "3A," and whose result is not a negative state), it becomes clear that the problematic scenario is more precisely characterized as a refueling at location "3A," which precedes location "4B." By identifying this insight, the system can provide recommendations that take into account patterns in refueling locations visited. For example, the system can provide recommendations that include optimal refueling locations as part of a sequence of refueling locations. Furthermore, the system can provide recommendations that include a sequence of optimal refueling locations to utilize.

[0149] The system herein may also provide route recommendations, including those that optimize the utilized refueling locations based on other parameters, including one or more of driving distance, driving time (speed), availability of maintenance locations along the route, etc. This may be performed in a variety of ways. As just one example, given a starting point and a destination, various techniques may be used to identify possible routes, including utilizing an API such as the "Directions API" commercially available as part of the Google Maps platform. Further, given a starting point, a destination, and waypoints such as a specific refueling location or a filter repair service provider location, various techniques may be used to identify an optimized route, including utilizing an API such as the "Directions API" commercially available as part of the Google Maps platform.

[0150] In various embodiments, for each route, a region of possible refueling stations ("refueling regions") can be calculated taking into account the vehicle's current fuel level and an estimate of fuel mileage. For example, an estimated fuel depletion point can be determined, and then all refueling locations along a given route up to a fixed distance before the depletion point can be estimated. The optimal refueling location, or an average of the top few refueling locations, can then be used as a hypothesis for the refueling locations to be utilized within the given refueling region, and the impact on the expected fuel filter load can then be calculated using stored data regarding the impact of such refueling locations on the filter load curve. This can be done across all refueling regions associated with a particular route initially identified as a possible route. In this way, the optimal route can be identified from a fuel filter load perspective. However, other factors may also be included / considered when calculating the optimal route, including but not limited to distance traveled, time required for the trip (speed), weather, availability of maintenance sites, availability of parts, fuel prices at refueling locations along the route, and the like.

[0151] In various embodiments, the refueling guidance system of vehicle 102 may include system control circuitry and may be configured to query a database comprising records of specific refueling locations and fuel filter load factor data associated with the specific refueling locations. The system may be configured to provide at least one of a route recommendation and a refueling location recommendation to mobile communication / guidance device 130 and / or a user output device based on the fuel filter load factor data. In some embodiments, the output device may include a user output device, such as a smartphone. In some embodiments, the output device may be a vehicle navigation system. In some embodiments, the output device may be a fleet management system.

[0152] In some embodiments, recommendations or guidance may be provided to a vehicle driver or fleet manager in the form of a map and / or data for display or presentation on a device. Figure 10 , shows a schematic diagram illustrating two different routes between two geographic points and fuel supply locations along the routes according to various embodiments of the present invention. The system can display a map 1000, which can show a starting location 1002 and an ending location 1004 (or destination). Map 1000 can further display a first route 1006 and a second route 1008, as well as fuel supply locations 116 along the routes (all fuel supply locations, or in some cases, only recommended fuel supply locations). In various embodiments, the system can be configured to calculate the cost of the two routes, including taking into account factors such as filter load rate, distance traveled, time required for the trip (speed), weather, availability of maintenance locations, availability of parts, fuel prices at fuel supply locations along the routes, etc.

[0153] In various embodiments, the system can be configured to calculate the remaining distance to a recommended refueling station, compare the remaining distance to the remaining vehicle range based on the remaining fuel level, and issue an alert to the vehicle driver or fleet operator when the vehicle driver leaves the range of a recommended refueling station or within a fixed distance of the range of a recommended refueling station. The remaining distance to the recommended refueling station can be calculated by obtaining the vehicle's current location and then comparing it to a database of recommended refueling locations (refueling stations). For all recommended refueling locations, or for each recommended refueling location that falls within a set of possible nearest refueling locations (such as the top 5, 10, or 20 refueling locations based on coordinates), a more accurate distance can be calculated by using a distance calculation API such as the "Distance Matrix API" commercially available as part of the Google Maps platform to select the nearest refueling location based on the distance that must be traveled.

[0154] In some embodiments, the shortest distance can be compared to the vehicle's remaining range (e.g., fuel level multiplied by fuel range), and an alert can then be generated and sent to the vehicle operator and / or fleet operator when the vehicle's remaining range is within a fixed distance (50 miles, 40 miles, 30 miles, 20 miles, 10 miles, 5 miles, 1 mile, or 0 miles) of the point where the vehicle's remaining range is less than the distance to the nearest recommended fueling station. In various embodiments, the system can be further configured to query a database of filter providers, calculate the distance to the filter providers, calculate the remaining useful life of the current fuel filter 208, and alert the driver of the vehicle 102 if the remaining useful life of the current fuel filter 208 is insufficient to reach at least one of these filter providers. In various embodiments, the system can be further configured to calculate the optimal location for a filter service provider to meet with the vehicle 102 requiring fuel filter 208 service based on the vehicle's planned route, minimizing travel time for the service provider and ensuring that the filter can be replaced before the end of its useful life.

[0155] In various embodiments, the present application may include a maintenance service guidance system. The system may include system control circuitry. The system may be configured to calculate, based on the vehicle's planned route, an optimal location for a filter service provider to meet a vehicle requiring fuel filter service, minimizing travel time for the service provider and ensuring that the filter is replaced before the end of its useful life. This may be accomplished by calculating the remaining filter life as described elsewhere herein and then determining a point along the currently planned route corresponding to when the remaining filter life will be exhausted (with or without a safety distance margin). For example, if it is determined that the currently used fuel filter has a remaining life of approximately 200 kilometers, a point along the vehicle's currently planned route that is approximately 200 kilometers (or less, if a safety factor is applied) from the current location may be determined. A route planning API, such as the "Directions API" commercially available as part of the Google Maps platform (e.g., to which data can be sent and received), may then be used to calculate a route for the filter service provider to meet the vehicle's fuel filter service needs. Time may also be assessed. For example, if it is determined that 200 kilometers will take 2.5 hours at an average speed, the filter repair service provider may be directed to arrive at the calculated rendezvous point within 2.5 hours.

[0156] In some embodiments, the present invention may include a service guidance system comprising system control circuitry, wherein the system is configured to calculate an optimal route to a filter service provider (e.g., which may be a fixed location such as a brick-and-mortar service station) based on a planned route of a vehicle, minimize the vehicle's travel time, and ensure that the filter is replaced before the end of its useful life. In some embodiments, the present invention may include a vehicle guidance system comprising system control circuitry, wherein the system is configured to consider the location of the filter service provider to calculate an optimal route to a destination, minimize the vehicle's travel time, and ensure that the filter is replaced before the end of its useful life. In some embodiments, the system is configured to consider the location of the filter service provider to optimize the vehicle's existing planned route, minimize the vehicle's travel time, and ensure that the filter is replaced before the end of its useful life.

[0157] In some cases, analysis of refueling locations may be triggered by or based on identifying an abnormal filter loading curve (eg, the onset of an abnormal filter loading curve) to determine which refueling locations may be adversely affecting fuel filter loading.

[0158] Now refer to Figure 11 , shows a graph of fuel filter pressure drop versus time showing different types of ideal filter loading curves. Specifically, Figure 11A normal load curve 1102 is shown, characterized by a relatively gradual initial increase in pressure drop (ΔP), followed by a sharp increase in pressure drop later in the filter's life. Figure 11 Two types of abnormal filter load curves are also shown. Specifically, Figure 11 An accelerated load curve 1104 and a sudden blockage curve 1106 are shown. The accelerated load curve 1104 may be caused by contaminants in the fuel (debris, dust, glycerin, etc.). The accelerated load curve 1104 has the same overall shape as the normal load curve 1102, but is characterized by a more rapid increase to a higher pressure drop value. Although Figure 11 Pressure drop is specifically shown, but it will be understood that other measures of filter resistance may exhibit similar patterns.

[0159] Sudden blockage curve 1106 may be caused by factors such as extremely contaminated fuel and / or adverse reactions between components within the fuel having different compositions (e.g., fuel chemistry) or additives (e.g., desiccants, preservatives, etc.), which may cause substances in solution to precipitate out or form other particulates. Particulates / precipitates may include, but are not limited to, amine carboxylates, metal carboxylates, and other compounds or salts.

[0160] It will be understood that Figure 11 The filter loading curve shown is an ideal curve. Further, the accelerated loading curve 1104 represents a specific level of contaminants / impurities and will vary depending on the contaminant / impurity level, with higher levels of contaminants / impurities resulting in faster loading. However, in some embodiments, specific filter loading curves can be stored within the system (e.g., stored in a memory and / or database) to serve as prototype filter loading curves (or templates). For example, the system can have multiple different prototype filter loading curves, such as 2, 3, 4, 5, 6, 8, 10, 15, 20, 30, 40, 50, 60, or more prototype filter loading curves corresponding to different filter loading conditions encountered in the field. Figure 11 The load curves shown serve as three specific examples of curves that can be used as prototypes. The observed filter load curves can then be matched against the set of prototype curves to determine which is the best match. Pattern matching and / or curve fitting techniques can be used to determine which is the best match. In some embodiments, a least squares-based approach can be used. In some embodiments, a machine learning-based approach (discussed in further detail below) can be used. Once a filter load curve prototype or template is found, a prediction can be performed based on extrapolation using the identified prototype or template filter load curve.

[0161] In various embodiments herein, the effect of a particular refueling location on fuel filter loading can be determined based on its effect on a filter load curve. In various embodiments, the system can be configured to distinguish between normal filter load curves and abnormal filter load curves. Specifically, in various embodiments, the system can be configured to distinguish between normal filter load curves, accelerated filter load curves, and sudden blockage curves. Aspects that can be used to distinguish such curves may include, but are not limited to, the maximum or average rate of change of the observed filter resistance (such as pressure drop or another metric) and the maximum or average rate of change of the observed filter resistance (such as pressure drop or another metric) for a given amount of distance the fuel filter has been used. In various embodiments, a filter load curve whose maximum rate of change (slope) exceeds a threshold is considered an abnormal filter load curve. In various embodiments, a filter load curve whose maximum rate of change (slope) exceeds a specific usage level (distance and / or time) threshold is considered an abnormal filter load curve. In various embodiments, multiple thresholds may be used. For example, a filter load curve (taking into account or not taking into account distance and / or usage time) whose maximum change rate (slope) exceeds a first threshold is considered abnormal, and is further considered as a sudden blockage curve if the maximum change rate also exceeds a second threshold, or is considered as an accelerated load curve if the maximum change rate does not exceed the second threshold.

[0162] In some embodiments, the system can be configured to identify a refueling location and / or refueling location pattern visited immediately before the onset of an abnormal filter load profile. In various embodiments, the system can be configured to identify a refueling location and / or refueling location pattern visited immediately before the filter load profile changes to exhibit a faster load. In various embodiments, the system control circuitry can be configured to determine a sequence of refueling locations visited immediately before the onset of the sudden blockage profile. The determined sequence can include 2, 3, 4, 5, 6, 7, 8, or more refueling locations previously visited.

[0163] After a particular refueling location has been identified as a possible source of fuel that is causing an abnormal fuel filter load profile, various other steps may be taken. In some embodiments, the system may classify the identified location and / or the identified location pattern as a source (or possible source) of contaminated fuel and may store this classification in a refueling location database along with information about the load profile generated by refueling at the specific refueling location. In various embodiments, the system may classify the identified location as a source or possible source of contaminated fuel and then query the database for additional data regarding the identified location, such as any confirmation data based on other refueling events (with either positive or negative results) that have been recorded regarding the same refueling location.

[0164] In some embodiments, the system herein can create and / or store a list of known high-quality (or approved) refueling locations based on their impact on fuel filter loading or other aspects. Similarly, in some embodiments, the system herein can create and / or store a list of known low-quality refueling locations based on their impact on fuel filter loading or other aspects. For example, when the system categorizes refueling locations as described above, the system can add these refueling locations to a data storage table that is part of the onboard system itself and / or part of a remote data storage facility accessible via a data network. These (multiple) lists can then be accessed by (multiple) systems that are part of the same vehicle in the future, other vehicles managed by the same fleet management system, and / or other vehicles not managed by the same fleet management system, in order to provide system guidance about optimal refueling locations and / or be considered as part of the optimal vehicle route calculation described herein. In some cases, other systems or other operators can further modify and / or annotate these lists for various purposes. As just one example, a fleet manager can modify and / or annotate these lists to identify refueling locations with which the fleet may have a fuel supply contract relationship.

[0165] It will be understood that the system herein may include many different components. Figure 12 , shows a block diagram of some components of a fuel monitoring system according to various embodiments herein. However, it will be understood that various embodiments may include a greater or lesser number of components, and that this diagram is merely illustrative. Specifically, Figure 12 A fuel filter monitoring device 210 is shown. The fuel filter monitoring device 210 may include a housing 1202 and system control circuitry 1204 or ("control circuitry"). The control circuitry 1204 may include a plurality of different electronic components, including, but not limited to, a microprocessor, a microcontroller, an FPGA (field programmable gate array) chip, an application specific integrated circuit (ASIC), etc. The control circuitry 1204 may perform the various operations described herein. However, it will be understood that the various operations described herein may be performed across multiple devices having separate physical circuitry, processors, or controllers, with different operations being performed redundantly or partitioned across different physical devices. As such, some operations may be performed (in whole or in part) at the edge, such as by circuitry / processors / controllers associated with the fuel filter monitoring device 210, while other operations may be performed (in whole or in part) by separate devices or in the cloud.

[0166] The system's fuel filter sensor arrangement or sensor package can include an upstream pressure sensor 204, which can be associated with an upstream portion of fuel line 1242 and positioned upstream of and / or as part of filter head unit 202 but upstream of the fuel filter. Upstream pressure sensor 204 can communicate with upstream pressure sensor channel interface 1214. The fuel filter sensor arrangement can also include a downstream pressure sensor 206, which can be associated with a downstream portion of fuel line 1244 and positioned downstream of and / or as part of filter head unit 202 but downstream of the fuel filter. Downstream pressure sensor 206 can communicate with downstream pressure sensor channel interface 1218.

[0167] In various embodiments, the fuel filter monitoring device 210 may include and / or communicate with the water-in-fuel sensor 1208 and the water-in-fuel sensor channel interface 1206. In various embodiments, the fuel filter monitoring device 210 may include and / or communicate with another type of sensor, such as a temperature sensor 1212 and a temperature sensor channel interface 1210. Other types of sensors herein may include vibration sensors, flow sensors, and the like.

[0168] The channel interface may include various components, such as amplifiers, analog-to-digital converters (ADCs), digital-to-analog converters (DACs), digital signal processors (DSPs), filters (high-pass, low-pass, band-pass), etc. In some cases, the channel interface may not exist as a discrete component, but may be integrated into the control circuit 1204.

[0169] The temperature sensor herein can be of various types. In some embodiments, the temperature sensor 1212 can be a thermistor, a resistance temperature device (RTD), a thermocouple, a semiconductor temperature sensor, or the like.

[0170] The pressure sensors herein can be of various types. Pressure sensors 204, 206 can include, but are not limited to, strain gauge pressure sensors, capacitive pressure sensors, piezoelectric pressure sensors, and the like. In some embodiments, the pressure sensors herein can be MEMS-based pressure sensors. In various embodiments, the pressure sensors can be high-speed (e.g., high sampling rate) pressure sensors. In various embodiments, the high-speed pressure sensors can sample at a rate of 1,000 Hz, 1,500 Hz, 2,000 Hz, 2,500 Hz, 3,000 Hz, 5,000 Hz, 10,000 Hz, 15,000 Hz, 20,000 Hz, or higher, or at a rate falling within a range between any of the foregoing. In various embodiments, the high-speed pressure sensors can have a response time of less than 10 milliseconds, 5 milliseconds, 2.5 milliseconds, 1 millisecond, 0.5 milliseconds, 0.25 milliseconds, 0.1 milliseconds, 0.05 milliseconds, or 0.01 milliseconds, or a response time falling within a range between any of the foregoing.

[0171] The processing power of the control circuit 1204 and its components can be sufficient to perform various operations, including various operations on signals / data from sensors (such as sensors 204, 206, 1208 and 1212), including but not limited to: averaging, averaging over time, statistical analysis, normalization, aggregation, classification, deletion, traversal, transformation, squeezing (such as eliminating selected data and / or converting data into a smaller granularity), compression (such as using a compression algorithm), merging, interpolation, time stamping, filtering, discarding outliers, calculating trends and trend lines (linear, logarithmic, polynomial, power, exponential, moving average, etc.), normalizing data / signals, etc. Fourier analysis can decompose a physical signal into multiple discrete frequencies or a spectrum within a continuous range. In various embodiments herein, the operations on the signal / data can include a fast Fourier transform (FFT) for converting the data / signal from the time domain to the frequency domain. Other operations on the signal / data here can include spectral estimation, frequency domain analysis, root mean square acceleration value (G RMS ), calculations of acceleration spectral density, power spectral density, Fourier series, Z-transform, resonant frequency determination, harmonic frequency determination, etc. It will be understood that while the various operations described herein (such as fast Fourier transforms) can be performed by a general-purpose microprocessor, they can also be more efficiently performed by a digital signal processor (DSP), which in some embodiments can be integrated with the control circuit 1204 or can exist as a separate discrete component.

[0172] In various embodiments herein, machine learning algorithms may be used to derive relationships between specific refueling locations and their impact on filter loading behavior. Furthermore, in various embodiments herein, machine learning algorithms may be used to match observed filter loading profiles with previously stored filter loading profiles (e.g., pattern matching with prototype profiles) to identify the type of observed load profile and / or predict the future impact of such profiles. The machine learning algorithms used herein may include, but are not limited to, supervised learning algorithms and unsupervised learning algorithms.

[0173] The machine learning algorithms used in this article may include, but are not limited to: classification algorithms (supervised algorithms that predict classification labels), clustering algorithms (unsupervised algorithms that predict classification labels), ensemble learning algorithms (supervised meta-algorithms for combining multiple learning algorithms), general algorithms for predicting arbitrary structured sets of labels, multilinear subspace learning algorithms (using tensor representation to predict labels of multidimensional data), real-valued sequence labeling algorithms (predicting sequences of real-valued labels), regression algorithms (predicting real-valued labels), and sequence labeling algorithms (predicting sequences of classification labels).

[0174] The machine learning algorithms herein may also include parametric algorithms (such as linear discriminant analysis, quadratic discriminant analysis, and maximum entropy classifiers) and non-parametric algorithms (such as decision trees, kernel estimation, naive Bayes classifiers, neural networks, perceptrons, and support vector machines). The clustering algorithms herein may include classification mixture models, deep learning methods, hierarchical clustering, K-means clustering, correlation clustering, and kernel principal component analysis. The ensemble learning algorithms herein may include boosting, bootstrap aggregation, ensemble averaging, and mixed experts. The general algorithms herein for predicting arbitrary structured sets of labels may include Bayesian networks and Markov random fields. The multilinear subspace learning algorithms herein may include multilinear principal component analysis (MPCA). The real-valued sequence labeling algorithms may include Kalman filters and particle filters. The regression algorithms herein may include both supervised (such as Gaussian process regression, linear regression, neural networks, and deep learning methods) and unsupervised (such as independent component analysis and principal component analysis) methods. The sequence labeling algorithms in this paper can include both supervised (such as conditional random fields, hidden Markov models, maximum entropy Markov models, and recurrent neural networks) and unsupervised (hidden Markov models and dynamic time warping) methods.

[0175] In various embodiments, the fuel filter monitoring device 210 may include a power circuit 1222. In some embodiments, the power circuit 1222 may include various components including, but not limited to, a battery 1224, a capacitor, a power receiver such as a wireless power receiver, a transformer, a rectifier, and the like.

[0176] In various embodiments, the fuel filter monitoring device 210 may include an output device 1226. The output device 1226 may include various components for visual and / or audio output, including but not limited to a light (e.g., an LED light), a display screen, a speaker, etc. In some embodiments, the output device may be used to provide notifications or alerts to system users, such as the current system status, problem indications, required user intervention, the appropriate time to perform maintenance actions, etc.

[0177] In various embodiments, fuel filter monitoring device 210 may include memory 1228 and / or a memory controller. The memory may include various types of memory components, including dynamic RAM (D-RAM), read-only memory (ROM), static RAM (S-RAM), disk storage, flash memory, EEPROM, battery-backed RAM such as S-RAM or D-RAM, and any other type of digital data storage component. In some embodiments, the electronic circuit or component includes volatile memory. In some embodiments, the electronic circuit or component includes non-volatile memory. In some embodiments, the electronic circuit or component may include transistors interconnected to operate as latches or flip-flops to provide positive feedback, thereby allowing the circuit to have two or more metastable states and remain in one of these states until altered by an external input. Data storage may be based on such a circuit including a flip-flop. Data storage may also be based on charge storage in capacitors or other principles. In some embodiments, non-volatile memory 1228 may be integrated with control circuit 1204.

[0178] In various embodiments, the fuel filter monitoring device 210 may include a clock circuit 1230. In some embodiments, the clock circuit 1230 may be integrated with the control circuit 1204. Although not shown in FIG. Figure 12 It is not shown, but it will be understood that various embodiments herein may include a data / communication bus to provide, for example, I 2 C. Data transmission between components such as a serial peripheral interface (SPI), a universal asynchronous receiver / transmitter (UART), etc. In some embodiments, an analog signal interface may be included. In some embodiments, a digital signal interface may be included.

[0179] In various embodiments, the fuel filter monitoring device 210 may include communication circuitry 1232. In various embodiments, the communication circuitry may include components such as an antenna 1234, an amplifier, a filter, a digital-to-analog converter, and / or an analog-to-digital converter. In some embodiments, the fuel filter monitoring device 210 may also include a wired input / output interface 1236 for wired communication with other systems / components, including but not limited to one or more vehicle ECUs, a CANBus network (Controller Area Network), and the like.

[0180] The fuel monitoring system for a vehicle may also include geolocation circuitry 1238. In various embodiments, geolocation circuitry 1238 may be configured to generate or receive geolocation data. In various embodiments, geolocation circuitry 1238 may receive geolocation data from a separate device. In various embodiments, geolocation circuitry 1238 may infer geolocation based on detection of wireless signals (e.g., Wi-Fi signals, cellular tower signals, etc.). In various embodiments, geolocation circuitry 1238 may include satellite communication circuitry.

[0181] The system and / or system control circuitry 1204 may be configured to perform various calculations as described herein. For example, in various embodiments, system control circuitry 1204 may be further configured to estimate an expected load rate associated with refueling at a particular refueling location 116 based on previously observed fuel filter 208 loads. In various embodiments, system control circuitry 1204 may be further configured to calculate a cost associated with a particular refueling location 116 based on the estimated expected fuel filter 208 load rate. In various embodiments, system control circuitry 1204 may be further configured to generate a list of recommended and non-recommended fueling stations. In various embodiments, system control circuitry 1204 may be further configured to generate an alert for the driver of vehicle 102 when vehicle 102 enters a non-recommended fueling station location. In various embodiments, system control circuitry 1204 may be further configured to generate a report describing the frequency with which different drivers in the fleet use recommended and non-recommended fueling stations. In various embodiments, system control circuitry 1204 may be configured to distinguish between normal filter load profiles. In various embodiments, the system control circuitry 1204 is configured to distinguish between a normal filter load profile and an abnormal filter load profile. In various embodiments, the system control circuitry 1204 may be configured to identify the refueling locations 116 visited immediately before the onset of the abnormal filter load profile. In various embodiments, the system control circuitry 1204 may be configured to identify the refueling locations 116 visited immediately before the filter load profile changed to exhibit a faster load. In various embodiments, the system control circuitry 1204 classifies the identified locations as sources of contaminated fuel and stores this classification in the refueling location 116 database. In various embodiments, the system control circuitry 1204 may be further configured to generate fuel system parts inventory recommendations based on the refueling location 116 database. In various embodiments, the system control circuitry 1204 classifies the identified locations as possible sources of contaminated fuel and queries the database to obtain additional data regarding the identified locations. In various embodiments, the system control circuitry 1204 may be configured to determine the order of the refueling locations visited immediately before the onset of the sudden blockage profile. In various embodiments, the system control circuitry 1204 may be further configured to evaluate at least one of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and the number of detected refuelings to identify the impact of a specific refueling location on fuel filter loading. In various embodiments, the system control circuitry 1204 may be further configured to evaluate data from a water-in-fuel sensor and correlate the refueling location with subsequent changes in the water-in-fuel sensor data to identify the impact of a specific refueling location on the water-in-fuel sensor data.

[0182] method

[0183] Many different methods are contemplated herein, including, but not limited to, methods of manufacture, methods of use, etc. Aspects of the system / device operations described elsewhere herein may be performed as operations of one or more methods according to various embodiments herein.

[0184] In an embodiment, a method of monitoring a fuel system may include measuring filter restriction, identifying a refueling location based on fuel level data and geolocation data, and calculating an impact of a specific refueling location on fuel filter loading by evaluating a filter restriction trend after refueling at the refueling location.

[0185] In an embodiment, the method may further include estimating an expected loading rate associated with refueling at the particular refueling location based on previously observed fuel filter loading. In an embodiment, the method may further include calculating a cost associated with the particular refueling location based on the estimated expected fuel filter loading rate.

[0186] In an embodiment, the method may further include generating a recommendation that may include a recommended refueling location. In an embodiment, the method may further include forwarding the recommendation to a mobile communication device associated with the vehicle or the vehicle driver. In an embodiment of the method, the recommendation is generated to include a fuel system parts inventory that takes into account the refueling location. In an embodiment, the method may further include generating a recommendation that may include a recommended refueling time. In an embodiment, the method may further include generating a recommendation that may include a recommended refueling location and a recommended refueling time. In an embodiment, the method may further include forwarding the recommendation to a mobile communication device associated with the vehicle or the vehicle driver.

[0187] In an embodiment, the method may further include generating a list of recommended and non-recommended fuel stations. In an embodiment, the method may further include alerting a vehicle driver when the vehicle enters a non-recommended fuel station location. In an embodiment, the method may further include generating a report describing the frequency with which different drivers in the fleet used recommended and non-recommended fuel stations.

[0188] In an embodiment, the method may further comprise distinguishing between a normal filter load curve, an accelerated filter load curve and a sudden blockage curve. In an embodiment, the method may further comprise distinguishing between a normal filter load curve and an abnormal filter load curve.

[0189] In an embodiment, the method may further comprise identifying a refueling location visited immediately before the abnormal filter loading profile begins. In an embodiment, the method may further comprise identifying a refueling location visited immediately before the filter loading profile changes to exhibit a faster load.

[0190] In an embodiment, the method may further comprise classifying the identified location as a source of contaminated fuel and storing the classification in a refueling location database.

[0191] In an embodiment, the method may further include generating a fuel system parts inventory recommendation based on the refueling location database. In an embodiment of the method, the fuel system parts inventory recommendation includes a recommendation to increase fuel filter inventory at a refueling location that occurs in a series of refueling locations subsequent to the identified location with contaminated fuel.

[0192] In an embodiment, the method may further include classifying the identified location as a possible source of contaminated fuel, and querying a database to obtain additional data regarding the identified location.

[0193] In an embodiment, the method may further comprise determining a sequence of refueling locations visited immediately prior to the onset of the sudden jam profile.

[0194] In an embodiment, the method may further include evaluating one or more of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and number of detected refuelings to identify the impact of a specific refueling location on fuel filter loading.

[0195] In an embodiment, identifying the refueling location based on the fuel level data and the geolocation data includes identifying the geolocation when the fuel level increases.

[0196] In an embodiment, the method may further include evaluating data from a water-in-fuel sensor and identifying an effect of a specific refueling location on the water-in-fuel sensor data.

[0197] In an embodiment, the method may further comprise estimating the remaining fuel filter life taking into account the refueling locations used.

[0198] It should be noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It should also be noted that the term "or" is generally employed in its sense including "and / or" unless the context clearly dictates otherwise.

[0199] It should also be noted that, as used in this specification and the appended claims, the phrase "configured to" describes a system, device, or other structure that is constructed or configured to perform a particular task or adopt a particular configuration. The phrase "configured to" may be used interchangeably with other similar phrases, such as arranged and configured, constructed and arranged, constructed, manufactured and arranged, etc.

[0200] All publications and patent applications in this specification are indicative of the levels of ordinary skill in the art to which the invention pertains. All publications and patent applications are incorporated herein by reference to the same extent as if each individual publication or patent application was specifically and individually indicated by reference.

[0201] As used herein, the recitations of numerical ranges by endpoints are intended to include all numbers within that range (eg, 2 to 8 includes 2.1, 2.8, 5.3, 7, etc.).

[0202] The headings used herein are provided to be consistent with the recommendations under 37 CFR 1.77 or to otherwise provide organizational cues. These headings should not be construed as limiting or characterizing the inventions set forth in any claims that may issue from this disclosure. As an example, although a heading may refer to a "Technical Field," such claims should not be limited by the language selected under this heading to describe the so-called technical field. In addition, the description of a technique in the "Background Art" is not an admission that the technique is prior art to any invention in this disclosure. Nor should the "Summary of the Invention" be construed as characterizing the invention set forth in the claims that have already been issued.

[0203] The embodiments described herein are not intended to be exhaustive or to limit the invention to the precise forms disclosed in the detailed description that follows. Rather, the embodiments are selected and described so that others skilled in the art may appreciate and understand the principles and practices. Thus, various aspects have been described with reference to various specific and preferred embodiments and techniques. However, it should be understood that many variations and modifications may be made within the spirit and scope of this disclosure.

Claims

1. A fuel monitoring system for a vehicle, the fuel monitoring system comprising: a fuel filter sensor device configured to generate data reflecting a filter resistance value of the fuel filter; geolocation circuitry configured to generate or receive geolocation data; A system control circuit configured to evaluating the fuel filter sensor device data to determine a change in the filter resistance value; receiving fuel level data; cross-referencing geolocation data and fuel level data to identify utilized refueling locations; The refueling location is correlated with subsequent changes in the filter restriction value to identify the impact of the specific refueling location utilized on fuel filter loading.

2. The fuel monitoring system of claim 1, wherein: The system control circuitry is further configured to estimate an expected load rate associated with refueling at a particular refueling location based on previously observed fuel filter loading.

3. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to calculate a cost associated with a particular refueling location based on the estimated expected fuel filter loading rate.

4. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate a recommendation including a recommended refueling location.

5. The fuel monitoring system of claim 4, wherein: The recommendation is forwarded to a mobile communication device associated with the vehicle or the driver of the vehicle.

6. The fuel monitoring system of claim 4, wherein: The recommendations are formed to include consideration of fuel system parts inventory at the refueling location.

7. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate a recommendation including a recommended refueling time.

8. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate a recommendation including a recommended refueling location and a recommended refueling time.

9. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate a list of recommended and non-recommended fueling stations.

10. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate an alert for a vehicle driver when the vehicle enters a non-recommended fuel station location.

11. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate a report describing the frequency with which different drivers in the fleet used recommended and non-recommended fueling stations.

12. The fuel monitoring system according to any one of claims 1 to 2, wherein: The fuel level data is received from the CANBus network.

13. The fuel monitoring system of any one of claims 1 to 2, wherein the fuel filter sensor device includes an upstream pressure sensor configured to sense pressure in a fuel line upstream of the fuel filter and a downstream pressure sensor configured to sense pressure in a fuel line downstream of the fuel filter.

14. The fuel monitoring system of any one of claims 1 to 2, the geolocation circuitry comprising satellite communication circuitry.

15. The fuel monitoring system according to any one of claims 1 to 2, wherein: The geolocation circuit receives geolocation data from a separate device.

16. The fuel monitoring system according to any one of claims 1 to 2, wherein: The geolocation circuitry infers geolocation based on detection of wireless signals.

17. The fuel monitoring system of claim 16, wherein the wireless signal comprises at least one of a WIFI signal and a cellular communication tower signal.

18. The fuel monitoring system according to any one of claims 1 to 2, wherein: The effect of a particular refueling location on fuel filter loading is determined based on the effect on the filter loading curve.

19. The fuel monitoring system of any one of claims 1 to 2, the system control circuit being configured to distinguish between a normal filter loading curve, an accelerated filter loading curve, and a sudden plugging curve.

20. The fuel monitoring system of any one of claims 1-2, the system control circuit being configured to distinguish between a normal filter loading curve and an abnormal filter loading curve.

21. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is configured to identify a refueling location visited immediately before the onset of an abnormal filter loading profile.

22. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is configured to identify a refueling location visited immediately before a filter loading profile changes to exhibit a faster loading.

23. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry classifies the identified location as a source of contaminated fuel and stores the classification in a refueling location database.

24. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to generate fuel system parts inventory recommendations based on the refueling location database.

25. The fuel monitoring system of claim 24, wherein: The fuel system parts inventory recommendations include recommendations to increase fuel filter inventory at refueling locations occurring in a series of refueling locations subsequent to the identified location having contaminated fuel.

26. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry classifies the identified location as a possible source of contaminated fuel and queries a database to obtain additional data regarding the identified location.

27. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is configured to determine a sequence of refueling locations visited immediately prior to the onset of a sudden jam profile.

28. The fuel monitoring system according to any one of claims 1 to 2, wherein: The system control circuitry is further configured to evaluate one or more of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and a number of detected refuelings to identify an effect of a specific refueling location on fuel filter loading.

29. The fuel monitoring system according to any one of claims 1 to 2, wherein: Cross-referencing the geolocation data and the fuel level data to identify a refueling location includes identifying the geolocation when the fuel level increases.

30. The fuel monitoring system of any one of claims 1-2, further comprising a water-in-fuel sensor, the system control circuitry being further configured to evaluate data from the water-in-fuel sensor and to correlate refueling locations with subsequent changes in the data from the water-in-fuel sensor to identify the impact of specific refueling locations on the water-in-fuel sensor data.

31. The fuel monitoring system of any one of claims 1-2, further comprising a particle counter, the system control circuitry being further configured to evaluate data from the particle counter and to correlate refueling locations with subsequent changes in the data from the particle counter to identify the effects of specific refueling locations on the particle counter data.

32. The fuel monitoring system of any one of claims 1 to 2, the system control circuitry being configured to estimate the remaining fuel filter life taking into account the refueling location used.

33. The fuel monitoring system according to any one of claims 1 to 2, wherein: The filter resistance value includes a pressure drop across the fuel filter.

34. A method of monitoring a fuel system, the method comprising Measuring the filter resistance of the fuel filter; identifying a refueling location based on the fuel level data and the geolocation data; and The effect of a specific refueling location on fuel filter loading is calculated by evaluating filter restriction trends after refueling at the refueling location.

35. The method of claim 34, further comprising estimating an expected loading rate associated with refueling at a particular refueling location based on previously observed fuel filter loading.

36. The method of any one of claims 34 to 35, further comprising calculating a cost associated with a particular refueling location based on the estimated expected fuel filter loading rate.

37. The method of any one of claims 34 to 35, further comprising generating a recommendation including a recommended refueling location.

38. The method of claim 37, further comprising forwarding the recommendation to a mobile communication device associated with the vehicle or a vehicle driver.

39. The method of claim 37, wherein: The recommendations are generated to include consideration of fuel system parts inventory at the refueling location.

40. The method of any one of claims 34 to 35, further comprising generating a recommendation including a recommended refueling time.

41. The method of any one of claims 34 to 35, further comprising generating a recommendation comprising a recommended refueling location and a recommended refueling time.

42. The method of claim 41 further comprising forwarding the recommendation to a mobile communication device associated with a vehicle or a vehicle driver.

43. The method of any one of claims 34 to 35, further comprising generating a list of recommended and non-recommended fueling stations.

44. The method of claim 43, further comprising generating an alert to a vehicle driver when the vehicle enters a non-recommended fuel station location.

45. The method of any one of claims 34 to 35, further comprising generating a report describing the frequency with which different drivers in the fleet use recommended and non-recommended fueling stations.

46. ​​The method of any one of claims 34 to 35, further comprising distinguishing between a normal filter loading curve, an accelerated filter loading curve, and a sudden clogging curve.

47. The method of any one of claims 34 to 35, further comprising distinguishing between a normal filter loading curve and an abnormal filter loading curve.

48. The method of any one of claims 34 to 35, further comprising identifying a refueling location visited immediately before the onset of the abnormal filter loading profile.

49. The method of any one of claims 34 to 35, further comprising identifying a refueling location visited immediately before the filter loading curve changes to exhibit a faster loading.

50. The method of any one of claims 34 to 35, further comprising classifying the identified location as a source of contaminated fuel and storing the classification in a refueling location database.

51. The method of claim 50, further comprising generating fuel system parts inventory recommendations based on the refueling location database.

52. The method of claim 51, wherein The fuel system parts inventory recommendations include recommendations to increase fuel filter inventory at refueling locations occurring in a series of refueling locations subsequent to the identified location having contaminated fuel.

53. The method of any one of claims 34 to 35, further comprising classifying the identified location as a possible source of contaminated fuel, and querying a database to obtain additional data about the identified location.

54. The method of any one of claims 34 to 35, further comprising determining a sequence of refueling locations visited immediately prior to the onset of the sudden blockage profile.

55. The method of any one of claims 34-35, further comprising evaluating one or more of weather data, temperature data, pressure data, humidity data, fuel filter model, engine model, driver ID, and number of detected refuelings to identify the impact of a specific refueling location on fuel filter loading.

56. The method of any one of claims 34 to 35, identifying a refueling location based on the fuel level data and the geolocation data comprises identifying a geolocation when the fuel level increases.

57. The method of any one of claims 34-35, further comprising evaluating data from a water-in-fuel sensor and identifying the impact of a specific refueling location on the water-in-fuel sensor data.

58. The method of any one of claims 34 to 35, further comprising estimating the remaining fuel filter life taking into account the refueling locations used.

59. A system for a vehicle, the system comprising: a fuel filter sensor device configured to generate data reflecting a filter resistance value of the fuel filter; geolocation circuitry configured to generate or receive geolocation data; Wherein, the system is configured as evaluating the fuel filter sensor data to determine a change in the filter resistance value; receiving fuel level data; cross-referencing geolocation data and fuel level data to identify utilized refueling locations; correlating a refueling location with subsequent changes in the filter resistance value to identify the effect of the particular refueling location utilized on fuel filter loading; and At least one of a route recommendation and a refueling location recommendation is provided to a user output device based on the fuel filter loading data.

60. The system of claim 59, wherein: The system is configured to query a database including records of specific refueling locations and fuel filter loading rate data associated with the specific refueling locations.

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