# US 10,309,793 B2 · Systems and methods for particulate filter regeneration > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,309,793 B2 - Document ID: US10309793B2 - Status: Granted - Kind: B2 - Application number: 15/606,791 - Filed: 2017-05-26 - Published: 2018-11-29 - Granted: 2019-06-04 - Earliest claimed: 2017-05-26 - Assignees: Ford Global Technologies, LLC - Applicants: Ford Global Technologies, LLC - Inventors: Devesh Upadhyay; Michael Brendan Hopka - Web page: https://patentgrep.com/patent/US10309793B2 ## CPC - G01C 21/3469: {Fuel consumption; Energy use; Emission aspects} - F01N 3/023: using means for regenerating the filters, e.g. by burning trapped particles - F01N 9/002: {of filter regeneration} - F01N 9/007: {Storing data relevant to operation of exhaust systems for later retrieval and analysis, e.g. to research exhaust system malfunctions} - F02D 41/00: Electrical control of supply of combustible mixture or its constituents (F02D43/00 takes precedence {; control of engine starters F02N11/08, electrical control of engine ignition timing F02P5/145}) - F02D 41/029: {the exhaust gas treating apparatus being a particulate filter} - F02D 41/1406: {with use of a optimisation method, e.g. iteration} - G01C 21/3415: {Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents} - G01C 21/3484: {Personalized, e.g. from learned user behaviour or user-defined profiles} - G01C 21/3492: {employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968)} - G01C 21/3611: {using character input or menus, e.g. menus of POIs (character input methods in general G06F3/0233)} - G01C 21/3617: {using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement} - G01C 21/3691: {Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions (arrangements for giving variable traffic instructions G08G1/09)} - F01N 2900/0402: using adaptive learning - F01N 2900/102: Travelling distance - F01N 2900/12: said parameters being related to the vehicle exterior - F01N 2900/1606: Particle filter loading or soot amount - F02D 2200/0812: Particle filter loading - F02D 2200/606: Driving style, e.g. sporty or economic driving - F02D 2200/701: Information about vehicle position, e.g. from navigation system or GPS signal - F02D 2200/702: Road conditions - Y02T 10/40: Engine management systems - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - F01N: GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES OR ENGINES IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNAL-COMBUSTION ENGINES (arrangements in connection with gas exhaust of propulsion units in vehicles B60K13/00; combustion-air intake silencers specially adapted for, or arranged on, internal-combustion engines F02M35/00; protecting against, or damping, noise in general G10K11/16) - F02D: CONTROLLING COMBUSTION ENGINES (vehicle fittings, acting on a single sub-unit only, for automatically controlling vehicle speed B60K31/00; conjoint control of vehicle sub-units of different type or different function, road vehicle drive control systems for purposes other than the control of a single sub-unit B60W) - Y02T: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION ## Abstract Methods and systems are provided for maintaining a database with details of frequently travelled routes and selecting a travel route for a vehicle from the database based on particulate filter regeneration requirements. In one example, a method may include selecting one or more routes from the database based on a current particulate filter soot level, fuel efficiency, travel time, operator behavior, etc., ranking the routes based on the particulate filter regeneration efficiency of each of the one or more routes. At vehicle key-off, the database may be updated with information regarding the travelled route including a level of particulate filter regeneration achieved during the drive cycle. ## Claims ### Claim 1 A method, comprising: learning, via an electronic controller, after a drive cycle, a particulate filter regeneration efficiency as a function of characteristics of a travelled route and operator behavior over the travelled route; updating routes of a database, via the controller, based on the learning; and at onset of a subsequent drive cycle, displaying to an operator one or more routes selected from the database, the selection based on a particulate filter soot load at the onset of the subsequent drive cycle. ### Claim 2 (depends on 1) The method of claim 1, wherein the selection is further based on an operator indicated destination for the drive cycle relative to an origin of the drive cycle. ### Claim 3 (depends on 1) The method of claim 1, wherein the selection is further based on an operator selected cost function including one or more of a highest fuel efficiency and a lowest travel time for the drive cycle. ### Claim 4 (depends on 1) The method of claim 1, further comprising, ranking the one or more routes as a weighted function of each of a particulate filter regeneration efficiency, a probability of completion of a particulate filter regeneration event, a fuel efficiency, and a travel time of each of the one or more routes. ### Claim 5 (depends on 4) The method of claim 4, wherein the particulate filter regeneration efficiency includes a degree of particulate filter regeneration predicted for the drive cycle, and wherein one or more characteristics of the traveled route include a number of stops, a road gradient, and traffic conditions. ### Claim 6 (depends on 4) The method of claim 4, wherein each of the particulate filter regeneration efficiency and the probability of completion of the particulate filter regeneration event are assigned higher weightages when the particulate filter soot load is higher than a threshold. ### Claim 7 (depends on 6) The method of claim 6, wherein each of the fuel efficiency and the travel time are assigned higher weightages when the particulate filter soot load is lower than the threshold. ### Claim 8 (depends on 1) The method of claim 1, further comprising, in response to the operator not selecting a route from the one or more routes displayed to the operator, dynamically predicting an upcoming route segment based on an operator driving history retrieved from the database. ### Claim 9 (depends on 8) The method of claim 8, wherein the operator driving history includes routes previously traveled as a function of one or more of time of day, day of week, and traffic conditions. ### Claim 10 (depends on 1) The method of claim 1, further comprising, in response to the operator selecting a route from the one or more routes displayed to the operator, and initiating travel along the selected route, but then deviating from the selected route, dynamically predicting an upcoming route segment based on an operator driving history retrieved from the database. ### Claim 11 (depends on 10) The method of claim 10, further comprising, based on the route selected by the operator from the one or more displayed routes, scheduling an active particulate filter regeneration event during the drive cycle, wherein during the active particulate filter regeneration event, a temperature of the particulate filter is increased by flowing electric current through the particulate filter. ### Claim 12 (depends on 1) The method of claim 1, further comprising, when a destination for the drive cycle is not specified by the operator, predicting the destination based on an operator driving history as retrieved from the database and displaying to the operator one or more routes selected from the database based on the predicted destination. ### Claim 13 (depends on 1) The method of claim 1, wherein the onset of the drive cycle includes a vehicle key-on event, and wherein updating the database based on the learning includes, at a vehicle key-off event, updating the database with route information, origin characteristics, destination characteristics, operator behavior, level of particulate filter regeneration achieved, engine operating conditions, date and time information, and traffic information. ### Claim 14 An engine method, comprising: in response to an operator destination selection indicated via a display of a vehicle; estimating an exhaust particulate filter soot load via an exhaust pressure sensor; determining a current location of the vehicle via a navigation system; retrieving one or more routes from the current location to a destination from a database via an electronic controller; ranking, via the controller, the one or more routes based on each of a particulate filter regeneration efficiency, fuel efficiency, and time of travel of each route; and displaying to the operator, via a user interface, the one or more routes to the selected destination in order of their rank. ### Claim 15 (depends on 14) The method of claim 14, further comprising, responsive to a higher than threshold particulate filter soot load, ranking the one or more routes by assigning a higher weightage to particulate filter regeneration efficiency and a lower weightage to each of the fuel efficiency and the time of travel. ### Claim 16 (depends on 15) The method of claim 15, further comprising, responsive to a lower than threshold particulate filter soot load, ranking the one or more routes by assigning the higher weightage to each of the fuel efficiency and the time of travel and assigning the lower weightage to the particulate filter regeneration efficiency. ### Claim 17 (depends on 14) The method of claim 14, further comprising, responsive to the operator not selecting a route from the one or more displayed routes or the operator deviating from a selected route, predicting one or more route segments from the current location to the destination based on operator drive history, retrieved from the database, and scheduling passive regeneration of the particulate filter based on the one or more predicted route segments. ### Claim 18 A vehicle method, comprising: in response to a destination for a drive cycle not being indicated by an operator; determining a current location of a vehicle via a navigation system; retrieving a driving history of the operator from a database via an electronic controller; predicting a destination based on the driving history via the controller; dynamically updating selection of one or more upcoming route segments based on the current location of the vehicle relative to the predicted destination via the controller; ranking, via the controller, the one or more upcoming route segments based on each of a corresponding particulate filter regeneration efficiency, a fuel efficiency, and a time of travel; and displaying to the operator, via a user interface, the one or more upcoming route segments to the predicted destination, hierarchically in order of their rank. ### Claim 19 (depends on 18) The method of claim 18, further comprising, in response to the operator not selecting a route from the one or more displayed upcoming route segments, dynamically updating the one or more upcoming route segments based on the driving history and scheduling active regeneration of the particulate filter based on the updated one or more route segments. ### Claim 20 (depends on 18) The method of claim 18, further comprising, at completion of a drive cycle, updating the database with route segment information including operator behavior, level of particulate filter regeneration achieved, engine operating conditions over the completed drive cycle, date and time of travel information, and traffic information over the drive cycle.