# US 2021/0276576 A1 · Failure detection and response > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0276576 A1 - Document ID: US20210276576A1 - Status: Published application - Kind: A1 - Application number: 16/612,293 - Filed: 2018-05-10 - Published: 2021-09-09 - Earliest claimed: 2017-05-08 - Assignees: The Regents of the University of Michigan - Applicants: The Regents of the University of Michigan - Inventors: William B. RIBBENS - Web page: https://patentgrep.com/patent/US20210276576A1 ## CPC - B60W 50/0205: {Diagnosing or detecting failures; Failure detection models} - B60W 50/00: Details of control systems for road vehicle drive control not related to the control of a particular sub-unit {, e.g. process diagnostic or vehicle driver interfaces} - B60W 50/02: Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures - B60W 50/0225: {Failure correction strategy} - B60W 50/14: Means for informing the driver, warning the driver or prompting a driver intervention - G05B 23/0254: {based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks} - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G07C 5/0816: {Indicating performance data, e.g. occurrence of a malfunction} - B60W 2050/0037: {Mathematical models of vehicle sub-units} - B60W 2050/021: {Means for detecting failure or malfunction} - B60W 2050/146: {Display means} - G05B 2219/2637: Vehicle, car, auto, wheelchair - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE ## Abstract A system and method of detecting and responding to a failure of one or more vehicle components, the method including: receiving system input at a failure detection module regarding the one or more vehicle components; determining a system state through use of one or more onboard vehicle sensors; obtaining a nominal state transition matrix and a nominal state input matrix; calculating a present state transition matrix estimate and a present state input matrix estimate based on the nominal state transition matrix, the nominal state input matrix, the system input, and a sampled state derivative; detecting a failure of at least one of the vehicle components based on one or more component parameters of the present state transition matrix estimate and/or the present state input matrix estimate; and performing a vehicle action in response to the detection of the failure. ## Claims ### Claim 1 A method of detecting and responding to a failure of one or more vehicle components, the method comprising: receiving system input at a failure detection module regarding the one or more vehicle components; determining a system state through use of one or more onboard vehicle sensors, wherein the system state relates to the one or more vehicle components; obtaining a nominal state transition matrix and a nominal state input matrix; calculating a present state transition matrix estimate and a present state input matrix estimate based on the nominal state transition matrix, the nominal state input matrix, the system input, and a sampled state derivative; detecting a failure of at least one of the vehicle components based on one or more component parameters of the present state transition matrix estimate and/or the present state input matrix estimate, wherein the one or more component parameters pertain to the at least one vehicle component; and performing a vehicle action in response to the detection of the failure. ### Claim 2 (depends on 1) The method of claim 1, wherein the detecting step further includes comparing the one or more component parameters of the present state transition matrix estimate and/or the present state input matrix estimate for a first vehicle component to a tolerance range for the first vehicle component. ### Claim 3 (depends on 2) The method of claim 2, wherein the detecting step further includes detecting whether the failure is an instant failure or a gradual failure. ### Claim 4 (depends on 3) The method of claim 3, wherein the performing step further includes: when it is detected that the failure is a current failure, issuing an instant alarm to a vehicle operator such that the issuance of the instant alarm constitutes the vehicle action; and when it is detected that the failure is a gradual failure, estimating a time to failure (TTF) and reporting the TTF to the vehicle operator or a vehicle services facility such that the estimation and report of the TTF constitutes the vehicle action. ### Claim 5 (depends on 1) The method of claim 1, wherein the one or more components are represented using a state variable model, wherein the state variable model is given by: {dot over (x)}k=Aixk+Biuk where xk is the system state at time k, uk is the system input at time k, Ai is a present state transition matrix, Bi is a present state input matrix, and {dot over (x)}k is the sampled state derivative at time k. ### Claim 6 (depends on 5) The method of claim 5, wherein the present state transition matrix estimate Âi and the present input value estimate {circumflex over (B)}i are calculated by: estimating the sampled state derivative {dot over (x)}k based on measurements of the system state xk via at least some of the onboard vehicle sensors; calculating a present state transition matrix deviation ΔA and a present state input matrix deviation ΔB using the equation: ΔAxk+ΔBuk={dot over (x)}k−Asxk−Bsuk where AS is the nominal state transition matrix and BS is the nominal state input matrix, wherein Âi=AS+ΔA and {circumflex over (B)}i=BS+ΔB. ### Claim 7 (depends on 6) The method of claim 6, wherein the estimating step includes estimating the sampled state derivative {dot over (x)}k using the following equation: x . k = 1 2 ⁡ [ ( x k + 1 - x k ) ( t k + 1 - t k ) + ( x k - x k - 1 ) ( t k - t k - 1 ) ] where xk+1 is the system state at time sample k+1, xk−1 is the system state at time sample k−1, tk is the time at time sample k, tk+1 is the time at time sample k+1, and tk−1 is the time at time sample k−1. ### Claim 8 (depends on 1) The method of claim 1, wherein the onboard vehicle sensors include at least one vehicle system sensor and at least one supplemental sensor, wherein the system state is represented by one or more system state variables, and wherein each of the one or more system state variables is provided by at least one of the onboard vehicle sensors. ### Claim 9 (depends on 8) The method of claim 8, further comprising the step of: synchronizing the at least one vehicle system sensor with the at least one supplemental sensor so that sensor values associated with the at least one vehicle system sensor and the at least one supplemental sensor are synchronized with respect to time, wherein the synchronization step includes carrying out a time synchronization process for one or more of the at least one vehicle system sensor(s). ### Claim 10 (depends on 9) The method of claim 9, wherein the time synchronizing process includes carrying out each of the following steps for each of the one or more vehicle system sensor(s): obtaining a set of sensor values, wherein the set of sensor values includes a plurality of sensor values that are each taken at different times over a sample time interval; using a polynomial modeling technique to obtain a polynomial model of the set of sensor values over the sample time interval; and deriving one or more adjusted sensor values from the polynomial model that correspond in time to the sensor values associated with the at least one supplemental sensor. ### Claim 11 (depends on 1) The method of claim 1, wherein the receiving, determining, obtaining, and calculating steps comprise a parameter estimation process, wherein the detecting step is carried out using a failure detection filter (FDF), and wherein the FDF uses the present state transition matrix estimate and the present state input matrix estimate obtained from the parameter estimation process to carry out the detecting step. ### Claim 12 A method of configuring a vehicle to detect and respond to a failure of one or more vehicle components, the method comprising: constructing a state variable analytical model for a system under monitoring (SUM); identifying system sensors that can be used to measure at least some state variables of the state variable analytical model; developing a time synchronization process that is particular to the identified system sensors, wherein the time synchronization process enables sensor values obtained by the system sensors to be adjusted so as to obtain adjusted sensor values, wherein the adjusted sensor values conform to a unified sample time; developing a parameter estimation process that can be used to obtain a present state transition matrix estimate and a present state input matrix estimate, wherein the parameter estimation process is developed based on the constructed state variable analytical model; and configuring vehicle electronics of the vehicle to carry out the parameter estimation process and the time synchronization process. ### Claim 13 (depends on 12) The method of claim 12, further comprising the step of: compiling the parameter estimation process and the time synchronization process into a computer program. ### Claim 14 (depends on 13) The method of claim 13, wherein the configuring step includes installing the computer program into the vehicle electronics of the vehicle. ### Claim 15 (depends on 14) The method of claim 14, further comprising the steps of: identifying one or more state variables of the state variable analytical model in which the vehicle is incapable of measuring using the system sensors; and providing one or more supplemental sensors to measure the identified state variables, wherein the one or more supplemental sensors are configured to provide sensor values containing information relating to the identified state variables to the parameter estimation process. ### Claim 16 (depends on 12) The method of claim 12, wherein the development of the parameter estimation process includes constructing a nominal state transition matrix and a nominal state input matrix. ### Claim 17 A vehicle failure detection system, comprising: a system under monitoring (SUM) that includes one or more vehicle electronic system components; one or more onboard vehicle sensors; a failure detection module that includes: a failure detection system (FDS) signal processor; and a memory containing a computer program; and a communication link between the failure detection model and the SUM; wherein the failure detection module is configured to execute the computer program that is stored in the memory of the vehicle failure detection system using the failure detection signal processor, and wherein execution of the computer program by the failure detection signal processor causes the failure detection module to: receive system input regarding the one or more vehicle electronic system components; determine a system state through use of the one or more onboard vehicle sensors, wherein the system state concerns the one or more state variables; obtain a nominal state transition matrix and a nominal state input matrix; calculate a present state transition matrix estimate and a present state input matrix estimate based on the nominal state transition matrix, the nominal state input matrix, the system input, and a sampled state derivative; detect a failure of at least one of the vehicle electronic system components based on one or more component parameters of the present state transition matrix estimate and/or the present state input matrix estimate, wherein the one or more component parameters pertain to the at least one vehicle electronic system component; and perform a vehicle action in response to the detection of the failure. ### Claim 18 (depends on 17) The vehicle failure detection system of claim 17, wherein the one or more onboard vehicle sensors are either or both of system sensors or supplemental sensors, wherein the supplemental sensors are a part of the failure detection module, and wherein the system sensors are either or both of sensors included as a part of the SUM or other system sensors. ### Claim 19 (depends on 17) The vehicle failure detection system of claim 17, wherein the communication link is a direct, hardwired connection between the failure detection model and the SUM. ### Claim 20 (depends on 17) The vehicle failure detection system of claim 17, wherein the communication link is a vehicle communications bus.