# US 2022/0032928 A1 · Robustness quotient for vehicle diagnostics and monitoring > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2022/0032928 A1 - Document ID: US20220032928A1 - Status: Published application - Kind: A1 - Application number: 16/945,003 - Filed: 2020-07-31 - Published: 2022-02-03 - Earliest claimed: 2020-07-31 - Assignees: Robert Bosch GmbH - Applicants: Robert Bosch GmbH - Inventors: Ming Yi - Web page: https://patentgrep.com/patent/US20220032928A1 ## CPC - B60W 50/0205: {Diagnosing or detecting failures; Failure detection models} - H04L 67/125: involving control of end-device applications over a network - G06F 16/2379: {Updates performed during online database operations; commit processing} - G07C 5/0808: {Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005)} - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G07C 2205/02: using a vehicle scan tool - 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 - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - 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 Methods and systems for evaluating robustness of vehicle diagnostics and monitoring. One system includes a memory, a communication interface, and an electronic processor. The electronic processor is configured to access diagnostic event data of a vehicle system. The electronic processor is also configured to determine a RQ variable for the current operation cycle based on a set of maximum debounce levels included in the diagnostic event data and a failure threshold. The electronic processor is also configured to store, in the memory, the RQ variable as RQ data at an end of the current operation cycle. The electronic processor is also configured to transmit, via the communication interface, the RQ data for an external robustness evaluation. The electronic processor is also configured to receive, via the communication interface, an update to the failure threshold based on the external robustness evaluation. ## Claims ### Claim 1 A system for evaluating robustness of vehicle diagnostics and monitoring, the system comprising: a memory; a communication interface; and an electronic processor coupled to the memory and the communication interface, the electronic processor configured to access diagnostic event data of a vehicle system, determine a robustness quotient (RQ) variable for the current operation cycle, the RQ variable based on a set of maximum debounce levels included in the diagnostic event data and a failure threshold, store, in the memory, the RQ variable as RQ data at an end of the current operation cycle, transmit, via the communication interface, the RQ data for an external robustness evaluation, and receive, via the communication interface, an update to the failure threshold based on the external robustness evaluation. ### Claim 2 (depends on 1) The system of claim 1, wherein the diagnostic event data includes a set of diagnostic events and a debounce level for each diagnostic event included in the set of diagnostic events. ### Claim 3 (depends on 2) The system of claim 2, wherein the maximum debounce level is the highest debounce level among the debounce levels associated with the set of diagnostic events. ### Claim 4 (depends on 1) The system of claim 1, wherein the RQ variable is an average of each maximum debounce level included in the set of maximum debounce level divided by the failure threshold. ### Claim 5 (depends on 1) The system of claim 1, wherein the RQ variable is a maximum of each maximum debounce level included in the set of maximum debounce level divided by the failure threshold. ### Claim 6 (depends on 1) The system of claim 1, wherein the electronic processor is configured to transmit the RQ data for the external robustness evaluation in response to receiving a request for the RQ data. ### Claim 7 (depends on 1) The system of claim 1, wherein the update is further based on at least one selected from a group consisting of secondary source data and additional data associated with at least one other vehicle. ### Claim 8 A method for evaluating robustness of vehicle diagnostics and monitoring, the method comprising: accessing diagnostic event data of a vehicle system; determining, with an electronic processor, a first robustness quotient (RQ) variable based on a set of maximum debounce levels included in the diagnostic event data and a failure threshold; storing, in memory, the first RQ variable as a first data entry in a RQ data log at an end of the first operation cycle; transmitting the RQ data log for an external robustness evaluation; receiving, via a communication interface, an update to the failure threshold based on the external robustness evaluation; and updating, with the electronic processor, the failure threshold based on the update. ### Claim 9 (depends on 8) The method of claim 8, further comprising: prior to transmitting the RQ data log for the external robustness evaluation, accessing subsequent diagnostic data of the vehicle system, determining a second RQ variable, and storing the second RQ variable as a second data entry in the RQ data log at an end of the second operation cycle. ### Claim 10 (depends on 8) The method of claim 8, further comprising: detecting, with a diagnostic monitor of the vehicle system, a set of diagnostic events of the vehicle system; debouncing, with a debounce function, the set of diagnostic events; and generating the diagnostic event data for the vehicle system based on the debouncing. ### Claim 11 (depends on 10) The method of claim 10, wherein debouncing the set of diagnostic events includes debouncing the set of diagnostic events using at least one selected from a group consisting of a time-based debounce function and a counter-based debounce function. ### Claim 12 (depends on 8) The method of claim 8, wherein determining the first RQ variable includes averaging quotients for each maximum debounce level included in the set of maximum debounce level divided by the failure threshold. ### Claim 13 (depends on 8) The method of claim 8, wherein determining the first RQ variable includes determining a maximum from quotients for each maximum debounce level included in the set of maximum debounce level divided by the failure threshold. ### Claim 14 (depends on 8) The method of claim 8, wherein storing the first RQ variable as the first data entry in the RQ data log at an end of the first operation cycle includes storing the first RQ variable as a first data entry including three bytes of data, wherein an identifier of a diagnostic monitor associated with the diagnostic event data is represented by two bytes of the three bytes of data and the first RQ variable is represented by one byte of the three bytes of data. ### Claim 15 A non-transitory, computer-readable medium storing instructions that, when executed by an electronic processor, perform a set of functions, the set of functions comprising: accessing diagnostic event data of the vehicle system; determining a robustness quotient (RQ) variable, the RQ variable based on a set of maximum debounce levels included in the diagnostic event data and a failure threshold; storing the RQ variable as RQ data at an end of the current operation cycle; transmitting the RQ data for an external robustness evaluation; receiving an update to the failure threshold based on the external robustness evaluation; and updating the failure threshold based on the update. ### Claim 16 (depends on 15) The computer-readable medium of claim 15, further comprising: detecting, with at least one diagnostic monitor, a set of diagnostic events of the vehicle system; debouncing, with a debounce function, the set of diagnostic events; and generating the diagnostic event data based on the debouncing. ### Claim 17 (depends on 16) The computer-readable medium of claim 16, wherein denouncing the set of diagnostic events includes debouncing the set of diagnostic events using at least one selected from a group consisting of a time-based debounce function and a counter-based debounce function. ### Claim 18 (depends on 15) The computer-readable medium of claim 15, wherein generating the diagnostic event data of the vehicle system includes generating diagnostic event data including (a) the set of diagnostic events detected by at least one diagnostic monitor of the vehicle system, (b) a debounce level for each diagnostic event included in the set of diagnostic events, and (c) a fault status for each diagnostic event included in the set of diagnostic events. ### Claim 19 (depends on 15) The computer-readable medium of claim 15, wherein determining the RQ variable includes averaging quotients for each maximum debounce level included in the set of maximum debounce level divided by the failure threshold. ### Claim 20 (depends on 15) The computer-readable medium of claim 15, wherein determining the RQ variable includes determining a maximum from quotients for each maximum debounce level included in the set of maximum debounce level divided by the failure threshold.