Patent classifications
G06F8/66
HOT UPDATES TO CONTROLLER SOFTWARE USING TOOL CHAIN
Disclosed embodiments relate to performing updates to Electronic Control Unit (ECU) software while an ECU of a vehicle is operating. Operations may include receiving, at the vehicle while the ECU of the vehicle is operating, a software update file for the ECU software; writing, while the ECU is operating, the software update file into a first memory location in a memory of the ECU while simultaneously executing a code segment of existing code in a second memory location in the memory of the ECU; and updating a plurality of memory addresses associated with the memory of the ECU based on the software update file and without interrupting the execution of the code segment currently being executed in the second memory location in the memory of the ECU.
Detecting anomalies online using controller processing activity
Disclosed embodiments relate to identifying Electronic Control Unit (ECU) anomalies in a vehicle. Operations may include monitoring, in the vehicle, data representing real-time processing activity of the ECU; accessing, in the vehicle, historical data relating to processing activity of the ECU, the historical data representing expected processing activity of the ECU; comparing, in the vehicle, the real-time processing activity data with the historical data, to identify at least one anomaly in the real-time processing activity of the ECU; and implementing a control action for the ECU when the at least one anomaly is identified.
Patching method, related apparatus, and system
A patching method includes generating an original image through compilation for a plurality of files. If a first file in the plurality of files changes, a new index mode of the first file or new data of the first file may be appended to an end of an original image to update the first file to obtain a new image.
NON-TERMINATING FIRMWARE UPDATE
A computing device of the control plane may disconnect a server from at least one of a network path or a first boot storage device, the server having an initial network address. The computing device of the control plane may store a server state of the server in a storage device of the control plane. The computing device of the control plane may connect the server to an update storage device containing an update code. The computing device of the control plane may instruct the server to execute the update code. The computing device of the control plane may determine that the server has executed the update code. The computing device of the control plane may restore the server to the server state. The computing device of the control plane may reconnect the server to at least one of the network path or the first boot storage device.
Detecting anomalies online using controller processing activity
Disclosed embodiments relate to identifying Electronic Control Unit (ECU) anomalies in a vehicle. Operations may include monitoring, in the vehicle, data representing real-time processing activity of the ECU; accessing, in the vehicle, historical data relating to processing activity of the ECU, the historical data representing expected processing activity of the ECU; comparing, in the vehicle, the real-time processing activity data with the historical data, to identify at least one anomaly in the real-time processing activity of the ECU; and implementing a control action for the ECU when the at least one anomaly is identified.
Orchestrator reporting of probability of downtime from machine learning process
Disclosed embodiments relate to reporting Electronic Control Unit (ECU) errors or faults to a remote monitoring server. Operations may include receiving operational data from a plurality of ECUs in the vehicle, the operational data being indicative of a plurality of runtime attributes of the plurality of ECUs; generating, through a machine learning process, a statistical model of the operational data; receiving live, runtime updates from the plurality of ECUs in the communications network of the vehicle; identifying an ECU error associated with an ECU in the communications network of the vehicle, the ECU error being determined by a comparison of the live, runtime updates with the statistical model of the operational data to identify at least one deviation from the operational data; and wirelessly sending a report to the remote monitoring server based on the live, runtime updates, the report identifying the ECU and the identified ECU error.
Self-healing learning system for one or more controllers
Disclosed embodiments relate to automatically providing updates to at least one vehicle. Operations may include receiving, at a server remote from the at least one vehicle, Electronic Control Unit (ECU) activity data from the at least one vehicle, the ECU activity data corresponding to actual operation of the ECU in the at least one vehicle; determining, at the server and based on the ECU activity data, a software vulnerability affecting the at least one vehicle, the software vulnerability being determined based on a deviation between the received ECU activity data and expected ECU activity data; identifying, at the server, an ECU software update based on the determined software vulnerability; and sending, from the server, a delta file configured to update software on tree ECU with a software update corresponding to the identified ECU software update.
ORCHESTRATOR REPORTING OF PROBABILITY OF DOWNTIME FROM MACHINE LEARNING PROCESS
Disclosed embodiments relate to reporting Electronic Control Unit (ECU) errors or faults to a remote monitoring server. Operations may include receiving operational data from a plurality of ECUs in the vehicle, the operational data being indicative of a plurality of runtime attributes of the plurality of ECUs; generating, through a machine learning process, a statistical model of the operational data; receiving live, runtime updates from the plurality of ECUs in the communications network of the vehicle; identifying an ECU error associated with an ECU in the communications network of the vehicle, the ECU error being determined by a comparison of the live, runtime updates with the statistical model of the operational data to identify at least one deviation from the operational data; and wirelessly sending a report to the remote monitoring server based on the live, runtime updates, the report identifying the ECU and the identified ECU error.
USING DATA DELTAS IN CONTROLLERS AND MANAGING INTERDEPENDENCIES BETWEEN SOFTWARE VERSIONS IN CONTROLLERS USING TOOL CHAIN
Disclosed embodiments relate to perform operations for receiving and integrating a delta file in a vehicle. Operations may include receiving, at an Electronic Control Unit (ECU) in the vehicle, a delta file, the delta file comprising a plurality of deltas corresponding to a software update for software on the ECU and startup code for executing the delta file in the ECU; executing the delta file, based on the startup code, in the ECU; and updating memory addresses in the ECU to correspond to the plurality of deltas from the delta file.
ROLL BACK OF DATA DELTA UPDATES
Disclosed embodiments relate to adjusting vehicle Electronic Control Unit (ECU) software versions. Operations may include receiving a prompt to adjust an ECU of a vehicle from executing a first version of ECU software to a second version of ECU software; configuring, in response to the prompt and based on a delta file corresponding to the second version of ECU software, the second version of ECU software on the ECU in the vehicle for execution; and configuring, in response to the prompt, the first version of ECU software on the ECU in the vehicle to become non-executable.