A vehicle judder diagnostic method using artificial intelligence applied to a mobile-based GDS according to the present disclosure is characterized in that the mobile-based GDS samples a plurality of sensor signals of a sensor mounted in a vehicle in a vehicle during operation in a judder evaluation mode to quickly, separately diagnose whether the judder phenomenon of the vehicle is a geometric judder or a friction judder by mounting a deep neural network (DNN) model, developed by the trial and error process of a DNN by using the plurality of sensor signals of a test vehicle mounted with a double clutch transmission (DCT), as a judder determination artificial intelligence model 30 in the mobile-based GDS.

A system for conducting a test of an active roll control (ARC) system in a vehicle while the vehicle is moving includes a module and a control module. The module is configured to receive a maneuver and an expected torque associated with the ARC system for the maneuver according to a defined velocity and a defined steering angle. The control module is configured to receive, while the vehicle is controlled to execute the maneuver, an actual torque of the ARC system, an actual velocity of the vehicle, and an actual steering angle of the vehicle. The module is configured to determine whether any one of the actual torque, the actual velocity, and the actual steering angle falls below the expected torque, the defined velocity, and the defined steering angle, respectively, and in response, generate a signal indicating a failure of the test. Other examples systems and methods are also disclosed.

A method for controlling a configuration state of at least one vehicle device of a motor vehicle, wherein calibration state data which signal a current calibration state of a self-calibration routine carried out by the calibration device during a driving operation of the motor vehicle are received from a calibration device of the vehicle device in question. A progress value is assigned to the respective current calibration state data in accordance with a predefined evaluation rule and a configuration data set which defines a configuration state of the vehicle device in question is selected from a plurality of predefined configuration data sets depending on the current progress value, and the vehicle device is configured by the selected configuration data set, wherein at least one function parameter is set according to the respective configuration data set for the execution of the least one sub-function.

The present disclosure relates to a diagnostics system (2) for a vehicle (1). The diagnostics system (2) comprises a plurality of application functions (10) for controlling functions of the vehicle, a plurality of I/O interface modules (30) hosting drivers for I/O devices associated with the application functions (10), and a vehicle diagnostics manager or VDM (20). The I/O interface modules (30) are configured to transmit output signals pertaining to operation of their associated I/O devices to the application functions (10) together with a signal tag identifying the I/O interface module that generated the output signal. Each I/O interface module (30) is also configured to run physical fault monitors in order to detect physical faults for its associated I/O devices, and to maintain a fault record of detected physical faults. Each application function (10) is configured to run strategic fault monitors in order to detect strategic faults for its associated vehicle function. The application functions (10) are configured, upon detection of a strategic fault, to identify the signal tag associated with the output signal that caused the detection of the strategic fault, and to report the detected strategic fault to the VDM (20) together with the associated signal tag. The VDM (20) is configured, upon receiving a notification of a detected strategic fault from an application function (10), to identify a source I/O interface module (30) in dependence on the received signal tag, to read physical faults from the identified source I/O interface module (30), and to triage the physical faults from the identified source I/O interface module (30) with the reported strategic fault in order to identify a cause fault for the reported strategic fault.

A method for testing a vehicular control system includes receiving, at a simulator, a discrete diagram identifying a plurality of tasks to be simulated and connections between the plurality of tasks, and receiving, at the simulator, a requested determinism level selected at a user device from a plurality of determinism levels. An optimal execution policy based on the simulator, the discrete diagram and the requested determinism level is selected from a plurality of execution policies. The plurality of tasks are simulated, by the simulator, using the selected optimal execution policy to simulate operation of the vehicular control system on a vehicle.

Systems and methods for real time and predictive diagnostics of vehicle electronic components. Circuit boards and similar vehicle electronic devices have input/output speeds on the order of tens of gigahertz (GHz). Signal integrity can be affected when operating in real time while a high speed signal travels across circuit boards. To maintain signal integrity, hardware around high speed signals is designed to match impedance and transmission lengths. Additionally, differences can occur from circuit board to circuit board due to aging during vehicle operation, and tolerances in the manufacturing process. Systems and methods are provided herein to compensate for the tolerances in the manufacturing process. The real time and predictive diagnostics of vehicle electronic components provided herein can prevent on-road vehicle failures.

The present disclosure relates to a distributed diagnostics architecture for a vehicle. The diagnostics architecture comprises a plurality of application functions hosted on a central compute platform (CCP) of the vehicle, a plurality of remote input/output concentrator modules (RIOs) provided at different locations within the vehicle, and a vehicle diagnostics manager (VDM). The application functions are configured to control vehicle functions. The application functions are further configured to run diagnostic fault monitors pertaining to strategic or system-level faults for their associated vehicle functions, and to transmit strategic fault data related to their associated vehicle functions to the VDM. The RIO are connected to I/O devices of the vehicle. The RIOs are configured to run diagnostic fault monitors pertaining to physical or component-level faults for their associated I/O devices, and to transmit physical fault data related to their associated I/O devices to the VDM. The VDM is configured to aggregate the received strategic and physical fault data, and to maintain a central fault record of strategic and physical faults.

The present disclosure relates to a control system (2) for a vehicle. The control system is configured to receive a request to initiate a diagnostic conversation, and attempt to initiate the requested diagnostic conversation while the vehicle is in a sleep state. The control system is further configured to determine one or more target participants that are required for participation in a requested diagnostic conversation, to determine an on-board energy status of the vehicle, and to energise the target participants without energising the entire vehicle and initiate the requested diagnostic conversation in dependence on the on-board energy status of the vehicle being sufficient to conduct the requested diagnostic conversation.

A system for performing an MTDM workflow. The system includes a vehicle data platform and a vehicle automation platform. The vehicle data platform is configured to provide a policy to a vehicle, where the policy includes an MTDM workflow element. The vehicle automation platform is configured to provide a recipe to the vehicle, where the recipe includes actions for an automated vehicle response. The vehicle data platform is further configured to receive collected data from the vehicle in response to an execution of at least one of the MTDM workflow element or the automated vehicle response by a controller of the vehicle.

A system comprising a vehicle subsystem comprising a plurality of modules and a vehicle chassis, wherein the plurality of modules (i) comprises mechanical or electronic components that simulate one or more vehicle or vehicle electronic functionalities, (ii) comprises a modular form factor corresponding to the vehicle chassis, and (iii) is coupled to a vehicle computer; an attacker subsystem configured to attack a module of the plurality of modules; and a controller subsystem configured to control operation of the vehicle subsystem and the attacker subsystem by (i) providing (a) a vehicle control command to the vehicle subsystem and (b) an attacker control command to the attacker subsystem and (ii) receiving (a) vehicle feedback from the vehicle subsystem and (b) attacker feedback from the attacker subsystem.