An obtainer obtains travel data of an electric vehicle. A predictor predicts a failure due to aging in a drive circuit of a motor which drives a driving wheel of the electric vehicle, based on the travel data of the electric vehicle. The travel data includes position data of the electric vehicle and data relating to power consumption of the electric vehicle. The predictor predicts the failure due to aging in the drive circuit based on a change in an increase of power consumption generated when the electric vehicle travels a same route.

An active air flow regulation system for diagnosing the operation of an active air flow regulation system for a vehicle comprises: an obstructing mechanical member; a mechatronic system having a housing containing a magnet motor driven by a control circuit and coupled to a movement transformation for moving the obstructing mechanical member; and electronic communication lines for exchanging information with the DCU of the vehicle or receiving commands from the DCU of the vehicle, A related method includes storing, during an operating cycle of the active air flow regulation system, a numerical sequence S of data in a memory, the data acquired by the control circuit inside the mechatronic system; applying an algorithmic statistical analysis model to the data stored in the memory to determine a singularity; and identifying a sporadic error associated with the singularity to provide information on the state of the active air flow regulation system.

The present disclosure provides a system for terrain classification and vehicle suspension sub-system health status indication. The system includes run-time terrain classification circuitry to determine a first terrain classification, for a vehicle travelling on a terrain segment, based on comparing a trained model to suspension sub-system sensor data and vehicle speed data; model accuracy determination circuitry to determine a second terrain classification, for the vehicle travelling on the terrain segment, based on the suspension sub-system sensor data and vehicle speed data and independent of the trained model; and sub-system health determination circuitry to determine a health indication of the suspension sub-system by comparing a difference between the first and second terrain classifications to at least one health threshold.