Electronic control unit and fuel type analysis method

An electronic control unit, ECU, for a vehicle with a combustion engine, comprising:

• an input interface configured to:
• receive at least one dynamic torque sensor value (DTSV) from a high pressure pump of the vehicle;
• receive at least one additional sensor value (ASV) including at least one pressure sensor value or at least one timing value;
• receive combustion performance data (CPD) indicating combustion properties of a current fuel type of a fuel currently present in the high pressure pump and a fuel rail;
• and
• grant access to a database (DB) containing:
• information about known fuel types;
• and
• a specific parameter configuration for fuel injectors operatively connected to the fuel rail, for each of the known fuel types;
• a computing unit including:
• a fuel type detection module (FTDM);
• an artificial intelligence module (AIM);
• and
• a fuel injection control module (FICM);
• wherein the fuel type detection module (FTDM) is configured to determine, based on the at least one received dynamic torque sensor value (DTSV) and the received at least one additional sensor value (ASV) whether the current fuel type is of:
• a first fuel type group including the known fuel types;
• a second fuel type group including fuel types within a predefined variation range about at least one fuel type of the first fuel type group;
• a third fuel type group including all other fuel types;
• wherein, in response to determining that the current fuel type is the first fuel type group:
• the fuel injection control module (FICM) is configured to generate control signals for the fuel injectors using the specific parameter configuration for the current fuel type from the database;
• wherein, in response to determining that the current fuel type is the third fuel type group:
• the fuel injection control module (FICM) is configured to generate control signals for the fuel injectors initially using a fallback parameter configuration;
• and
• the AIM is configured to implement and train a new fuel type parameter artificial neural network (NFTPANN) for determining a specific parameter configuration for the current fuel type.