Method and apparatus for estimating data for engine control

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises a fuel deposition rate in an intake manifold, and said input information comprises at least one of an engine rotational speed, an intake air volume and an intake vacuum.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises an evaporation time constant in said intake manifold, and said input information comprises at least one of an intake manifold wall temperature, an engine speed, an intake air volume and an intake vacuum pressure.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises a torque fluctuation amount, and said input information comprises at least one of a fluctuation of an engine revolution speed, the engine revolution speed, an intake air volume and a time data for a combustion chamber pressure.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises a combustion chamber temperature, and said input information comprises at least one of an intake manifold wall temperature, an ambient air temperature and an elapsed time from the engine start.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises an intake manifold wall temperature, and said input information comprises at least one of a coolant temperature, a cylinder block temperature and an oil temperature.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises an air/fuel ratio, and said input information comprises at least one of an exhaust gas temperature, an atmospheric temperature, an engine speed, an intake air volume, an intake vacuum pressure, an ignition timing and a throttle valve opening angle.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises an air/fuel ratio around an ignition location of a spark plug, and said input information comprises at least one of an engine rotational speed, a throttle opening angle, fuel an injection volume, a fuel injection timing, an ignition timing, and an intake/exhaust valve timing.

A data estimation method for engine control in which data for at least one engine condition is identified as an estimated parameter, the method comprising the steps of:

• obtaining input information from one or more sensors;
• providing said input information to one or more inputs of a fuzzy neural network;
• using said fuzzy neural network to estimate said estimated parameter;
• and obtaining said estimated parameter as an output of said fuzzy neural network, wherein said estimated parameter comprises an amount of NOx components in an exhaust gas inside a catalyst system, and said input information comprises at least one of an engine speed, a throttle opening angle, a coolant temperature, a gas temperature at an input of said catalyst system, a gas temperature at an output of said catalyst system, a traveling distance, and an air/fuel ratio.