Importance

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Abstract

A system and method for learning and controlling an air/fuel mixture ratio for an internal combustion engine are disclosed which can achieve the compatibility of both learning convergence characteristic and accuracy of learning and which can prevent a stepwise change in correction coefficients to a basic fuel supply quantity when the present engine driving condition makes the present one of the driving conditions to the other one of the driving conditions. In a preferred embodiment of the air/fuel mixture ratio learning and controlling system, a plurality of learning maps in which the whole driving region is divided into 16 regions and is divided into 258 regions. The learnings of the air/fuel mixture ratio learning correction coefficients KBLRC1 for the 16 driving regions on the first learning map are followed by those of the other air/fuel mixture ratio learning correction coefficients KBLRC2 for the 256 driving regions on the second learning map. After loads of corrections on the learning correction coefficients KBLRC1 are transferred to those of the learning correction coefficients KBLRC2 for the 256 driving regions, the system reads a modified learning correction coefficient KBLRC2 derived through an interpolation between the 256 region learning map. A final learning correction coefficient KBLRC is set using the read correction coefficient KBLRC2 and the learning correction coefficient KBLRC0 applied to the whole driving region so as to correct the basic fuel supply quantity.

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First Claim