摘要:
In a control device for an internal combustion engine, a learning map includes at least one partitioned operating region. The at least one partitioned operating region corresponds to at least one of operating conditions of the internal combustion engine. The learning map includes a value of at least one control parameter stored in the at least one partitioned operating region. A control unit controls the internal combustion engine in accordance with the at least one control parameter. An updating unit learns a value of the at least one control parameter for the at least one of the operating conditions, thus performing an updating of the value of the at least one control parameter stored in the at least one partitioned operating region to the learned value. A partition changing unit changes a partition pattern of the learning map.
摘要:
An oxygen storage state of a catalyst is estimated based on an output of an air-fuel ratio sensor, and the oxygen storage state of the catalyst is controlled, such that the oxygen storage state of the catalyst reaches a neutral state, based on an estimation value of the oxygen storage state. In addition, the estimation value of the oxygen storage state is corrected based on the estimation value of the oxygen storage state and an output of an oxygen sensor such that deterioration of accuracy of the oxygen storage state estimation is restricted. Furthermore, a constant current is caused to flow in a direction in which rich detection by the oxygen sensor is expedited in a case of transition of the output of the oxygen sensor to a lean side. The constant current is caused to flow in a direction in which lean detection by the oxygen sensor is expedited in a case of transition of the output of the oxygen sensor to a rich side. Accordingly, an air-fuel ratio change in the catalyst and a change in actual oxygen storage state of the catalyst can be detected early based on the output of the oxygen sensor, and the deterioration of the accuracy of the oxygen storage state estimation can be detected early.
摘要:
A state estimation apparatus includes: a rate calculating configured to calculate, based on both a flow rate and an air-fuel ratio of exhaust gas flowing into an oxygen storage catalyst, a rate of change in an oxygen storage amount in the oxygen storage catalyst; a limit calculating unit configured to calculate a limit rate which is a limit value for the rate of change; and a storage-amount updating unit configured to update, based on the rate of change and the limit rate, an estimated value of the oxygen storage amount. Moreover, the storage-amount updating unit is further configured to: update, when the rate of change does not exceed the limit rate, the estimated value based on the rate of change; and update, when the rate of change exceeds the limit rate, the estimated value based on the limit rate.
摘要:
When executing a Local-learning, an air-fuel ratio detecting time is corrected so that a dispersion of detection values of an air-fuel ratio sensor becomes a maximum value in one cycle of an engine. While executing a cylinder-by-cylinder air-fuel ratio control, a Global-learning is executed. In the Global-learning, the air-fuel ratio detecting time is corrected based on a relationship between a variation in estimated air fuel ratio of each cylinder and a variation in fuel quantity correction value of each cylinder. In the Global-learning, a computer computes a correlation coefficient between the variation in estimated air-fuel ratio and the variation in fuel quantity correction value of the cylinder for each case where the cylinder assumed to correspond to the estimated air fuel ratio is hypothetically varied in multiple ways. Then, the air-fuel ratio detecting time is corrected so that this correlation coefficient becomes a maximum value.
摘要:
When executing a Local-learning, an air-fuel ratio detecting time is corrected so that a dispersion of detection values of an air-fuel ratio sensor becomes a maximum value in one cycle of an engine. While executing a cylinder-by-cylinder air-fuel ratio control, a Global-learning is executed. In the Global-learning, the air-fuel ratio detecting time is corrected based on a relationship between a variation in estimated air fuel ratio of each cylinder and a variation in fuel quantity correction value of each cylinder. In the Global-learning, a computer computes a correlation coefficient between the variation in estimated air-fuel ratio and the variation in fuel quantity correction value of the cylinder for each case where the cylinder assumed to correspond to the estimated air fuel ratio is hypothetically varied in multiple ways. Then, the air-fuel ratio detecting time is corrected so that this correlation coefficient becomes a maximum value.