AFR-Based Fuel Ethanol Content Estimation in Flex-Fuel Engines Tolerant to MAF Sensor Drifts

摘要

Flexible fuel vehicles (FFVs) can operate on a blend of ethanol and gasoline in any volumetric concentration of up to 85% ethanol (93% in Brazil). Existing FFVs rely on ethanol sensor installed in the vehicle fueling system, or on an ethanol estimation based on air-to-fuel ratio (AFR) regulation via an exhaust gas oxygen (EGO) or $lambda $ sensor. The EGO-based ethanol detection is desirable from cost and maintenance perspectives but it is known to be prone to large errors during mass air flow sensor drifts. Ethanol content estimation can be realized by a feedback-based fuel correction of the feedforward-based fuel calculation using an exhaust gas oxygen sensor. When the fuel correction is attributed to the difference in stoichiometric air-to-fuel ratio (SAFR) between ethanol and gasoline, it can be used for ethanol estimation. When the fuel correction is attributed to a mass air flow (MAF) sensor error, it can be used for sensor drift estimation and correction. Deciding under which condition to blame (and detect) ethanol and when to switch to sensor correction burdens the calibration of FFV engine controllers. Moreover, erroneous decisions can lead to biases in ethanol estimation and in MAF sensor correction. In this paper, we present AFR-based ethanol content estimation, associated sensitivity and dynamical analysis, and a cylinder air flow estimation scheme that accounts for MAF sensor drift or bias using an intake manifold absolute pressure (MAP) sensor. The proposed fusion of the MAF, MAP, and $lambda $ sensor measurements prevents severe misestimation of ethanol content in flex fuel vehicles.