Unscented Kalman Filter for Estimation of Manifold Absolute Pressure in Engines.

In a global scenario, the exhaust emissions of automobiles need to be regulated. These emission regulations are met by maintaining the air-fuel ratio resulting in improved automobile performance like better engine torque and fuel economy. The air-fuel ratio of Spark Ignition (SI) engines needs to be maintained at a stoichiometric value of 14.7:1. To maintain this ratio, the estimation of the in-cylinder mass airflow rate is highly significant. One of the important parameters that influence the mass airflow rate is Manifold Absolute Pressure (MAP). The conventional methods that make use of MAP sensors have oscillations at engine firing frequency and poor dynamic response. This research paper uses an Unscented Kalman Filter (UKF) for the estimation of MAP in SI engines. The complete system consisting of the engine model and UKF algorithm has been simulated in Matlab/Simulink. With Root Mean Square Error (RMSE) as the performance metric, the accuracy in the estimation of MAP with UKF is higher than the Extended Kalman Filter (EKF). Hence, the UKF algorithm works out to be a better estimator for the efficient fuel injection in an engine management system. [ABSTRACT FROM AUTHOR]