Disturbance Rejection based Engine Speed Control with Rotational Inertia Online Estimation

The performance of engine speed control is an important operating matrix of Diesel engines, but suffers from various uncertainties, internal and external. For instance, the moment of entire rotational inertia, for the engine-gearbox coupled system, is affected by the size of the gear box and transmission ratio. The load torque is also unknown. To achieve enhanced disturbance rejection performance and get rid of time-tedious control parameters calibration, a compound disturbance rejection control algorithm is proposed in this paper. First, an extended state observer is designed based on a control-oriented engine speed dynamic model, estimating and compensating the load torque in real-time. Then for enhanced performance, two rotational inertia online estimators (RIOE), extremum seeking (ES) and recursive least-square (RLS), are attempted and evaluated in simulation. Results show that RIOE can gradually estimate the inertia hence reduce the maximum speed deviation by 39% in the presence of abrupt load torque disturbance, relative to the case without RIOE. In comparison with ES, RLS converges faster than ES (62sec versus 300sec), but is less accurate in inertia estimation and more sensitive to model uncertainty.