Self-Adaptive Air-path Health Management for a Heavy Duty-Diesel Engine

Abstract

This paper presents the air-path health management strategy with the ability to estimate the mass-flows and mitigate (adapt to) the air-path faults in the exhaust system of a heavy-duty diesel combustion engine equipped with a twin-scroll turbine. Based on the engine component models applied in the quasi-steady-state mass-balancing approach, two main engine mass-flow quantities are estimated: the Air mass-flow (AMF) and the Exhaust gas recirculation (EGR) mass-flow. The health management system is monitoring for three kinds of air-path faults that can occur through the combustion engine operation, related either to the after-treatment system, EGR valve, or to the turbine balance valve hardware. For each fault, a fault-mitigation strategy based on in-observer-reconfigurable mass-balance equations with excluded faulty component model and utilized exhaust pressure sensor is proposed. The applied observer is using the iterated Kalman filter (IKF) as the core fault mitigating solver for the quasi-steady-state mass-balancing problem. It is further demonstrated how the individual faults are robustly isolated using the Sequential Probability Ratio Test (SPRT). The strategy and results are validated using the test cycle driving data.