Sampled Data Model Predictive Idle Speed Control of Ultra-Lean Burn Hydrogen Engines

Abstract

A model-based approach for the idle speed control of ultra-lean burn engines is presented. The results from model predictive control (MPC) are extended and collectively used with the existing sampled data control theory to obtain a rigorously developed idle speed control strategy. Controller is designed using MPC theory and facilitated by successive online linearizations of the nonlinear discrete-time model at each sampling instant. Simultaneously, the approximations due to the discretization of the nonlinear engine model are explicitly considered by designing the control within a previously proposed control design framework to obtain appropriate stability guarantees of an exact (unknown) discrete-time engine model. The proposed idle speed control method is experimentally validated on a prototype 6-cylinder hydrogen engine.