Efficient calibration of real-time model-based controllers for diesel engines — Part I: Approach and drive cycle results

摘要

Controlling a diesel engine air path to achieve optimal engine performance is a challenging problem, given its multivariable nature and high degree of nonlinearity. Modelbased control approaches like MPC have the potential for providing effective controller design, in the presence of operating constraints. However, conventional MPC formulations have too many tuning parameters for efficient calibration to meet transient performance specifications. Furthermore, they generally involve the solution of an online optimisation problem, making real-time implementation difficult for all but extremely short prediction horizons. These challenges may be addressed by introducing an MPC formulation suitable for real-time control of a diesel-engine air path, incorporating an appropriate cost-function parameterisation to aid calibration. In this paper, data-driven prediction models identified from engine bench tests are used within the proposed MPC formulation, and implemented on a production automotive diesel. Preliminary experiments show the efficacy of the implementation in tracking desired air path reference trajectories over the UDC and EUDC drive cycles.