Stochastic Set-Point Optimization for In-Cycle Closed-Loop Combustion Control Operation

Abstract

The constrained indicated efficiency optimization of the set-point reference for in-cycle closed-loop combustion regulators is investigated in this article. Closed-loop combustion control is able to reduce the stochastic cyclic variations of the combustion by the adjustment of multiple-injections, a pilot and main injection in this work. The set-point is determined by the demand on engine load, burned pilot mass reference and combustion timing. Two strategies were investigated, the regulation of the start of combustion (SOC) and the center of combustion (CA50).The novel approach taken in this investigation consists of including the effect of the controlled variables on the combustion dispersion, instead of using mean-value models, and solve the stochastic optimization problem. A stochastic heat release model is developed for simulation and calibrated with extensive data from a Scania D13 six-cylinder engine. A Monte Carlo approach is taken for the simulations. The set-point optimization is based on the stochastic simulation of the heat release shape, including operational constraints on the maximum pressure, maximum pressure rise rate, maximum and minimum exhaust temperature.By exploiting the reduction of the cyclic variations, the indicated efficiency can be increased by up to +1.8%unit at low loads and +0.6%unit at medium loads, compared to open-loop operation. The greatest advantage resulted by the regulation of CA50 under demanding maximum pressure rise rate constraints. By considering the risk of pilot misfire, the indicated efficiency can be increased additionally by +0.3%unit. The benefits of the in-cycle closed-loop combustion control reduces as the engine load increases, due to the lower sensitivity to combustion variations. Future work can use the same approach to include other constraints such as NOx, additional fuel injections and regulators. (Less)