Model Predictive Control of Diesel Fuel Consumption and On-road Emission Constraints
Duraiarasan, Saravanan
2021
Abstract
Diesel engines continue to be an important powerplant in heavy-duty trucks due to their inherent advantages such as range, robustness to operating conditions, and wide range of torque deliverability. With the introduction of on-road-focused emission regulations, one would explore an adaptive calibration scheme, where the fuel efficiency is maximized subject to tailpipe NOx emission constraint. Nowadays, the engine calibration setpoints are a function of speed and load calibrated offline, considering various driving profiles and certified on a specific drive cycle. This thesis explores adjusting engine setpoints online to enable future integration with the trip ahead and a preview of the load affecting the thermal and, thus, the aftertreatment conditions. Recognizing that the engine-out NOx increases by more than 50 % for a corresponding decrease of 1 % in brake-specific fuel consumption (BSFC). It is essential to control the engine at the low BSFC conditions only when the selective catalytic reduction (SCR) is predicted to operate efficiently. Similarly, the engine operation should support the warm-up of the SCR and avoid the generation of NOx when the SCR cannot convert it. In this thesis, a hierarchical predictive engine and aftertreatment control architecture is designed to alter the engine setpoints to achieve the best fuel economy while the SCR effectively reduces the corresponding increase in engine-out NOx. The advantage of the model predictive controller in handling time-delayed systems addresses the slow thermo-chemical dynamics of SCR. To implement this controller in real-time, physics-based engine airpath, engine-out NOx emission, and aftertreatment thermodynamic models are developed. The hierarchical controller architecture consists of a supervisory thermal management controller with a long prediction horizon and an air path controller with short prediction horizon. The supervisory controller aims to improve and maintain the aftertreatment temperature above a set catalyst light-off temperature with intake manifold pressure and the start of injection (SOI) as control variables. After the aftertreatment warm-up, the supervisory controller balances and initiates transitions to “fuel save” mode and provides fuel-optimal references. The air path controller tracks the references dictated by the supervisory controller while it also controls the transient engine-out NOx by compensating the reference SOI. The sub-components of this hierarchical controller are experimentally validated for real-time feasibility and prediction capability. The overall architecture is validated in a software-in-the-loop (SIL) simulation environment, and results show improved fuel economy with reduced tailpipeDeep Blue DOI
Subjects
Diesel Engine Powertrain Control Emissions Control Model Predictive Control Hierarchical Model Predictive Control Fuel Economy
Types
Thesis
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