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Technical Paper

Supervisory Controller for a Light Duty Diesel Engine with an LNT-SCR After-Treatment System

2018-09-10
2018-01-1767
Look ahead information can be used to improve the powertrain’s fuel consumption while efficiently controlling exhaust emissions. A passenger car propelled by a Euro 6d capable diesel engine is studied. In the conventional approach, the diesel powertrain subsystem control is rule based. It uses no information of future load requests but is operated with the objective of low engine out exhaust emission species until the Exhaust After-Treatment System (EATS) light off has occurred, even if fuel economy is compromised greatly. Upon EATS light off, the engine is operated more fuel efficiently since the EATS system is able to treat emissions effectively. This paper presents a supervisory control structure with the intended purpose to operate the complete powertrain using a minimum of fuel while improving the robustness of exhaust emissions.
Technical Paper

Comparing Dynamic Programming Optimal Control Strategies for a Series Hybrid Drivetrain

2017-10-08
2017-01-2457
A two-state forward dynamic programming algorithm is evaluated in a series hybrid drive-train application with the objective to minimize fuel consumption when look-ahead information is available. The states in the new method are battery state-of-charge and engine speed. The new method is compared to one-state dynamic programming optimization methods where the requested generator power is found such that the fuel consumption is minimized and engine speed is given by the optimum power-speed efficiency line. The other method compared is to run the engine at a given operating point where the system efficiency is highest, finding the combination of engine run requests over the drive-cycle that minimizes the fuel consumption. The work has included the engine torque and generator power as control signals and is evaluated in a full vehicle-simulation model based on the Volvo Car Corporation VSIM tool.
Technical Paper

A Structure and Calibration Method for Data-Driven Modeling of NOX and Soot Emissions from a Diesel Engine

2012-04-16
2012-01-0355
The development and implementation of a new structure for data-driven models for NOX and soot emissions is described. The model structure is a linear regression model, where physically relevant input signals are used as regressors, and all the regression parameters are defined as grid-maps in the engine speed/injected fuel domain. The method of using grid-maps in the engine speed/injected fuel domain for all the regression parameters enables the models to be valid for changes in physical parameters that affect the emissions, without having to include these parameters as input signals to the models. This is possible for parameters that are dependent only on the engine speed and the amount of injected fuel. This means that models can handle changes for different parameters in the complete working range of the engine, without having to include all signals that actually effect the emissions into the models.
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