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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.

Different Vibe function model structures for parameterized diesel engine heat release models are investigated. The work is motivated by the need of such models when closed-loop combustion control is implemented based on torque domain combustion phasing analysis. Starting from the studied model structures, models are created by estimating the model parameters using a separable least squares approach. After this, the models are evaluated according to two different performance criteria. The first criterion rates the ability of the estimated models to describe reference mass fraction burned traces. The second criterion assesses how accurately the models estimate the reference combustion phasing measure. As expected, the analysis shows that the models based on the most flexible model structure achieve the best results, both regarding mass fraction burned estimation and combustion phasing estimation.

Combustion model structures based on Vibe functions are outlined and investigated in this work. The focus of the study is the use of such model structures for estimation of diesel combustion properties by reconstructing in-cylinder pressure from measurements of crankshaft torque. Investigated combustion properties include the start and phasing of the combustion as well as maximum values of the in-cylinder pressure and its derivative. The accuracy associated with the proposed estimation method is evaluated using ideal torque data, i.e. torque calculated from in-cylinder pressure, that is generated using both simulations and experiments. The results indicate that the uncertainty associated with the estimation of a selected combustion property tends to increase if that property is located close to TDC, where the signal-to-noise ratio is low for a torque signal.

Mathematical models of a torque sensor equipped crankshaft in a light-duty diesel engine are identified, validated, and compared. The models are based on in-cylinder pressure and crankshaft torque data collected from a 5-cylinder common-rail diesel engine running at multiple operating points. The work is motivated by the need of a crankshaft model in a closed-loop combustion control system based on crankshaft torque measurements. In such a system a crankshaft model is used in order to separate the measured crankshaft torque into cylinder individual torque contributions. A method for this is described and used for IMEP estimation. Not surprisingly, the results indicate that higher order models are able to estimate crankshaft torque more accurately than lower order models, even if the differences are small. For IMEP estimation using the cylinder separation method however, these differences have large effects on accuracy.

A simulation model for the dynamic properties of multi-cylinder engines is developed. Specifically, the model is used to describe the relation between the individual cylinder pressures and the resulting torque in the crankshaft. The model is validated against a 5-cylinder SI-engine equipped with a crankshaft integrated torque sensor. The simulation model developed is based on a system of first order nonlinear differential equations where the crankshaft dynamics are expressed as interconnected mass-spring-damper elements. The motivation is to investigate how instantaneous crankshaft torque measurements can be used to deduce information on the combustion process, cylinder by cylinder, for the purpose of engine control. Therefore, a computationally simple simulation method is introduced.

An electrically heated catalyst (EHC) in the three-way catalyst (TWC) aftertreatment system of a gasoline internal combustion engine (ICE) provides cold engine start exhaust pollutant emission reduction potential. The EHC can be started before switching on the ICE, thereby offering the possibility to pre-heat (PRH) the TWC, in the absence of exhaust flow. The EHC can also provide post engine start heat (PSH) when the heat is accompanied by exhaust mass flow over the TWC. A mixed heating strategy (MXH) comprises both PRH and PSH. All three strategies are evaluated under a range of engine start variations using an ICE-exhaust aftertreatment (EATS) simulation framework. It is driven by an engine speed-torque requested trace, with an engine-out emissions model focused on cold-start, engine heating and catalyst heating engine measures and a physics- based EATS with EHC model.

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.

The three-way-catalyst (TWC) is an essential part of the exhaust aftertreatment system in spark-ignited powertrains, converting nearly all toxic emissions to harmless gasses. The TWC’s conversion efficiency is significantly temperature-dependent, and cold-starts can be the dominating source of emissions for vehicles with frequent start/stops (e.g. hybrid vehicles). In this paper we develop a thermal TWC model and calibrate it with experimental data. Due to the few number of state variables the model is well suited for fast offline simulation as well as subsequent on-line control, for instance using non-linear state-feedback or explicit MPC. Using the model could allow an on-line controller to more optimally adjust the engine ignition timing, the power in an electric catalyst pre-heater, and/or the power split ratio in a hybrid vehicle when the catalyst is not completely hot.